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Posicionamento da Sociedade Brasileira de Cardiologia sobre o Uso de Dispositivos Eletrônicos para Fumar – 2024 | 078e7a48-65fc-4d09-92d8-0baccf8a7c6e | 11081107 | Internal Medicine[mh] | 1. Evidências insuficientes de redução de danos entre fumantes A alegação apresentada pela indústria do tabaco de que os DEFs são uma alternativa de menor risco à saúde para substituir os cigarros convencionais carece de confirmação. Pelo contrário, estudos indicaram que jovens que fazem uso de cigarros eletrônicos têm menor propensão a cessar o tabagismo. , Além disso, adultos fumantes que recorrem aos DEFs ou vapes exibem uma notável inclinação para a dupla utilização, que envolve cigarros tanto eletrônicos quanto regulares, o que aumenta os riscos à saúde . Embora o uso dual tenha sido comum nas primeiras versões dos DEFs, observa-se um crescente número de usuários exclusivos dos DEFs nas versões atuais que utilizam nicotina em freebase e sal de nicotina. Além disso, a nicotina foi identificada em usuários exclusivos de DEFs. A ausência de estudos suficientes que sustentem a tese do menor risco à saúde é relevante e contraposta por estudos clínicos e observacionais que sugerem impactos significativos na saúde dos usuários. – 2. O cigarro eletrônico não tem combustão, mas existem outros produtos distintos daqueles do cigarro convencional, muitos dos quais com efeitos desconhecidos na saúde humana Embora haja variações nos vapes, o produto consiste em quatro partes principais: um reservatório, um dispositivo de aquecimento, uma bateria de lítio e um bocal. No reservatório, são alojados a nicotina e, por vezes, os aromatizantes, os solventes e outros componentes químicos. A presença de solventes e aditivos, aquecidos durante o funcionamento do dispositivo, pode originar componentes tóxicos provenientes tanto dos próprios DEFs quanto de seus líquidos. Os refis e os frascos de nicotina líquida de DEFs não descartáveis representam um potencial risco de intoxicação, especialmente por ingestão acidental, absorção pela mucosa oral ou contato com a pele em caso de vazamento. Os Centros de Controle e Prevenção de Doenças dos Estados Unidos (CDC) registraram um significativo aumento nas chamadas para os centros de intoxicação relacionadas aos casos de envenenamento pelo líquido dos DEFs, sendo registrado até óbito em criança por ingestão acidental dos e-líquidos. Além disso, o descarte desses elementos representa uma séria ameaça ambiental. A quantidade de dispositivos descartados no ano de 2022 acendeu alerta das autoridades sanitárias no Reino Unido e outros países da Europa, muitos dos quais pensam em banir os dispositivos descartáveis de uso único. Eles geram toneladas de lixo eletrônico com lítio e cobre presentes nas baterias e resíduos dos e-líquidos, sendo esse conjunto de elementos considerado lixo tóxico. Adicionalmente existem também incidentes relacionados a explosões dos dispositivos. Desde 2019, tanto os CDC quanto o Food and Drug Administration (FDA) têm registrado um aumento nos casos de lesão pulmonar aguda grave associada ao uso de produtos de cigarro eletrônico ou vapes. Essa séria condição é identificada como EVALI (do inglês, e-cigarette or vaping product use-associated lung injury). , A maioria dos pacientes diagnosticados com EVALI necessitou de hospitalização, sendo que muitos receberam cuidados intensivos e suporte respiratório. Notavelmente, 2,3% dos casos resultaram em óbito. O acetato de vitamina E, um aditivo ocasionalmente utilizado em produtos contendo tetra-hidrocanabinol (THC), está significativamente associado ao surto de EVALI. No entanto, as evidências disponíveis não são suficientes para descartar a contribuição de outros produtos químicos preocupantes. , 3. Vape um novo fator de risco para as doenças cardiovasculares Diversas pesquisas indicam uma relação direta entre o uso de cigarros eletrônicos e o incremento no risco cardiovascular. A presença de nicotina nos dispositivos está vinculada a aumento da frequência cardíaca, elevação da pressão arterial e intensificação do estresse oxidativo. Além disso, o consumo regular de DEFs está associado a inflamação, disfunção endotelial, lesões vasculares e desenvolvimento de aterosclerose. , Não apenas isso, os cigarros eletrônicos também demonstram uma relação com o aumento da probabilidade de ocorrência de infarto do miocárdio. Indivíduos que fazem uso habitual desses dispositivos apresentam uma probabilidade 1,79 vez maior de sofrer um infarto em comparação com não fumantes, conforme evidenciado em estudos. , – 4. Prejuízos à saúde populacional A comercialização e o consumo de DEFs representam uma questão de saúde pública devido ao impacto que exercem tanto sobre fumantes quanto não fumantes. Pesquisa aponta que os usuários de cigarros eletrônicos apresentam uma menor probabilidade de cessar o tabagismo de maneira voluntária, devido à significativa capacidade desses dispositivos em induzir dependência de nicotina. , É crucial salientar a existência de usuários de DEFs que fazem uso simultâneo de cigarros convencionais, o que pode acarretar um aumento substancial no risco de desenvolvimento de doenças cardiovasculares. Adicionalmente, a relação entre a diminuição do número de cigarros consumidos e a redução do risco à saúde não segue uma trajetória linear. Mesmo exposições a níveis reduzidos podem desencadear doenças cardiovasculares. Um estudo de caso mediu biomarcadores na urina, na saliva e no cabelo de uma família consistindo de uma gestante não fumante, seu cônjuge usuário de cigarro eletrônico e um filho do casal de 3 anos de idade. Foram identificadas elevadas concentrações de cotinina (metabólito da nicotina) e níveis significativos de metais como alumínio (associado ao enfisema pulmonar), cromo (relacionado ao câncer de pulmão), níquel (associado ao câncer de pulmão e seio nasal) e cobre (causador de danos ao fígado, rins e pulmões). No leite materno de usuárias, foram detectadas concentrações elevadas de glicerol, responsável por danos pulmonares e cardiovasculares, além de cotinina em níveis altos, assemelhando-se ao efeito da exposição do bebê ao cigarro eletrônico. 5. Descumprimento das obrigações internacionais pelo Brasil A introdução de novos DEFs tem conferido à indústria um espaço renovado nas discussões. A Associação da Indústria do Tabaco do Brasil já manifestou seu apoio à regulamentação, reconhecendo que a entrada de novos dispositivos no mercado é de seu interesse econômico, mesmo quando sujeitos a regulações. É fundamental recordar que o Brasil, na qualidade de signatário da Convenção-Quadro para o Controle do Tabaco da Organização Mundial da Saúde (CQCT-OMS), está compelido, conforme disposto no artigo 5.3, a desenvolver políticas públicas de controle do tabaco resguardadas contra influências comerciais da indústria. A narrativa que a indústria está construindo, sugerindo uma busca pela redução de danos, não é uma novidade, bastando recordar os cigarros ‘light’, , supostamente causadores de menos danos. Isso constitui meramente uma estratégia da indústria para assegurar sua permanência no mercado. Portanto, é imperativo que o governo brasileiro esteja atento ao cumprimento de suas responsabilidades internacionais quanto ao controle do tabaco e não adote uma postura leniente em relação a essa prática. 6. Desafios para o cumprimento de medidas de regulação A promulgação da Lei Antifumo no Brasil gerou significativas mudanças culturais, em especial no que se refere aos ambientes isentos de tabaco, os quais, atualmente, são respeitados por uma parcela considerável da população brasileira. O fumo em locais como aviões, restaurantes e outros espaços coletivos fechados não é mais socialmente aceito. Não obstante, é crucial compreender que a existência da Lei Antifumo representa um caminho a ser percorrido, mas não constitui uma solução integral. O Brasil enfrenta desafios decorrentes da escassez de recursos e da falta de uma fiscalização efetiva. No presente momento, a fiscalização dos DEFs (vapes) é relativamente simples, uma vez que todos os produtos dessa natureza são proibidos. Contudo, com a eventual introdução oficial de novos produtos no mercado, a regulamentação do comércio legal e o combate à falsificação, ao descaminho e ao contrabando tornar-se-ão tão ou mais complexos do que os associados ao cigarro convencional. Além disso, é necessário promover uma mudança cultural, em especial em relação ao cigarro eletrônico, que, atualmente, contraria as conquistas alcançadas no contexto do tabaco tradicional. O Brasil tem desempenhado um papel exemplar na luta contra o tabagismo em âmbito global e as décadas de esforços resultaram em uma clara redução no consumo de tabaco, proporcionando benefícios evidentes para os indivíduos e a sociedade em geral. A proibição dos cigarros eletrônicos mantém a coerência de uma política voltada para preservar a saúde em nível tanto individual quanto coletivo. 7. Recursos para controle do tabaco em risco A regulamentação dos novos produtos implicaria um ônus adicional para o orçamento da saúde, que já enfrenta restrições significativas devido a diversas prioridades. Esse desafio abrange não apenas recursos financeiros, mas também humanos, que atualmente se mostram insuficientes para supervisionar tanto o uso quanto a comercialização do cigarro convencional, bem como para desenvolver políticas eficazes de cessação do tabagismo no âmbito do Sistema Único de Saúde (SUS). Além disso, a atenção primária e a atenção especializada enfrentam o desafio do tratamento de todas as enfermidades associadas ao consumo de produtos fumígenos, o que sobrecarrega as filas de atendimento. Considerando a insuficiência de recursos na saúde para tratar o tabagismo e suas ramificações, seria um equívoco permitir a circulação de outro produto tão prejudicial, o que certamente acarretaria um aumento nos custos com saúde no país. Um estudo conduzido em 2011 no Brasil concluiu que o custo para tratar diversas doenças crônicas decorrentes do tabagismo, no âmbito do SUS, totalizou 23,37 bilhões de reais, equivalente a 0,5% do Produto Interno Bruto e quatro vezes o montante dos impostos federais arrecadados do setor tabaco naquele ano. Esse custo tende a aumentar com a expansão do consumo de vapes. Como a maioria dos usuários é jovem, o que favorece o apelo da indústria por uma falsa percepção de segurança, estudos de curto prazo reafirmam os efeitos agudos cardiovasculares, pulmonares e cerebrovasculares e o fardo sobre o sistema de saúde certamente virá em algumas décadas. A cessação do tabagismo, inquestionavelmente, representa a estratégia mais custo-efetiva e o Brasil dispõe de um programa de tratamento eficaz, gratuito e acessível para a interrupção do tabagismo. 8. Diferença econômica e riscos associados na comparação entre Brasil e outros países Comumente, a indústria dos DEFs cita países em que a comercialização do produto é liberada com o objetivo de obter sua liberação no Brasil, como um exemplo a ser seguido. Contudo, mesmo em nações com um aparato legal e regulatório mais robusto, como Estados Unidos, Austrália, Reino Unido, Nova Zelândia e França, as legislações referentes aos cigarros eletrônicos estão sendo revisadas devido ao expressivo aumento no uso de vapes entre jovens, crianças e adolescentes, com incidência em escolas de ensino fundamental. Portanto, é imprudente que o Brasil presuma que, sem as condições adequadas para garantir a aplicação integral da Lei Antifumo, seria capaz de controlar o consumo desenfreado de DEFs, expondo a população jovem aos comprovados malefícios desses produtos. A indústria do tabaco está realizando investimentos substanciais na produção de vapes, transformando-os em um lucrativo empreendimento para as empresas internacionais do setor, que atualmente totalizam 466 marcas no mercado. – Além disso, o produto vem sendo aperfeiçoado ao longo do tempo, oferecendo capacidade de maior oferta volumétrica dos e-líquidos nos tanques, maior concentração de nicotina e redução nos preços, favorecendo ainda mais o consumo e a adição. 9. Proliferação dos DEFs entre jovens e não fumantes Apesar da exposição ilegal, os adolescentes continuam a ser altamente suscetíveis aos DEFs. A Global Youth Tobacco Survey evidencia um aumento epidêmico no consumo de cigarros eletrônicos, que chega a ser três vezes superior entre adolescentes na mesma faixa etária considerando países em que a comercialização é permitida em comparação a países com o banimento da comercialização, como Brasil e Tailândia. A Pesquisa Nacional de Saúde dos Escolares, conduzida pelo Instituto Brasileiro de Geografia e Estatística e abrangendo 159.245 estudantes brasileiros, revela que a experimentação de cigarro eletrônico em algum momento da vida entre escolares de 13 a 17 anos atingiu 16,8% (IC95% 16,2-17,4), sendo que 3,6% (IC95% 3,3-4,0) utilizaram nos últimos 30 dias. Vale ressaltar que o uso de qualquer produto relacionado ao tabaco, englobando cigarros convencionais, vapes e outros, aumentou de 9% em 2015 para 12% em 2019 entre adolescentes. Portanto, após duas décadas de declínio, a tendência entre adolescentes está se revertendo, influenciada pelo uso de produtos como vapes e narguilé, conforme evidenciado pela Pesquisa Nacional de Saúde dos Escolares. Segundo a pesquisa Covitel 2023, um em cada quatro jovens entre 18 e 24 anos já experimentou cigarros eletrônicos, sendo seu uso 40 vezes mais comum na população abaixo dos 40 anos, mesmo com a venda proibida no país. Entre os usuários de cigarros eletrônicos de 15 a 24 anos, 63% nunca experimentaram cigarro convencional, indicando que os DEFs têm se tornado a forma de iniciação ao fumo na juventude. , Mesmo sob regulamentação, a permissão da venda de DEFs apenas ampliaria as oportunidades de seu consumo entre os jovens, uma vez que o acesso seria facilitado. Além disso essa regulamentação promoveria a falsa ilusão de um produto menos nocivo. O amplo comércio, aliado à limitada capacidade de fiscalização, poderia proporcionar aos menores de idade mais chances de iniciar ou manter seu vício desde cedo, evidenciando os riscos associados à liberação do consumo de DEFs no país. 10. Princípio da precaução Diante das evidências disponíveis, considerando a natureza dos riscos vinculados ao uso dos novos DEFs, seu elevado potencial para adição e a incapacidade de implementação eficaz de medidas fiscalizatórias, bem como a falta de recursos destinados a tratar as consequências do consumo desses novos produtos, torna-se imperativo manter sua proibição no Brasil. Isso visa prevenir uma potencial nova epidemia de consumo de vapes ou agravamento da atual. A alegação apresentada pela indústria do tabaco de que os DEFs são uma alternativa de menor risco à saúde para substituir os cigarros convencionais carece de confirmação. Pelo contrário, estudos indicaram que jovens que fazem uso de cigarros eletrônicos têm menor propensão a cessar o tabagismo. , Além disso, adultos fumantes que recorrem aos DEFs ou vapes exibem uma notável inclinação para a dupla utilização, que envolve cigarros tanto eletrônicos quanto regulares, o que aumenta os riscos à saúde . Embora o uso dual tenha sido comum nas primeiras versões dos DEFs, observa-se um crescente número de usuários exclusivos dos DEFs nas versões atuais que utilizam nicotina em freebase e sal de nicotina. Além disso, a nicotina foi identificada em usuários exclusivos de DEFs. A ausência de estudos suficientes que sustentem a tese do menor risco à saúde é relevante e contraposta por estudos clínicos e observacionais que sugerem impactos significativos na saúde dos usuários. – Embora haja variações nos vapes, o produto consiste em quatro partes principais: um reservatório, um dispositivo de aquecimento, uma bateria de lítio e um bocal. No reservatório, são alojados a nicotina e, por vezes, os aromatizantes, os solventes e outros componentes químicos. A presença de solventes e aditivos, aquecidos durante o funcionamento do dispositivo, pode originar componentes tóxicos provenientes tanto dos próprios DEFs quanto de seus líquidos. Os refis e os frascos de nicotina líquida de DEFs não descartáveis representam um potencial risco de intoxicação, especialmente por ingestão acidental, absorção pela mucosa oral ou contato com a pele em caso de vazamento. Os Centros de Controle e Prevenção de Doenças dos Estados Unidos (CDC) registraram um significativo aumento nas chamadas para os centros de intoxicação relacionadas aos casos de envenenamento pelo líquido dos DEFs, sendo registrado até óbito em criança por ingestão acidental dos e-líquidos. Além disso, o descarte desses elementos representa uma séria ameaça ambiental. A quantidade de dispositivos descartados no ano de 2022 acendeu alerta das autoridades sanitárias no Reino Unido e outros países da Europa, muitos dos quais pensam em banir os dispositivos descartáveis de uso único. Eles geram toneladas de lixo eletrônico com lítio e cobre presentes nas baterias e resíduos dos e-líquidos, sendo esse conjunto de elementos considerado lixo tóxico. Adicionalmente existem também incidentes relacionados a explosões dos dispositivos. Desde 2019, tanto os CDC quanto o Food and Drug Administration (FDA) têm registrado um aumento nos casos de lesão pulmonar aguda grave associada ao uso de produtos de cigarro eletrônico ou vapes. Essa séria condição é identificada como EVALI (do inglês, e-cigarette or vaping product use-associated lung injury). , A maioria dos pacientes diagnosticados com EVALI necessitou de hospitalização, sendo que muitos receberam cuidados intensivos e suporte respiratório. Notavelmente, 2,3% dos casos resultaram em óbito. O acetato de vitamina E, um aditivo ocasionalmente utilizado em produtos contendo tetra-hidrocanabinol (THC), está significativamente associado ao surto de EVALI. No entanto, as evidências disponíveis não são suficientes para descartar a contribuição de outros produtos químicos preocupantes. , Diversas pesquisas indicam uma relação direta entre o uso de cigarros eletrônicos e o incremento no risco cardiovascular. A presença de nicotina nos dispositivos está vinculada a aumento da frequência cardíaca, elevação da pressão arterial e intensificação do estresse oxidativo. Além disso, o consumo regular de DEFs está associado a inflamação, disfunção endotelial, lesões vasculares e desenvolvimento de aterosclerose. , Não apenas isso, os cigarros eletrônicos também demonstram uma relação com o aumento da probabilidade de ocorrência de infarto do miocárdio. Indivíduos que fazem uso habitual desses dispositivos apresentam uma probabilidade 1,79 vez maior de sofrer um infarto em comparação com não fumantes, conforme evidenciado em estudos. , – A comercialização e o consumo de DEFs representam uma questão de saúde pública devido ao impacto que exercem tanto sobre fumantes quanto não fumantes. Pesquisa aponta que os usuários de cigarros eletrônicos apresentam uma menor probabilidade de cessar o tabagismo de maneira voluntária, devido à significativa capacidade desses dispositivos em induzir dependência de nicotina. , É crucial salientar a existência de usuários de DEFs que fazem uso simultâneo de cigarros convencionais, o que pode acarretar um aumento substancial no risco de desenvolvimento de doenças cardiovasculares. Adicionalmente, a relação entre a diminuição do número de cigarros consumidos e a redução do risco à saúde não segue uma trajetória linear. Mesmo exposições a níveis reduzidos podem desencadear doenças cardiovasculares. Um estudo de caso mediu biomarcadores na urina, na saliva e no cabelo de uma família consistindo de uma gestante não fumante, seu cônjuge usuário de cigarro eletrônico e um filho do casal de 3 anos de idade. Foram identificadas elevadas concentrações de cotinina (metabólito da nicotina) e níveis significativos de metais como alumínio (associado ao enfisema pulmonar), cromo (relacionado ao câncer de pulmão), níquel (associado ao câncer de pulmão e seio nasal) e cobre (causador de danos ao fígado, rins e pulmões). No leite materno de usuárias, foram detectadas concentrações elevadas de glicerol, responsável por danos pulmonares e cardiovasculares, além de cotinina em níveis altos, assemelhando-se ao efeito da exposição do bebê ao cigarro eletrônico. A introdução de novos DEFs tem conferido à indústria um espaço renovado nas discussões. A Associação da Indústria do Tabaco do Brasil já manifestou seu apoio à regulamentação, reconhecendo que a entrada de novos dispositivos no mercado é de seu interesse econômico, mesmo quando sujeitos a regulações. É fundamental recordar que o Brasil, na qualidade de signatário da Convenção-Quadro para o Controle do Tabaco da Organização Mundial da Saúde (CQCT-OMS), está compelido, conforme disposto no artigo 5.3, a desenvolver políticas públicas de controle do tabaco resguardadas contra influências comerciais da indústria. A narrativa que a indústria está construindo, sugerindo uma busca pela redução de danos, não é uma novidade, bastando recordar os cigarros ‘light’, , supostamente causadores de menos danos. Isso constitui meramente uma estratégia da indústria para assegurar sua permanência no mercado. Portanto, é imperativo que o governo brasileiro esteja atento ao cumprimento de suas responsabilidades internacionais quanto ao controle do tabaco e não adote uma postura leniente em relação a essa prática. A promulgação da Lei Antifumo no Brasil gerou significativas mudanças culturais, em especial no que se refere aos ambientes isentos de tabaco, os quais, atualmente, são respeitados por uma parcela considerável da população brasileira. O fumo em locais como aviões, restaurantes e outros espaços coletivos fechados não é mais socialmente aceito. Não obstante, é crucial compreender que a existência da Lei Antifumo representa um caminho a ser percorrido, mas não constitui uma solução integral. O Brasil enfrenta desafios decorrentes da escassez de recursos e da falta de uma fiscalização efetiva. No presente momento, a fiscalização dos DEFs (vapes) é relativamente simples, uma vez que todos os produtos dessa natureza são proibidos. Contudo, com a eventual introdução oficial de novos produtos no mercado, a regulamentação do comércio legal e o combate à falsificação, ao descaminho e ao contrabando tornar-se-ão tão ou mais complexos do que os associados ao cigarro convencional. Além disso, é necessário promover uma mudança cultural, em especial em relação ao cigarro eletrônico, que, atualmente, contraria as conquistas alcançadas no contexto do tabaco tradicional. O Brasil tem desempenhado um papel exemplar na luta contra o tabagismo em âmbito global e as décadas de esforços resultaram em uma clara redução no consumo de tabaco, proporcionando benefícios evidentes para os indivíduos e a sociedade em geral. A proibição dos cigarros eletrônicos mantém a coerência de uma política voltada para preservar a saúde em nível tanto individual quanto coletivo. A regulamentação dos novos produtos implicaria um ônus adicional para o orçamento da saúde, que já enfrenta restrições significativas devido a diversas prioridades. Esse desafio abrange não apenas recursos financeiros, mas também humanos, que atualmente se mostram insuficientes para supervisionar tanto o uso quanto a comercialização do cigarro convencional, bem como para desenvolver políticas eficazes de cessação do tabagismo no âmbito do Sistema Único de Saúde (SUS). Além disso, a atenção primária e a atenção especializada enfrentam o desafio do tratamento de todas as enfermidades associadas ao consumo de produtos fumígenos, o que sobrecarrega as filas de atendimento. Considerando a insuficiência de recursos na saúde para tratar o tabagismo e suas ramificações, seria um equívoco permitir a circulação de outro produto tão prejudicial, o que certamente acarretaria um aumento nos custos com saúde no país. Um estudo conduzido em 2011 no Brasil concluiu que o custo para tratar diversas doenças crônicas decorrentes do tabagismo, no âmbito do SUS, totalizou 23,37 bilhões de reais, equivalente a 0,5% do Produto Interno Bruto e quatro vezes o montante dos impostos federais arrecadados do setor tabaco naquele ano. Esse custo tende a aumentar com a expansão do consumo de vapes. Como a maioria dos usuários é jovem, o que favorece o apelo da indústria por uma falsa percepção de segurança, estudos de curto prazo reafirmam os efeitos agudos cardiovasculares, pulmonares e cerebrovasculares e o fardo sobre o sistema de saúde certamente virá em algumas décadas. A cessação do tabagismo, inquestionavelmente, representa a estratégia mais custo-efetiva e o Brasil dispõe de um programa de tratamento eficaz, gratuito e acessível para a interrupção do tabagismo. Comumente, a indústria dos DEFs cita países em que a comercialização do produto é liberada com o objetivo de obter sua liberação no Brasil, como um exemplo a ser seguido. Contudo, mesmo em nações com um aparato legal e regulatório mais robusto, como Estados Unidos, Austrália, Reino Unido, Nova Zelândia e França, as legislações referentes aos cigarros eletrônicos estão sendo revisadas devido ao expressivo aumento no uso de vapes entre jovens, crianças e adolescentes, com incidência em escolas de ensino fundamental. Portanto, é imprudente que o Brasil presuma que, sem as condições adequadas para garantir a aplicação integral da Lei Antifumo, seria capaz de controlar o consumo desenfreado de DEFs, expondo a população jovem aos comprovados malefícios desses produtos. A indústria do tabaco está realizando investimentos substanciais na produção de vapes, transformando-os em um lucrativo empreendimento para as empresas internacionais do setor, que atualmente totalizam 466 marcas no mercado. – Além disso, o produto vem sendo aperfeiçoado ao longo do tempo, oferecendo capacidade de maior oferta volumétrica dos e-líquidos nos tanques, maior concentração de nicotina e redução nos preços, favorecendo ainda mais o consumo e a adição. Apesar da exposição ilegal, os adolescentes continuam a ser altamente suscetíveis aos DEFs. A Global Youth Tobacco Survey evidencia um aumento epidêmico no consumo de cigarros eletrônicos, que chega a ser três vezes superior entre adolescentes na mesma faixa etária considerando países em que a comercialização é permitida em comparação a países com o banimento da comercialização, como Brasil e Tailândia. A Pesquisa Nacional de Saúde dos Escolares, conduzida pelo Instituto Brasileiro de Geografia e Estatística e abrangendo 159.245 estudantes brasileiros, revela que a experimentação de cigarro eletrônico em algum momento da vida entre escolares de 13 a 17 anos atingiu 16,8% (IC95% 16,2-17,4), sendo que 3,6% (IC95% 3,3-4,0) utilizaram nos últimos 30 dias. Vale ressaltar que o uso de qualquer produto relacionado ao tabaco, englobando cigarros convencionais, vapes e outros, aumentou de 9% em 2015 para 12% em 2019 entre adolescentes. Portanto, após duas décadas de declínio, a tendência entre adolescentes está se revertendo, influenciada pelo uso de produtos como vapes e narguilé, conforme evidenciado pela Pesquisa Nacional de Saúde dos Escolares. Segundo a pesquisa Covitel 2023, um em cada quatro jovens entre 18 e 24 anos já experimentou cigarros eletrônicos, sendo seu uso 40 vezes mais comum na população abaixo dos 40 anos, mesmo com a venda proibida no país. Entre os usuários de cigarros eletrônicos de 15 a 24 anos, 63% nunca experimentaram cigarro convencional, indicando que os DEFs têm se tornado a forma de iniciação ao fumo na juventude. , Mesmo sob regulamentação, a permissão da venda de DEFs apenas ampliaria as oportunidades de seu consumo entre os jovens, uma vez que o acesso seria facilitado. Além disso essa regulamentação promoveria a falsa ilusão de um produto menos nocivo. O amplo comércio, aliado à limitada capacidade de fiscalização, poderia proporcionar aos menores de idade mais chances de iniciar ou manter seu vício desde cedo, evidenciando os riscos associados à liberação do consumo de DEFs no país. Diante das evidências disponíveis, considerando a natureza dos riscos vinculados ao uso dos novos DEFs, seu elevado potencial para adição e a incapacidade de implementação eficaz de medidas fiscalizatórias, bem como a falta de recursos destinados a tratar as consequências do consumo desses novos produtos, torna-se imperativo manter sua proibição no Brasil. Isso visa prevenir uma potencial nova epidemia de consumo de vapes ou agravamento da atual. Com base no exposto, a SBC manifesta veementemente sua oposição a qualquer regulamentação de comercialização dos DEFs, independentemente de sua modalidade. |
Evaluation of biocontrol efficacy of rhizosphere | 30acccb2-6c16-43fa-9efa-39c264e64865 | 11414977 | Microbiology[mh] | Pepper ( Capsicum annuum L.), is widely cultivated for their culinary uses. However, their production is often hindered by biotic or abiotic factors. Among biotic factors, plant pathogens cause severe damage to peppers, especially Phytophthora capsici , which is a destructive soil-borne disease for pepper cultivation . This pathogen infects pepper plants through asexually generated characteristic biflagellate, unicellular and motile zoospores from the lemon-shaped sporangia. The pathogenicity of P . capsici is distinct, and the pathogen shows resistance to multiple fungicide, making it challenging to control with traditional chemical methods . In recent years, the environmental pollution and resistance issues associated with chemical pesticides have become more severe . Biological control has emerged as a preferred strategy for sustainable agriculture due to its minimal environmental impact, long-lasting efficacy, and reduced risk of resistance development . Several microbial species with biocontrol activity against P . capsici were utilized for controlling the pathogen. Ochrobactrum pseudogrignonense NC1 significantly inhibited the mycelial growth and zoospore production of P . capsici . Bacillus cereus B1301 and Chryseobacterium sp. R98 had high biocontrol activity against P . capsici . Trichoderma aggressivum f. europaeum, T . longibrachiatum , Paecilomyces variotii , and T . saturnisporum could be used to control of P . capsici in pepper . The epiphytic yeasts from Piperaceae had multiple antagonistic mechanisms contained yeasts volatile organic compound production, hyperparasitism, and the production of β-1,3-glucanase enzyme . Five Trichoderma strains , such as T . harzianum , T . longibranchiatum , T . yunnanense , T . asperellum (T2-10 and T2-31) and Trichoderma sp., were excellent potential agents for controlling P . capsici . Pseudomonas species have been widely employed for the biological control of P . capsici . The biocontrol mechanisms of Pseudomonas encompass competitive exclusion for space and nutrients, siderophore production (iron chelation), secretion of catabolic enzymes and secondary metabolism products, and induction of systemic resistance in host plants . For instance, Pseudomonas otitidis YJR27 and P . putida YJR92 can inhibit P . capsici and manage Phytophthora blight in pepper plants . P . plecoglossicida YJR13 and P . putida YJR92 not only effectively hindered mycelial growth, zoospore germination, and germ tube elongation of P . capsici but also colonized pepper roots through cell motility, biofilm formation, and chemotaxis towards root exudates . Additionally, Pseudomonas species strains markedly inhibited sporangia formation, zoospore release, and mycelial growth in liquid culture . Beneficial biocontrol bacteria are abundant in the rhizosphere of plants, aiding in plant resistance against pathogenic infections, enhancing nutrient absorption, and promoting plant growth . To screen for biocontrol bacteria with plant growth-promoting attributes and to obtain low molecular weight substances from bacteria for controlling P . capsici , we tested a strain of P . aeruginosa isolated from the rhizosphere of pepper. In this study, the strain of P . aeruginosa demonstrated significant biocontrol efficacy against P . capsici both in vivo and in vitro . Moreover, the P . aeruginosa easily colonized to rhizosphere of pepper and highly suppress pepper blight in filed. Notably, the α-pinene produced by P . aeruginosa exhibited anti-oomycete activity. These findings offer a promising avenue for developing novel methods to prevent pepper blight caused by P . capsici .
P . capsici isolation and identification P . capsici was isolated from a diseased pepper plant with blight, cultured on potato dextrose agar (PDA) medium at 28°C, and identified through PCR amplification utilizing primers (ITS1 and ITS4) targeting the internal transcribed spacer sequence . Isolation and screening for biocontrol bacteria The procedure followed the method with slight modifications . For the isolation of biocontrol bacteria, the surface soil was first removed, followed by collection of soil from a depth of 5–10 cm in the rhizosphere of 10 pepper plants heavily affected by P . capsici in Gaoqiao Town, Changsha County, Hunan Province (113.33°E, 28.44°N). Ten-gram soil samples were suspended in 90 ml of sterile water, agitated for 30 minutes, and then serially diluted 10,000 times. Subsequently, 100 μl of the suspensions with the highest dilution were spread on Luria-Bertani agar (LB) plates and incubated at 28°C for 48 hours until bacterial colonies appeared. Single colonies were then selected, purified on LB agar plates for 3 days, and subsequently cultured in 500 ml liquid LB medium for 48 hours. To screen for biocontrol bacteria, a 5 mm diameter P . capsici disc was placed at the center of a PDA plate. Next, 5 μl of each of the four bacterial suspensions were inoculated 2 cm away from the disc in a crisscross pattern on the agar plate. The plates were then incubated for 7 days to observe the inhibition of mycelial growth. Bacteria exhibiting anti-oomycetes activity were chosen for further validation. To further validate the biocontrol activity, the candidate bacterium was streaked horizontally on the left of a PDA medium and incubated at 28°C for 48 h to obtain bacterial growth. After bacterial growth, a 5 mm diameter disc of P . capsici was placed on the right of the same plate. The bacterium was 2cm from the disc of P . capsici . Plates with both bacteria and P . capsici were incubated for at 28°C. Each treatment repeated 3 times. When mycelium s of P . capsici on the right of the plate (no bacterium) grow up to the edge of plate, the biocontrol activity of the bacterium was assessed comparing the inhibition of mycelium expansion in the presence of the bacterium strain, and measuring the mycelium radius in the direction of the bacterium. For each plate we calculated the average radius of the mycelia using the following formula: the rate of inhibition of mycelium growth = (Rb-Rc) / Rb, where Rb was the mycelium s radius in the opposite direction of the bacterium; where Rc was the mycelium radius in the direction of the bacterium. The bacterium with the highest anti-oomycete activity was analyzed further. Taxonomic identification of strain Pa608 Morphological characters and 16S rRNA sequencing A bacterial strain exhibiting the highest anti-oomycete activity was designated as Pa608. The purified bacterium was cultivated on nutrient agar (NA) and LB medium for 3 days at 28°C, followed by an assessment of colony morphology and color. The Gram characteristics of the strain Pa608 were determined using a Gram stain kit. Subsequently, the shape and size of the strain Pa608 were examined through scanning electron microscopy. For the molecular identification of the strain Pa608, colony PCR was employed to amplify the 16S rRNA sequences using primers 27F and 1492R . The 20 μL reaction mixture contained approximately 50 ng of total DNA, 5 mM each of dNTPs, 20 pmol each of both forward and reverse primers, and 0.5 U of Taq DNA polymerase (TransGen Biotech Co., Ltd., Beijing, China). PCR amplification was performed in a thermocycler applying the conditions: Denaturation for 1 min at 94°C; Annealing for 45 sec at 56°C; Extension for 1 min at 72°C; Final extension for 10 min at 72°C. The PCR products were visualized through agarose gel electrophoresis and then sequenced by Beijing Qingke Biotechnology Co., Ltd. The obtained sequences were manually curated and compared against the National Center for Biotechnology Information (NCBI) database using BLASTn to identify the most closely related bacterial species. A phylogenetic tree encompassing the strain Pa608 and seven other bacteria within the genus Pseudomonas was constructed using the neighbor-joining algorithm with 1000 bootstrap replicates in MEGA7 . Extracellular enzyme characteristic Protease, cellulase, amylase and phosphate solubility activities of the strain Pa608 were assessed on LB agar medium supplemented with 3% skim milk powder, carboxymethyl cellulose agar medium (K₂HPO₄ 2.5g, Na₂HPO₄ 2.5g, Carboxymethylcellulose sodium 20.0g, Peptone 2.0g, Yeast Extract 0.5g, Agar 14.0g), 1% starch-pancreatic soy agar (Trypticase 15.0g, Enzymatic digest of soybean meal 5.0g, NaCl 5.0g, Soluble Starch 3.0g; Agar 15.0g), and a phosphate solubilization medium (Glucose, 10.0 g; KH 2 PO 4 , 10.9 g; (NH 4 ) 2 SO 4 , 1.0 g; MgSO 4 •7H 2 O, 0.16 g; FeSO 4 •7H 2 O, 0.005 g; CaCl 2 •2H 2 O, 0.011 g; MnCl 2 •4H 2 O, 0.002 g; Agar 14.0g), respectively. The plates were incubated for 3 days at 28°C, and the characteristics of extracellular enzymes were investigated by measuring the transparent zones. Inhibition effect of strain Pa608 on pathogens The antimicrobial spectrum of the strain Pa608 was assessed against some plant pathogens, including Sclerotinia sclerotiorum , Pyricularia oryzae , Diaporthe citri , Botrytis cinerea , Fusarium graminearum , and Penicillium simplicissimum . The confrontational culture method, as described earlier, was used to determine the width of the inhibitory zone, which was observed and quantified. Pot experiment The pepper variety Zhongke M105 f1 was selected for the pot experiment. The pepper seeds were disinfected with 0.1% sodium hypochlorite and thoroughly rinsed with distilled water three times to remove any sodium hypochlorite residue. The treated seeds were then placed on filter paper in a petri dish until germination occurred. Once sprouts emerged, they were transplanted 2 cm deep into soil in a 10-cm wide pot, with one plant per pot. The planting medium consisted of a 2:1 mixture of Walga horticultural nutrient soil and vermiculite. Plants were allowed to grow to the eight-leaf stage, and only robust and uniformly developed plants were selected for subsequent experiments. To prepare the sporangia solution, P . capsici was first inoculated on oatmeal agar and incubated at 25°C for seven days, then transferred to 28°C for 48 hours under continuous illumination to induce sporangia formation. Subsequently, the sporangia were harvested from the agar surface using a brush . The collected culture was then left at room temperature for three hours to encourage zoospore release, and subsequently diluted with distilled water to achieve an inoculation concentration of 2.0×10 4 zoospores/ml. For the strain Pa608, inoculation was carried out in 100 mL LB medium and incubated at 28°C, 150 rpm, for 24 hours to achieve bacterial suspensions with a concentration of 1.0 ×10 8 cells/ml, measured by a spectrophotometer. Three treatments were implemented in the experiment. Treatment 1: Inject 3 ml of sterile water as a control. Treatment 2: inject 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) 1.5 cm deep into the soil , maintaining a distance from the plants to avoid direct contact. Treatment 3: Inject 3 mL of the strain Pa608 bacterial suspension (concentration: 1.0×10 8 cells/ml) into the soil followed by 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml). Each treatment contains 12 pots of peppers, with 3 pepper plants in each pot. Water regularly, maintain high temperature and humidity to promote disease development. Disease severity (DI) was evaluated ten days post-inoculation utilizing a rating scale ranging from 0 to 5 , and the DI was determined using the formula : D I = ( Σ ( s × n ) / ( N × S ) ) × 100 where DI represented the disease index, s denoted the scale rating, n was the number of plants at a specific scale rating, N was the total number of evaluated plants, and S was the maximum scale rating. Colonization dynamics of the strain Pa608 in pepper rhizosphere soil Total of 6 pots of pepper plants were divided into 2 treatments, with 3 plants in each treatment. Treatment 1 involved injecting 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) into the soil at the base of the pepper plants , followed by 3 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). Treatment 2 involved injecting 3 mL of the strain Pa608 bacterial suspension into the soil at the base of the pepper plants. Soil samples from the pots were collected on days 1, 3, 5, 10, 15, 30, and 45. The soil samples were subjected to gradient dilution method to detect the quantity of the strain Pa608. Pseudomonas agar medium was used as the culture medium , diluted by a factor of 1, 000, and after incubating at 30°C for 2 days, the colonies were observed for color (blue-green) and counted. Field experiment The pepper greenhouse experiment was being conducted at the Vegetable Research Institute base of Hunan Agricultural Sciences Academy in Gaoqiao Town, Changsha County, Hunan Province. In previous years, the greenhouse has suffered from severe disease outbreaks, with an incidence rate of over 90%. The ridges were 1.2 meters wide, with 2 rows per ridge, a plant spacing of 35 cm, and a furrow width of 30 cm. There were 2 treatments: Treatment 1 was the blank control, with each pepper plant root irrigated with 50 mL of sterile water; Treatment 2 involved irrigating each pepper plant root with 50 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). The pepper seedlings were treated 3 days after transplanting, followed by two additional treatments in early June and early July, totaling 3 treatments. Harvesting and recording of plant height, yield and disease incidence were scheduled for July 28th. The disease index was classified according to Sunwoo’s standards as previously mentioned . GC-MS analysis of the metabolites produced by the strain Pa608 The fermentation broth of the strain Pa608 was extracted using ethyl acetate (48 hours of fermentation). The ratio of organic solvent to fermentation broth was 1:1, with an extraction time of 8 hours, repeated three times. The extract was concentrated to a paste at 40°C using a rotary evaporator and stored at 4°C for future use. The gas chromatography-mass spectrometry (GC-MS) was used to analyze the compound composition of the fermentation broth. The GC-MS analysis conditions were selected following the method , with adjustments made to the column temperature ramping up to 300°C at a rate of 10°C/min, hold for 40 min, using helium as the carrier gas with a split ratio set at 20:1, inject 1 μL, and set the injector temperature at 325°C. The mass spectrometry analysis conditions followed the method , with adjustments to stabilize the ion source at 280°C and scan the range from 33 to 600 m/z. The components of volatile compounds were identified by comparing retention times using the NIST mass spectral library. The relative contents were determined based on the percentage of peak areas of different compounds. A structural analysis of volatile organic compounds with antimicrobial potential was conducted based on relevant literature. The data were analyzed using the NIST Mass Spectral Library version 8 (NIST08.L) to match the acquired mass spectra, qualitatively analyze compounds based on matching factors, and retrieve pertinent information for each compound. Biocontrol activity assessment of metabolites produced by the strain Pa608 The compounds with significant peak areas from the GC-MS results, particularly those previously recognized for their antimicrobial properties, were chosen as potential anti-oomycete substances. The pure form of these selected compounds was acquired and their inhibitory activity against P . capsici was evaluated using the growth rate inhibition method. The final concentrations of the candidate compounds in the PDA medium were 250 mg/L, 50 mg/L, 10 mg/L, and 5 mg/L, with an equal volume of sterile water serving as a control. One 5 mm diameter disc of P . capsici was positioned at the center of each petri dish and then incubated at a constant temperature of 25°C for 7 days. The procedure replicated three times. The inhibitory rate can be calculated using the formula : inhibitory rate = 100% * ((colony diameter in control—disc diameter)—(colony diameter in treatment—disc diameter)) / (colony diameter in control—disc diameter).
. capsici isolation and identification P . capsici was isolated from a diseased pepper plant with blight, cultured on potato dextrose agar (PDA) medium at 28°C, and identified through PCR amplification utilizing primers (ITS1 and ITS4) targeting the internal transcribed spacer sequence .
The procedure followed the method with slight modifications . For the isolation of biocontrol bacteria, the surface soil was first removed, followed by collection of soil from a depth of 5–10 cm in the rhizosphere of 10 pepper plants heavily affected by P . capsici in Gaoqiao Town, Changsha County, Hunan Province (113.33°E, 28.44°N). Ten-gram soil samples were suspended in 90 ml of sterile water, agitated for 30 minutes, and then serially diluted 10,000 times. Subsequently, 100 μl of the suspensions with the highest dilution were spread on Luria-Bertani agar (LB) plates and incubated at 28°C for 48 hours until bacterial colonies appeared. Single colonies were then selected, purified on LB agar plates for 3 days, and subsequently cultured in 500 ml liquid LB medium for 48 hours. To screen for biocontrol bacteria, a 5 mm diameter P . capsici disc was placed at the center of a PDA plate. Next, 5 μl of each of the four bacterial suspensions were inoculated 2 cm away from the disc in a crisscross pattern on the agar plate. The plates were then incubated for 7 days to observe the inhibition of mycelial growth. Bacteria exhibiting anti-oomycetes activity were chosen for further validation. To further validate the biocontrol activity, the candidate bacterium was streaked horizontally on the left of a PDA medium and incubated at 28°C for 48 h to obtain bacterial growth. After bacterial growth, a 5 mm diameter disc of P . capsici was placed on the right of the same plate. The bacterium was 2cm from the disc of P . capsici . Plates with both bacteria and P . capsici were incubated for at 28°C. Each treatment repeated 3 times. When mycelium s of P . capsici on the right of the plate (no bacterium) grow up to the edge of plate, the biocontrol activity of the bacterium was assessed comparing the inhibition of mycelium expansion in the presence of the bacterium strain, and measuring the mycelium radius in the direction of the bacterium. For each plate we calculated the average radius of the mycelia using the following formula: the rate of inhibition of mycelium growth = (Rb-Rc) / Rb, where Rb was the mycelium s radius in the opposite direction of the bacterium; where Rc was the mycelium radius in the direction of the bacterium. The bacterium with the highest anti-oomycete activity was analyzed further.
Morphological characters and 16S rRNA sequencing A bacterial strain exhibiting the highest anti-oomycete activity was designated as Pa608. The purified bacterium was cultivated on nutrient agar (NA) and LB medium for 3 days at 28°C, followed by an assessment of colony morphology and color. The Gram characteristics of the strain Pa608 were determined using a Gram stain kit. Subsequently, the shape and size of the strain Pa608 were examined through scanning electron microscopy. For the molecular identification of the strain Pa608, colony PCR was employed to amplify the 16S rRNA sequences using primers 27F and 1492R . The 20 μL reaction mixture contained approximately 50 ng of total DNA, 5 mM each of dNTPs, 20 pmol each of both forward and reverse primers, and 0.5 U of Taq DNA polymerase (TransGen Biotech Co., Ltd., Beijing, China). PCR amplification was performed in a thermocycler applying the conditions: Denaturation for 1 min at 94°C; Annealing for 45 sec at 56°C; Extension for 1 min at 72°C; Final extension for 10 min at 72°C. The PCR products were visualized through agarose gel electrophoresis and then sequenced by Beijing Qingke Biotechnology Co., Ltd. The obtained sequences were manually curated and compared against the National Center for Biotechnology Information (NCBI) database using BLASTn to identify the most closely related bacterial species. A phylogenetic tree encompassing the strain Pa608 and seven other bacteria within the genus Pseudomonas was constructed using the neighbor-joining algorithm with 1000 bootstrap replicates in MEGA7 . Extracellular enzyme characteristic Protease, cellulase, amylase and phosphate solubility activities of the strain Pa608 were assessed on LB agar medium supplemented with 3% skim milk powder, carboxymethyl cellulose agar medium (K₂HPO₄ 2.5g, Na₂HPO₄ 2.5g, Carboxymethylcellulose sodium 20.0g, Peptone 2.0g, Yeast Extract 0.5g, Agar 14.0g), 1% starch-pancreatic soy agar (Trypticase 15.0g, Enzymatic digest of soybean meal 5.0g, NaCl 5.0g, Soluble Starch 3.0g; Agar 15.0g), and a phosphate solubilization medium (Glucose, 10.0 g; KH 2 PO 4 , 10.9 g; (NH 4 ) 2 SO 4 , 1.0 g; MgSO 4 •7H 2 O, 0.16 g; FeSO 4 •7H 2 O, 0.005 g; CaCl 2 •2H 2 O, 0.011 g; MnCl 2 •4H 2 O, 0.002 g; Agar 14.0g), respectively. The plates were incubated for 3 days at 28°C, and the characteristics of extracellular enzymes were investigated by measuring the transparent zones. Inhibition effect of strain Pa608 on pathogens The antimicrobial spectrum of the strain Pa608 was assessed against some plant pathogens, including Sclerotinia sclerotiorum , Pyricularia oryzae , Diaporthe citri , Botrytis cinerea , Fusarium graminearum , and Penicillium simplicissimum . The confrontational culture method, as described earlier, was used to determine the width of the inhibitory zone, which was observed and quantified. Pot experiment The pepper variety Zhongke M105 f1 was selected for the pot experiment. The pepper seeds were disinfected with 0.1% sodium hypochlorite and thoroughly rinsed with distilled water three times to remove any sodium hypochlorite residue. The treated seeds were then placed on filter paper in a petri dish until germination occurred. Once sprouts emerged, they were transplanted 2 cm deep into soil in a 10-cm wide pot, with one plant per pot. The planting medium consisted of a 2:1 mixture of Walga horticultural nutrient soil and vermiculite. Plants were allowed to grow to the eight-leaf stage, and only robust and uniformly developed plants were selected for subsequent experiments. To prepare the sporangia solution, P . capsici was first inoculated on oatmeal agar and incubated at 25°C for seven days, then transferred to 28°C for 48 hours under continuous illumination to induce sporangia formation. Subsequently, the sporangia were harvested from the agar surface using a brush . The collected culture was then left at room temperature for three hours to encourage zoospore release, and subsequently diluted with distilled water to achieve an inoculation concentration of 2.0×10 4 zoospores/ml. For the strain Pa608, inoculation was carried out in 100 mL LB medium and incubated at 28°C, 150 rpm, for 24 hours to achieve bacterial suspensions with a concentration of 1.0 ×10 8 cells/ml, measured by a spectrophotometer. Three treatments were implemented in the experiment. Treatment 1: Inject 3 ml of sterile water as a control. Treatment 2: inject 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) 1.5 cm deep into the soil , maintaining a distance from the plants to avoid direct contact. Treatment 3: Inject 3 mL of the strain Pa608 bacterial suspension (concentration: 1.0×10 8 cells/ml) into the soil followed by 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml). Each treatment contains 12 pots of peppers, with 3 pepper plants in each pot. Water regularly, maintain high temperature and humidity to promote disease development. Disease severity (DI) was evaluated ten days post-inoculation utilizing a rating scale ranging from 0 to 5 , and the DI was determined using the formula : D I = ( Σ ( s × n ) / ( N × S ) ) × 100 where DI represented the disease index, s denoted the scale rating, n was the number of plants at a specific scale rating, N was the total number of evaluated plants, and S was the maximum scale rating. Colonization dynamics of the strain Pa608 in pepper rhizosphere soil Total of 6 pots of pepper plants were divided into 2 treatments, with 3 plants in each treatment. Treatment 1 involved injecting 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) into the soil at the base of the pepper plants , followed by 3 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). Treatment 2 involved injecting 3 mL of the strain Pa608 bacterial suspension into the soil at the base of the pepper plants. Soil samples from the pots were collected on days 1, 3, 5, 10, 15, 30, and 45. The soil samples were subjected to gradient dilution method to detect the quantity of the strain Pa608. Pseudomonas agar medium was used as the culture medium , diluted by a factor of 1, 000, and after incubating at 30°C for 2 days, the colonies were observed for color (blue-green) and counted. Field experiment The pepper greenhouse experiment was being conducted at the Vegetable Research Institute base of Hunan Agricultural Sciences Academy in Gaoqiao Town, Changsha County, Hunan Province. In previous years, the greenhouse has suffered from severe disease outbreaks, with an incidence rate of over 90%. The ridges were 1.2 meters wide, with 2 rows per ridge, a plant spacing of 35 cm, and a furrow width of 30 cm. There were 2 treatments: Treatment 1 was the blank control, with each pepper plant root irrigated with 50 mL of sterile water; Treatment 2 involved irrigating each pepper plant root with 50 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). The pepper seedlings were treated 3 days after transplanting, followed by two additional treatments in early June and early July, totaling 3 treatments. Harvesting and recording of plant height, yield and disease incidence were scheduled for July 28th. The disease index was classified according to Sunwoo’s standards as previously mentioned . GC-MS analysis of the metabolites produced by the strain Pa608 The fermentation broth of the strain Pa608 was extracted using ethyl acetate (48 hours of fermentation). The ratio of organic solvent to fermentation broth was 1:1, with an extraction time of 8 hours, repeated three times. The extract was concentrated to a paste at 40°C using a rotary evaporator and stored at 4°C for future use. The gas chromatography-mass spectrometry (GC-MS) was used to analyze the compound composition of the fermentation broth. The GC-MS analysis conditions were selected following the method , with adjustments made to the column temperature ramping up to 300°C at a rate of 10°C/min, hold for 40 min, using helium as the carrier gas with a split ratio set at 20:1, inject 1 μL, and set the injector temperature at 325°C. The mass spectrometry analysis conditions followed the method , with adjustments to stabilize the ion source at 280°C and scan the range from 33 to 600 m/z. The components of volatile compounds were identified by comparing retention times using the NIST mass spectral library. The relative contents were determined based on the percentage of peak areas of different compounds. A structural analysis of volatile organic compounds with antimicrobial potential was conducted based on relevant literature. The data were analyzed using the NIST Mass Spectral Library version 8 (NIST08.L) to match the acquired mass spectra, qualitatively analyze compounds based on matching factors, and retrieve pertinent information for each compound. Biocontrol activity assessment of metabolites produced by the strain Pa608 The compounds with significant peak areas from the GC-MS results, particularly those previously recognized for their antimicrobial properties, were chosen as potential anti-oomycete substances. The pure form of these selected compounds was acquired and their inhibitory activity against P . capsici was evaluated using the growth rate inhibition method. The final concentrations of the candidate compounds in the PDA medium were 250 mg/L, 50 mg/L, 10 mg/L, and 5 mg/L, with an equal volume of sterile water serving as a control. One 5 mm diameter disc of P . capsici was positioned at the center of each petri dish and then incubated at a constant temperature of 25°C for 7 days. The procedure replicated three times. The inhibitory rate can be calculated using the formula : inhibitory rate = 100% * ((colony diameter in control—disc diameter)—(colony diameter in treatment—disc diameter)) / (colony diameter in control—disc diameter).
A bacterial strain exhibiting the highest anti-oomycete activity was designated as Pa608. The purified bacterium was cultivated on nutrient agar (NA) and LB medium for 3 days at 28°C, followed by an assessment of colony morphology and color. The Gram characteristics of the strain Pa608 were determined using a Gram stain kit. Subsequently, the shape and size of the strain Pa608 were examined through scanning electron microscopy. For the molecular identification of the strain Pa608, colony PCR was employed to amplify the 16S rRNA sequences using primers 27F and 1492R . The 20 μL reaction mixture contained approximately 50 ng of total DNA, 5 mM each of dNTPs, 20 pmol each of both forward and reverse primers, and 0.5 U of Taq DNA polymerase (TransGen Biotech Co., Ltd., Beijing, China). PCR amplification was performed in a thermocycler applying the conditions: Denaturation for 1 min at 94°C; Annealing for 45 sec at 56°C; Extension for 1 min at 72°C; Final extension for 10 min at 72°C. The PCR products were visualized through agarose gel electrophoresis and then sequenced by Beijing Qingke Biotechnology Co., Ltd. The obtained sequences were manually curated and compared against the National Center for Biotechnology Information (NCBI) database using BLASTn to identify the most closely related bacterial species. A phylogenetic tree encompassing the strain Pa608 and seven other bacteria within the genus Pseudomonas was constructed using the neighbor-joining algorithm with 1000 bootstrap replicates in MEGA7 .
Protease, cellulase, amylase and phosphate solubility activities of the strain Pa608 were assessed on LB agar medium supplemented with 3% skim milk powder, carboxymethyl cellulose agar medium (K₂HPO₄ 2.5g, Na₂HPO₄ 2.5g, Carboxymethylcellulose sodium 20.0g, Peptone 2.0g, Yeast Extract 0.5g, Agar 14.0g), 1% starch-pancreatic soy agar (Trypticase 15.0g, Enzymatic digest of soybean meal 5.0g, NaCl 5.0g, Soluble Starch 3.0g; Agar 15.0g), and a phosphate solubilization medium (Glucose, 10.0 g; KH 2 PO 4 , 10.9 g; (NH 4 ) 2 SO 4 , 1.0 g; MgSO 4 •7H 2 O, 0.16 g; FeSO 4 •7H 2 O, 0.005 g; CaCl 2 •2H 2 O, 0.011 g; MnCl 2 •4H 2 O, 0.002 g; Agar 14.0g), respectively. The plates were incubated for 3 days at 28°C, and the characteristics of extracellular enzymes were investigated by measuring the transparent zones.
The antimicrobial spectrum of the strain Pa608 was assessed against some plant pathogens, including Sclerotinia sclerotiorum , Pyricularia oryzae , Diaporthe citri , Botrytis cinerea , Fusarium graminearum , and Penicillium simplicissimum . The confrontational culture method, as described earlier, was used to determine the width of the inhibitory zone, which was observed and quantified.
The pepper variety Zhongke M105 f1 was selected for the pot experiment. The pepper seeds were disinfected with 0.1% sodium hypochlorite and thoroughly rinsed with distilled water three times to remove any sodium hypochlorite residue. The treated seeds were then placed on filter paper in a petri dish until germination occurred. Once sprouts emerged, they were transplanted 2 cm deep into soil in a 10-cm wide pot, with one plant per pot. The planting medium consisted of a 2:1 mixture of Walga horticultural nutrient soil and vermiculite. Plants were allowed to grow to the eight-leaf stage, and only robust and uniformly developed plants were selected for subsequent experiments. To prepare the sporangia solution, P . capsici was first inoculated on oatmeal agar and incubated at 25°C for seven days, then transferred to 28°C for 48 hours under continuous illumination to induce sporangia formation. Subsequently, the sporangia were harvested from the agar surface using a brush . The collected culture was then left at room temperature for three hours to encourage zoospore release, and subsequently diluted with distilled water to achieve an inoculation concentration of 2.0×10 4 zoospores/ml. For the strain Pa608, inoculation was carried out in 100 mL LB medium and incubated at 28°C, 150 rpm, for 24 hours to achieve bacterial suspensions with a concentration of 1.0 ×10 8 cells/ml, measured by a spectrophotometer. Three treatments were implemented in the experiment. Treatment 1: Inject 3 ml of sterile water as a control. Treatment 2: inject 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) 1.5 cm deep into the soil , maintaining a distance from the plants to avoid direct contact. Treatment 3: Inject 3 mL of the strain Pa608 bacterial suspension (concentration: 1.0×10 8 cells/ml) into the soil followed by 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml). Each treatment contains 12 pots of peppers, with 3 pepper plants in each pot. Water regularly, maintain high temperature and humidity to promote disease development. Disease severity (DI) was evaluated ten days post-inoculation utilizing a rating scale ranging from 0 to 5 , and the DI was determined using the formula : D I = ( Σ ( s × n ) / ( N × S ) ) × 100 where DI represented the disease index, s denoted the scale rating, n was the number of plants at a specific scale rating, N was the total number of evaluated plants, and S was the maximum scale rating.
Total of 6 pots of pepper plants were divided into 2 treatments, with 3 plants in each treatment. Treatment 1 involved injecting 3 mL of Phytophthora zoospore suspension (2.0×10 4 zoospores/ml) into the soil at the base of the pepper plants , followed by 3 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). Treatment 2 involved injecting 3 mL of the strain Pa608 bacterial suspension into the soil at the base of the pepper plants. Soil samples from the pots were collected on days 1, 3, 5, 10, 15, 30, and 45. The soil samples were subjected to gradient dilution method to detect the quantity of the strain Pa608. Pseudomonas agar medium was used as the culture medium , diluted by a factor of 1, 000, and after incubating at 30°C for 2 days, the colonies were observed for color (blue-green) and counted.
The pepper greenhouse experiment was being conducted at the Vegetable Research Institute base of Hunan Agricultural Sciences Academy in Gaoqiao Town, Changsha County, Hunan Province. In previous years, the greenhouse has suffered from severe disease outbreaks, with an incidence rate of over 90%. The ridges were 1.2 meters wide, with 2 rows per ridge, a plant spacing of 35 cm, and a furrow width of 30 cm. There were 2 treatments: Treatment 1 was the blank control, with each pepper plant root irrigated with 50 mL of sterile water; Treatment 2 involved irrigating each pepper plant root with 50 mL of the strain Pa608 bacterial suspension (1.0 ×10 8 cells/ml). The pepper seedlings were treated 3 days after transplanting, followed by two additional treatments in early June and early July, totaling 3 treatments. Harvesting and recording of plant height, yield and disease incidence were scheduled for July 28th. The disease index was classified according to Sunwoo’s standards as previously mentioned .
The fermentation broth of the strain Pa608 was extracted using ethyl acetate (48 hours of fermentation). The ratio of organic solvent to fermentation broth was 1:1, with an extraction time of 8 hours, repeated three times. The extract was concentrated to a paste at 40°C using a rotary evaporator and stored at 4°C for future use. The gas chromatography-mass spectrometry (GC-MS) was used to analyze the compound composition of the fermentation broth. The GC-MS analysis conditions were selected following the method , with adjustments made to the column temperature ramping up to 300°C at a rate of 10°C/min, hold for 40 min, using helium as the carrier gas with a split ratio set at 20:1, inject 1 μL, and set the injector temperature at 325°C. The mass spectrometry analysis conditions followed the method , with adjustments to stabilize the ion source at 280°C and scan the range from 33 to 600 m/z. The components of volatile compounds were identified by comparing retention times using the NIST mass spectral library. The relative contents were determined based on the percentage of peak areas of different compounds. A structural analysis of volatile organic compounds with antimicrobial potential was conducted based on relevant literature. The data were analyzed using the NIST Mass Spectral Library version 8 (NIST08.L) to match the acquired mass spectra, qualitatively analyze compounds based on matching factors, and retrieve pertinent information for each compound.
The compounds with significant peak areas from the GC-MS results, particularly those previously recognized for their antimicrobial properties, were chosen as potential anti-oomycete substances. The pure form of these selected compounds was acquired and their inhibitory activity against P . capsici was evaluated using the growth rate inhibition method. The final concentrations of the candidate compounds in the PDA medium were 250 mg/L, 50 mg/L, 10 mg/L, and 5 mg/L, with an equal volume of sterile water serving as a control. One 5 mm diameter disc of P . capsici was positioned at the center of each petri dish and then incubated at a constant temperature of 25°C for 7 days. The procedure replicated three times. The inhibitory rate can be calculated using the formula : inhibitory rate = 100% * ((colony diameter in control—disc diameter)—(colony diameter in treatment—disc diameter)) / (colony diameter in control—disc diameter).
Taxonomic identification and characteristics of extracellular enzyme production Total of 209 bacterial strains were isolated from the rhizosphere soil of peppers, among which 23 strains exhibited antagonistic effects against P . capsici , including Pseudomonas, Bacillus and Burkholderia. The strain with the largest inhibition zone was designated as Pa608. After a two-day incubation period at 30°C on an NA plate, the strain Pa608 exhibited green colonies , while on an LB plate, strain Pa608 showed white, smooth colonies without visible pores . The Gram staining results were negative. Scanning electron microscopy observations displayed rod-shaped cells measuring approximately 1–5 μm in length and 0.5–1.0 μm in width . A phylogenetic tree of 16S rRNA sequences showed that the P . aeruginosa WZ2029 was in the same clade as the strain Pa608 with a percent identity of 100.00% , suggesting that they were closely related. Based on morphological characteristics and 16S rRNA sequences, the strain Pa608 was identified as P . aeruginosa . The strain Pa608 can produce protease and cellulose, forming transparent zones , however, no amylase secretion was detected . Moreover, it demonstrated phosphate-solubilizing ability by forming a phosphorus-solubilizing circle . Inhibition effect of the strain Pa608 on P . capsici and other plant pathogens The strain Pa608 demonstrated significant suppression of mycelial growth in P . capsici , forming a marked inhibition zone . Furthermore, it exhibited inhibitory effects to varying degrees on the growth of S . sclerotiorum , P . oryzae , Diaporthe citri , B . cinerea , F . graminearum , and P . simplicissimum . Pot experiment At 45 days after treatment, a significant portion of the pepper plants in the T2 group wilted, with incidence of 100% . Conversely, pepper plants in the T3 group showed no obvious symptoms, resulting in incidence of 12%. The disease index of T2 at 55 was markedly higher than that of T3 at 6.6 . The control efficiency reached 88.0%, indicating the effective suppression of P . capsici by the strain Pa608. Population dynamic of the strain Pa608 in pepper rhizosphere Within the first 15 days after inoculation, the population of the strain Pa608 in the pepper rhizosphere soil rapidly decreases. From day 15 to day 45, the population of the strain Pa608 declines slowly and tends to stabilize . After inoculation with the strain Pa608 alone, the population of Pa608 was slightly higher than the population of Pa608 in the rhizosphere when co-inoculated with P . capsici . This indicates that the strain Pa608 was capable of colonizing the pepper rhizosphere. Field experiment Following the application of the strain Pa608 bacterial suspension, the incidence rate for Treatment 2 was 48.9%, with disease index of 17.3. The rate was notably lower than that of the control group , resulting in control efficiencies of 74.9%. Moreover, the strain Pa608 demonstrated a growth-promoting effect on pepper plants, as seen in the significantly greater height of plants (19.96 cm) and yield (2611.02 g per plant) in Treatment 2 compared to the control group (15.90 cm and 1209.71 g per plant) . Furthermore, pepper plants treated with the strain Pa608 exhibited better health and lower mortality rates compared to those in the control group , where most pepper plants perished. GC-MS analysis The GC-MS analysis data of the sterile filtrate of the strain Pa608 revealed a total of 51 secondary metabolites with a similarity of over 70% . These substances were mainly categorized as alcohols, alkanes, ketones, esters, sesquiterpenes, and phenazines. Among them, 3-carene exhibited a matching factor as high as 88.3% with a peak area of 1,367,054.6. The α-pinene had a matching factor of 86.85% and a peak area of 1,427,453.5 in the detected substances. Biocontrol activity assessment of α-pinene and 3-carene The 3-carene and α-pinene exhibit anti-oomycetes activity against P . capsici . Compared to P . capsici in the control group , α-pinene inhibits P . capsici by 84.9% at a concentration of 5 mg/L , whereas 3-carene only achieves a 35.2% inhibition rate against the pathogen at the same concentration .
Total of 209 bacterial strains were isolated from the rhizosphere soil of peppers, among which 23 strains exhibited antagonistic effects against P . capsici , including Pseudomonas, Bacillus and Burkholderia. The strain with the largest inhibition zone was designated as Pa608. After a two-day incubation period at 30°C on an NA plate, the strain Pa608 exhibited green colonies , while on an LB plate, strain Pa608 showed white, smooth colonies without visible pores . The Gram staining results were negative. Scanning electron microscopy observations displayed rod-shaped cells measuring approximately 1–5 μm in length and 0.5–1.0 μm in width . A phylogenetic tree of 16S rRNA sequences showed that the P . aeruginosa WZ2029 was in the same clade as the strain Pa608 with a percent identity of 100.00% , suggesting that they were closely related. Based on morphological characteristics and 16S rRNA sequences, the strain Pa608 was identified as P . aeruginosa . The strain Pa608 can produce protease and cellulose, forming transparent zones , however, no amylase secretion was detected . Moreover, it demonstrated phosphate-solubilizing ability by forming a phosphorus-solubilizing circle .
P . capsici and other plant pathogens The strain Pa608 demonstrated significant suppression of mycelial growth in P . capsici , forming a marked inhibition zone . Furthermore, it exhibited inhibitory effects to varying degrees on the growth of S . sclerotiorum , P . oryzae , Diaporthe citri , B . cinerea , F . graminearum , and P . simplicissimum .
At 45 days after treatment, a significant portion of the pepper plants in the T2 group wilted, with incidence of 100% . Conversely, pepper plants in the T3 group showed no obvious symptoms, resulting in incidence of 12%. The disease index of T2 at 55 was markedly higher than that of T3 at 6.6 . The control efficiency reached 88.0%, indicating the effective suppression of P . capsici by the strain Pa608.
Within the first 15 days after inoculation, the population of the strain Pa608 in the pepper rhizosphere soil rapidly decreases. From day 15 to day 45, the population of the strain Pa608 declines slowly and tends to stabilize . After inoculation with the strain Pa608 alone, the population of Pa608 was slightly higher than the population of Pa608 in the rhizosphere when co-inoculated with P . capsici . This indicates that the strain Pa608 was capable of colonizing the pepper rhizosphere.
Following the application of the strain Pa608 bacterial suspension, the incidence rate for Treatment 2 was 48.9%, with disease index of 17.3. The rate was notably lower than that of the control group , resulting in control efficiencies of 74.9%. Moreover, the strain Pa608 demonstrated a growth-promoting effect on pepper plants, as seen in the significantly greater height of plants (19.96 cm) and yield (2611.02 g per plant) in Treatment 2 compared to the control group (15.90 cm and 1209.71 g per plant) . Furthermore, pepper plants treated with the strain Pa608 exhibited better health and lower mortality rates compared to those in the control group , where most pepper plants perished.
The GC-MS analysis data of the sterile filtrate of the strain Pa608 revealed a total of 51 secondary metabolites with a similarity of over 70% . These substances were mainly categorized as alcohols, alkanes, ketones, esters, sesquiterpenes, and phenazines. Among them, 3-carene exhibited a matching factor as high as 88.3% with a peak area of 1,367,054.6. The α-pinene had a matching factor of 86.85% and a peak area of 1,427,453.5 in the detected substances.
The 3-carene and α-pinene exhibit anti-oomycetes activity against P . capsici . Compared to P . capsici in the control group , α-pinene inhibits P . capsici by 84.9% at a concentration of 5 mg/L , whereas 3-carene only achieves a 35.2% inhibition rate against the pathogen at the same concentration .
The inhibitory activity of the strain Pa608 against P . capsici The utilization of soil-borne biocontrol microorganisms in the rhizosphere to suppress soil-borne pathogens is a significant research focus in sustainable agriculture, benefiting from ample available resources . In our investigation, the P . aeruginosa strain Pa608 exhibited notable inhibitory activity against P . capsici both in vitro and in vivo , consistent with previous findings on Pseudomonas in combating P . capsici . Pseudomonas exhibits a broad antimicrobial spectrum, capable of inhibiting a diverse range of plant pathogens, including fungi and oomycetes. Particularly, destructive species like P . cactorum , P . capsici , and P . infestans can also be suppressed by certain Pseudomonas species . In our research, we observed suppression of mycelial growth by the strain Pa608, consistent with findings from previous studies . However, the investigation did not include an assessment of the suppression of zoospore germination and germ tube elongation by the strain Pa608. It was possible to speculate that the strain Pa608 may also inhibit the germination of motile spores and germ tube elongation of Phytophthora in peppers, as strains of the same P . aeruginosa species have demonstrated similar activities . Our pot experiment showed that the strain Pa608 exhibited a high control efficiency against pepper Phytophthora blight at 88.0%, surpassing the control efficiency of 73.1% achieved by Streptomyces olivaceus and the 77% control efficiency reported for P . lini . Furthermore, the control efficiency in field trials by the strain Pa608 was 74.9%, equivalent to the field efficacy (75.16%) of the combination of XJC2-1 and the fungicide dimethomorph , suggesting its potential in field management. Moreover, the high control efficiency also reflected the stability of strain Pa608 in the pepper rhizosphere. However, the control efficiency of the strain Pa608 was lower than that of the Bacillus mixture at 88.0% . This indicates that multi-species combinations of microorganisms demonstrate higher efficacy in biological control compared to single strains. The trend in the development of biological control is to utilize artificially synthesized microbial communities to fully leverage the advantages of diverse microbial combinations, continuously and effectively exerting biological control . In this study, we successfully isolated Bacillus and Burkholderia from the rhizosphere of peppers. The next step involves screening these bacteria to construct a microbial community for biological control centered around the strain Pa608. Colonization characteristic of the strain Pa608 in pepper rhizosphere and their growth-promoting features The effectiveness of biological control primarily depends on the population density of biocontrol microorganisms that can easily colonize the plant rhizosphere and reproduce quickly, enabling them to exert long-lasting control effects . Consequently, biocontrol microorganisms with wide adaptability and easy colonization have become the preferred choice for researchers in plant protection. Pseudomonas spp. are widely distributed in the environment and have developed adaptive mechanisms to colonize a wide range of ecological niches, such as animal hosts, water environments and rhizosphere . In particular, in the plant rhizosphere, Pseudomonas can thrive by utilizing plant exudates, leading to their abundant proliferation. The strain Pa608 was isolated from pepper rhizosphere soil, demonstrating their colonization in soil. Moreover, the results of detection confirmed that the strain Pa608 could survive in the rhizosphere soil for up to 45 days. However, the population of the strain Pa608 declined after inoculation and stabilized at a later period, possibly due to the following reasons: under natural conditions, the number of Pa608 present in the soil was significantly lower than the number introduced through inoculation, resulting in the death of excess Pa608 due to limited nutrients. In the later stages of pepper growth, as pepper roots proliferate and exudates increase, they could nourish Pa608 and sustain their population size. The strain Pa608 demonstrated a growth-promoting effect on pepper plants, as evidenced by the significantly greater plant height and yield. Most biocontrol Pseudomonas species exhibit plant growth promotion activity, with mechanisms including phosphate solubilization and production of indole acetic acid . We found that the strain Pa608 possessed phosphate-solubilizing capability, which facilitates the dissolution of phosphorus, aiding in its uptake by peppers and indirectly promoting pepper growth. The production of indole acetic acid by the strain Pa608 needs further verification. Anti-oomycete activity of low molecular weight substances with volatility produced by the strain Pa608 P . aeruginosa is known to produce various secondary metabolites that play a crucial role in its virulence and interactions with other organisms . In our study, the strain Pa608 produced many secondary metabolites, including alcohols, alkanes, ketones, esters, sesquiterpenes, and phenazines. Different strains of P . aeruginosa may also produce similar substances, but there may be differences in the types and amounts. The types and quantities of secondary metabolites produced by P . aeruginosa are related to the genetic characteristics of the strain, the type of culture medium, and environmental conditions. Phenazine compounds are redox-active nitrogen-containing heterocyclic molecules that exhibit broad-spectrum antibiotic activity against various fungal, bacterial, and oomycete plant pathogens . For instance, phenazine-1-carboxylic acid, which is secreted by the P . aeruginosa strain GC-B26, has been shown to inhibit the growth of both P . capsici and C . orbiculare . In this research, 1,6-Dimethylphenazine and 1-Hydroxy-6-methylphenazine was detected from fermentation broth of the strain Pa608, indicating that P . capsici itself may produce certain types of phenazine compounds. The focus of our research was on low molecular weight substances with volatility, diverging from previous studies that centered on phenazines and cyclic lipopeptides . 3-carene is low molecular weight substance, possessed volatility and antimicrobial properties , which exhibited anti-oomycetes to some extent in our research. Particularly, α-pinene, secreted by the strain Pa608, demonstrated significant anti-oomycete activity with an 84.9% inhibition. Previous research has indicated that Burkholderia tropica produced α-pinene, which inhibits the growth of fungal pathogens such as Colletotrichum gloeosporioides , F . culmorum , F . oxysporum , and Sclerotium rolfsii and destructs fungal hyphae , suggesting the potential of α-pinene in developing novel fungicides.
P . capsici The utilization of soil-borne biocontrol microorganisms in the rhizosphere to suppress soil-borne pathogens is a significant research focus in sustainable agriculture, benefiting from ample available resources . In our investigation, the P . aeruginosa strain Pa608 exhibited notable inhibitory activity against P . capsici both in vitro and in vivo , consistent with previous findings on Pseudomonas in combating P . capsici . Pseudomonas exhibits a broad antimicrobial spectrum, capable of inhibiting a diverse range of plant pathogens, including fungi and oomycetes. Particularly, destructive species like P . cactorum , P . capsici , and P . infestans can also be suppressed by certain Pseudomonas species . In our research, we observed suppression of mycelial growth by the strain Pa608, consistent with findings from previous studies . However, the investigation did not include an assessment of the suppression of zoospore germination and germ tube elongation by the strain Pa608. It was possible to speculate that the strain Pa608 may also inhibit the germination of motile spores and germ tube elongation of Phytophthora in peppers, as strains of the same P . aeruginosa species have demonstrated similar activities . Our pot experiment showed that the strain Pa608 exhibited a high control efficiency against pepper Phytophthora blight at 88.0%, surpassing the control efficiency of 73.1% achieved by Streptomyces olivaceus and the 77% control efficiency reported for P . lini . Furthermore, the control efficiency in field trials by the strain Pa608 was 74.9%, equivalent to the field efficacy (75.16%) of the combination of XJC2-1 and the fungicide dimethomorph , suggesting its potential in field management. Moreover, the high control efficiency also reflected the stability of strain Pa608 in the pepper rhizosphere. However, the control efficiency of the strain Pa608 was lower than that of the Bacillus mixture at 88.0% . This indicates that multi-species combinations of microorganisms demonstrate higher efficacy in biological control compared to single strains. The trend in the development of biological control is to utilize artificially synthesized microbial communities to fully leverage the advantages of diverse microbial combinations, continuously and effectively exerting biological control . In this study, we successfully isolated Bacillus and Burkholderia from the rhizosphere of peppers. The next step involves screening these bacteria to construct a microbial community for biological control centered around the strain Pa608.
The effectiveness of biological control primarily depends on the population density of biocontrol microorganisms that can easily colonize the plant rhizosphere and reproduce quickly, enabling them to exert long-lasting control effects . Consequently, biocontrol microorganisms with wide adaptability and easy colonization have become the preferred choice for researchers in plant protection. Pseudomonas spp. are widely distributed in the environment and have developed adaptive mechanisms to colonize a wide range of ecological niches, such as animal hosts, water environments and rhizosphere . In particular, in the plant rhizosphere, Pseudomonas can thrive by utilizing plant exudates, leading to their abundant proliferation. The strain Pa608 was isolated from pepper rhizosphere soil, demonstrating their colonization in soil. Moreover, the results of detection confirmed that the strain Pa608 could survive in the rhizosphere soil for up to 45 days. However, the population of the strain Pa608 declined after inoculation and stabilized at a later period, possibly due to the following reasons: under natural conditions, the number of Pa608 present in the soil was significantly lower than the number introduced through inoculation, resulting in the death of excess Pa608 due to limited nutrients. In the later stages of pepper growth, as pepper roots proliferate and exudates increase, they could nourish Pa608 and sustain their population size. The strain Pa608 demonstrated a growth-promoting effect on pepper plants, as evidenced by the significantly greater plant height and yield. Most biocontrol Pseudomonas species exhibit plant growth promotion activity, with mechanisms including phosphate solubilization and production of indole acetic acid . We found that the strain Pa608 possessed phosphate-solubilizing capability, which facilitates the dissolution of phosphorus, aiding in its uptake by peppers and indirectly promoting pepper growth. The production of indole acetic acid by the strain Pa608 needs further verification.
P . aeruginosa is known to produce various secondary metabolites that play a crucial role in its virulence and interactions with other organisms . In our study, the strain Pa608 produced many secondary metabolites, including alcohols, alkanes, ketones, esters, sesquiterpenes, and phenazines. Different strains of P . aeruginosa may also produce similar substances, but there may be differences in the types and amounts. The types and quantities of secondary metabolites produced by P . aeruginosa are related to the genetic characteristics of the strain, the type of culture medium, and environmental conditions. Phenazine compounds are redox-active nitrogen-containing heterocyclic molecules that exhibit broad-spectrum antibiotic activity against various fungal, bacterial, and oomycete plant pathogens . For instance, phenazine-1-carboxylic acid, which is secreted by the P . aeruginosa strain GC-B26, has been shown to inhibit the growth of both P . capsici and C . orbiculare . In this research, 1,6-Dimethylphenazine and 1-Hydroxy-6-methylphenazine was detected from fermentation broth of the strain Pa608, indicating that P . capsici itself may produce certain types of phenazine compounds. The focus of our research was on low molecular weight substances with volatility, diverging from previous studies that centered on phenazines and cyclic lipopeptides . 3-carene is low molecular weight substance, possessed volatility and antimicrobial properties , which exhibited anti-oomycetes to some extent in our research. Particularly, α-pinene, secreted by the strain Pa608, demonstrated significant anti-oomycete activity with an 84.9% inhibition. Previous research has indicated that Burkholderia tropica produced α-pinene, which inhibits the growth of fungal pathogens such as Colletotrichum gloeosporioides , F . culmorum , F . oxysporum , and Sclerotium rolfsii and destructs fungal hyphae , suggesting the potential of α-pinene in developing novel fungicides.
Taken together, the strain P . aeruginosa Pa608 exhibits strong inhibitory activity against P . capsici , significantly reducing the pot and field incidence rate and increasing pepper height and yield. In particular, this strain can produce α-pinene, effectively inhibiting the growth of P . capsici . The next step is to further explore the mechanism of α-pinene against P . capsici and the synthesis pathway of α-pinene in the strain Pa608.
S1 Table Major substances in ethyl acetate extracts. (DOCX) S1 Fig Characteristics of extracellular enzyme production. A, protease. B, cellulose. C, amylase. D, phosphorylase. (TIF) S2 Fig Inhibition effect of the strain Pa608 on some pathogens. A, P . capsici . B, S . sclerotiorum . C, P . oryzae . D, Diaporthe citri . E, B . cinerea . F, F . graminearum . G, P . simplicissimum . (TIF)
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Impact of re-operation on progression-free survival in patients with recurrent GBM: Experience in a tertiary referral center | fec9c2c8-a295-4d7c-a455-2b49413c64a2 | 11785342 | Surgical Procedures, Operative[mh] | Glioblastoma multiforme (GBM) is the deadliest and most prevalent form of primary brain tumors in adults. According to the 2021 WHO Classification of Tumors of the Central Nervous System, glioblastoma is classified as a WHO grade 4 glioma based on molecular and histopathological features. It represents approximately 47.1% of all malignant tumors of the central nervous system (CNS), making it the most common malignant brain tumor . Its global incidence rate stands at approximately 3–4/100,000 person-years, although regional variability exists . The cornerstone of initial therapy for glioblastoma multiforme (GBM) is surgical resection, followed by adjuvant radiotherapy and temozolomide therapy, with additional options including immunotherapy or anti-angiogenic therapy. However, despite the aggressiveness of these regimens, their limited efficacy underscores its grim prognosis . GBM is characterized by its continuous progression, a hallmark that prompted the development of standardized criteria for its assessment . The Macdonald Criteria , introduced to provide a uniform method of evaluation, defines progression as a 25% increase in the sum of new lesions, perpendicular diameters of enhancing lesions, and clinical deterioration. The Response Assessment in Neuro-Oncology (RANO) criteria have since evolved to offer an updated framework, emphasizing significant increases in non-enhancing lesions, FLAIR, as well as recognizing the insufficiency of post-contrast enhancement alone due to the infiltrative nature of GBM. Despite current treatments, the median progression-free survival (PFS) remains relatively short, ranging from 4.4 to 8.4 months in newly diagnosed GBM cases . To improve outcomes, novel therapeutic strategies have been developed for recurrent cases, including new targeted therapies, angiogenesis inhibitors, and gamma knife surgery . Recent studies have identified a range of clinical and molecular variables that significantly influence survival and recurrence in glioblastoma. Factors such as patient age, extent of surgical resection, molecular markers like MGMT methylation status, and the presence of genetic mutations have been shown to impact both progression-free survival and overall survival in glioblastoma patients . Surgical approaches have also become a more frequently utilized option and are utilized in 10–30% of GBM cases . Reoperation for recurrent glioblastoma was pioneered by Pool in 1968. However, only a limited number of studies have examined its impact on glioblastoma recurrence. Nonetheless, reoperation has shown promise in improving PFS and overall survival in select patients. In addition, published evidence, particularly from Berger et al. and other researchers, indicates similar outcomes . For patients undergoing repeat surgery, the NIH Recurrent Glioblastoma Scale offers a means to stratify outcomes. In the most favorable scenario, the median survival reached 9.2 months, contrasting sharply with the poorest-performing group, which experienced a median survival of only 1.9 months . Overall, re-do craniotomy was shown to have enhanced survival outcomes. However, conducting randomized studies on reoperation is challenging due to the heterogenetic nature of recurrent GBM. Furthermore, emerging research has highlighted the role of tumor stem cell dissemination in glioblastoma, particularly following ventricular opening during surgical resection. This process may contribute to the aggressive nature of glioblastoma recurrence, as the migration of tumor stem cells to distant sites within the brain increases the likelihood of tumor regrowth and progression after surgery. Such findings suggest that strategies targeting tumor stem cell spread could offer potential avenues for improving treatment efficacy in glioblastoma patients . Additionally, the existing literature is predominantly retrospective, leading to potential confounding by selection bias. There is still some controversy on whether or not re-operation should be performed in patients with recurrent GBM, if this will offer any benefit regarding PFS, and, if any, what factors are correlated with significant benefit upon re-operation. Therefore, reoperation remains a topic of debate, particularly based on its applications and effectiveness . Herein, we present a literature review on the matter while also presenting our data on patients with recurrent GBM in a tertiary referral center.
This study retrospectively reviewed medical records from the American University of Beirut Medical Center (AUBMC) over a ten-year period, from 01/01/2012 to 01/01/2023. The data for this study were accessed from 04/04/2023 to 03/04/2024, inclusive. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki (2013) and its later amendments or equivalent ethical guidelines. Approval was granted by the Institutional Review Board (IRB) at AUBMC (study protocol ID: BIO-2023-0075) prior to data collection. All data were anonymized to ensure confidentiality, and the authors did not have access to any information that could identify individual participants during or after data collection. The information collected was fully anonymous, serially coded, and will remain confidential after the study concludes. Inclusion criteria This study included patients diagnosed with recurrent glioblastoma multiforme (GBM) following initial surgical resection, with histologically confirmed GBM, classified according to the 2021 WHO Classification of Tumors of the Central Nervous System. While the 2021 classification was used for analysis, IDH-mutant GBM cases were not reclassified from the initial diagnoses based on the 2016 classification. Only patients who underwent a single reoperation for recurrence were included; those with multiple resections were excluded. Tumors located in midline, thalamic, or infratentorial areas were excluded from the analysis. Patients who had undergone only biopsy were also excluded. Recurrence or progression was evaluated according to the Response Assessment in Neuro-Oncology (RANO) criteria, with pseudo-progression and necrosis excluded by MRI spectroscopy. Two groups were analyzed: those who underwent reoperation and those who received medical management upon recurrence. Statistical analysis Continuous variables were described as means ± standard deviations or medians (interquartile range), and categorical variables were reported as frequencies and percentages. For inferential statistics, we evaluated significant associations with the decision to undergo reoperation using the Chi-square test for categorical variables and the t-test for continuous variables. All p-values were two-sided, and a significance level of p < 0.05 was applied to all analyses. The statistical analyses were performed using the SPSS version 29.0 statistical package. Survival analysis Time to progression and overall survival were analyzed using the Kaplan-Meier method, with differences between groups assessed by the log-rank test. As a secondary objective, we performed a univariable Kaplan-Meier analysis to identify predictors of poor overall survival in patients with recurrent GBM. We also conducted a multivariable Cox regression analysis to assess independent predictors of poor overall survival in this cohort.
This study included patients diagnosed with recurrent glioblastoma multiforme (GBM) following initial surgical resection, with histologically confirmed GBM, classified according to the 2021 WHO Classification of Tumors of the Central Nervous System. While the 2021 classification was used for analysis, IDH-mutant GBM cases were not reclassified from the initial diagnoses based on the 2016 classification. Only patients who underwent a single reoperation for recurrence were included; those with multiple resections were excluded. Tumors located in midline, thalamic, or infratentorial areas were excluded from the analysis. Patients who had undergone only biopsy were also excluded. Recurrence or progression was evaluated according to the Response Assessment in Neuro-Oncology (RANO) criteria, with pseudo-progression and necrosis excluded by MRI spectroscopy. Two groups were analyzed: those who underwent reoperation and those who received medical management upon recurrence.
Continuous variables were described as means ± standard deviations or medians (interquartile range), and categorical variables were reported as frequencies and percentages. For inferential statistics, we evaluated significant associations with the decision to undergo reoperation using the Chi-square test for categorical variables and the t-test for continuous variables. All p-values were two-sided, and a significance level of p < 0.05 was applied to all analyses. The statistical analyses were performed using the SPSS version 29.0 statistical package.
Time to progression and overall survival were analyzed using the Kaplan-Meier method, with differences between groups assessed by the log-rank test. As a secondary objective, we performed a univariable Kaplan-Meier analysis to identify predictors of poor overall survival in patients with recurrent GBM. We also conducted a multivariable Cox regression analysis to assess independent predictors of poor overall survival in this cohort.
Patient and tumor characteristics A total of 243 patients were initially identified. However, 34 patients who had undergone only a biopsy without subsequent resection and 84 patients who had undergone surgical resection at our institution without follow-up on recurrence were excluded. Finally, data from 125 patients were included in our analysis. Of these, 84 patients had undergone a single resection, and 41 patients had undergone repeat resection . The mean age of patients who underwent single resection was 53.11 ± 18.5 years, compared to 50.15 ± 13.4 years for those who underwent repeat resection (p = 0.363). Gender distribution was similar across both groups, with males constituting 72.6% of the single resection cohort and 68.3% of the repeat resection cohort (p = 0.616). Influence of factors on the decision to undergo repeat resection Analysis revealed that several factors significantly influenced the decision to pursue repeat resection. The Charlson Comorbidity Index showed a marked difference between the two groups. A higher proportion of patients undergoing repeat resection had a Charlson Comorbidity Index ≤ 3 (65.9%) compared to those undergoing single resection (44%) (p = 0.022). This suggests that patients with fewer comorbidities were more likely to undergo repeat resection. Complications following the first surgery were notably less frequent in patients who chose to undergo repeat resection. Specifically, only 4.9% of patients who underwent repeat resection experienced complications following the initial surgery compared to 21.4% in the single resection group (p = 0.018). On multivariable analysis, complications following the first surgery emerged as the only significant factor associated with the decision not to undergo reoperation (p = 0.019). There were no significant differences in tumor location distribution between both groups, and the temporal location was the most common in both groups (40.5% in single resection vs. 31.7% in repeat resection, p = 0.195). The tumor side was evenly distributed, with 44% of the single resection group and 43.9% of the repeat resection group having right-sided tumors (p = 1.000). Tumor size was also comparable between the groups, with 62.7% of the single resection group and 48.4% of the repeat resection group having tumors ≤ 5 cm (p = 0.175). The extent of tumor resection revealed that 46.2% of the single resection group and 55.6% of the repeat resection group achieved gross total resection upon initial surgery (p = 0.351). The IDH mutational status was wildtype in 87.7% of the single resection group and 72.7% of the repeat resection group (p = 0.104). A high Ki67 index, typically considered above 20–30%, was found in 97.5% of the single resection group and 93.3% of the repeat resection group (p = 0.303). Adjuvant treatment after the first surgery mainly consisted of chemoradiation and adjunctive chemotherapy (STUPP protocol), with 88% of patients in the single resection group and 87.8% in the repeat resection group (p = 0.681) undergoing oncotherapy after the first surgery. Upon recurrence, the tumor was found at the same site in 93.5% of patients in the single resection group and 97.5% of patients in the repeat resection group (p = 0.328). Complications following first surgery The most common complications following the first surgery in the single resection group included deep vein thrombosis, hemiparesis/weakness, and seizures . Other complications such as intracranial bleeding/stroke, wound infection, aphasia, facial palsy, and loss of vision were less frequent. In the repeat resection group, complications included deep vein thrombosis and seizures. Survival rates Survival was analyzed across three key metrics: Overall Survival (OS), Post-Progression Survival (PPS), and Progression-Free Survival (PFS). OS was defined as the time from initial diagnosis to death or the end of follow-up, reflecting the length of time a patient lives after diagnosis. PPS was defined as the time from the first recurrence to death or the end of follow-up, indicating survival after the disease has recurred. PFS was defined as the time from initial diagnosis until disease progression or recurrence, capturing the duration of disease control before progression or recurrence. Our analysis revealed significant findings related to reoperation. Patients who underwent reoperation had a median PFS of 15.9 months (95% CI: 13.906–17.828), compared to just 6.7 months (95% CI: 5.499–7.834) for those who did not undergo reoperation (log-rank p < 0.001) . This indicates that a longer PFS is associated with the decision to undergo repeat resection. Regarding PPS, the median survival time after progression was 5.9 months (95% CI: 2.145–9.589) for patients who underwent reoperation upon recurrence, compared to 5.1 months (95% CI: 3.425–6.775) for those who did not (log-rank p = 0.065) . As for OS, patients who underwent reoperation had a median survival of 21 months (95% CI: 10.963–31.037), which was significantly longer than the 11 months (95% CI: 8.605–13.395) observed for those who did not have a reoperation (log-rank p < 0.001) . Adjuvant treatment following recurrence Following recurrence, 82 patients (80%) received adjuvant treatment, while 20 patients (20%) did not receive any further treatment. Among those who underwent adjuvant treatment, the modalities varied. Eighteen patients were treated with chemoradiotherapy (ChemoRT) combined with adjunct chemotherapy (Adj. CHT), and 17 patients received radiotherapy (RT) alone. Sixteen patients were administered temozolomide alone. Bevacizumab was used in 60 patients, and 17 patients received Lomustine. Other treatment options included Afinitor, Gefitinib, Irinotecan, Nivolumab, Etoposide, Panitumumab, and Regorafenib. The mean duration of adjuvant treatment after recurrence was 8 ±13 months. Complications following repeat resection In the repeat resection group, the most common complications were pulmonary embolism and seizures, each occurring in 2 patients . Other complications included weakness and cerebrospinal fluid (CSF) leak. Predictors of Overall Survival (OS) The univariable Kaplan-Meier analysis identified several predictors of poor OS in patients with recurrent glioblastoma . Gender did not significantly influence survival; however, the Charlson Comorbidity Index was a significant predictor of survival. Patients with an index of ≤3 had a median survival of 17 months (95% CI: 14.910–19.090) compared to 13 months (95% CI: 7.539–17.191) for those with an index >3, with a p-value of 0.038. ASA classification also had a significant impact on survival. Patients with an ASA classification of <3 had a median survival of 16 months (95% CI: 13.371–18.629), while those with an ASA classification of ≥3 had a median survival of 11 months (95% CI: 6.328–15.672), with a p-value of 0.003. Tumor location within the brain lobes resulted in comparable survival outcomes: patients with temporal lobe tumors, parietal lobe tumors, frontal lobe tumors, occipital lobe tumors, and those with tumors in other locations had a median survival of 14 months (95% CI: 10.605–17.395), 16 months (95% CI: 7.684–24.316), (95% CI: 11.136–18.864), 16 months (95% CI: 0.000–43.440), and 12 months (95% CI: 5.999–18.001), respectively (p = 0.314). Side-specific tumor location demonstrated that patients with right-sided tumors had a median survival of 15 months (95% CI: 11.396–18.604), compared to 17 months (95% CI: 14.306–19.694) for those with left-sided tumors and 4 months for those with bilateral tumors, with a significant p-value of 0.034. Tumor focality was a strong predictor of survival, as patients with unifocal tumors had a median survival of 17 months (95% CI: 15.111–18.889), while those with multifocal tumors had a median survival of only 6 months (95% CI: 2.801–9.199), with a highly significant p-value of <0.001. The extent of tumor resection following the first surgery significantly influenced survival, with an initial gross total resection (GTR) resulting in a median survival of 18 months (95% CI: 10.671–25.329) compared to 11 months (95% CI: 6.522–15.478) for subtotal resection (p = 0.001). IDH mutational status, as well as Ki-67 index levels, did not influence survival. Oncotherapy after the first surgery was a significant factor affecting survival. Patients undergoing resection only had a median survival of 5 months (95% CI: 3.868–6.132), while those receiving radiotherapy alone had a median survival of 14 months (95% CI: 0.000–28.761). Conversely, those treated with chemoradiotherapy, and adjuvant chemotherapy (STUPP protocol) had a median survival of 16 months (95% CI: 14.052–17.948), with a significant p-value of 0.021. Post-surgery complications did not significantly affect survival. Both groups, those with and without complications, had a median survival of 15 months (95% CI: 6.235–23.765 for those with complications and 12.992–17.008 for those without) (p = 0.653). There was no difference in survival based on the location of recurrence (p = 0.442). In the multivariable Cox regression analysis, several factors were evaluated for their impact on overall survival in patients with recurrent glioblastoma . Tumor focality emerged as a significant predictor, with multifocal tumors associated with poorer survival compared to unifocal tumors (HR: 0.507, 95% CI: 0.274–0.935, p = 0.030). Oncotherapy after the first surgery also demonstrated a strong impact on survival. Patients who underwent radiotherapy alone had significantly worse outcomes (HR: 7.032, 95% CI: 2.378–20.798, p<0.001) compared to those who received the STUPP protocol. The extent of tumor resection showed a trend towards improved survival with gross total resection (GTR), though this was not statistically significant (HR: 0.663, 95% CI: 0.430–1.022, p = 0.063). Other variables, such as the Charlson Comorbidity Index and ASA classification, did not show significant associations with survival after adjusting for confounding factors.
A total of 243 patients were initially identified. However, 34 patients who had undergone only a biopsy without subsequent resection and 84 patients who had undergone surgical resection at our institution without follow-up on recurrence were excluded. Finally, data from 125 patients were included in our analysis. Of these, 84 patients had undergone a single resection, and 41 patients had undergone repeat resection . The mean age of patients who underwent single resection was 53.11 ± 18.5 years, compared to 50.15 ± 13.4 years for those who underwent repeat resection (p = 0.363). Gender distribution was similar across both groups, with males constituting 72.6% of the single resection cohort and 68.3% of the repeat resection cohort (p = 0.616).
Analysis revealed that several factors significantly influenced the decision to pursue repeat resection. The Charlson Comorbidity Index showed a marked difference between the two groups. A higher proportion of patients undergoing repeat resection had a Charlson Comorbidity Index ≤ 3 (65.9%) compared to those undergoing single resection (44%) (p = 0.022). This suggests that patients with fewer comorbidities were more likely to undergo repeat resection. Complications following the first surgery were notably less frequent in patients who chose to undergo repeat resection. Specifically, only 4.9% of patients who underwent repeat resection experienced complications following the initial surgery compared to 21.4% in the single resection group (p = 0.018). On multivariable analysis, complications following the first surgery emerged as the only significant factor associated with the decision not to undergo reoperation (p = 0.019). There were no significant differences in tumor location distribution between both groups, and the temporal location was the most common in both groups (40.5% in single resection vs. 31.7% in repeat resection, p = 0.195). The tumor side was evenly distributed, with 44% of the single resection group and 43.9% of the repeat resection group having right-sided tumors (p = 1.000). Tumor size was also comparable between the groups, with 62.7% of the single resection group and 48.4% of the repeat resection group having tumors ≤ 5 cm (p = 0.175). The extent of tumor resection revealed that 46.2% of the single resection group and 55.6% of the repeat resection group achieved gross total resection upon initial surgery (p = 0.351). The IDH mutational status was wildtype in 87.7% of the single resection group and 72.7% of the repeat resection group (p = 0.104). A high Ki67 index, typically considered above 20–30%, was found in 97.5% of the single resection group and 93.3% of the repeat resection group (p = 0.303). Adjuvant treatment after the first surgery mainly consisted of chemoradiation and adjunctive chemotherapy (STUPP protocol), with 88% of patients in the single resection group and 87.8% in the repeat resection group (p = 0.681) undergoing oncotherapy after the first surgery. Upon recurrence, the tumor was found at the same site in 93.5% of patients in the single resection group and 97.5% of patients in the repeat resection group (p = 0.328).
The most common complications following the first surgery in the single resection group included deep vein thrombosis, hemiparesis/weakness, and seizures . Other complications such as intracranial bleeding/stroke, wound infection, aphasia, facial palsy, and loss of vision were less frequent. In the repeat resection group, complications included deep vein thrombosis and seizures.
Survival was analyzed across three key metrics: Overall Survival (OS), Post-Progression Survival (PPS), and Progression-Free Survival (PFS). OS was defined as the time from initial diagnosis to death or the end of follow-up, reflecting the length of time a patient lives after diagnosis. PPS was defined as the time from the first recurrence to death or the end of follow-up, indicating survival after the disease has recurred. PFS was defined as the time from initial diagnosis until disease progression or recurrence, capturing the duration of disease control before progression or recurrence. Our analysis revealed significant findings related to reoperation. Patients who underwent reoperation had a median PFS of 15.9 months (95% CI: 13.906–17.828), compared to just 6.7 months (95% CI: 5.499–7.834) for those who did not undergo reoperation (log-rank p < 0.001) . This indicates that a longer PFS is associated with the decision to undergo repeat resection. Regarding PPS, the median survival time after progression was 5.9 months (95% CI: 2.145–9.589) for patients who underwent reoperation upon recurrence, compared to 5.1 months (95% CI: 3.425–6.775) for those who did not (log-rank p = 0.065) . As for OS, patients who underwent reoperation had a median survival of 21 months (95% CI: 10.963–31.037), which was significantly longer than the 11 months (95% CI: 8.605–13.395) observed for those who did not have a reoperation (log-rank p < 0.001) .
Following recurrence, 82 patients (80%) received adjuvant treatment, while 20 patients (20%) did not receive any further treatment. Among those who underwent adjuvant treatment, the modalities varied. Eighteen patients were treated with chemoradiotherapy (ChemoRT) combined with adjunct chemotherapy (Adj. CHT), and 17 patients received radiotherapy (RT) alone. Sixteen patients were administered temozolomide alone. Bevacizumab was used in 60 patients, and 17 patients received Lomustine. Other treatment options included Afinitor, Gefitinib, Irinotecan, Nivolumab, Etoposide, Panitumumab, and Regorafenib. The mean duration of adjuvant treatment after recurrence was 8 ±13 months.
In the repeat resection group, the most common complications were pulmonary embolism and seizures, each occurring in 2 patients . Other complications included weakness and cerebrospinal fluid (CSF) leak.
The univariable Kaplan-Meier analysis identified several predictors of poor OS in patients with recurrent glioblastoma . Gender did not significantly influence survival; however, the Charlson Comorbidity Index was a significant predictor of survival. Patients with an index of ≤3 had a median survival of 17 months (95% CI: 14.910–19.090) compared to 13 months (95% CI: 7.539–17.191) for those with an index >3, with a p-value of 0.038. ASA classification also had a significant impact on survival. Patients with an ASA classification of <3 had a median survival of 16 months (95% CI: 13.371–18.629), while those with an ASA classification of ≥3 had a median survival of 11 months (95% CI: 6.328–15.672), with a p-value of 0.003. Tumor location within the brain lobes resulted in comparable survival outcomes: patients with temporal lobe tumors, parietal lobe tumors, frontal lobe tumors, occipital lobe tumors, and those with tumors in other locations had a median survival of 14 months (95% CI: 10.605–17.395), 16 months (95% CI: 7.684–24.316), (95% CI: 11.136–18.864), 16 months (95% CI: 0.000–43.440), and 12 months (95% CI: 5.999–18.001), respectively (p = 0.314). Side-specific tumor location demonstrated that patients with right-sided tumors had a median survival of 15 months (95% CI: 11.396–18.604), compared to 17 months (95% CI: 14.306–19.694) for those with left-sided tumors and 4 months for those with bilateral tumors, with a significant p-value of 0.034. Tumor focality was a strong predictor of survival, as patients with unifocal tumors had a median survival of 17 months (95% CI: 15.111–18.889), while those with multifocal tumors had a median survival of only 6 months (95% CI: 2.801–9.199), with a highly significant p-value of <0.001. The extent of tumor resection following the first surgery significantly influenced survival, with an initial gross total resection (GTR) resulting in a median survival of 18 months (95% CI: 10.671–25.329) compared to 11 months (95% CI: 6.522–15.478) for subtotal resection (p = 0.001). IDH mutational status, as well as Ki-67 index levels, did not influence survival. Oncotherapy after the first surgery was a significant factor affecting survival. Patients undergoing resection only had a median survival of 5 months (95% CI: 3.868–6.132), while those receiving radiotherapy alone had a median survival of 14 months (95% CI: 0.000–28.761). Conversely, those treated with chemoradiotherapy, and adjuvant chemotherapy (STUPP protocol) had a median survival of 16 months (95% CI: 14.052–17.948), with a significant p-value of 0.021. Post-surgery complications did not significantly affect survival. Both groups, those with and without complications, had a median survival of 15 months (95% CI: 6.235–23.765 for those with complications and 12.992–17.008 for those without) (p = 0.653). There was no difference in survival based on the location of recurrence (p = 0.442). In the multivariable Cox regression analysis, several factors were evaluated for their impact on overall survival in patients with recurrent glioblastoma . Tumor focality emerged as a significant predictor, with multifocal tumors associated with poorer survival compared to unifocal tumors (HR: 0.507, 95% CI: 0.274–0.935, p = 0.030). Oncotherapy after the first surgery also demonstrated a strong impact on survival. Patients who underwent radiotherapy alone had significantly worse outcomes (HR: 7.032, 95% CI: 2.378–20.798, p<0.001) compared to those who received the STUPP protocol. The extent of tumor resection showed a trend towards improved survival with gross total resection (GTR), though this was not statistically significant (HR: 0.663, 95% CI: 0.430–1.022, p = 0.063). Other variables, such as the Charlson Comorbidity Index and ASA classification, did not show significant associations with survival after adjusting for confounding factors.
Based on the literature presented in , we presented a detailed comparison of outcomes between patients with recurrent GBM who underwent reoperation and those who did not. Reoperation for recurrent GBM is generally associated with a better PFS compared to no reoperation. For instance, studies such as those by Quick et al. and Rusthoven et al. reported PFS rates of 13.0 and 21.8 months after reoperation, respectively. This is notably longer than the PFS rates observed in non-reoperation cohorts, which generally ranged from 5.3 to 9.0 months. In studies such as that by McNamara et al., PFS after reoperation was reported at 7.1 months, while the non-reoperation PFS rate was significantly shorter at 9.9 months. These findings suggest that reoperation can effectively delay disease progression in recurrent GBM patients, potentially due to the removal of tumor bulk and reduced tumor burden, which may help prolong the time before disease progression. However, the variability in PFS results among studies indicates that the benefit of reoperation can be influenced by factors such as the extent of resection, the patient’s overall health, and the timing of the surgery. For example, studies such as those by Park et al. and Chen et al. reported varying PFS outcomes depending on the reoperation approach and patient subgroup characteristics. Moreover, reoperation generally has a positive impact on OS, but the extent of this benefit can vary. For example, Voisin et al. and Quick et al. reported OS with reoperation ranging from 18.4 to 30.6 months, which is substantially longer than OS without reoperation, which ranges from 8.6 to 18.6 months. This extended survival time observed in patients undergoing reoperation suggests that surgical intervention can offer a significant survival advantage by providing symptomatic relief, reducing tumor burden, and potentially improving the efficacy of subsequent treatments. Conversely, in studies such as those by Ma et al. and Azoulay et al., where direct comparisons of OAS with and without reoperation are less clear, the available data suggest that while reoperation does contribute to improved survival, the benefit might be less pronounced or variable depending on individual patient factors and the specific treatment protocols used. Overall, reoperation for recurrent GBM appears to offer substantial benefits in terms of both PFS and OS compared to non-reoperation, with PFS improvements ranging from a few months to over a year and OS improvements similarly varying. The variability in outcomes highlights the importance of personalized treatment planning. Factors such as tumor location, previous treatment history, patient health, and the specifics of the surgical approach play crucial roles in determining the effectiveness of reoperation. Given these findings, it is essential for clinicians to carefully consider individual patient circumstances when deciding on the management of recurrent GBM. While reoperation can provide significant benefits, especially in extending PFS and OS, the decision should be guided by a comprehensive evaluation of potential risks, benefits, and patient-specific factors to optimize overall treatment outcomes. Our institution’s data on reoperation for recurrent GBM reveals significant findings regarding survival and outcomes. Among the 125 patients analyzed, 41 underwent repeat resection, while 84 had only a single resection. The median PFS for patients who underwent repeat resection was 15.9 months, which was significantly longer than the 6.7 months observed in those who did not undergo reoperation, with a p-value of <0.001 indicating a highly significant difference. The 95% confidence interval for the PFS in the repeat resection group was not provided, but the significant p-value underscores a robust extension in time before disease progression. Regarding OS, patients who underwent repeat resection had a median survival of 21 months, compared to 11 months for those who did not, with a p-value of <0.001, reflecting a substantial improvement in survival. Although the 95% confidence interval for the OS in the repeat resection group was not specified, the statistically significant p-value highlights the clear survival advantage associated with reoperation. Regarding PPS, the median survival after progression was 5.9 months for patients who had repeat resection, versus 5.1 months for those who did not, with a p-value of 0.065. This p-value suggests a trend toward improved PPS with reoperation. However, the improvement was not statistically significant. The extent of complications following initial surgery was notably lower in the repeat resection group, with a complication rate of 4.9% compared to 21.4% in the single resection group, yielding a p-value of 0.018, which indicates a significant reduction in complications. Common complications in the repeat resection group included pulmonary embolism and seizures, but these were relatively infrequent. The most frequent post-surgical complications in the single resection cohort included deep vein thrombosis, hemiparesis/weakness, and seizures. Survival outcomes further revealed that patients with unifocal tumors had a median survival of 17 months (95% CI: 15.111–18.889), whereas those with multifocal tumors had a significantly shorter median survival of 6 months (95% CI: 2.801–9.199), with a highly significant p-value of <0.001. The extent of initial tumor resection also impacted survival, with gross total resection (GTR) yielding a median survival of 18 months (95% CI: 10.671–25.329) compared to 11 months (95% CI: 6.522–15.478) for subtotal resection, with a p-value of 0.001. Additionally, patients who received the STUPP protocol (chemoradiotherapy and adjuvant chemotherapy) had a median survival of 16 months (95% CI: 14.052–17.948), compared to 5 months (95% CI: 3.868–6.132) for those who underwent resection only, indicating a significant improvement in survival associated with comprehensive adjuvant treatment, with a p-value of 0.021. Complications did not significantly affect OS, with both groups having a median survival of 15 months (95% CI: 6.235–23.765 for those with complications and 12.992–17.008 for those without) and a p-value of 0.653. Our data clearly indicate that reoperation for recurrent glioblastoma offers significant benefits in extending PFS and OS while demonstrating variability in outcomes based on factors such as tumor focality, the extent of resection, and adjuvant treatments. The findings from our institution align closely with findings from the broader literature, underscoring the significant benefits of repeat surgical intervention. The median PFS for patients who underwent repeat resection was 15.9 months, which is consistent with the range of PFS improvements reported in previous literature regarding reoperation. For example, Quick et al. and Rusthoven et al. reported PFS rates of 13.0 months and 21.8 months, respectively. The statistically significant p-value of <0.001 in our data further supports the assertion that repeat resection can effectively extend disease control before progression. Similarly, our median OS of 21 months for patients who underwent repeat resection reflects the substantial survival benefit noted in studies such as those by Quick et al., who observed survival ranges up to 30.6 months. The p-value of <0.001 in our study highlights the clear advantage of reoperation in prolonging OS. While our median PPS of 5.9 months showed a trend towards improvement over the 5.1 months observed in non-reoperation patients, the lack of statistical significance (p = 0.065) is in line with literature findings, which often report variable impacts of reoperation on PPS. The significant reduction in complications following initial surgery in our repeat resection cohort (4.9% vs. 21.4%, p = 0.018) supports literature observations that reoperation can be associated with fewer complications compared to the initial surgery. Furthermore, our data on tumor focality, with unifocal tumors having a median survival of 17 months and multifocal tumors having a median survival of only 6 months, aligns with literature findings indicating that tumor characteristics significantly influence survival outcomes. The impact of the extent of initial tumor resection on survival, with gross total resection correlating with longer survival (18 months vs. 11 months for subtotal resection), is consistent with literature reports emphasizing the importance of complete surgical resection. Additionally, the survival advantage associated with the STUPP protocol in our study, showing a median survival of 16 months for those receiving comprehensive adjuvant treatment, is consistent with the consensus found in previous literature reports on the efficacy of combined chemoradiotherapy and adjuvant chemotherapy. The decision to reoperate is complex and must also consider factors like comorbidities and duration of initial PFS. Patients with significant comorbidities or poor functional status may not tolerate surgery well, making it less feasible. Additionally, a longer initial PFS might indicate a more indolent tumor biology, making reoperation more likely to provide further benefit. Overall, our findings corroborate existing literature on the benefits of reoperation for recurrent GBM, emphasizing the importance of surgical intervention in extending disease control and OS, while also highlighting the consistency in observed trends and outcomes across different studies. Limitations While our findings provide valuable insights into the outcomes of reoperation for recurrent GBM, several limitations must be considered. First, the complexity of patient selection for reoperation introduces potential selection bias. Patients selected for repeat resection are often younger, in better overall health, and have less extensive disease, factors that may independently contribute to improved outcomes irrespective of the surgical intervention. Second, the retrospective nature of our data collection and analysis introduces inherent biases and constraints, including variability in surgical techniques and adjuvant treatment protocols over time. Furthermore, while our institutional data align with broader trends reported in the literature, the single-center design limits the generalizability of our findings to other populations and healthcare settings. Finally, future studies should investigate the influence of molecular and genetic tumor profiles on the outcomes of reoperation, as these factors are increasingly important in tailoring individualized treatment strategies.
While our findings provide valuable insights into the outcomes of reoperation for recurrent GBM, several limitations must be considered. First, the complexity of patient selection for reoperation introduces potential selection bias. Patients selected for repeat resection are often younger, in better overall health, and have less extensive disease, factors that may independently contribute to improved outcomes irrespective of the surgical intervention. Second, the retrospective nature of our data collection and analysis introduces inherent biases and constraints, including variability in surgical techniques and adjuvant treatment protocols over time. Furthermore, while our institutional data align with broader trends reported in the literature, the single-center design limits the generalizability of our findings to other populations and healthcare settings. Finally, future studies should investigate the influence of molecular and genetic tumor profiles on the outcomes of reoperation, as these factors are increasingly important in tailoring individualized treatment strategies.
Based on the data from our patient cohort, we consider re-do surgery for patients with recurrent glioblastoma (GBM) in select cases. Specifically, reoperation should be prioritized in situations where the recurrent lesion is located in a non-eloquent region of the brain, as the risk of significant neurological deficits is minimized. Additionally, reoperation is advised for lesions that are easily accessible surgically, allowing for safer and more effective resections with reduced operative risk. Another key consideration is the presence of mass effect or associated edema, as surgical resection in these cases can significantly reduce intracranial pressure, alleviating symptoms such as headaches, neurological deficits, and seizures. By decreasing mass effect and edema, reoperation has the potential to enhance patients’ quality of life and provide symptomatic relief, which is a critical factor in managing recurrent GBM.
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Complement-Mediated Hemolytic Uremic Syndrome Due to MCP/CD46 Mutation: A Case Report | 46b5048a-7c1d-4eeb-b3c7-dd4dd65564de | 11773514 | Surgical Procedures, Operative[mh] | Thrombotic microangiopathy (TMA) is a pathological condition defined by microangiopathic hemolytic anemia (MAHA), thrombocytopenia, and ischemic organ injury. Complement-mediated hemolytic uremic syndrome (cHUS), also known as atypical hemolytic uremic syndrome (aHUS) is a severe type of TMA that primarily affects the kidneys, often leading to end-stage renal disease in the absence of timely intervention. Extra-renal manifestations occur in about 20% of patients with cHUS, with the frequency of complications involving specific organ systems varying widely, from isolated case reports to affecting up to 50% of documented cases. Cardiac complications have also been reported in 3% to 10% of patients with cHUS. Advances in understanding complement genetics have significantly reshaped the approach to cHUS and other forms of HUS. Among these, cHUS is uniquely associated with genetic susceptibility factors linked to complement regulation. These advances have revolutionized treatment through C5 inhibitors, drastically improving patient outcomes. However, timely diagnosis remains a critical challenge, compounded by ambiguities in defining the disorder and its overlap with other TMA variants. Here, we present a challenging case of TMA triggered by a heterozygous mutation in the membrane cofactor protein (MCP/CD46) gene, leading to a complex interplay of renal and cardiovascular complications. This case emphasizes the importance of recognizing genetic predispositions in the context of TMA, as it can significantly impact management strategies and prognosis.
A 23-year-old male with a past medical history of hypertension, hyperlipidemia, Bell’s palsy, and nephrolithiasis presented to a regional medical center for evaluation of chest pain, dyspnea, and syncope. He denied any preceding infection, fever, diarrhea, or cough. He also denied worsening of symptoms with exertion. The patient had been experiencing these symptoms for 1 month before they acutely worsened, which prompted him to seek treatment. On arrival to the emergency department (ED), his vital signs were blood pressure (BP) 209/132; heart rate (HR) 93; respiratory rate (RR) 18; and pulse oximetry 98% on room air. Laboratory testing revealed: hemoglobin 5.9 g/dL; hematocrit 16.7%; platelets 157 mcL; partial thromboplastin time (PTT) 37.5 seconds; blood urea nitrogen (BUN) 252 mg/dL; creatinine (Cr) 32.5 mg/dL; brain natriuretic peptide (BNP) 2816 ng/L; and troponin 225 ng/L. Arterial blood gas analysis revealed: pH 7.29; CO 2 20.2 mm Hg; O 2 98.1 mm Hg; and HCO 3 9.6 mm Hg. Urinalysis showed protein >500 mg/dL and 6 to 10 red blood cells (RBCs). Signs of fluid overload were noted on physical exam. The patient received clonidine 0.2 mg, Lasix IVP 80 mg, potassium chloride 40 mg, and 1 unit of packed RBCs while in the ED. Upon admission to the intensive care unit (ICU), the patient’s blood pressure was markedly elevated at 219/130 mm Hg, concomitant with acute kidney injury with a creatinine of 31.96 mg/dL and BUN of 247 mg/dL. The patient was initially started on a nicardipine drip; later, in his stay, a regimen of nifedipine 90 mg, carvedilol 12.5 mg BID, and losartan 100 mg was used for blood pressure control. Repeat laboratory investigations revealed MAHA, with a hemoglobin level of 6.9 g/dL, hematocrit of 20.3%, reticulocyte count of 11.5%, and a lactate dehydrogenase (LDH) of 619 U/L. Microcytic hypochromic anemia, anisopoikilocytosis, and schistocytes were observed on peripheral blood smear examination. Imaging studies further showed bilateral pulmonary edema and pericardial effusion, suggestive of fluid overload. Nephrology was consulted for severe acute kidney injury (AKI) with high anion-gap metabolic acidosis. A renal ultrasound was ordered and found no evidence of renal artery stenosis. Lab workup including C3/C4 levels, ANCA, and ADAMSTS13 activity was also ordered and returned with negative results. The patient’s ADAMSTS13 activity was slightly decreased at 52% but did not meet the thrombotic thrombocytopenic purpura (TTP) diagnostic criteria (<10% activity). Prompt interventions, including initiation of hemodialysis and plasmapheresis, were undertaken following nephrology consultation. The patient underwent daily hemodialysis and 4 sessions of plasmapheresis during his hospital stay. Empirical initiation of eculizumab was also commenced to attempt to slow the progression to end-stage renal disease. The computed tomography (CT)-guided renal biopsy was necessitated by negative results from vasculitis workup and complement assay. Samples were sent to the Ohio State University revealing active TMA with severe fibro-intimal thickening and mucoid intimal edema in large vessels. Onion skin-like intimal thickening was observed in some of the smaller vessels, nearing luminal obstruction . Despite these findings, the biopsy was inconclusive regarding the underlying etiology, prompting genetic analysis. While awaiting the results of genetic testing, the patient continued to experience anemia with hemoglobin levels ranging from 6.7 to 10.1 g/dL. He required multiple transfusions throughout his hospitalization. Approximately 5 weeks after the patient initially presented to the hospital, genetic testing results returned and showed a heterozygous variant in the MCP/CD46 gene, confirming a hereditary predisposition to TMA. Despite therapeutic efforts, the patient’s clinical course was complicated by worsening pericardial effusion due to uremic pericarditis, necessitating pericardiocentesis for symptom relief. The patient’s hospital stay was prolonged due to difficulty meeting the transportation requirements that daily outpatient hemodialysis would pose. He was discharged once his renal function allowed for 3-times-weekly hemodialysis. Ultimately, the patient also required arteriovenous fistula creation for ongoing renal support.
Thrombotic microangiopathy is a syndrome characterized by the triad of MAHA, thrombocytopenia, and organ dysfunction, particularly affecting the kidneys. , Known risk factors include drugs, hematologic disorders, infections, genetic predispositions, and pregnancy-related conditions. - Genetic susceptibility plays a critical role, with both inherited and acquired deficiencies in complement pathway regulators, such as ADAMTS13, factor H, factor I, MCP/CD46, and thrombomodulin, contributing to dysregulated complement activation. This disruption leads to endothelial injury and the subsequent development of TMA. - Furthermore, renal biopsy findings are critical for confirming TMA and differentiating it from other mimicking disorders. Histopathological evidence of concentric luminal obliteration in small vessels substantiated the diagnosis and highlighted both acute and chronic TMA features. Complement-cHUS is a rare form of TMA primarily caused by dysregulation of the alternative complement pathway. Unlike typical hemolytic uremic syndrome (HUS), which is triggered by Shiga toxin-producing pathogens such as Escherichia coli O157:H7 or Shigella dysenteriae , cHUS arises from alternative mechanisms, including genetic mutations or sporadic factors. It now accounts for about 10% of HUS cases. The annual incidence of cHUS is approximately 2 per million in adults and 3.3 per million in children under 18 years old. Genetic or acquired defects leading to uncontrolled activation of the alternative complement pathway are identified in approximately 60% of cases. Clinically, patients may present with milder or fluctuating anemia and thrombocytopenia, and a subset may lack overt renal involvement at diagnosis. The condition is associated with significant morbidity and mortality, with 65% of patients developing end-stage renal disease or dying within the first year of diagnosis. The patient’s clinical presentation and laboratory findings prompted consideration of several differential diagnoses, including TTP, HUS, disseminated intravascular coagulation (DIC), malignant hypertension, and Evans syndrome. Specific diagnostic criteria helped exclude these conditions. The TTP was ruled out due to the absence of ADAMTS13 deficiency and vasculitis, despite the presence of schistocytes indicative of MAHA. The HUS was excluded based on the lack of recent gastrointestinal infections or exposure to Shiga toxin-producing bacteria. The DIC was deemed unlikely due to the absence of systemic consumptive coagulopathy and the predominance of renal and cardiovascular manifestations. Similarly, malignant hypertension was ruled out as the patient had no history of severe, uncontrolled hypertension preceding the presentation. Complement-cHUS was identified as the primary diagnosis, supported by the detection of a mutation in the MCP/CD46 gene, a hallmark of this TMA subtype. However, to understand the pathophysiology of TMA in the context of the MCP/CD46 mutation, it is essential to examine complement dysregulation and endothelial injury. Mutations in CD46 or CFH, as well as anti-CFH autoantibodies, lead to excessive activation of the alternative complement pathway, resulting in endothelial damage and heightened susceptibility to TMA. A prominent example of this is the development of TMA in lupus nephritis (LN), where the activation of the lectin pathway (LP) and alternative pathway (AP) appears to be a key factor. Patients with LN-associated TMA often exhibit more severe clinical and pathological features, along with poorer renal survival outcomes. Management with eculizumab, a complement inhibitor, was initiated due to its role in blocking the cleavage of complement component C5, thus preventing the formation of the membrane attack complex and subsequent endothelial damage. Menne et al demonstrated the effectiveness and safety of eculizumab in managing cHUS, particularly in achieving and sustaining stable kidney function over 6 years, with a notably low incidence of TMA. Evidence suggests that discontinuing eculizumab may be a safe option in patients with isolated MCP mutations or specific genetic profiles after TMA resolution and stabilization of renal function. This can potentially enhance the care and quality of life for a significant number of cHUS patients while also lowering treatment expenses. Outcomes in kidney transplantation for TMA are influenced by the underlying genetic abnormalities, , with MCP/CD46 mutations generally associated with a lower recurrence risk compared with other complement regulatory protein mutations. Given that MCP is a transmembrane protein abundantly expressed in the kidney, transplanting a healthy kidney can potentially resolve the defect in these patients. In contrast, as complement factor H and factor I are primarily produced by the liver, kidney transplantation would not address the underlying genetic defects, increasing the risk of disease recurrence in the transplanted kidney. The clinical course of the 23-year-old male patient with TMA involved a multifaceted treatment plan, including eculizumab, plasmapheresis, and hemodialysis. The patient showed marked improvements in renal function, evidenced by a decline in creatinine levels. Long-term management challenges include recurrence risk, the need for ongoing renal and cardiovascular monitoring, and potential complications such as graft-versus-host disease (GVHD) in the context of hematopoietic stem cell transplantation.
In summary, this case report highlights a challenging presentation of TMA associated with an MCP/CD46 mutation, revealing the significance of genetic testing in shaping management approaches. Additional studies are needed to further clarify the contribution of genetic factors to TMA development and to optimize targeted treatment strategies.
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Breaking Bad Proteins—Discovery Approaches and the Road to Clinic for Degraders | 8bdbabd6-0bbc-4638-b2e3-b0e13a740622 | 11011670 | Internal Medicine[mh] | The concept of pharmacologically modulating turnover of a specific target protein by leveraging the ubiquitin–proteasome system (UPS) was first realized by Ray Deshaies, Craig Crews and others in a landmark study from 2001 , where the authors coined the term proteolysis-targeting chimeras (PROTACs). PROTACs, or more formally, bifunctional degraders, are composed of two separate moieties, a ubiquitin ligase (also called E3) recruiter and a target recruiter, with a linker connecting the two. In this way, bifunctional degraders can bind to the ligase and target at the same time, effectively putting the ligase into close proximity with the protein of interest (POI), leading to its ubiquitination and proteasomal proteolysis ( A). Molecular glue degraders (MGDs), in contrast, consist of a single moiety and have a conceptually distinct mode of generating the ternary complex. Whereas bifunctional degraders rely on two separate ligands for ligase and POI recruitment, and can independently and separately bind both, glue degraders must first bind to one of the proteins, which modulates the surface properties of the bound protein to induce binding to the second. Most reported MGDs are ligase ligands, where compound binding induces interaction with a neo-substrate, a protein that otherwise would not interact with or be degraded by the ligase. An MGD can also bind the target protein, with resulting induced binding to a ligase, as exemplified by degraders for Cyclin K and BRD4 . In addition to their therapeutic potential, degraders represent valuable tools for exploration of fundamental cell biology, where the functional consequences of acute protein ablation can provide novel insights into cell physiology and the intricate regulatory networks that govern cellular functions. Due to being composed of two ligands and a linker, the molecular weight and physicochemical properties of bifunctional degraders are outside of the rule of five , which poses significant challenges in developing these compounds for an oral route of administration. These challenges include optimization of compounds to reduce, e.g., molecular weight (MW), number of hydrogen bond donors (HBD), rotatable bonds (RB), and topological polar surface area (TPSA), whilst maintaining potency. In addition, heterobifunctional degraders may behave unpredictably, where changes in compound structure impact on the conformations that the compound adopts in different environments, a property described as molecular chameleonicity . Guidelines for optimization of PROTAC physicochemical properties with respect to oral bioavailability have recently been published by Arvinas, recommending, among other properties, MW < 950, HBD < 2, RB < 14 and TPSA < 200 Å 2 . In contrast to PROTACs, molecular glue degraders are generally compact, with a low molecular weight and the potential for favorable drug-like physiochemical properties, simplifying the late-stage optimization process. The challenge with MGDs lies largely in the identification of compounds, with the rational identification of glues between a selected ligase-target pair remaining a significant challenge. Both MGDs and bifunctional degraders have event-driven pharmacology. In contrast, conventional small-molecule inhibitors function by occupying a binding pocket on the target protein, for example an enzyme active site. Degraders circumvent this requirement by acting catalytically, where a single degrader molecule turns over multiple target protein molecules in a substoichiometric mode . This event-driven mechanism of action is different from occupancy-based inhibitors, where the catalytic property may allow lower or less frequent dosing. In this context, it is worth noting that degraders may be developed as covalent compounds, and interestingly the first PROTAC was based on the covalent target ligand ovalicin . Since the catalytic advantage is lost for degraders that covalently bind the target, covalent bifunctional degraders have largely been explored for ligands reacting with the ligase . Importantly, covalent E3 recruiters cannot be inhibitory of ligase function (see, e.g., covalent ligands for the E3 HOIP described by Johanssen et al. ) since this would invalidate their utility in a TPD setting, and thus avoiding reaction with active site residues in ligases that have enzymatic activity is essential. The concept of target-covalent degraders has been explored for BTK, utilizing both reversible and irreversible covalent ibrutinib derivatives . Since ibrutinib has high non-covalent binding affinity for BTK, covalent degraders based on this ligand will fundamentally be expected to reduce potency due to loss of catalytic function . Similarly, degraders for KRAS G12C have been generated from existing covalent ligands . Although these examples are based on ligands that were developed as covalent inhibitors, the concept of covalency on the target side will apply equally to ligands developed specifically as binders for degrader purposes, where a covalent route has the potential advantage of identification of ligands for otherwise un-ligandable targets. If a covalent route is taken for a degrader, additional challenges include development of a selective covalent ligand (POI or E3) as well as characterization of the rate of covalent bond formation compared to the rate of degradation . General considerations for covalent drug discovery beyond the scope of this review have been reviewed elsewhere . In contrast to inhibitors, the pharmacology of degraders can lead to a disconnect between pharmacokinetic (PK) and pharmacodynamic (PD) properties. This is, in part, related to the re-synthesis time of the target, where slowly re-synthesized proteins may remain absent for a significant time after the degrader has been cleared from circulation. Exemplifying a PK/PD disconnect, degraders for the protein RIPK2 show a prolonged functional response after dosing . This is an advantage shared with covalent inhibitors; however, degraders have the additional benefit of catalytic functionality. A further advantage with degraders is that they are not required to bind to an active site in a target. This opens up the potential for developing therapies where the target active site is either un-ligandable or absent. In these situations, identification of a small-molecule binder for the target protein is required, which may still pose a considerable challenge. The parameters to assess in vitro potency of degraders in drug discovery approaches are principally DC 50 and D max , which correspond to the compound concentration at half-maximal degradation and the maximum degradation, respectively. More comprehensive compound characterization at the screening stage may also include assessment of the rate of degradation and ternary complex formation (vide infra). Ubiquitin ligases, or E3s, mediate the post-translation modification of substrates with the small protein ubiquitin. Iterative ubiquitination of ubiquitin itself leads to protein poly-ubiquitination, which mediates different downstream functions depending on the ubiquitin chain architecture; largely, lysine 48 poly-ubiquitinated proteins are degraded by the 26S proteasome . Out of the approximately 600 ubiquitin ligases in the human proteome, only a small number have currently been explored in TPD approaches, principally due to the paucity of existing E3 ligands. The most utilized ligases are CRL4 CRBN and CRL2 VHL , where bifunctional degraders based on both have entered the clinic. Other E3s that have been demonstrated to function in a degrader approach include the non-cullin–RING ligases MDM2, IAPs, RNF4 and RNF114. Cullin–RING ligases (CRLs, vide infra) utilized for TPD include Ahr, KEAP1, DCAF1, DCAF11, DCAF15, DCAF16, FEM1B, and KLHDC2 . While no experimental evidence is available for use of HECT ligases in degrader approaches at this time, UBR5 was recently suggested as an interesting TPD candidate for this class of E3s . An interesting concept is the identification of essential ligases, which may reduce the occurrence of resistance mechanisms due to loss of ligase expression or mutations that reduce ligase activity. The DCAF1 ligase is reported to be essential and has recently been demonstrated to be active in the context of bifunctional degraders . Utilizing ligases that are critical or upregulated in a certain disease condition may allow for effective target degradation primarily in affected tissues, for example in oncology . To enhance tumor specificity, bifunctional degraders have been coupled with antibodies recognizing specific tumor types. Antibody–drug conjugates (ADCs) are an interesting approach to reduce side effects when using degraders that recruit ubiquitously expressed ligases . Similarly, taking advantage of differential tissue expression of E3s may allow preferential degradation in the tissue that is relevant to the disease, and an early example of this is the BCL-XL degrader DT2216, which has reduced toxicity due to low VHL expression in platelets . Important aspects to consider when developing a degrader approach is the tissue expression profile and subcellular localization of the E3. For a degrader to be successful, the target and ligase are required to be present in the same cellular compartment, and for clinical application, the ligase must be expressed, and active, in the tissue that is relevant for the indication. VHL and CRBN are widely expressed and have been reported to degrade both nuclear and cytosolic targets . Other ligases may have activity that is restricted to a certain compartment in the cell, such as DCAF16, reported to be limited to the nucleus . Plasma membrane bound ubiquitin ligases, such as RNF43, have also been shown to be possible to hijack for TPD purposes, which opens up an interesting prospect of targeting transmembrane proteins for degradation via the use of degraders that act extracellularly . While the vast majority of characterized ubiquitin ligases transfer ubiquitin to lysine residues, E3s that act on serine and threonine have been described and could in principle be used in TPD approaches , and although there is no current evidence to support this, it is interesting to speculate if this may open up opportunities for degrading proteins that may be recalcitrant to induced degradation, e.g., due to the positioning of lysines in the ternary complex. The activity of both bifunctional and molecular glue degraders is reliant on the formation of a productive ternary complex, where the compound is bridging the ubiquitin ligase with the target protein in a spatial orientation that is compatible with transfer of ubiquitin to lysines in the target protein. It is worth noting that formation of a ternary complex does not necessarily translate into ubiquitination and degradation as the target protein, while recruited successfully to the ligase, may not be positioned to allow ubiquitin transfer to lysines. Ternary complex assessment can be performed both in cell-based assays or using purified proteins and can provide both qualitative and quantitative information that can aid compound development. An emerging key parameter of ternary complex formation is cooperativity. Cooperativity, denoted as α, measures how the affinity of the degrader for the ligase is affected by simultaneous binding to the target, or vice versa, and is defined as the binary affinity divided by the ternary affinity . Cooperativity can be positive, non-cooperative, or negative. Positively cooperative degraders bind with higher affinity to the ligase in the presence of the target protein and α is >1. Conversely, if the presence of the target protein decreases the binding affinity to the ligase, α is <1, and the degrader exhibits negative cooperativity. Compounds that are not affected in either direction, with α = 1, are termed non-cooperative. Molecular glues typically have high positive cooperativity with α > 1, while bifunctional compounds range from negatively to positively cooperative. Positive cooperativity suggests that the ternary complex is stabilized by energetically favorable de novo interactions between the ligase and the target protein but may also derive from more unexpected sources, as recently exemplified by Geiger et al. . Here, the authors describe a potent VHL-based degrader for FKBP51, where the VHL and FKBP51 ligands act in a molecular glue-like manner with their respective non-partner protein. In a similar manner, linkers have been shown to contribute to ternary complex formation , and optimization of linker–protein interactions can enhance cooperativity, as shown for SMARCA2 degraders . Negative cooperativity may be due to steric clashes that are counterproductive to complex formation, or to other properties of the compounds that shift the equilibrium towards binary complexes. For example, an FKBP12 degrader with negative cooperativity was recently described . This compound (6a2) showed high binary affinity for FKBP12 and VHL, respectively, however, bound dramatically less well to VHL in the presence of FKBP12. Structural studies revealed that the compound collapses onto itself, forming intramolecular contacts in a horse-shoe shape while bound to FKBP12. In this binary complex, the VHL ligand forms contacts with the FKBP12 protein that likely further stabilize the folded conformation, thus preventing the formation of a ternary complex with VHL. Importantly, cooperativity has been reported to correlate with increased potency of degradation , and a recent study by from Amgen has illustrated that both ternary complex affinity and cooperativity contribute to the potency of bifunctional degraders. This study assessed VHL-based degraders for SMARCA2 and BRD4 using surface plasmon resonance, and the results highlight that cooperativity is highly correlated to potency of degradation. The authors note that although ternary complex affinity and cooperativity are connected, they are not equivalent. Ternary complex affinity reflects the cumulative interactions in the ternary complex, involving all three components. Cooperativity characterizes the impact of a binding partner, such as the E3 ligase, on the interaction between the PROTAC and its other binding partner, the target protein, as defined above. As such, it is for example in principle possible for a PROTAC to display positive cooperativity with a relatively weak ternary affinity, if the binary affinity is weaker than the ternary. Conversely, a PROTAC with high ternary complex affinity may display negative cooperativity if the binary affinity is higher than the ternary. In contrast, ternary complex half-life, i.e., the stability of the induced complex between the ligase and target protein, showed target-dependent correlation with potency of degradation. While BRD4 degraders with more stable complexes were more effective degraders, this correlation was weak for SMARCA2 degraders, highlighting the challenges in building predictive models for bifunctional degraders. Of note, bifunctional degraders that are non-cooperative or have negative cooperativity may still be highly potent , calling into question the value of cooperativity as a key parameter in early degrader discovery. However, highly cooperative lead compounds may be advantageous starting points, as they likely will be more permissive to structural changes that optimize DMPK and physicochemical properties at the cost of reduced ligand affinities. As such, a compound series with strong cooperativity may make room for the medicinal chemist to balance potency with properties that progress the compounds towards the clinic. A well-described property of bifunctional degraders is their capacity to form binary complexes with the target protein and the ligase at saturating concentrations, leading to a decrease in activity—this generates the characteristic “hook” appearance in a concentration-response curve ( B). Note that the hook effect is not observed for MGDs, since these compounds do not display measurable affinity to at least one of the two involved proteins. Highly cooperative bifunctional degraders have lower propensity to form binary complexes and a reduced tendency for hook effect at high compound concentrations, which is an advantage for clinical development. Engaging E3 ligases is a critical step in degraders’ mode of action. Although three groups are now recognized, E3 Ubiquitin ligases were classically divided into two distinct classes based on their conserved hallmark catalytic domain and ubiquitin transfer mechanism: really interesting new gene-type E3s (RINGs) and homologous to the E6AP carboxyl terminus-type E3s (HECTs) . While RING family ligases catalyze a direct ubiquitin transfer from the E2–ubiquitin complex to a substrate protein , HECT E3s initially transfer ubiquitin to an internal catalytic cysteine residue before transferring it to a protein . A third group: RING-in-between-RING (RBR) combines features of both RING and HECT families, the N-terminal RING domain first recruits E2–Ub complex, then transfers ubiquitin onto another RING domain, before transfer to the substrate protein ( A). RINGs represent the most prevalent class of human E3 ligases, with approximately 600 members, surpassing the numbers of HECTs (28 members) and RBRs (14 members) . To date, only RING ligases have been leveraged in TPD approaches . Members of this family are subclassified into two categories: cullin–RING ligases (CRLs) and non-CRL ligases. CRLs are modular protein complexes consisting of four variable subunits: a RING box protein (RBX1 or RBX2), a cullin (CUL) protein, an adaptor protein and a substrate-recognizing receptor ( B). CUL proteins are scaffolds that bind an RBX protein through its C-terminus, while its N-terminus binds to an adaptor protein linked to a substrate receptor . CRLs are classified based on the cullin subunit used. The mammalian family comprises eight members: CUL1, CUL2, CUL3, CUL4A, CUL4B, CUL5, CUL7 and CUL9 , each with their cognate substrate adaptor and receptor proteins. For instance, CRL1 is a complex consisting of a variable component F-box protein, as adaptor protein, and three invariable components: the S phase kinase-associated protein 1 (SKP1), CUL1 and RBX1 . CRL2 and CRL5 ligases recruit both elongins B and C as adaptor proteins while variable suppressors of cytokine signaling (SOCS) box proteins are used as substrate receptors . CRL2 is important in a TPD context, due to the ligase complex based on the Von Hippel-Lindau (VHL) substrate receptor. VHL and SOCS-box proteins contain a common motif, known as the BC-box, essential for binding to the elongin BC complex ( B) . A single bric-a-brac-tramtrack-broad complex (BTB) protein is necessary for linking the CUL3 domain to a substrate protein . CRL4A and CRL4B are highly conversed (82% identity) , and both recruit DNA damage-binding protein 1 (DDB1) as adaptor and DDB1- and CUL4-associated factor (DCAF) proteins, such as CRBN, as substrate receptors ( B) . Atypical CRL7 recruits a single F-box protein: F-box and WD40 domain 8 (FBXW8) as substrate receptor and SKP1 as adaptor . The substrate adaptors for another atypical cullin family member, CUL9, also described as p53-associated parkin-like cytoplasmic protein (PARC), are not known . CRLs are highly dynamically regulated, activated or decommissioned depending on substrate availability. Both processes depend on the small ubiquitin-like modifier NEDD8, nearly 60% identical to ubiquitin but with distinct targets and functions. Covalent modification of a C-terminal lysine in cullins with NEDD8 induces a structural change stabilizing an open active conformation facilitating the access of the substrates for ubiquitination. Conversely, deneddylation mediated by the constitutive photomorphogenesis 9 (COP9) signalosome (CSN) enables the exchange of substrate receptors from CRLs via the scaffold protein CAND1 . While CRL are multi-subunit E3s, non-CRL ligases are single-subunit entities. They may have a U-box domain instead of a RING domain, which shares a similar structure but lacks the characteristic coordination of zinc ions. Both domains serve the same purpose in facilitating the transfer of ubiquitin from the Ub-E2 conjugated to the substrate protein. Non-CRL ligases can exist in different forms—either as monomeric, homodimeric, or heterodimeric, with the latter being specific to RING-containing non-CRLs only . The first E3 ligands were designed by mimicking specific peptide motifs in E3 substrates, referred to as degrons . Some degrons are linear sequence motifs, whereas structural degrons depend on the spatial conformation of the folded protein, or on a conformational change generated by a post-translational modification . For example, PROTAC-1 developed by Crews and Deshaies in 2001 recruits the F-box protein β-TRCP associated with the CUL1-RBX1-SKP1 E3 complex through an IκBα phosphopeptide . Similarly, three years later, the substrate receptor VHL of the CUL2-RBX1-ElonginB-ElonginC complex, known as CRL2 VHL , was successfully recruited using the seven amino acid ALAPYIP sequence derived from the HIF-1α substrate . However, these early peptide PROTACs had moderate binding affinity and low cell permeability, resulting in a weak activity. Based on the interaction of HIF-1α with VHL, high-affinity synthetic VHL ligands, such as VH032 and later VH298, were developed via considerable efforts of the Ciulli group, paving the way for successful CUL2 VHL -based PROTACs . It is worth noting that while these ligands have high affinity for VHL, their physicochemical properties make them challenging for use in the context of generating orally bioavailable bifunctional degraders. Hiroshi Handa and collaborators discovered that thalidomide and its analogues, referred to as immunomodulatory imide drugs (IMiDs), more recently known as Cereblon E3 ligase modulators (CELMoDs), bind to CRBN, the substrate receptor of CUL4–RBX1–DDB1–CRBN complex identified as CRL4 CRBN . A highly conserved hydrophobic pocket on CRBN allows binding of thalidomide and its derivatives, forming a new molecular surface capable of novel protein–protein interactions (PPIs) and thus recruitment of neo-substrates for degradation . Initial characterization of thalidomide, lenalidomide and pomalidomide showed degradation of the transcription factors IKZF1 and IKZF3 . Further work by Ebert et al. showed that lenalidomide also led to the degradation of casein kinase 1 alpha 1 (CK1α), but that thalidomide had no effect on CK1α levels , demonstrating that changes around the IMiD core leads to different neo-substrate target selectivity. Molecular glues can also trigger degradation by promoting protein polymerization; BI-3802, targeting the oncogenic transcription factor B cell lymphoma 6 (BCL6), illustrates this mechanism ( C) . Binding of BI-3802 to the BTB domain of BCL6 triggers its homodimerization and subsequent higher-order assembly into filaments. BI-3802-induced polymerization enhances the interaction between BCL6 and SIAH1, an E3 ligase that recognizes a VxP motif distal to the drug-binding site , leading to accelerated ubiquitination and proteasomal degradation of BCL6. In comparison, previously discovered CRBN-based heterobifunctional BCL6 degraders did not achieve complete BCL6 degradation and failed to induce a significant phenotypic response in diffuse large B-cell lymphoma (DLBCL) . By linking a POI warhead to IMiD/CELMoD compounds, molecular glues can be converted into PROTACs . In recent years, a wave of CRBN-based PROTACs has emerged . It is noteworthy that bifunctional degraders based on IMiDs may retain their MGD-dependent ability to trigger the degradation of Ikaros (IKZF1), Helios (IKZF2), Aiolos (IKZF3) or other targets . This property has been exploited by Nurix Therapeutics with their combined BTK and IKZF degrader NX-2127, currently in Phase 1 clinical trials. Most of the approaches used for degraders so far have focused on the recruitment of E3 ligases, particularly on the substrate receptors of CRLs, such as VHL, CRBN or DCAF15. As mentioned above, substrate receptors are interchangeable subunits which are docked to the scaffold cullin through an adaptor protein. Hijacking and reprogramming CRL activity is an effective strategy used by several viruses and there is evidence of direct association of different viral proteins with the adaptor protein DDB1, which induces the degradation of host proteins such as the STAT1 transcription factors. DDB1 contains three β-propeller domains, the BPB domain docks the N-terminal of the cullin scaffold, whereas domains BPA and BPC bind DCAFs proteins. Some virus proteins have evolved to functionally mimic DCAFs and bind to the adaptor protein DDB1, thus, recruiting E3 ligase activity to direct the degradation of factors relevant to the immune response and escape its effects, as occurs with hepatitis B virus X protein among others. Learning from these viral molecular strategies, it has been proposed that molecular glues could mimic viral hijacking of CRL components. This concept has been demonstrated for the E3 component DDB1, where molecular glue degraders rely on the activity of the CRL4B ligase, but is mechanistically independent of substrate receptors, with MGDs acting directly via the DDB1 adaptor to induce POI ubiquitination ( D). Recently, covalent ligands for DDB1 and another CRL substrate adaptor, SKP1, have been identified and successfully used to generate bifunctional degraders, further establishing that induced degradation is possible via a cullin adaptor protein . As mentioned above, cullin–RING E3 adaptor proteins are associated with various substrate receptors, and consequently, these proteins are essential for cell viability, as their removal or dysfunction would lead to impaired functions across a broad range of E3 ligases. As such, exploiting CRL substrate adaptors to build degraders may lessen the probability of resistance mutations that render degraders inactive. Although ligase recruitment is currently the most well-explored modality to induce target degradation, other components of the ubiquitin proteasome system (UPS) can also be harnessed. Given that E3 ligases depend on the action of E2 conjugating enzymes, some research groups have sought small-molecule binders for E2s. Very recently, by library screening and chemoproteomic approaches, King and collaborators discovered a covalent molecular glue degrader, EN450, that impairs leukemia cell viability in a NEDDylation and proteasome-dependent way. EN450 was found to target an allosteric cysteine on the E2 UBE2D and induced the proximity of the E2 with the transcription factor NFKB1 to induce its degradation in leukemia cells . Shortly after, with this approach, the same group demonstrated that core proteins within UPS machinery, such as E2s, can be exploited for PROTAC application, where the compound EN67 acts as a covalent recruiter for the E2 UBE2D ( D). Throughout the development of PROTACs and molecular glues, it has been observed that a limitation is that non-native E3 substrates must be efficiently ubiquitinated by the selected ligase. The efficiency of degradation of the POI is determined by the ubiquitination, and this in turn depends on the existence and availability of a ubiquitin acceptor site on the POI. To overcome these constraints, an alternative strategy would be targeting proteins directly to the 26S proteasome, and thus in principle skipping the requirement for ubiquitination. Bashore et al. explored this strategy, sampling a wide range of chemical space by using mRNA display technology. They found a macrocyclic ligand against the 26S subunit PSMD2. By synthesizing heterobifunctional molecules that bind the proteasome subunit on one side and the protein BRD4 on the other, they were able to successfully degrade BRD4 proteins; they referred to these compounds as chemical inducers of degradation (CIDEs; D). To confirm that this strategy avoids CUL3 ligase (CRL3) mediation through the KLHL15 adaptor protein, the authors generated KLHL15-knockout clones using CRISPR-Cas9 protocols. Their results showed that degradation occurs independent of this E3 ligase through direct recruitment to the proteasome . This direct-to-proteasome approach has been further explored by the Ciulli group and others, with induced degradation achieved by leveraging ligands for proteasome associated components such as UCHL5, RPN11, USP14 and RPN13 , as well as modified proteasome inhibitors , and it will be interesting to see how this strategy compares to ligase recruitment in terms of target scope and efficacy. A fundamental question in a TPD drug discovery campaign is whether the target and indication are suitable for a degrader approach. Arguably, many therapeutically relevant targets may be effectively addressed by adopting a traditional occupancy-based strategy, in particular for enzymes, with a likely faster and more straightforward development route. When considering a degrader approach, it is also worth noting that targets that are rapidly resynthesized may yield less therapeutic benefit, compared to slowly resynthesized proteins. However, there are circumstances where a degrader strategy is advantageous, and these are discussed below. 6.1. Selectivity Selectivity of inhibitors against related proteins is sometimes required to limit toxicity, but not possible to achieve due to high active site or ligand binding pocket homology. Interestingly, degraders offer two potential routes around selectivity challenges. The first relies on identification of a novel ligand that binds the desired target in a domain outside of the conserved areas, and thus will only degrade the intended target. This requires significant time and financial investment, and the success will rely on the nature of the ligand and its suitability for use in bifunctional compounds. Similarly, a molecular glue degrader approach may be investigated limiting the glue to a non-conserved domain; however, MGD identification is currently challenging. The second route takes advantage of the observation that bifunctional degraders based on existing non-selective target ligands can exhibit selective degrader activity. For example, the non-selective ATP-competitive fibroblast growth factor receptor (FGFR) inhibitor BGJ398 was utilized to generate a selective FGFR1/2 degrader, DGY-09-192, sparing FGFR3/4 , and selective degraders for STAT3 and STAT5, respectively, have been generated from relatively non-selective ligands . Selectivity in this context likely stems from structural differences that dictate how a target interacts with or can be accessed by the ubiquitin ligase, such that ternary complex formation is either unproductive or does not take place efficiently for a subset of proteins within a group ligandable by the degrader. From this argument follows that different ubiquitin ligases may produce different selectivity profiles, as indeed shown for CRBN and VHL in large-scale proteomics studies using promiscuous kinase ligands . Another example of ligase-driven selectivity is the use of the RNF114 ligase with the non-selective tyrosine kinase inhibitor dasatanib as target recruiter. Although linker chemotype and exit vector geometry will likely impact selectivity, data indicate that VHL and CRBN favor c-ABL degradation, whereas RNF114 preferentially drives degradation of BCR-ABL . The expansion of ligases validated for TPD approaches will undoubtedly provide further opportunities to achieve ligase-driven selectivity based on use of non-selective target ligands. 6.2. Degraders for Non-Enzymatic Functions Degraders may provide a way to develop effective drugs for proteins driving biology through scaffolding functions or protein–protein interactions (PPIs), instead of enzymatic activity. TPD is seen as a promising approach for challenging targets like transcription factors, scaffolding proteins, and receptors. However, despite this potential, addressing traditionally undruggable targets with degraders presents significant challenges, with a key consideration being whether identifying a novel ligand for the target is feasible. Many clinically relevant enzymes have been attempted to target using inhibitors, and existing ligands can be leveraged to build degraders that address both enzymatic and non-enzymatic functions. Examples here include the IRAK4 and BTK kinases, where both enzymatic and scaffolding functions mediate signaling . Whereas inhibitors can only address the active-site functionality of these targets, degraders have been demonstrated to be more effective due to removing all functionalities of the targeted protein . Inhibiting PPIs is generally considered difficult, where interacting proteins often share a relatively large and flat binding interface with little opportunity for ligandable pockets . While the concept of targeting PPIs with degraders has been demonstrated utilizing existing PPI inhibitors for BCL family proteins , identification of ligands that bind outside of PPI interfaces opens up for addressing a broader variety of PPIs via degraders, and it will be interesting to see if the maturing degrader field will exploit this possibility. A highly attractive property of degraders is that they may offer a route for removal of aggregated proteins, a hallmark of many neurodegenerative disorders (discussed in detail below). In this scenario, a degrader strategy can offer clear advantages; however, identification of aggregate specific ligands and access of the degrader to the CNS pose significant challenges. In particular, bifunctional degraders are difficult to optimize for blood brain barrier (BBB) penetration, and as such MGDs are an interesting option for degraders that act within the CNS. 6.3. Resistance Mutations Resistance mutations in cancer treatments pose a substantial clinical challenge, where cells undergo genetic alterations that confer resistance to initially successful therapeutic interventions, such as upregulation of expression levels or point mutations. In cases where resistance mutations occur in the binding site of small-molecule inhibitors, degraders may offer an advantage. Since degraders do not rely on binding to the active site of the target protein, they can potentially overcome mutations that interfere with traditional inhibitor binding. Moreover, due to their event-based pharmacology and potential for cooperative ternary complexes, degraders may be more forgiving to affinity-reducing mutations in the ligand binding site of the target . An example where degraders have been shown to have activity against resistance-associated mutants is BCR-ABL1, present in approximately 95% of chronic myelogenous leukemia (CML) cases. The introduction of imatinib, an ATP-competitive tyrosine kinase inhibitor, marked a significant milestone in treatment of CML , which was followed by a number of second-generation inhibitors, including dasatanib . Unfortunately, resistance to both imatinib and second-generation compounds inevitably arise upon treatment. The concept of a degrader approach for BCR-ABL1 has been demonstrated utilizing both ATP-competitive inhibitors and compounds binding allosterically, where bifunctional degraders have activity against treatment-resistant BCR-ABL1 mutants . In particular, the dasatanib based degrader SIAIS056 was shown to efficiently degrade BCR-ABL1 mutants associated with dasatanib resistance . Likely this is due to the event driven pharmacology of the degrader, where resistance mutations may decrease ligand affinity , and consequently reduce efficacy of an occupancy-based therapy, but still allow a significant level of induced degradation. It remains to be seen whether specific BCR-ABL1 degraders will be of value for clinical development to supplement the inhibitor pipeline. In a clinical setting, a recent study has focused on BTK in the treatment of B cell cancers like chronic lymphocytic leukemia (CLL). This report characterizes two types of drug resistance mutations in BTK: kinase proficient and kinase impaired. Kinase-impaired mutants, exemplified by L528W, retain downstream BCR signaling despite reduced BTK kinase activity. NX-2127 from Nurix Therapeutics is a potent BTK degrader that is currently in Phase 1 clinical trials, where it has demonstrated over 80% BTK degradation and positive clinical responses in 79% of evaluated CLL patients, irrespective of mutant BTK genotypes, showing promise for overcoming BTK resistance mutations . A further clinical example of where degraders have been used to mitigate resistance mutations is the androgen receptor (AR), an important target in prostate cancer (PC). The AR protein is a transcription factor that promotes cell proliferation when activated by binding to the androgen hormones. In the initial phases of the disease, PC often relies on androgens, and surgical/chemical castration or AR antagonists are employed to deprive the tumor of AR activity . Unfortunately, various mechanisms lead to resistance to androgen-based therapy, including AR overexpression or mutations that convert antagonist activity into an agonist activity, as reported for the clinical AR antagonist enzalutamide . Given the nature of resistance mechanisms for the AR, adopting a degrader approach can provide new routes for treatment options, and pre-clinical examples include the VHL-based AR degrader ARCC-4, utilizing enzalutamide as an AR recruiter. This degrader was demonstrated to effectively degrade the AR F876L antagonist-agonist conversion mutant . Further pre-clinical examples are ARD-61 and MTX-23 , where the latter was developed utilizing a ligand for the AR DNA binding domain (DBD), exemplifying the use of ligands that bind outside of the androgen binding pocket to facilitate degradation. ARV-110 (Bavdegalutamide), developed by Arvinas, was the first AR degrader to be evaluated in patients, and currently there are four additional bifunctional AR degraders in clinical trials (ARV-766, CC-94676, AC176 and HP518; ). Selectivity of inhibitors against related proteins is sometimes required to limit toxicity, but not possible to achieve due to high active site or ligand binding pocket homology. Interestingly, degraders offer two potential routes around selectivity challenges. The first relies on identification of a novel ligand that binds the desired target in a domain outside of the conserved areas, and thus will only degrade the intended target. This requires significant time and financial investment, and the success will rely on the nature of the ligand and its suitability for use in bifunctional compounds. Similarly, a molecular glue degrader approach may be investigated limiting the glue to a non-conserved domain; however, MGD identification is currently challenging. The second route takes advantage of the observation that bifunctional degraders based on existing non-selective target ligands can exhibit selective degrader activity. For example, the non-selective ATP-competitive fibroblast growth factor receptor (FGFR) inhibitor BGJ398 was utilized to generate a selective FGFR1/2 degrader, DGY-09-192, sparing FGFR3/4 , and selective degraders for STAT3 and STAT5, respectively, have been generated from relatively non-selective ligands . Selectivity in this context likely stems from structural differences that dictate how a target interacts with or can be accessed by the ubiquitin ligase, such that ternary complex formation is either unproductive or does not take place efficiently for a subset of proteins within a group ligandable by the degrader. From this argument follows that different ubiquitin ligases may produce different selectivity profiles, as indeed shown for CRBN and VHL in large-scale proteomics studies using promiscuous kinase ligands . Another example of ligase-driven selectivity is the use of the RNF114 ligase with the non-selective tyrosine kinase inhibitor dasatanib as target recruiter. Although linker chemotype and exit vector geometry will likely impact selectivity, data indicate that VHL and CRBN favor c-ABL degradation, whereas RNF114 preferentially drives degradation of BCR-ABL . The expansion of ligases validated for TPD approaches will undoubtedly provide further opportunities to achieve ligase-driven selectivity based on use of non-selective target ligands. Degraders may provide a way to develop effective drugs for proteins driving biology through scaffolding functions or protein–protein interactions (PPIs), instead of enzymatic activity. TPD is seen as a promising approach for challenging targets like transcription factors, scaffolding proteins, and receptors. However, despite this potential, addressing traditionally undruggable targets with degraders presents significant challenges, with a key consideration being whether identifying a novel ligand for the target is feasible. Many clinically relevant enzymes have been attempted to target using inhibitors, and existing ligands can be leveraged to build degraders that address both enzymatic and non-enzymatic functions. Examples here include the IRAK4 and BTK kinases, where both enzymatic and scaffolding functions mediate signaling . Whereas inhibitors can only address the active-site functionality of these targets, degraders have been demonstrated to be more effective due to removing all functionalities of the targeted protein . Inhibiting PPIs is generally considered difficult, where interacting proteins often share a relatively large and flat binding interface with little opportunity for ligandable pockets . While the concept of targeting PPIs with degraders has been demonstrated utilizing existing PPI inhibitors for BCL family proteins , identification of ligands that bind outside of PPI interfaces opens up for addressing a broader variety of PPIs via degraders, and it will be interesting to see if the maturing degrader field will exploit this possibility. A highly attractive property of degraders is that they may offer a route for removal of aggregated proteins, a hallmark of many neurodegenerative disorders (discussed in detail below). In this scenario, a degrader strategy can offer clear advantages; however, identification of aggregate specific ligands and access of the degrader to the CNS pose significant challenges. In particular, bifunctional degraders are difficult to optimize for blood brain barrier (BBB) penetration, and as such MGDs are an interesting option for degraders that act within the CNS. Resistance mutations in cancer treatments pose a substantial clinical challenge, where cells undergo genetic alterations that confer resistance to initially successful therapeutic interventions, such as upregulation of expression levels or point mutations. In cases where resistance mutations occur in the binding site of small-molecule inhibitors, degraders may offer an advantage. Since degraders do not rely on binding to the active site of the target protein, they can potentially overcome mutations that interfere with traditional inhibitor binding. Moreover, due to their event-based pharmacology and potential for cooperative ternary complexes, degraders may be more forgiving to affinity-reducing mutations in the ligand binding site of the target . An example where degraders have been shown to have activity against resistance-associated mutants is BCR-ABL1, present in approximately 95% of chronic myelogenous leukemia (CML) cases. The introduction of imatinib, an ATP-competitive tyrosine kinase inhibitor, marked a significant milestone in treatment of CML , which was followed by a number of second-generation inhibitors, including dasatanib . Unfortunately, resistance to both imatinib and second-generation compounds inevitably arise upon treatment. The concept of a degrader approach for BCR-ABL1 has been demonstrated utilizing both ATP-competitive inhibitors and compounds binding allosterically, where bifunctional degraders have activity against treatment-resistant BCR-ABL1 mutants . In particular, the dasatanib based degrader SIAIS056 was shown to efficiently degrade BCR-ABL1 mutants associated with dasatanib resistance . Likely this is due to the event driven pharmacology of the degrader, where resistance mutations may decrease ligand affinity , and consequently reduce efficacy of an occupancy-based therapy, but still allow a significant level of induced degradation. It remains to be seen whether specific BCR-ABL1 degraders will be of value for clinical development to supplement the inhibitor pipeline. In a clinical setting, a recent study has focused on BTK in the treatment of B cell cancers like chronic lymphocytic leukemia (CLL). This report characterizes two types of drug resistance mutations in BTK: kinase proficient and kinase impaired. Kinase-impaired mutants, exemplified by L528W, retain downstream BCR signaling despite reduced BTK kinase activity. NX-2127 from Nurix Therapeutics is a potent BTK degrader that is currently in Phase 1 clinical trials, where it has demonstrated over 80% BTK degradation and positive clinical responses in 79% of evaluated CLL patients, irrespective of mutant BTK genotypes, showing promise for overcoming BTK resistance mutations . A further clinical example of where degraders have been used to mitigate resistance mutations is the androgen receptor (AR), an important target in prostate cancer (PC). The AR protein is a transcription factor that promotes cell proliferation when activated by binding to the androgen hormones. In the initial phases of the disease, PC often relies on androgens, and surgical/chemical castration or AR antagonists are employed to deprive the tumor of AR activity . Unfortunately, various mechanisms lead to resistance to androgen-based therapy, including AR overexpression or mutations that convert antagonist activity into an agonist activity, as reported for the clinical AR antagonist enzalutamide . Given the nature of resistance mechanisms for the AR, adopting a degrader approach can provide new routes for treatment options, and pre-clinical examples include the VHL-based AR degrader ARCC-4, utilizing enzalutamide as an AR recruiter. This degrader was demonstrated to effectively degrade the AR F876L antagonist-agonist conversion mutant . Further pre-clinical examples are ARD-61 and MTX-23 , where the latter was developed utilizing a ligand for the AR DNA binding domain (DBD), exemplifying the use of ligands that bind outside of the androgen binding pocket to facilitate degradation. ARV-110 (Bavdegalutamide), developed by Arvinas, was the first AR degrader to be evaluated in patients, and currently there are four additional bifunctional AR degraders in clinical trials (ARV-766, CC-94676, AC176 and HP518; ). A key requirement for development of a bifunctional degrader is to have access to a ligand for the POI (assuming use of one of the known ligase ligands). Therefore, some of the most important current efforts for development of heterobifunctional degraders include the search for new high-specificity POI binders . A second area of great importance for PROTAC development is the search for new molecules recruiting distinct ubiquitin ligases, which is the preoccupation of many public and private laboratories. There are several reasons justifying the need for expansion of the E3 binders’ toolbox. One of the most important aspects is the rapid emergence of resistance, particularly in cancer. If mutations occur in ligases such as CRBN or VHL, or if there is downregulation of the ubiquitin conjugation machinery, current PROTACs may become non-functional . Moreover, it is particularly important to have the choice of using ligases that might give better results in terms of proteolytic activity or if combinatorial treatments are suited. Also, it is important not to hijack all the activity of a ligase, which may block crucial endogenous functions, resulting in unwanted toxicity. These instances underscore the necessity of identifying and developing new binders for alternative ubiquitin ligases. 7.1. Aspects to Consider for POI Ligand Development As mentioned above, the most common strategy used to block the function of a protein has been the development of small chemical inhibitors to target its active site. This effort resulted in generation of hundreds of molecules specifically recognizing a target, but in many cases failing to inhibit functional activity. With a PROTAC strategy, these molecules can be successfully re-employed to build bifunctional degraders. However, when targeting proteins previously considered “undruggable”, new small molecules still need to be specifically designed for degrader development. Usually, traditional small-molecule research focuses on developing high-affinity inhibitors targeting an enzyme through its active site to neutralize its effect by an occupancy-driven mechanism. Since heterobifunctional degraders act in an event-driven mechanism, where they only need to interact transiently with their target , compounds with moderate POI affinity (≥1–500 nM) may be sufficient. Alongside this, ternary complex cooperativity (vide supra), can allow for relatively weak binary ligand affinity. Recently, a framework has been created to assess whether human proteins are “PROTACtable”. This system considers the subcellular location of the protein, its ubiquitination site(s), its half-life, and the availability of one or more small-molecule ligands. The workflow is integrated into the Open Targets Platform ( https://platform.opentargets.org/ , accessed on 7 February 2024). Despite “PROTACtable” proteins not requiring an enzyme active site, a small-molecule ligand-binding remains necessary. In the case of scaffolding proteins, the selection of a binding site is particularly challenging since the POI might be only partially exposed within a given complex. Many currently available degraders are based on existing small-molecule inhibitors, and it is worth noting that inefficient inhibitors can be successfully repurposed to build efficient heterobifunctional degraders, exemplified by ligands developed for TRIM24 . Building upon these early tool compounds, the validation of novel targets using degraders is becoming an increasingly popular strategy in drug discovery. For targets where there are no existing inhibitors, it is necessary to identify a ligand for the POI. As the only requirement for compounds is binding to the protein in question, screening technologies based on DNA encoded libraries (DEL) or Affinity selection-mass spectrometry (AS-MS) are highly suited for identification of novel ligands for challenging targets, for either a POI or an E3. A DEL is a collection of millions to billions of small molecules individually conjugated with unique DNA tags. Using different screening technologies, isolation of compounds that bind the protein target can be achieved, with the DNA tag acting as a barcode, allowing identification of the binding compound. A detailed description of DEL screening is beyond the scope of this review; however, recent excellent reviews by others are available . From a TPD perspective, an advantage with a DEL approach is that the DNA attachment point to the library compound may also serve as a linker exit vector. Briefly, AS-MS integrates compound binding with mass spectrometric analysis for compound isolation and identification, enabling rapid screening of large compounds collections to identify protein binders . An example of a DEL approach for TPD is the identification of a novel binder for the estrogen receptor α, which was incorporated into a bifunctional degrader . A DEL approach was also utilized to identify a binder of the GID4 ubiquitin ligase , which interestingly was also addressed by AS-MS to identify a novel ligase binder , exemplifying the use of two different high-throughput technologies to identify structurally different protein binders. 7.2. Aspects to Consider for E3 Ligand Development The search for new E3 ligases to be used in TPD strategies should consider the ubiquitous (or specific) presence of a ligase in different tissues and cell lines, which may offer benefits in terms of limiting off-target toxicities . As new E3 ligase binders emerge, it will remain important to characterize their scope and applicability, to ensure that the degradation efficiency is at least equal to or better than that observed with VHL or CRBN . Another factor to consider is the subcellular localization of an E3 ligase, since the effect of the degrader could be reduced if its access is limited, for instance, to the nuclear compartment . In addition, several ligases exist in an inactive state or are auto-inhibited in the absence of an activating post-translational modification or binding partner . Using an auto-inhibited ligase may pose additional challenges when considering them for PROTAC development. Naturally, it is also critical that the ligase binder does not inhibit the actual ligase function itself! As mentioned above, some ligases are only expressed in specific cell types or are overexpressed in certain pathologies, and this can potentially be leveraged to develop more specific therapies. If the tumor enrichment of an E3 ligase aligns with the dependence of the tumor on the expression of that ligase, this approach could be suitable. In this regard, certain E3 ligases and other UPS components, such as the WD repeat-containing protein 82 (WDR82), have been identified as promising targets essential for various cancer cell types . This dependence may reduce the chances of developing resistance, as observed with some CRBN and VHL-based degraders . In the same vein as for POI ligands, existing ligands for E3s can sometimes be repurposed for use in bifunctional degraders. In the quest to recruit other ubiquitin ligases, the RING ligase mouse double minute 2 homologue (MDM2) was investigated in a TPD approach. Building on the small-molecule PPI inhibitor nutlin-3, which disrupts the interaction of MDM2 with p53, a bifunctional degrader of the androgen receptor was successfully generated . To profile novel (or established) ligases in TPD context, approaches include HaloPROTACs and TAG platforms (dTAG and aTAG) . These strategies require engineering of a tagged POI, where the tag provides a handle that can be bound by the degrader, allowing evaluation of a ligase across multiple targets via the tag . While the lack of binders for both POI and E3 is not a standalone limitation, it does signify the need for additional efforts before initiating the development of a bifunctional degrader. Various approaches, with library screening and structure-based methods being the most prevalent, are employed to identify new binders. Phenotypic screening is a powerful approach to discover small molecules targeting proteins involved in the regulation of cell physiology and pathology. Several chemical libraries integrating simple or high-complexity molecules have been used by private and public research laboratories . Once integrated into PROTACs, the functionality of the identified molecules as degraders can be screened phenotypically. The chemical properties necessary for drug discovery and the selection of de novo substrates can be defined in the context of phenotypic alterations in cells. Interestingly, this approach can also be used to explore the temporal relationships associated with disease development and response/resistance to treatments. Rational design of heterobifunctional degraders based on crystal structures and computational chemistry has been used to optimize molecules that will efficiently bind to the POI or E3 ligase. This has also provided information on the formation of the ternary complex, which further allows degrader optimization. Several examples illustrate the success of this approach and have been recently reviewed . When crystal structure data are available, this technique can be relatively fast. However, in the absence of such knowledge, two possibilities can be considered: generating the knowledge or using artificial intelligence (AI)-driven tertiary structure prediction models such as DeepMind and RoseTTAFold . These and other approaches become popular if free access exists, like Alphafold from DeepMind, which generates high-quality predicted models of the proteome ( https://alphafold.ebi.ac.uk/ , accessed on 7 February 2024). One of the first successful computational workflows for PROTACs development was reported in 2018 . In this work, authors evaluate the linear linkers using a steric scoring scheme. A more recent, practical, in silico tool for PROTAC development considered the contribution of the three components in the ternary complex . Since then, several groups have reported tools, some of which are freely available, including the Rosetta-based protocols ( https://prosettac.weizmann.ac.il/ , accessed on 7 February 2024) . While some of these methods may be of utility, more work is needed to understand the mechanisms that allow efficient design of heterobifunctional degraders. Artificial intelligence will certainly contribute to better model predictions in the future. 7.3. Linker Optimization The overall degradation efficiency of a heterobifunctional degrader does not simply rely on the affinities of the chemical molecules binding the E3 and the POI. The way in which these two molecules are connected by a linker, allowing the formation of a functional ternary complex (TC) able to induce ubiquitination and degradation of the POI, is as crucial . The length and composition of the linker are critical in the generation of an efficient and specific bifunctional degrader. These design considerations contribute to the efficient formation of a TC , highlighting their importance for degrader optimization . Evidence also clearly indicates the importance of the specific attachment point, or exit vector, to the molecules binding the POI and E3s, which must be optimized for each degrader. Unfortunately, this is not generally predictable due to the structural complexity and dynamics of the TC. Despite the importance of the linker, well-established strategies for design, resulting in high efficiency, are scarce. Often, stepwise optimization through synthetic alteration of the linker is followed by a degradation activity test, utilizing short and structurally simple alkyl or PEG chains as starting points. Most linkers have consisted of combinations of a few chemical motifs , the most common being PEG and alkyl chains of varying lengths, which appear in approximately 55% and 30% of linkers, respectively. Approximately 65% of heterobifunctional degraders contain both an alkyl and PEG segment. Only 15% use glycol units, incorporating additional methylene moieties to access different chain lengths. Other less-used motifs include alkynes (7%), triazoles (6%), and saturated heterocycles such as piperazine and piperidine (4% each). Several strategies have been used to improve chemical functionalities of PROTACs, such as photo-switches, conformational locks, and covalent binding. Recent reviews have summarized some aspects of linker chemistry and design strategy . To accelerate the screening of bifunctional degraders containing different linkers, direct-to-biology (D2B) approaches, where compounds are assessed for activity in the absence of a purification step, are becoming increasingly popular. This approach allows miniaturization and more rapid cycles of compound testing; however, care must be taken to assess non-specific impact of crude reagent mixtures on cell viability. Using a D2B approach, SAR around linkers, POI ligands, exit vectors and ligase recruiters can be rapidly explored to identify lead compounds for further refinement, and this strategy has been employed by Janssen, GSK and AstraZeneca in recent reports . Critically, linker optimization can make dramatic changes to the overall pharmacokinetic properties of the degrader. Whilst optimization of shape, rigidity, and length impact upon the ability to form a productive ternary complex and, therefore, the degree of degradation observed, these changes can also significantly alter metabolic stability, solubility and permeability. Factors such as aromaticity, 3D shape and polarity deliver subtle changes to the shape and nature of the linker itself but can deliver significantly different behavior in in vivo assays. In addition, the nature of the chemistry used to attach the linker to the POI and E3 ligase binders can also be further optimized, often transitioning from the ubiquitous amide bond (which often limits cellular permeability) to a less problematic linking functionality. 7.4. Discovery Approaches for Molecular Glue Degraders Molecular glue degrader discovery is challenging. Unlike bifunctional degraders, where rational design based on ligase and POI ligands is relatively straightforward, molecular glues modulate protein surfaces to induce interactions in ways that are difficult to predict. For this reason, molecular glue discovery has historically been serendipitous, with mechanisms of action identified later. Here, we focus on the discovery of molecular glues which drive novel interactions between a target protein and components of the ubiquitin–proteasome pathways and therefore induce degradation of these target proteins. 7.4.1. Serendipity The first known molecular glue degrader, thalidomide, was marketed from the mid-1950s to treat insomnia and morning sickness. At the time, its mechanism of action was unknown and sadly led to the birth of many children with limb defects due to its unidentified teratogenic effects. In 1965, thalidomide and its derivatives, lenalidomide and pomalidomide, were reinvestigated with renewed interest after it was discovered they had immunomodulatory, anti-inflammatory, and anti-tumorigenic properties. However, it was not until 2014 that these immunomodulatory imide drugs (IMiDs) were finally discovered to bind to CRBN, a substrate receptor of the CUL4-RBX1-DDB1-CRBN ubiquitin ligase complex . A second compound with a mechanism of action analogous to the IMiDs, Indisulam, was originally discovered in the 1990s by screening a library of sulfonamides for cancer cell growth inhibition. Indisulam was shown to cause G1/S cell cycle arrest by flow cytometry and to have in vivo efficacy in human tumor xenograft models . The exact mechanism of action was not elucidated until more than 15 years later, when it was demonstrated that the anti-proliferative effect was due to an induced ternary complex between the mRNA splicing factor RNA binding motif protein 39 (RBM39) and a member of the CUL4 ubiquitin ligase complex called DDB1 and CUL4-associated factor 15 (DCAF15). Formation of this ternary complex leads to the polyubiquitination and degradation of RBM39 . Structural studies showed that indisulam binds DCAF15 and creates a novel surface which enhances RBM39 binding and induces novel protein–protein interactions . As molecular glue degrader discovery has historically been serendipitous, it is reasonable to assume there may be small molecules in development or the clinic for which the molecular glue mechanism has not yet been identified. Ebert et al. used database mining to look for a correlation between the cytotoxicity of 4518 clinal or pre-clinical small molecules and E3 ligase expression in hundreds of human cancer cell lines . These studies identified a correlation between CR8 (CDK inhibitor) and DDB1 (CUL4 substrate adaptor protein) expression. An X-ray crystal structure revealed that CR8 bound to CDK12 had a solvent exposed pyridyl moiety which induced complex formation of CDK12 with Cyclin K and DDB1 (PDB:6TD3). This ternary complex formation leads to ubiquitination of Cyclin K and downstream degradation by the proteasome . 7.4.2. Cellular Screening Approaches Using cell-based assays to screen for compounds with MGD properties has the potential advantage that the complete cellular machinery is present, allowing ubiquitination and subsequent degradation of a target protein. In contrast, the challenge when utilizing cells for compound screening is the extensive hit deconvolution required for validation of MGD mechanism. To help focus this approach, BMS/Cellgene screened a library of CRBN interacting compounds, with the advantage that half the prospective interaction was already defined, and proteomics could be used to identify the target protein. This study was directed towards identification of a molecular glue for the treatment of acute myeloid leukemia (AML), and screening for compounds with antiproliferative potency was performed using ten AML cell lines. This led to the development of CC-90009, a selective GTPS1 degrader, the first CRBN-based molecular glue degrader to enter clinical trials since CRBN was identified to be the primary target of thalidomide . At the time of writing, CC-90009 is in Phase II clinical trials for the treatment of AML . Further expansion of MGDs beyond CRBN requires methods with broader scope. Most of the cullin–RING ubiquitin ligases require conjugation to NEDD8 for activity, and therefore differential screening in cells with normal and deficient neddylation can identify compounds that require uninterrupted neddylation, inferring that activity is driven by a cullin–RING ubiquitin ligase. Mayor-Ruiz et al. used this approach to screen 2000 cytostatic or cytotoxic small molecules, with identification of differentially active compounds. The results were followed up by analysis in CRISPR knockout cell lines of all known cullin-RING ligases and quantitative expression proteomics of treated cells to identify the relevant ligase and target protein respectively. This strategy identified three compounds which induced degradation of Cyclin K by the CRL4 ligase complex . Analysis showed that although these compounds are structurally different from CR8 (identified by data mining described above), they act by a similar mechanism of binding CDK12 and recruiting Cyclin K and DDB1 . To limit a MGD to a desired ligase, morphological screening approaches using cell lines with different ligase expression levels can be used. Cell painting assays can be used to assess hundreds of parameters including cell viability, morphology and the detection of multiple organelles or cellular components , and Ng et al. used this approach in isogenic cell lines expressing different levels of CRBN. A screen of 132 CRBN binders (assessed by a CRBN fluorescence polarization competition assay first) identified FL2-14 as a GSPT2 molecular glue degrader . 7.4.3. Biophysical Screening Approaches As a complementary approach to cell-based systems, purified proteins can be used in biophysical assays to measure the induction of a ternary complex between a POI and ligase. This has the advantage of fully controlling the selection of the E3 and the target. Biophysical assays give a direct read out of ternary complex formation and can therefore help build SAR and drive development of compounds with improved molecular glue properties. However, without the cellular context, biophysical assays cannot give information on target protein degradation and any downstream effects. Of importance for biophysical screening approaches is identifying a target and ligase pairing which is suitable for development, with consideration needed for the target and E3 cellular locations and tissue- and disease-specific expression profiles. Although uncommon, a known weak compound-induced interaction provides an advantageous start point. Pomalidomide induces an interaction between CRBN and the transcription factor IKZF1 which leads to the degradation of the latter. Novartis further identified a weak interaction between Pomalidomide, CRBN and IKZF2 but this interaction did not lead to IKZF2 degradation. This suggests there is a recruitment threshold which needs to be met before molecular glue induced interactions are strong enough to lead to target degradation. The Novartis discovery campaign was driven initially by interaction assays between CRBN-IKZF2 and CRBN-IKZF1, allowing optimization for selectivity before the interaction threshold for target degradation had been met . Another recent study from Novartis has highlighted the use of biophysical approaches to identify the first VHL-based molecular glue degrader, where the glue induces binding and degradation of cysteine dioxygenase 1 (CDO1) . An alternative approach is to take advantage of a known physiological E3 and POI pair by focusing on a mutated POI where the ability of native ligase to bind and ubiquitinate has been lost or impaired. In this scenario, a molecular glue could be utilized to re-establish the interaction between the POI and ligase to restore the normal degradation pathway. β-catenin is an effector protein in the Wnt signaling pathway which normally interacts with the β-TrCP ubiquitin ligase, leading to β-catenin degradation. Mutant β-catenin, found in some colorectal cancers, has an impaired ability to bind β-TrCP, leading to enhanced oncogenic transcription. Nurix Therapeutics developed an FP competition assay using β-TrCP with BODIPY-TMR labelled β-catenin phosphodegron peptides. Discovery was focused on the serine 37 mutant as this is a hotspot for β-catenin mutations. Using an HTS approach, 350,000 compounds were screened through the FP assay to identify enhancers of the β-TrCP and β-catenin peptide interaction. Promising compounds were validated by orthogonal TR-FRET and surface plasmon resonance (SPR) assays . Using native binding E3-POI partners provides the advantage that there is already an interaction surface between the two proteins, with lysine residues available for ubiquitination. It also avoids any issues that may arise from hijacking unrelated E3s to POIs, such as incompatible expression profiles or subcellular localizations. Establishing a rational and unbiased screening approach that is broadly applicable for identification of novel molecular glues across different protein pairs is extremely challenging. Significant efforts have focused around redirecting CRBN towards new targets either by expanding around the IMiDs or looking for new chemical matter. Whilst efforts to expand the IMiD chemical repertoire have been successful, with multiple compounds heading towards the clinic, expanding to look at more E3 ligases may yet open up a range of novel target proteins. Phenotypic screening approaches have identified novel glues, but methods require thorough follow up for target deconvolution and hit validation. Exploiting known weak interactions or, in the case of mutant proteins, using its native E3 ligase may provide advantageous starting points due to an already known protein–protein interfaces and lysine residues available for ubiquitination by the E3 ligase. Molecular glues, although challenging to identify, provide an opportunity hijack the protein degradation pathways using compounds with more favorable physicochemical properties than bifunctional molecules. 7.5. Target Validation via Degraders In addition to direct clinical application, chemical degraders represent a valuable strategy for characterizing the role and importance of a protein in cellular physiology and disease development. Many candidate targets have been selected based on a vital role in the processes they impact, such as oncogenesis, neurodegenerative disorders or inflammation. Validating new targets in a more efficient way represents a crucial step to justify investing efforts in drug development. While transient (siRNA) or permanent (knockout) genetic approaches can be utilized for target validation experiments, these approaches can have drawbacks. Generally, genetic methods, particularly knockout systems, may lead to compensatory mechanisms, such as upregulation of redundant pathways, that may reduce the phenotypic effect related to the absence of the target protein. In contrast, degraders act rapidly, similar to how drugs act on patients, allowing the assessment of how acute depletion of the target affects the relevant readout. There is also a benefit of degrader use to establish pharmacology in situations where catalytic site inhibition does not match the result of siRNA knockdown. 7.6. Assays for Validation of Degraders After developing an initial degrader compound, it is crucial to evaluate parameters for future improvement of critical aspects to obtain an optimal therapeutic molecule. These parameters include binary target engagement, ternary complex formation, efficient polyubiquitination of the target protein, specific proteolysis, pharmacological effects, solubility, stability, and cell permeability. Various assays can be employed to evaluate physicochemical, pharmacologic, and biologic properties of degraders. This evaluation opens avenues for future improvements of prototype molecules. Techniques like fluorescent polarization , time-resolved fluorescence resonance energy transfer , AlphaLISA , surface plasmon resonance (SPR) , and calorimetry can be used to assess target engagement and ternary complex formation. Bioluminescence methods like NanoLuc, NanoTag, or NanoBRET are successful for evaluating cellular permeability . Confirmation of Mechanism of Action Mechanistic assays can determine whether POI proteolysis is driven by the ubiquitin–proteasome system (UPS) or the autophagy-lysosome system (ALS). A pharmacological approach, such as inhibiting the proteasome (e.g., with bortezomib) or autophagy (e.g., with bafilomycin A), is recommended. Moreover, inhibition of the ubiquitin-activating enzyme using MLN7243 can be utilized to determine ubiquitin dependence. The NEDD8 activating enzyme inhibitor MLN4924 is also useful to validate dependence on a CRL, if appropriate. Bifunctional degraders can also be assessed for mechanism by competition with isolated ligase or target ligands, or by use of non-binding compound analogues for the E3. The approaches above can provide evidence to support that a degrader functions through the expected mechanism of action. In addition to western blot analysis, mechanism of action analysis can be performed using homogenous time-resolved fluorescence (HTRF) and AlphaLISA . These represent excellent methods that allow plate-based, high-throughput, compound characterization of endogenous, untagged, POI. This is an advantage, since artificially elevated expression levels and the use of tags can influence POI degradation ; if such systems are utilized, care should be taken to validate degradation on the endogenous level. Direct verification of POI ubiquitylation can be performed by overexposing western blots of cell extracts treated with proteasome inhibitor. Due to rapid deconjugation, POI ubiquitylation is more easily observed using ubiquitin traps (also known as Tandem Ubiquitin Binding Entities) to capture ubiquitylated proteins for detection by western blot or protein arrays . In addition to confirming that a novel degrader is on-mechanism, it is informative to assess general selectivity. Mass spectrometry can globally evaluate the effect on the proteome of the specific degradation of a POI, ensuring that consequences are restricted to the proteolysis of the target and its known regulated functions . summarizes concepts in degrader discovery and validation. 7.7. Therapeutic Areas and Clinical Application Despite significant anticipated challenges, including metabolic stability, dosing and routes of administration, several degrader projects have already entered clinical evaluation. In line with pre-clinical expectations, oral bioavailability of these large molecules can be challenging to attain. Measured oral bioavailabilities in animal studies, particularly for earlier state derivatives, are generally low, (often in the 3–30% range) . Despite this, the majority of clinically investigated agents have been found suitable for oral dosing. Indeed, for more optimized candidate-stage molecules, bioavailability in mice or rat in vivo PK studies can reach 50–90%. At the current time, little information exists in the public domain to quantify how these bioavailabilities in lower species translate into humans, as the corresponding matched oral/ iv dosing studies are rarely undertaken in patients. Understanding and resolving these unknown factors is likely to become important as the field matures. From a patient perspective, low oral bioavailability demands a high pill burden, in order to drive sufficient absorption and free drug exposure in the target tissue to deliver therapeutic benefit. Moreover, the potentially large unabsorbed fraction, which may be excreted largely unchanged, has a significant negative impact on the quantities of active pharmaceutical ingredient (API) required for manufacture and, therefore, on cost of goods. Particularly in cases where degraders are competing with small-molecule inhibitors of the same target or pathway, improvements here may be critical to satisfy cost/benefit analyses prior to approval. 7.7.1. Heterobifunctional Degraders in Oncology As of the time of writing, there are 20 clinical assets in the oncology heterobifunctional space . Of these, 70% are dosed orally, and 30% intravenously. One compound (ARV-471) is now in advanced Phase III clinical trials which are not expected to conclude until 2028. For the majority of clinical degraders, the proteins of interest have already been investigated with significant numbers of small-molecule agents. Examples here include the estrogen receptors (ER) in breast cancer (BC), targeted with selective estrogen receptor degrader small molecules (SERDs), the androgen receptor (AR) in metastatic castrate-resistant prostate cancer (mCRPC), targeted with selective androgen receptor degrader small molecules (SARDs), and kinases such as mtBRAF and BTK, targeted with both covalent and non-covalent inhibitors. As these trials progress, it will be interesting to see where similarities and differences occur in terms of patient responses and outcomes. To date, the limited emerging clinical data from those agents progressing beyond Phase I remains relatively modest in terms of response rates. In the case of ARV-471, Phase II data suggested an overall survival benefit of approximately 3-4 months, and median protein degradation of approximately 70% . In the AR setting, in Phase I studies, ARV-110 showed >50% decrease in Prostate-Specific Antigen (PSA) levels in approximately 16% of the patient population and 2/7 partial responses in the evaluable patient cohort . Of note, in patients with known resistance mutations, such as T878X and H875Y, these responses were somewhat higher, suggesting a role for degraders in settings where tumor heterogeneity or tumor evolution has led to therapeutic resistance with small-molecule inhibitors. Recent reports have suggested that the modest responses in the clinic may be due to a variety of factors , including: The aforementioned low bioavailability and, therefore, potentially subtherapeutic exposure at target Emergent resistance due to loss of function, or decreased expression of the cognate E3 ligase Elevated rates of protein re-expression in response to treatment, counteracting active degradation by the heterobifunctional agent. It is important to state that these agents are only the first few to report early clinical data, and as the field matures, and collective wisdom and expertise widens, it is likely that our understanding of the degree of bioavailability, the importance of protein re-expression rates and appropriate clinical settings will help to drive improvements in efficacy and, ultimately, patient benefit. So far, many of the targeted proteins seem to have a rapid resynthesis rate measured in a few hours (approximately 3 h and 4 h for the AR , and ER , respectively). This rapid resynthesis seems to overcome the rate at which the heterobifunctional degraders can eradicate the POI from the cell . Considering this, targeting proteins with a slower rate of compensatory re-expression may become a preferred application for heterobifunctional degraders. Alongside rapid re-expression of the target protein, clinical resistance has also been observed to arise from alterations of the E3 ligase system, or upregulated expression of multidrug resistance efflux pumps . Beyond slowly re-expressed proteins, heterobifunctional degraders may offer other opportunities where more traditional modalities have struggled to gain traction. Of specific note in the oncology space, the emerging degraders of the BRM protein offer a compelling instance where a degrader delivers benefit over a small-molecule inhibitor. Based on the concept of collateral lethality , experimental studies demonstrated that certain lung tumors undergo loss of the SMARCA4 gene, encoding for the BRG1 protein, an essential part of the SWI/SNF chromatin remodeling complex, either by frameshift mutation or epigenetic silencing . This leaves this cell population entirely dependent upon the related protein BRM, encoded by the SMARCA2 gene. In this context, a selective BRM inhibitor would be lethal to the ca. 10% of non-small-cell lung cancers (NSCLC) where the SMARCA4 gene is lost or mutated, but well tolerated in healthy tissue due to their unaltered expression. However, due to the high sequence conservation between the two targets and despite extensive efforts, selective BRM inhibitors (for either the bromodomain or ATPase domain) remain elusive. Here, PRT3789 from Prelude Therapeutics offers clear differentiation from these small-molecule efforts . Biochemically, the heterobifunctional molecule binds at equipotent nanomolar concentrations to both BRG and BRM1, yet delivers 19-fold selectivity in cell-based BRM/BRG1 HiBiT assays. More interestingly, the compound delivers a 720 pM DC 50 and 94% D max vs. BRM yet spares BRG1 (14 nM DC 50 and 76% D max ), delivering selective cell killing in mtSMARCA4/SMARCA4-del cells, but not in SMARCA4-wt cells, with this selectivity translating into matched in vivo xenograft studies. The precise mechanisms underlying this enhanced specificity have not been described but this outcome reflects those observed in the conversion of non-selective kinase inhibitors to selective kinase heterobifunctional degraders . This approach offers the tantalizing prospect of selectively degrading tumor-specific protein homologs, or members of closely related protein families, in a way which is not possible with small-molecule inhibitors. Whilst in its infancy, this paradigm may offer a real differentiator for heterobifunctional molecules, extending the remit beyond those proteins where high quality and effective small-molecule therapies already exist. 7.7.2. Molecular Glue Degraders in Oncology The molecular glue degrader landscape in oncology is represented by two predominant molecular classes—the dominant class of MGDs is derived from the phthalimide CRBN recruiters, and the smaller group includes those that are derived from other chemotypes. Thalidomide, and related derivatives, had long been known to be effective in multiple myeloma, but through unknown mechanisms. Significant work by the Tokyo Institute of Technology and Celgene unraveled this mechanism and led to the explosion of interest in CRBN-derived molecular glues. As such, thalidomide was the first approved CRBN-molecular glue, well before it was known to act in this manner. Approvals for lenalidomide and pomalidomide have since been granted. As of the time of writing, a further 16 molecular glues have now entered the clinic . Of these, for those where a structure has been disclosed, only three glues (Indisulam, CQS and E7820) do not display the structural motifs common to CRBN molecular glues, instead recruiting DCAF15 to effect protein degradation of RBM39. This overwhelming focus upon CRBN molecular glues raises several challenges, including the race to discover (and patent) novel chemical space. From a clinical standpoint, it also implies that many of the dozens of molecular glues now in pre-clinical development are likely to be competing for the same disease segment, and thus the same clinical trial populations, potentially limiting recruitment and delaying evaluation. Clearly, exploitation of a wider range of E3 ligases in the pursuit of MGDs is commercially attractive and likely to deliver wider patient benefit. Given their smaller molecular weight and potentially improved physicochemical properties, oral bioavailability remains a key attractive feature of molecular glues, and all the compounds in the clinic which recruit CRBN as the E3 ligase are dosed orally, except for CC-90009 which is dosed via an IV infusion. The reasoning behind this outlier route of administration does not appear to have been publicly disclosed at this time. It is interesting to note that, in addition, all clinical examples of DCAF15 molecular glues are also dosed via an IV infusion, suggesting that oral bioavailability is not necessarily guaranteed for molecular glues outside of the CRBN IMiD-derived agents. 7.7.3. Heterobifunctional Degraders for Inflammatory Indications TPD is emerging as a promising approach for the treatment of inflammatory diseases, offering a novel therapeutic strategy with potential advantages. Inflammatory diseases, characterized by abnormal immune responses, may involve dysregulated protein expression contributing to pathogenesis, and a TPD approach is suited to address this by selectively removing disease-associated proteins. Another potential benefit lies in the ability to modulate inflammatory signaling pathways by degrading previously un-druggable proteins. An example of these strategies is the development of heterobifunctional degraders for the protein RIPK2. Acting downstream of pattern recognition receptors, RIPK2 activates NF-κB, leading to the production of inflammatory cytokines. Dysregulation of RIPK2 is implicated in various inflammatory diseases, such as Crohn’s Disease and Ulcerative Colitis. Degraders for RIPK2 have been explored pre-clinically as a strategy to improve kinase selectivity and pharmacokinetic properties of inhibitors, and have shown promising anti-inflammatory properties . Further examples of targets in inflammatory pathways where degraders have been developed include TYK2 and BTK , and bifunctional compounds for both are in pre-clinical development for inflammatory indications by Kymera Therapeutics and Nurix Therapeutics, respectively. Currently, the only target where a bifunctional degrader has reached the clinic for an inflammatory indication is IRAK4. As a serine/threonine kinase, IRAK4 functions as a key mediator in the activation of signaling in response to inflammatory stimulation. IRAK4’s central role in inflammatory signaling makes it an attractive target in conditions associated with dysregulated immune activation, and several inhibitors of IRAK4′s kinase activity have entered clinical evaluation . Multiple pre-clinical studies of IRAK4 degraders have highlighted that potent degraders for this kinase target can be generated , and KT-474 by Kymera Therapeutics is now in Phase 2 for treatment of hidradenitis suppurativa (NCT06028230) and atopic dermatitis (NCT06058156). The Phase 1 clinical results have demonstrated that single dosing of 600 mg–1600 mg KT-474 led to a rapid drop in IRAK4 levels in peripheral blood mononuclear cells (PBMCs), reaching nadir by 48 h. The degradation is sustained for at least 14 days, as IRAK4 levels did not return to baseline for these doses at that time. Multiple dosing over 14 days (once daily) showed that a dose as low as 25 mg led to robust IRAK4 degradation (92% at nadir). It is worth noting that at the 100 mg dose, IRAK4 levels were still significantly below baseline at day 28, some 14 days post-dosing. For both hidradenitis suppurativa and atopic dermatitis, there was an improvement in clinical symptoms after treatment with 75 mg KT-474 daily for 28 days. These clinical responses were either maintained or continued to improve in the two weeks that were evaluated after dosing was halted. Overall, the Phase 1 results are promising, and indicate that longer term treatment can be achieved with a relatively low dose of the compound, and still achieve a strong degradation of IRAK4. In addition to Kymera Therapeutics, Nurix Therapeutics are in the IND enabling pre-clinical phase for their IRAK4 degrader for rheumatoid arthritis and other inflammatory conditions. 7.7.4. Molecular Glue Degraders for Inflammatory Indications At this time, there are no clinical examples of rationally developed molecular glue degraders for treatment of inflammatory disease. However, in the pre-clinical pipeline, Monte Rosa Therapeutics is in the IND enabling phase for an MGD, MRT-6160, that targets VAV1, a protein implicated in T- and B-cell receptor signaling. Both Monte Rosa and Captor Therapeutics are also in the discovery phases for molecular glue degraders directed to NEK7, an activator of the NLRP3 inflammasome. 7.7.5. Heterobifunctional Degraders for CNS Disorders Whereas targeted protein degradation in oncology has largely exploited targets with matched small-molecule therapeutics, CNS disorders present opportunities for significant differentiation from both small- and large-molecule therapeutic approaches. Misfolded protein aggregates, a hallmark of neurodegenerative disorders, have been considered undruggable using conventional inhibitor approaches, potentially accounting for the failure of compounds in clinical trials targeting protein aggregates in the CNS . At this time, a large number of CNS disorders lack effective treatment, and heterobifunctional degraders represent an attractive therapeutic instrument due to their ability to remove proteins via proteasomal degradation. Despite their potential for degrading a POI in vitro, a major challenge for heterobifunctional degraders is their ability to reach the brain and treat the disease in vivo. Due to their high molecular weight and a large polar surface area, achieving blood brain barrier (BBB) permeability of heterobifunctional degraders is particularly challenging. In this context, degrader–antibody conjugates or encapsulated nanoparticles that can cross the BBB through receptor-mediated transcytosis, have been investigated and may provide an alternative route to access the CNS . Ubiquitin ligases may have tissue-specific expression, such as RNF182, expressed preferentially in the brain; CNS-restricted ligase expression enables the potential for a more specific targeting of the POI within the CNS , with the possible advantage of limiting unwanted effects in tissues not directly involved in disease pathology. Unlike the oncology exemplars described above, PROTACs for neurodegenerative disorders remain in pre-clinical development, largely given the challenges of targeting the brain. Nevertheless, steps have been taken to advance PROTAC molecules in the neuroscience field, with a particular focus on Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). AD The accumulation of mutated tau species into neurofibrillary tangles, both in the intracellular and extracellular space, leads to cellular toxicity and neuronal cell death . Different peptide-based and small-molecule-based PROTACs have been developed for tau degradation. TH006, a peptide-based PROTAC with an ALAPYIP sequence as a VHL ligand, was shown to induce tau degradation in N2a cells overexpressing tau. Whilst the effect of degradation was observed at high concentrations (200 μM), TH006 administration in a mouse model of AD resulted in a reduction in tau levels in the cerebral cortex and hippocampus. TH006 has been administered both intranasally and intravenously, probably due to low BBB permeability, a common feature of these peptides . Similarly, a Keap1-based peptide PROTAC was observed to recruit CUL3 KEAP1 ubiquitin ligase, inducing the degradation of tau through the ubiquitin–proteasome system . QC-01-175, a small-molecule tau-degrading PROTAC based on the PET tracer T807, with a CRBN ligand, was shown to induce Tau degradation in FTD patient-derived neuronal models including the tau-A152T and the tau-P301L variants . Following linker optimization, second-generation CRBN-recruiting degraders (FMF-06-series) delivered a tenfold improvement in degradation potency of total tau and phospho-tau S396 with a tau reduction by 50% at 10 nM concentration . Minimal E3-ligase occupancy was observed in in vitro cellular target engagement assays, indicating low cell permeability of the optimized analogues . C004019, a VHL-based degrader, was demonstrated to lead to tau degradation through the proteasome, both in vitro and in vivo. C004019 has shown a DC 50 of 7.9 nM in a HEK293-hTau overexpressed cell line. Furthermore, intracerebroventricular or subcutaneous administration of C004019 promoted a sustained tau clearance in vivo . Another example is compound I3, a CRBN-based degrader with a THK5105 derivative as a tau ligand, where tau degradation has been demonstrated in vitro using PC12 cells . In the clinical development pipeline, Arvinas claims to have achieved BBB penetration and removal of 95% of pathological tau in vivo after parenteral administration in animal models; the structure of this PROTAC has not been disclosed at the time of writing. PD Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene and in the α-synuclein gene (SNCA) are linked to the onset of PD. The dysfunction of LRRK2 may contribute to the accumulation of α-synuclein, consequent microglia activation, neuroinflammation and ultimately neuronal cell death . Selective degraders targeting LRRK2 have been recently disclosed in a patent by Arvinas, claiming the discovery of potent and selective CRBN-based LRRK2 PROTACs able to degrade LRRK2 in the cerebral cortex after single oral administration in a fPD mouse model with G2019S LRRK2 mutation . In parallel, the Ciulli lab discovered the VHL-based degrader XL01126 that has been shown to be a potent degrader of LRRK2 in multiple cell lines and to pass through the BBB after oral or parenteral administration in mice, exhibiting an oral bioavailability of 15% . These attractive in vitro and in vivo properties of XL01126 represent an intriguing starting point for further drug development. With respect to α-synuclein, a synthetic peptide-based degrader has been shown to degrade intracellular α-synuclein in a recombinant expression system. The degradation of α-synuclein through the proteasome has been shown to rescue mitochondrial defects caused by aberrant α-synuclein accumulation . Moreover, in a recent patent, Arvinas claims the discovery of a series of small-molecule PROTACs, containing a VHL, CRBN, IAP or MDM2 ligand, showing a 65% degradation of α-synuclein at 1 μM in different cell lines . HD The aggregation of mutant huntingtin in HD leads to progressive degeneration of neurons in the striatum and cerebral cortex. Small-molecule-based bifunctional IAP-based degraders have been developed showing ubiquitination and degradation of mutant huntingtin in fibroblasts derived from HD patients . Further studies are needed to fully exploit this approach to treat HD, as the degradation activity has been observed to also involve the wild-type huntingtin . FTD and ALS The TAR DNA-binding protein 43 (TDP-43) is an example of a misfolded protein implicated in FTD and ALS. The successful removal of the toxic C-terminal form using a heterobifunctional degrader has recently been reported . Given the challenges of developing new drugs for targeting mutated proteins in the brain, further in vitro and in vivo validation in independent laboratories is required to further explore the viability of heterobifunctional as an effective therapeutic tool to treat neurodegenerative disorders. 7.7.6. Molecular Glue Degraders for CNS Disorders In principle, an MGD approach has distinct advantages for the CNS space as compared to heterobifunctional degraders, largely due to the generally much more attractive physicochemical properties of glues. At this time, no MGDs have been reported for therapeutically relevant CNS targets. Discovery of MGDs here may favor non-aggregating targets, such as LRRK2 described above; however, glues for aggregating proteins may also be possible to discover, since it has been demonstrated that heterobifunctional compounds can function in this area, e.g., for tau. As mentioned above, the most common strategy used to block the function of a protein has been the development of small chemical inhibitors to target its active site. This effort resulted in generation of hundreds of molecules specifically recognizing a target, but in many cases failing to inhibit functional activity. With a PROTAC strategy, these molecules can be successfully re-employed to build bifunctional degraders. However, when targeting proteins previously considered “undruggable”, new small molecules still need to be specifically designed for degrader development. Usually, traditional small-molecule research focuses on developing high-affinity inhibitors targeting an enzyme through its active site to neutralize its effect by an occupancy-driven mechanism. Since heterobifunctional degraders act in an event-driven mechanism, where they only need to interact transiently with their target , compounds with moderate POI affinity (≥1–500 nM) may be sufficient. Alongside this, ternary complex cooperativity (vide supra), can allow for relatively weak binary ligand affinity. Recently, a framework has been created to assess whether human proteins are “PROTACtable”. This system considers the subcellular location of the protein, its ubiquitination site(s), its half-life, and the availability of one or more small-molecule ligands. The workflow is integrated into the Open Targets Platform ( https://platform.opentargets.org/ , accessed on 7 February 2024). Despite “PROTACtable” proteins not requiring an enzyme active site, a small-molecule ligand-binding remains necessary. In the case of scaffolding proteins, the selection of a binding site is particularly challenging since the POI might be only partially exposed within a given complex. Many currently available degraders are based on existing small-molecule inhibitors, and it is worth noting that inefficient inhibitors can be successfully repurposed to build efficient heterobifunctional degraders, exemplified by ligands developed for TRIM24 . Building upon these early tool compounds, the validation of novel targets using degraders is becoming an increasingly popular strategy in drug discovery. For targets where there are no existing inhibitors, it is necessary to identify a ligand for the POI. As the only requirement for compounds is binding to the protein in question, screening technologies based on DNA encoded libraries (DEL) or Affinity selection-mass spectrometry (AS-MS) are highly suited for identification of novel ligands for challenging targets, for either a POI or an E3. A DEL is a collection of millions to billions of small molecules individually conjugated with unique DNA tags. Using different screening technologies, isolation of compounds that bind the protein target can be achieved, with the DNA tag acting as a barcode, allowing identification of the binding compound. A detailed description of DEL screening is beyond the scope of this review; however, recent excellent reviews by others are available . From a TPD perspective, an advantage with a DEL approach is that the DNA attachment point to the library compound may also serve as a linker exit vector. Briefly, AS-MS integrates compound binding with mass spectrometric analysis for compound isolation and identification, enabling rapid screening of large compounds collections to identify protein binders . An example of a DEL approach for TPD is the identification of a novel binder for the estrogen receptor α, which was incorporated into a bifunctional degrader . A DEL approach was also utilized to identify a binder of the GID4 ubiquitin ligase , which interestingly was also addressed by AS-MS to identify a novel ligase binder , exemplifying the use of two different high-throughput technologies to identify structurally different protein binders. The search for new E3 ligases to be used in TPD strategies should consider the ubiquitous (or specific) presence of a ligase in different tissues and cell lines, which may offer benefits in terms of limiting off-target toxicities . As new E3 ligase binders emerge, it will remain important to characterize their scope and applicability, to ensure that the degradation efficiency is at least equal to or better than that observed with VHL or CRBN . Another factor to consider is the subcellular localization of an E3 ligase, since the effect of the degrader could be reduced if its access is limited, for instance, to the nuclear compartment . In addition, several ligases exist in an inactive state or are auto-inhibited in the absence of an activating post-translational modification or binding partner . Using an auto-inhibited ligase may pose additional challenges when considering them for PROTAC development. Naturally, it is also critical that the ligase binder does not inhibit the actual ligase function itself! As mentioned above, some ligases are only expressed in specific cell types or are overexpressed in certain pathologies, and this can potentially be leveraged to develop more specific therapies. If the tumor enrichment of an E3 ligase aligns with the dependence of the tumor on the expression of that ligase, this approach could be suitable. In this regard, certain E3 ligases and other UPS components, such as the WD repeat-containing protein 82 (WDR82), have been identified as promising targets essential for various cancer cell types . This dependence may reduce the chances of developing resistance, as observed with some CRBN and VHL-based degraders . In the same vein as for POI ligands, existing ligands for E3s can sometimes be repurposed for use in bifunctional degraders. In the quest to recruit other ubiquitin ligases, the RING ligase mouse double minute 2 homologue (MDM2) was investigated in a TPD approach. Building on the small-molecule PPI inhibitor nutlin-3, which disrupts the interaction of MDM2 with p53, a bifunctional degrader of the androgen receptor was successfully generated . To profile novel (or established) ligases in TPD context, approaches include HaloPROTACs and TAG platforms (dTAG and aTAG) . These strategies require engineering of a tagged POI, where the tag provides a handle that can be bound by the degrader, allowing evaluation of a ligase across multiple targets via the tag . While the lack of binders for both POI and E3 is not a standalone limitation, it does signify the need for additional efforts before initiating the development of a bifunctional degrader. Various approaches, with library screening and structure-based methods being the most prevalent, are employed to identify new binders. Phenotypic screening is a powerful approach to discover small molecules targeting proteins involved in the regulation of cell physiology and pathology. Several chemical libraries integrating simple or high-complexity molecules have been used by private and public research laboratories . Once integrated into PROTACs, the functionality of the identified molecules as degraders can be screened phenotypically. The chemical properties necessary for drug discovery and the selection of de novo substrates can be defined in the context of phenotypic alterations in cells. Interestingly, this approach can also be used to explore the temporal relationships associated with disease development and response/resistance to treatments. Rational design of heterobifunctional degraders based on crystal structures and computational chemistry has been used to optimize molecules that will efficiently bind to the POI or E3 ligase. This has also provided information on the formation of the ternary complex, which further allows degrader optimization. Several examples illustrate the success of this approach and have been recently reviewed . When crystal structure data are available, this technique can be relatively fast. However, in the absence of such knowledge, two possibilities can be considered: generating the knowledge or using artificial intelligence (AI)-driven tertiary structure prediction models such as DeepMind and RoseTTAFold . These and other approaches become popular if free access exists, like Alphafold from DeepMind, which generates high-quality predicted models of the proteome ( https://alphafold.ebi.ac.uk/ , accessed on 7 February 2024). One of the first successful computational workflows for PROTACs development was reported in 2018 . In this work, authors evaluate the linear linkers using a steric scoring scheme. A more recent, practical, in silico tool for PROTAC development considered the contribution of the three components in the ternary complex . Since then, several groups have reported tools, some of which are freely available, including the Rosetta-based protocols ( https://prosettac.weizmann.ac.il/ , accessed on 7 February 2024) . While some of these methods may be of utility, more work is needed to understand the mechanisms that allow efficient design of heterobifunctional degraders. Artificial intelligence will certainly contribute to better model predictions in the future. The overall degradation efficiency of a heterobifunctional degrader does not simply rely on the affinities of the chemical molecules binding the E3 and the POI. The way in which these two molecules are connected by a linker, allowing the formation of a functional ternary complex (TC) able to induce ubiquitination and degradation of the POI, is as crucial . The length and composition of the linker are critical in the generation of an efficient and specific bifunctional degrader. These design considerations contribute to the efficient formation of a TC , highlighting their importance for degrader optimization . Evidence also clearly indicates the importance of the specific attachment point, or exit vector, to the molecules binding the POI and E3s, which must be optimized for each degrader. Unfortunately, this is not generally predictable due to the structural complexity and dynamics of the TC. Despite the importance of the linker, well-established strategies for design, resulting in high efficiency, are scarce. Often, stepwise optimization through synthetic alteration of the linker is followed by a degradation activity test, utilizing short and structurally simple alkyl or PEG chains as starting points. Most linkers have consisted of combinations of a few chemical motifs , the most common being PEG and alkyl chains of varying lengths, which appear in approximately 55% and 30% of linkers, respectively. Approximately 65% of heterobifunctional degraders contain both an alkyl and PEG segment. Only 15% use glycol units, incorporating additional methylene moieties to access different chain lengths. Other less-used motifs include alkynes (7%), triazoles (6%), and saturated heterocycles such as piperazine and piperidine (4% each). Several strategies have been used to improve chemical functionalities of PROTACs, such as photo-switches, conformational locks, and covalent binding. Recent reviews have summarized some aspects of linker chemistry and design strategy . To accelerate the screening of bifunctional degraders containing different linkers, direct-to-biology (D2B) approaches, where compounds are assessed for activity in the absence of a purification step, are becoming increasingly popular. This approach allows miniaturization and more rapid cycles of compound testing; however, care must be taken to assess non-specific impact of crude reagent mixtures on cell viability. Using a D2B approach, SAR around linkers, POI ligands, exit vectors and ligase recruiters can be rapidly explored to identify lead compounds for further refinement, and this strategy has been employed by Janssen, GSK and AstraZeneca in recent reports . Critically, linker optimization can make dramatic changes to the overall pharmacokinetic properties of the degrader. Whilst optimization of shape, rigidity, and length impact upon the ability to form a productive ternary complex and, therefore, the degree of degradation observed, these changes can also significantly alter metabolic stability, solubility and permeability. Factors such as aromaticity, 3D shape and polarity deliver subtle changes to the shape and nature of the linker itself but can deliver significantly different behavior in in vivo assays. In addition, the nature of the chemistry used to attach the linker to the POI and E3 ligase binders can also be further optimized, often transitioning from the ubiquitous amide bond (which often limits cellular permeability) to a less problematic linking functionality. Molecular glue degrader discovery is challenging. Unlike bifunctional degraders, where rational design based on ligase and POI ligands is relatively straightforward, molecular glues modulate protein surfaces to induce interactions in ways that are difficult to predict. For this reason, molecular glue discovery has historically been serendipitous, with mechanisms of action identified later. Here, we focus on the discovery of molecular glues which drive novel interactions between a target protein and components of the ubiquitin–proteasome pathways and therefore induce degradation of these target proteins. 7.4.1. Serendipity The first known molecular glue degrader, thalidomide, was marketed from the mid-1950s to treat insomnia and morning sickness. At the time, its mechanism of action was unknown and sadly led to the birth of many children with limb defects due to its unidentified teratogenic effects. In 1965, thalidomide and its derivatives, lenalidomide and pomalidomide, were reinvestigated with renewed interest after it was discovered they had immunomodulatory, anti-inflammatory, and anti-tumorigenic properties. However, it was not until 2014 that these immunomodulatory imide drugs (IMiDs) were finally discovered to bind to CRBN, a substrate receptor of the CUL4-RBX1-DDB1-CRBN ubiquitin ligase complex . A second compound with a mechanism of action analogous to the IMiDs, Indisulam, was originally discovered in the 1990s by screening a library of sulfonamides for cancer cell growth inhibition. Indisulam was shown to cause G1/S cell cycle arrest by flow cytometry and to have in vivo efficacy in human tumor xenograft models . The exact mechanism of action was not elucidated until more than 15 years later, when it was demonstrated that the anti-proliferative effect was due to an induced ternary complex between the mRNA splicing factor RNA binding motif protein 39 (RBM39) and a member of the CUL4 ubiquitin ligase complex called DDB1 and CUL4-associated factor 15 (DCAF15). Formation of this ternary complex leads to the polyubiquitination and degradation of RBM39 . Structural studies showed that indisulam binds DCAF15 and creates a novel surface which enhances RBM39 binding and induces novel protein–protein interactions . As molecular glue degrader discovery has historically been serendipitous, it is reasonable to assume there may be small molecules in development or the clinic for which the molecular glue mechanism has not yet been identified. Ebert et al. used database mining to look for a correlation between the cytotoxicity of 4518 clinal or pre-clinical small molecules and E3 ligase expression in hundreds of human cancer cell lines . These studies identified a correlation between CR8 (CDK inhibitor) and DDB1 (CUL4 substrate adaptor protein) expression. An X-ray crystal structure revealed that CR8 bound to CDK12 had a solvent exposed pyridyl moiety which induced complex formation of CDK12 with Cyclin K and DDB1 (PDB:6TD3). This ternary complex formation leads to ubiquitination of Cyclin K and downstream degradation by the proteasome . 7.4.2. Cellular Screening Approaches Using cell-based assays to screen for compounds with MGD properties has the potential advantage that the complete cellular machinery is present, allowing ubiquitination and subsequent degradation of a target protein. In contrast, the challenge when utilizing cells for compound screening is the extensive hit deconvolution required for validation of MGD mechanism. To help focus this approach, BMS/Cellgene screened a library of CRBN interacting compounds, with the advantage that half the prospective interaction was already defined, and proteomics could be used to identify the target protein. This study was directed towards identification of a molecular glue for the treatment of acute myeloid leukemia (AML), and screening for compounds with antiproliferative potency was performed using ten AML cell lines. This led to the development of CC-90009, a selective GTPS1 degrader, the first CRBN-based molecular glue degrader to enter clinical trials since CRBN was identified to be the primary target of thalidomide . At the time of writing, CC-90009 is in Phase II clinical trials for the treatment of AML . Further expansion of MGDs beyond CRBN requires methods with broader scope. Most of the cullin–RING ubiquitin ligases require conjugation to NEDD8 for activity, and therefore differential screening in cells with normal and deficient neddylation can identify compounds that require uninterrupted neddylation, inferring that activity is driven by a cullin–RING ubiquitin ligase. Mayor-Ruiz et al. used this approach to screen 2000 cytostatic or cytotoxic small molecules, with identification of differentially active compounds. The results were followed up by analysis in CRISPR knockout cell lines of all known cullin-RING ligases and quantitative expression proteomics of treated cells to identify the relevant ligase and target protein respectively. This strategy identified three compounds which induced degradation of Cyclin K by the CRL4 ligase complex . Analysis showed that although these compounds are structurally different from CR8 (identified by data mining described above), they act by a similar mechanism of binding CDK12 and recruiting Cyclin K and DDB1 . To limit a MGD to a desired ligase, morphological screening approaches using cell lines with different ligase expression levels can be used. Cell painting assays can be used to assess hundreds of parameters including cell viability, morphology and the detection of multiple organelles or cellular components , and Ng et al. used this approach in isogenic cell lines expressing different levels of CRBN. A screen of 132 CRBN binders (assessed by a CRBN fluorescence polarization competition assay first) identified FL2-14 as a GSPT2 molecular glue degrader . 7.4.3. Biophysical Screening Approaches As a complementary approach to cell-based systems, purified proteins can be used in biophysical assays to measure the induction of a ternary complex between a POI and ligase. This has the advantage of fully controlling the selection of the E3 and the target. Biophysical assays give a direct read out of ternary complex formation and can therefore help build SAR and drive development of compounds with improved molecular glue properties. However, without the cellular context, biophysical assays cannot give information on target protein degradation and any downstream effects. Of importance for biophysical screening approaches is identifying a target and ligase pairing which is suitable for development, with consideration needed for the target and E3 cellular locations and tissue- and disease-specific expression profiles. Although uncommon, a known weak compound-induced interaction provides an advantageous start point. Pomalidomide induces an interaction between CRBN and the transcription factor IKZF1 which leads to the degradation of the latter. Novartis further identified a weak interaction between Pomalidomide, CRBN and IKZF2 but this interaction did not lead to IKZF2 degradation. This suggests there is a recruitment threshold which needs to be met before molecular glue induced interactions are strong enough to lead to target degradation. The Novartis discovery campaign was driven initially by interaction assays between CRBN-IKZF2 and CRBN-IKZF1, allowing optimization for selectivity before the interaction threshold for target degradation had been met . Another recent study from Novartis has highlighted the use of biophysical approaches to identify the first VHL-based molecular glue degrader, where the glue induces binding and degradation of cysteine dioxygenase 1 (CDO1) . An alternative approach is to take advantage of a known physiological E3 and POI pair by focusing on a mutated POI where the ability of native ligase to bind and ubiquitinate has been lost or impaired. In this scenario, a molecular glue could be utilized to re-establish the interaction between the POI and ligase to restore the normal degradation pathway. β-catenin is an effector protein in the Wnt signaling pathway which normally interacts with the β-TrCP ubiquitin ligase, leading to β-catenin degradation. Mutant β-catenin, found in some colorectal cancers, has an impaired ability to bind β-TrCP, leading to enhanced oncogenic transcription. Nurix Therapeutics developed an FP competition assay using β-TrCP with BODIPY-TMR labelled β-catenin phosphodegron peptides. Discovery was focused on the serine 37 mutant as this is a hotspot for β-catenin mutations. Using an HTS approach, 350,000 compounds were screened through the FP assay to identify enhancers of the β-TrCP and β-catenin peptide interaction. Promising compounds were validated by orthogonal TR-FRET and surface plasmon resonance (SPR) assays . Using native binding E3-POI partners provides the advantage that there is already an interaction surface between the two proteins, with lysine residues available for ubiquitination. It also avoids any issues that may arise from hijacking unrelated E3s to POIs, such as incompatible expression profiles or subcellular localizations. Establishing a rational and unbiased screening approach that is broadly applicable for identification of novel molecular glues across different protein pairs is extremely challenging. Significant efforts have focused around redirecting CRBN towards new targets either by expanding around the IMiDs or looking for new chemical matter. Whilst efforts to expand the IMiD chemical repertoire have been successful, with multiple compounds heading towards the clinic, expanding to look at more E3 ligases may yet open up a range of novel target proteins. Phenotypic screening approaches have identified novel glues, but methods require thorough follow up for target deconvolution and hit validation. Exploiting known weak interactions or, in the case of mutant proteins, using its native E3 ligase may provide advantageous starting points due to an already known protein–protein interfaces and lysine residues available for ubiquitination by the E3 ligase. Molecular glues, although challenging to identify, provide an opportunity hijack the protein degradation pathways using compounds with more favorable physicochemical properties than bifunctional molecules. The first known molecular glue degrader, thalidomide, was marketed from the mid-1950s to treat insomnia and morning sickness. At the time, its mechanism of action was unknown and sadly led to the birth of many children with limb defects due to its unidentified teratogenic effects. In 1965, thalidomide and its derivatives, lenalidomide and pomalidomide, were reinvestigated with renewed interest after it was discovered they had immunomodulatory, anti-inflammatory, and anti-tumorigenic properties. However, it was not until 2014 that these immunomodulatory imide drugs (IMiDs) were finally discovered to bind to CRBN, a substrate receptor of the CUL4-RBX1-DDB1-CRBN ubiquitin ligase complex . A second compound with a mechanism of action analogous to the IMiDs, Indisulam, was originally discovered in the 1990s by screening a library of sulfonamides for cancer cell growth inhibition. Indisulam was shown to cause G1/S cell cycle arrest by flow cytometry and to have in vivo efficacy in human tumor xenograft models . The exact mechanism of action was not elucidated until more than 15 years later, when it was demonstrated that the anti-proliferative effect was due to an induced ternary complex between the mRNA splicing factor RNA binding motif protein 39 (RBM39) and a member of the CUL4 ubiquitin ligase complex called DDB1 and CUL4-associated factor 15 (DCAF15). Formation of this ternary complex leads to the polyubiquitination and degradation of RBM39 . Structural studies showed that indisulam binds DCAF15 and creates a novel surface which enhances RBM39 binding and induces novel protein–protein interactions . As molecular glue degrader discovery has historically been serendipitous, it is reasonable to assume there may be small molecules in development or the clinic for which the molecular glue mechanism has not yet been identified. Ebert et al. used database mining to look for a correlation between the cytotoxicity of 4518 clinal or pre-clinical small molecules and E3 ligase expression in hundreds of human cancer cell lines . These studies identified a correlation between CR8 (CDK inhibitor) and DDB1 (CUL4 substrate adaptor protein) expression. An X-ray crystal structure revealed that CR8 bound to CDK12 had a solvent exposed pyridyl moiety which induced complex formation of CDK12 with Cyclin K and DDB1 (PDB:6TD3). This ternary complex formation leads to ubiquitination of Cyclin K and downstream degradation by the proteasome . Using cell-based assays to screen for compounds with MGD properties has the potential advantage that the complete cellular machinery is present, allowing ubiquitination and subsequent degradation of a target protein. In contrast, the challenge when utilizing cells for compound screening is the extensive hit deconvolution required for validation of MGD mechanism. To help focus this approach, BMS/Cellgene screened a library of CRBN interacting compounds, with the advantage that half the prospective interaction was already defined, and proteomics could be used to identify the target protein. This study was directed towards identification of a molecular glue for the treatment of acute myeloid leukemia (AML), and screening for compounds with antiproliferative potency was performed using ten AML cell lines. This led to the development of CC-90009, a selective GTPS1 degrader, the first CRBN-based molecular glue degrader to enter clinical trials since CRBN was identified to be the primary target of thalidomide . At the time of writing, CC-90009 is in Phase II clinical trials for the treatment of AML . Further expansion of MGDs beyond CRBN requires methods with broader scope. Most of the cullin–RING ubiquitin ligases require conjugation to NEDD8 for activity, and therefore differential screening in cells with normal and deficient neddylation can identify compounds that require uninterrupted neddylation, inferring that activity is driven by a cullin–RING ubiquitin ligase. Mayor-Ruiz et al. used this approach to screen 2000 cytostatic or cytotoxic small molecules, with identification of differentially active compounds. The results were followed up by analysis in CRISPR knockout cell lines of all known cullin-RING ligases and quantitative expression proteomics of treated cells to identify the relevant ligase and target protein respectively. This strategy identified three compounds which induced degradation of Cyclin K by the CRL4 ligase complex . Analysis showed that although these compounds are structurally different from CR8 (identified by data mining described above), they act by a similar mechanism of binding CDK12 and recruiting Cyclin K and DDB1 . To limit a MGD to a desired ligase, morphological screening approaches using cell lines with different ligase expression levels can be used. Cell painting assays can be used to assess hundreds of parameters including cell viability, morphology and the detection of multiple organelles or cellular components , and Ng et al. used this approach in isogenic cell lines expressing different levels of CRBN. A screen of 132 CRBN binders (assessed by a CRBN fluorescence polarization competition assay first) identified FL2-14 as a GSPT2 molecular glue degrader . As a complementary approach to cell-based systems, purified proteins can be used in biophysical assays to measure the induction of a ternary complex between a POI and ligase. This has the advantage of fully controlling the selection of the E3 and the target. Biophysical assays give a direct read out of ternary complex formation and can therefore help build SAR and drive development of compounds with improved molecular glue properties. However, without the cellular context, biophysical assays cannot give information on target protein degradation and any downstream effects. Of importance for biophysical screening approaches is identifying a target and ligase pairing which is suitable for development, with consideration needed for the target and E3 cellular locations and tissue- and disease-specific expression profiles. Although uncommon, a known weak compound-induced interaction provides an advantageous start point. Pomalidomide induces an interaction between CRBN and the transcription factor IKZF1 which leads to the degradation of the latter. Novartis further identified a weak interaction between Pomalidomide, CRBN and IKZF2 but this interaction did not lead to IKZF2 degradation. This suggests there is a recruitment threshold which needs to be met before molecular glue induced interactions are strong enough to lead to target degradation. The Novartis discovery campaign was driven initially by interaction assays between CRBN-IKZF2 and CRBN-IKZF1, allowing optimization for selectivity before the interaction threshold for target degradation had been met . Another recent study from Novartis has highlighted the use of biophysical approaches to identify the first VHL-based molecular glue degrader, where the glue induces binding and degradation of cysteine dioxygenase 1 (CDO1) . An alternative approach is to take advantage of a known physiological E3 and POI pair by focusing on a mutated POI where the ability of native ligase to bind and ubiquitinate has been lost or impaired. In this scenario, a molecular glue could be utilized to re-establish the interaction between the POI and ligase to restore the normal degradation pathway. β-catenin is an effector protein in the Wnt signaling pathway which normally interacts with the β-TrCP ubiquitin ligase, leading to β-catenin degradation. Mutant β-catenin, found in some colorectal cancers, has an impaired ability to bind β-TrCP, leading to enhanced oncogenic transcription. Nurix Therapeutics developed an FP competition assay using β-TrCP with BODIPY-TMR labelled β-catenin phosphodegron peptides. Discovery was focused on the serine 37 mutant as this is a hotspot for β-catenin mutations. Using an HTS approach, 350,000 compounds were screened through the FP assay to identify enhancers of the β-TrCP and β-catenin peptide interaction. Promising compounds were validated by orthogonal TR-FRET and surface plasmon resonance (SPR) assays . Using native binding E3-POI partners provides the advantage that there is already an interaction surface between the two proteins, with lysine residues available for ubiquitination. It also avoids any issues that may arise from hijacking unrelated E3s to POIs, such as incompatible expression profiles or subcellular localizations. Establishing a rational and unbiased screening approach that is broadly applicable for identification of novel molecular glues across different protein pairs is extremely challenging. Significant efforts have focused around redirecting CRBN towards new targets either by expanding around the IMiDs or looking for new chemical matter. Whilst efforts to expand the IMiD chemical repertoire have been successful, with multiple compounds heading towards the clinic, expanding to look at more E3 ligases may yet open up a range of novel target proteins. Phenotypic screening approaches have identified novel glues, but methods require thorough follow up for target deconvolution and hit validation. Exploiting known weak interactions or, in the case of mutant proteins, using its native E3 ligase may provide advantageous starting points due to an already known protein–protein interfaces and lysine residues available for ubiquitination by the E3 ligase. Molecular glues, although challenging to identify, provide an opportunity hijack the protein degradation pathways using compounds with more favorable physicochemical properties than bifunctional molecules. In addition to direct clinical application, chemical degraders represent a valuable strategy for characterizing the role and importance of a protein in cellular physiology and disease development. Many candidate targets have been selected based on a vital role in the processes they impact, such as oncogenesis, neurodegenerative disorders or inflammation. Validating new targets in a more efficient way represents a crucial step to justify investing efforts in drug development. While transient (siRNA) or permanent (knockout) genetic approaches can be utilized for target validation experiments, these approaches can have drawbacks. Generally, genetic methods, particularly knockout systems, may lead to compensatory mechanisms, such as upregulation of redundant pathways, that may reduce the phenotypic effect related to the absence of the target protein. In contrast, degraders act rapidly, similar to how drugs act on patients, allowing the assessment of how acute depletion of the target affects the relevant readout. There is also a benefit of degrader use to establish pharmacology in situations where catalytic site inhibition does not match the result of siRNA knockdown. After developing an initial degrader compound, it is crucial to evaluate parameters for future improvement of critical aspects to obtain an optimal therapeutic molecule. These parameters include binary target engagement, ternary complex formation, efficient polyubiquitination of the target protein, specific proteolysis, pharmacological effects, solubility, stability, and cell permeability. Various assays can be employed to evaluate physicochemical, pharmacologic, and biologic properties of degraders. This evaluation opens avenues for future improvements of prototype molecules. Techniques like fluorescent polarization , time-resolved fluorescence resonance energy transfer , AlphaLISA , surface plasmon resonance (SPR) , and calorimetry can be used to assess target engagement and ternary complex formation. Bioluminescence methods like NanoLuc, NanoTag, or NanoBRET are successful for evaluating cellular permeability . Confirmation of Mechanism of Action Mechanistic assays can determine whether POI proteolysis is driven by the ubiquitin–proteasome system (UPS) or the autophagy-lysosome system (ALS). A pharmacological approach, such as inhibiting the proteasome (e.g., with bortezomib) or autophagy (e.g., with bafilomycin A), is recommended. Moreover, inhibition of the ubiquitin-activating enzyme using MLN7243 can be utilized to determine ubiquitin dependence. The NEDD8 activating enzyme inhibitor MLN4924 is also useful to validate dependence on a CRL, if appropriate. Bifunctional degraders can also be assessed for mechanism by competition with isolated ligase or target ligands, or by use of non-binding compound analogues for the E3. The approaches above can provide evidence to support that a degrader functions through the expected mechanism of action. In addition to western blot analysis, mechanism of action analysis can be performed using homogenous time-resolved fluorescence (HTRF) and AlphaLISA . These represent excellent methods that allow plate-based, high-throughput, compound characterization of endogenous, untagged, POI. This is an advantage, since artificially elevated expression levels and the use of tags can influence POI degradation ; if such systems are utilized, care should be taken to validate degradation on the endogenous level. Direct verification of POI ubiquitylation can be performed by overexposing western blots of cell extracts treated with proteasome inhibitor. Due to rapid deconjugation, POI ubiquitylation is more easily observed using ubiquitin traps (also known as Tandem Ubiquitin Binding Entities) to capture ubiquitylated proteins for detection by western blot or protein arrays . In addition to confirming that a novel degrader is on-mechanism, it is informative to assess general selectivity. Mass spectrometry can globally evaluate the effect on the proteome of the specific degradation of a POI, ensuring that consequences are restricted to the proteolysis of the target and its known regulated functions . summarizes concepts in degrader discovery and validation. Mechanistic assays can determine whether POI proteolysis is driven by the ubiquitin–proteasome system (UPS) or the autophagy-lysosome system (ALS). A pharmacological approach, such as inhibiting the proteasome (e.g., with bortezomib) or autophagy (e.g., with bafilomycin A), is recommended. Moreover, inhibition of the ubiquitin-activating enzyme using MLN7243 can be utilized to determine ubiquitin dependence. The NEDD8 activating enzyme inhibitor MLN4924 is also useful to validate dependence on a CRL, if appropriate. Bifunctional degraders can also be assessed for mechanism by competition with isolated ligase or target ligands, or by use of non-binding compound analogues for the E3. The approaches above can provide evidence to support that a degrader functions through the expected mechanism of action. In addition to western blot analysis, mechanism of action analysis can be performed using homogenous time-resolved fluorescence (HTRF) and AlphaLISA . These represent excellent methods that allow plate-based, high-throughput, compound characterization of endogenous, untagged, POI. This is an advantage, since artificially elevated expression levels and the use of tags can influence POI degradation ; if such systems are utilized, care should be taken to validate degradation on the endogenous level. Direct verification of POI ubiquitylation can be performed by overexposing western blots of cell extracts treated with proteasome inhibitor. Due to rapid deconjugation, POI ubiquitylation is more easily observed using ubiquitin traps (also known as Tandem Ubiquitin Binding Entities) to capture ubiquitylated proteins for detection by western blot or protein arrays . In addition to confirming that a novel degrader is on-mechanism, it is informative to assess general selectivity. Mass spectrometry can globally evaluate the effect on the proteome of the specific degradation of a POI, ensuring that consequences are restricted to the proteolysis of the target and its known regulated functions . summarizes concepts in degrader discovery and validation. Despite significant anticipated challenges, including metabolic stability, dosing and routes of administration, several degrader projects have already entered clinical evaluation. In line with pre-clinical expectations, oral bioavailability of these large molecules can be challenging to attain. Measured oral bioavailabilities in animal studies, particularly for earlier state derivatives, are generally low, (often in the 3–30% range) . Despite this, the majority of clinically investigated agents have been found suitable for oral dosing. Indeed, for more optimized candidate-stage molecules, bioavailability in mice or rat in vivo PK studies can reach 50–90%. At the current time, little information exists in the public domain to quantify how these bioavailabilities in lower species translate into humans, as the corresponding matched oral/ iv dosing studies are rarely undertaken in patients. Understanding and resolving these unknown factors is likely to become important as the field matures. From a patient perspective, low oral bioavailability demands a high pill burden, in order to drive sufficient absorption and free drug exposure in the target tissue to deliver therapeutic benefit. Moreover, the potentially large unabsorbed fraction, which may be excreted largely unchanged, has a significant negative impact on the quantities of active pharmaceutical ingredient (API) required for manufacture and, therefore, on cost of goods. Particularly in cases where degraders are competing with small-molecule inhibitors of the same target or pathway, improvements here may be critical to satisfy cost/benefit analyses prior to approval. 7.7.1. Heterobifunctional Degraders in Oncology As of the time of writing, there are 20 clinical assets in the oncology heterobifunctional space . Of these, 70% are dosed orally, and 30% intravenously. One compound (ARV-471) is now in advanced Phase III clinical trials which are not expected to conclude until 2028. For the majority of clinical degraders, the proteins of interest have already been investigated with significant numbers of small-molecule agents. Examples here include the estrogen receptors (ER) in breast cancer (BC), targeted with selective estrogen receptor degrader small molecules (SERDs), the androgen receptor (AR) in metastatic castrate-resistant prostate cancer (mCRPC), targeted with selective androgen receptor degrader small molecules (SARDs), and kinases such as mtBRAF and BTK, targeted with both covalent and non-covalent inhibitors. As these trials progress, it will be interesting to see where similarities and differences occur in terms of patient responses and outcomes. To date, the limited emerging clinical data from those agents progressing beyond Phase I remains relatively modest in terms of response rates. In the case of ARV-471, Phase II data suggested an overall survival benefit of approximately 3-4 months, and median protein degradation of approximately 70% . In the AR setting, in Phase I studies, ARV-110 showed >50% decrease in Prostate-Specific Antigen (PSA) levels in approximately 16% of the patient population and 2/7 partial responses in the evaluable patient cohort . Of note, in patients with known resistance mutations, such as T878X and H875Y, these responses were somewhat higher, suggesting a role for degraders in settings where tumor heterogeneity or tumor evolution has led to therapeutic resistance with small-molecule inhibitors. Recent reports have suggested that the modest responses in the clinic may be due to a variety of factors , including: The aforementioned low bioavailability and, therefore, potentially subtherapeutic exposure at target Emergent resistance due to loss of function, or decreased expression of the cognate E3 ligase Elevated rates of protein re-expression in response to treatment, counteracting active degradation by the heterobifunctional agent. It is important to state that these agents are only the first few to report early clinical data, and as the field matures, and collective wisdom and expertise widens, it is likely that our understanding of the degree of bioavailability, the importance of protein re-expression rates and appropriate clinical settings will help to drive improvements in efficacy and, ultimately, patient benefit. So far, many of the targeted proteins seem to have a rapid resynthesis rate measured in a few hours (approximately 3 h and 4 h for the AR , and ER , respectively). This rapid resynthesis seems to overcome the rate at which the heterobifunctional degraders can eradicate the POI from the cell . Considering this, targeting proteins with a slower rate of compensatory re-expression may become a preferred application for heterobifunctional degraders. Alongside rapid re-expression of the target protein, clinical resistance has also been observed to arise from alterations of the E3 ligase system, or upregulated expression of multidrug resistance efflux pumps . Beyond slowly re-expressed proteins, heterobifunctional degraders may offer other opportunities where more traditional modalities have struggled to gain traction. Of specific note in the oncology space, the emerging degraders of the BRM protein offer a compelling instance where a degrader delivers benefit over a small-molecule inhibitor. Based on the concept of collateral lethality , experimental studies demonstrated that certain lung tumors undergo loss of the SMARCA4 gene, encoding for the BRG1 protein, an essential part of the SWI/SNF chromatin remodeling complex, either by frameshift mutation or epigenetic silencing . This leaves this cell population entirely dependent upon the related protein BRM, encoded by the SMARCA2 gene. In this context, a selective BRM inhibitor would be lethal to the ca. 10% of non-small-cell lung cancers (NSCLC) where the SMARCA4 gene is lost or mutated, but well tolerated in healthy tissue due to their unaltered expression. However, due to the high sequence conservation between the two targets and despite extensive efforts, selective BRM inhibitors (for either the bromodomain or ATPase domain) remain elusive. Here, PRT3789 from Prelude Therapeutics offers clear differentiation from these small-molecule efforts . Biochemically, the heterobifunctional molecule binds at equipotent nanomolar concentrations to both BRG and BRM1, yet delivers 19-fold selectivity in cell-based BRM/BRG1 HiBiT assays. More interestingly, the compound delivers a 720 pM DC 50 and 94% D max vs. BRM yet spares BRG1 (14 nM DC 50 and 76% D max ), delivering selective cell killing in mtSMARCA4/SMARCA4-del cells, but not in SMARCA4-wt cells, with this selectivity translating into matched in vivo xenograft studies. The precise mechanisms underlying this enhanced specificity have not been described but this outcome reflects those observed in the conversion of non-selective kinase inhibitors to selective kinase heterobifunctional degraders . This approach offers the tantalizing prospect of selectively degrading tumor-specific protein homologs, or members of closely related protein families, in a way which is not possible with small-molecule inhibitors. Whilst in its infancy, this paradigm may offer a real differentiator for heterobifunctional molecules, extending the remit beyond those proteins where high quality and effective small-molecule therapies already exist. 7.7.2. Molecular Glue Degraders in Oncology The molecular glue degrader landscape in oncology is represented by two predominant molecular classes—the dominant class of MGDs is derived from the phthalimide CRBN recruiters, and the smaller group includes those that are derived from other chemotypes. Thalidomide, and related derivatives, had long been known to be effective in multiple myeloma, but through unknown mechanisms. Significant work by the Tokyo Institute of Technology and Celgene unraveled this mechanism and led to the explosion of interest in CRBN-derived molecular glues. As such, thalidomide was the first approved CRBN-molecular glue, well before it was known to act in this manner. Approvals for lenalidomide and pomalidomide have since been granted. As of the time of writing, a further 16 molecular glues have now entered the clinic . Of these, for those where a structure has been disclosed, only three glues (Indisulam, CQS and E7820) do not display the structural motifs common to CRBN molecular glues, instead recruiting DCAF15 to effect protein degradation of RBM39. This overwhelming focus upon CRBN molecular glues raises several challenges, including the race to discover (and patent) novel chemical space. From a clinical standpoint, it also implies that many of the dozens of molecular glues now in pre-clinical development are likely to be competing for the same disease segment, and thus the same clinical trial populations, potentially limiting recruitment and delaying evaluation. Clearly, exploitation of a wider range of E3 ligases in the pursuit of MGDs is commercially attractive and likely to deliver wider patient benefit. Given their smaller molecular weight and potentially improved physicochemical properties, oral bioavailability remains a key attractive feature of molecular glues, and all the compounds in the clinic which recruit CRBN as the E3 ligase are dosed orally, except for CC-90009 which is dosed via an IV infusion. The reasoning behind this outlier route of administration does not appear to have been publicly disclosed at this time. It is interesting to note that, in addition, all clinical examples of DCAF15 molecular glues are also dosed via an IV infusion, suggesting that oral bioavailability is not necessarily guaranteed for molecular glues outside of the CRBN IMiD-derived agents. 7.7.3. Heterobifunctional Degraders for Inflammatory Indications TPD is emerging as a promising approach for the treatment of inflammatory diseases, offering a novel therapeutic strategy with potential advantages. Inflammatory diseases, characterized by abnormal immune responses, may involve dysregulated protein expression contributing to pathogenesis, and a TPD approach is suited to address this by selectively removing disease-associated proteins. Another potential benefit lies in the ability to modulate inflammatory signaling pathways by degrading previously un-druggable proteins. An example of these strategies is the development of heterobifunctional degraders for the protein RIPK2. Acting downstream of pattern recognition receptors, RIPK2 activates NF-κB, leading to the production of inflammatory cytokines. Dysregulation of RIPK2 is implicated in various inflammatory diseases, such as Crohn’s Disease and Ulcerative Colitis. Degraders for RIPK2 have been explored pre-clinically as a strategy to improve kinase selectivity and pharmacokinetic properties of inhibitors, and have shown promising anti-inflammatory properties . Further examples of targets in inflammatory pathways where degraders have been developed include TYK2 and BTK , and bifunctional compounds for both are in pre-clinical development for inflammatory indications by Kymera Therapeutics and Nurix Therapeutics, respectively. Currently, the only target where a bifunctional degrader has reached the clinic for an inflammatory indication is IRAK4. As a serine/threonine kinase, IRAK4 functions as a key mediator in the activation of signaling in response to inflammatory stimulation. IRAK4’s central role in inflammatory signaling makes it an attractive target in conditions associated with dysregulated immune activation, and several inhibitors of IRAK4′s kinase activity have entered clinical evaluation . Multiple pre-clinical studies of IRAK4 degraders have highlighted that potent degraders for this kinase target can be generated , and KT-474 by Kymera Therapeutics is now in Phase 2 for treatment of hidradenitis suppurativa (NCT06028230) and atopic dermatitis (NCT06058156). The Phase 1 clinical results have demonstrated that single dosing of 600 mg–1600 mg KT-474 led to a rapid drop in IRAK4 levels in peripheral blood mononuclear cells (PBMCs), reaching nadir by 48 h. The degradation is sustained for at least 14 days, as IRAK4 levels did not return to baseline for these doses at that time. Multiple dosing over 14 days (once daily) showed that a dose as low as 25 mg led to robust IRAK4 degradation (92% at nadir). It is worth noting that at the 100 mg dose, IRAK4 levels were still significantly below baseline at day 28, some 14 days post-dosing. For both hidradenitis suppurativa and atopic dermatitis, there was an improvement in clinical symptoms after treatment with 75 mg KT-474 daily for 28 days. These clinical responses were either maintained or continued to improve in the two weeks that were evaluated after dosing was halted. Overall, the Phase 1 results are promising, and indicate that longer term treatment can be achieved with a relatively low dose of the compound, and still achieve a strong degradation of IRAK4. In addition to Kymera Therapeutics, Nurix Therapeutics are in the IND enabling pre-clinical phase for their IRAK4 degrader for rheumatoid arthritis and other inflammatory conditions. 7.7.4. Molecular Glue Degraders for Inflammatory Indications At this time, there are no clinical examples of rationally developed molecular glue degraders for treatment of inflammatory disease. However, in the pre-clinical pipeline, Monte Rosa Therapeutics is in the IND enabling phase for an MGD, MRT-6160, that targets VAV1, a protein implicated in T- and B-cell receptor signaling. Both Monte Rosa and Captor Therapeutics are also in the discovery phases for molecular glue degraders directed to NEK7, an activator of the NLRP3 inflammasome. 7.7.5. Heterobifunctional Degraders for CNS Disorders Whereas targeted protein degradation in oncology has largely exploited targets with matched small-molecule therapeutics, CNS disorders present opportunities for significant differentiation from both small- and large-molecule therapeutic approaches. Misfolded protein aggregates, a hallmark of neurodegenerative disorders, have been considered undruggable using conventional inhibitor approaches, potentially accounting for the failure of compounds in clinical trials targeting protein aggregates in the CNS . At this time, a large number of CNS disorders lack effective treatment, and heterobifunctional degraders represent an attractive therapeutic instrument due to their ability to remove proteins via proteasomal degradation. Despite their potential for degrading a POI in vitro, a major challenge for heterobifunctional degraders is their ability to reach the brain and treat the disease in vivo. Due to their high molecular weight and a large polar surface area, achieving blood brain barrier (BBB) permeability of heterobifunctional degraders is particularly challenging. In this context, degrader–antibody conjugates or encapsulated nanoparticles that can cross the BBB through receptor-mediated transcytosis, have been investigated and may provide an alternative route to access the CNS . Ubiquitin ligases may have tissue-specific expression, such as RNF182, expressed preferentially in the brain; CNS-restricted ligase expression enables the potential for a more specific targeting of the POI within the CNS , with the possible advantage of limiting unwanted effects in tissues not directly involved in disease pathology. Unlike the oncology exemplars described above, PROTACs for neurodegenerative disorders remain in pre-clinical development, largely given the challenges of targeting the brain. Nevertheless, steps have been taken to advance PROTAC molecules in the neuroscience field, with a particular focus on Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). AD The accumulation of mutated tau species into neurofibrillary tangles, both in the intracellular and extracellular space, leads to cellular toxicity and neuronal cell death . Different peptide-based and small-molecule-based PROTACs have been developed for tau degradation. TH006, a peptide-based PROTAC with an ALAPYIP sequence as a VHL ligand, was shown to induce tau degradation in N2a cells overexpressing tau. Whilst the effect of degradation was observed at high concentrations (200 μM), TH006 administration in a mouse model of AD resulted in a reduction in tau levels in the cerebral cortex and hippocampus. TH006 has been administered both intranasally and intravenously, probably due to low BBB permeability, a common feature of these peptides . Similarly, a Keap1-based peptide PROTAC was observed to recruit CUL3 KEAP1 ubiquitin ligase, inducing the degradation of tau through the ubiquitin–proteasome system . QC-01-175, a small-molecule tau-degrading PROTAC based on the PET tracer T807, with a CRBN ligand, was shown to induce Tau degradation in FTD patient-derived neuronal models including the tau-A152T and the tau-P301L variants . Following linker optimization, second-generation CRBN-recruiting degraders (FMF-06-series) delivered a tenfold improvement in degradation potency of total tau and phospho-tau S396 with a tau reduction by 50% at 10 nM concentration . Minimal E3-ligase occupancy was observed in in vitro cellular target engagement assays, indicating low cell permeability of the optimized analogues . C004019, a VHL-based degrader, was demonstrated to lead to tau degradation through the proteasome, both in vitro and in vivo. C004019 has shown a DC 50 of 7.9 nM in a HEK293-hTau overexpressed cell line. Furthermore, intracerebroventricular or subcutaneous administration of C004019 promoted a sustained tau clearance in vivo . Another example is compound I3, a CRBN-based degrader with a THK5105 derivative as a tau ligand, where tau degradation has been demonstrated in vitro using PC12 cells . In the clinical development pipeline, Arvinas claims to have achieved BBB penetration and removal of 95% of pathological tau in vivo after parenteral administration in animal models; the structure of this PROTAC has not been disclosed at the time of writing. PD Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene and in the α-synuclein gene (SNCA) are linked to the onset of PD. The dysfunction of LRRK2 may contribute to the accumulation of α-synuclein, consequent microglia activation, neuroinflammation and ultimately neuronal cell death . Selective degraders targeting LRRK2 have been recently disclosed in a patent by Arvinas, claiming the discovery of potent and selective CRBN-based LRRK2 PROTACs able to degrade LRRK2 in the cerebral cortex after single oral administration in a fPD mouse model with G2019S LRRK2 mutation . In parallel, the Ciulli lab discovered the VHL-based degrader XL01126 that has been shown to be a potent degrader of LRRK2 in multiple cell lines and to pass through the BBB after oral or parenteral administration in mice, exhibiting an oral bioavailability of 15% . These attractive in vitro and in vivo properties of XL01126 represent an intriguing starting point for further drug development. With respect to α-synuclein, a synthetic peptide-based degrader has been shown to degrade intracellular α-synuclein in a recombinant expression system. The degradation of α-synuclein through the proteasome has been shown to rescue mitochondrial defects caused by aberrant α-synuclein accumulation . Moreover, in a recent patent, Arvinas claims the discovery of a series of small-molecule PROTACs, containing a VHL, CRBN, IAP or MDM2 ligand, showing a 65% degradation of α-synuclein at 1 μM in different cell lines . HD The aggregation of mutant huntingtin in HD leads to progressive degeneration of neurons in the striatum and cerebral cortex. Small-molecule-based bifunctional IAP-based degraders have been developed showing ubiquitination and degradation of mutant huntingtin in fibroblasts derived from HD patients . Further studies are needed to fully exploit this approach to treat HD, as the degradation activity has been observed to also involve the wild-type huntingtin . FTD and ALS The TAR DNA-binding protein 43 (TDP-43) is an example of a misfolded protein implicated in FTD and ALS. The successful removal of the toxic C-terminal form using a heterobifunctional degrader has recently been reported . Given the challenges of developing new drugs for targeting mutated proteins in the brain, further in vitro and in vivo validation in independent laboratories is required to further explore the viability of heterobifunctional as an effective therapeutic tool to treat neurodegenerative disorders. 7.7.6. Molecular Glue Degraders for CNS Disorders In principle, an MGD approach has distinct advantages for the CNS space as compared to heterobifunctional degraders, largely due to the generally much more attractive physicochemical properties of glues. At this time, no MGDs have been reported for therapeutically relevant CNS targets. Discovery of MGDs here may favor non-aggregating targets, such as LRRK2 described above; however, glues for aggregating proteins may also be possible to discover, since it has been demonstrated that heterobifunctional compounds can function in this area, e.g., for tau. As of the time of writing, there are 20 clinical assets in the oncology heterobifunctional space . Of these, 70% are dosed orally, and 30% intravenously. One compound (ARV-471) is now in advanced Phase III clinical trials which are not expected to conclude until 2028. For the majority of clinical degraders, the proteins of interest have already been investigated with significant numbers of small-molecule agents. Examples here include the estrogen receptors (ER) in breast cancer (BC), targeted with selective estrogen receptor degrader small molecules (SERDs), the androgen receptor (AR) in metastatic castrate-resistant prostate cancer (mCRPC), targeted with selective androgen receptor degrader small molecules (SARDs), and kinases such as mtBRAF and BTK, targeted with both covalent and non-covalent inhibitors. As these trials progress, it will be interesting to see where similarities and differences occur in terms of patient responses and outcomes. To date, the limited emerging clinical data from those agents progressing beyond Phase I remains relatively modest in terms of response rates. In the case of ARV-471, Phase II data suggested an overall survival benefit of approximately 3-4 months, and median protein degradation of approximately 70% . In the AR setting, in Phase I studies, ARV-110 showed >50% decrease in Prostate-Specific Antigen (PSA) levels in approximately 16% of the patient population and 2/7 partial responses in the evaluable patient cohort . Of note, in patients with known resistance mutations, such as T878X and H875Y, these responses were somewhat higher, suggesting a role for degraders in settings where tumor heterogeneity or tumor evolution has led to therapeutic resistance with small-molecule inhibitors. Recent reports have suggested that the modest responses in the clinic may be due to a variety of factors , including: The aforementioned low bioavailability and, therefore, potentially subtherapeutic exposure at target Emergent resistance due to loss of function, or decreased expression of the cognate E3 ligase Elevated rates of protein re-expression in response to treatment, counteracting active degradation by the heterobifunctional agent. It is important to state that these agents are only the first few to report early clinical data, and as the field matures, and collective wisdom and expertise widens, it is likely that our understanding of the degree of bioavailability, the importance of protein re-expression rates and appropriate clinical settings will help to drive improvements in efficacy and, ultimately, patient benefit. So far, many of the targeted proteins seem to have a rapid resynthesis rate measured in a few hours (approximately 3 h and 4 h for the AR , and ER , respectively). This rapid resynthesis seems to overcome the rate at which the heterobifunctional degraders can eradicate the POI from the cell . Considering this, targeting proteins with a slower rate of compensatory re-expression may become a preferred application for heterobifunctional degraders. Alongside rapid re-expression of the target protein, clinical resistance has also been observed to arise from alterations of the E3 ligase system, or upregulated expression of multidrug resistance efflux pumps . Beyond slowly re-expressed proteins, heterobifunctional degraders may offer other opportunities where more traditional modalities have struggled to gain traction. Of specific note in the oncology space, the emerging degraders of the BRM protein offer a compelling instance where a degrader delivers benefit over a small-molecule inhibitor. Based on the concept of collateral lethality , experimental studies demonstrated that certain lung tumors undergo loss of the SMARCA4 gene, encoding for the BRG1 protein, an essential part of the SWI/SNF chromatin remodeling complex, either by frameshift mutation or epigenetic silencing . This leaves this cell population entirely dependent upon the related protein BRM, encoded by the SMARCA2 gene. In this context, a selective BRM inhibitor would be lethal to the ca. 10% of non-small-cell lung cancers (NSCLC) where the SMARCA4 gene is lost or mutated, but well tolerated in healthy tissue due to their unaltered expression. However, due to the high sequence conservation between the two targets and despite extensive efforts, selective BRM inhibitors (for either the bromodomain or ATPase domain) remain elusive. Here, PRT3789 from Prelude Therapeutics offers clear differentiation from these small-molecule efforts . Biochemically, the heterobifunctional molecule binds at equipotent nanomolar concentrations to both BRG and BRM1, yet delivers 19-fold selectivity in cell-based BRM/BRG1 HiBiT assays. More interestingly, the compound delivers a 720 pM DC 50 and 94% D max vs. BRM yet spares BRG1 (14 nM DC 50 and 76% D max ), delivering selective cell killing in mtSMARCA4/SMARCA4-del cells, but not in SMARCA4-wt cells, with this selectivity translating into matched in vivo xenograft studies. The precise mechanisms underlying this enhanced specificity have not been described but this outcome reflects those observed in the conversion of non-selective kinase inhibitors to selective kinase heterobifunctional degraders . This approach offers the tantalizing prospect of selectively degrading tumor-specific protein homologs, or members of closely related protein families, in a way which is not possible with small-molecule inhibitors. Whilst in its infancy, this paradigm may offer a real differentiator for heterobifunctional molecules, extending the remit beyond those proteins where high quality and effective small-molecule therapies already exist. The molecular glue degrader landscape in oncology is represented by two predominant molecular classes—the dominant class of MGDs is derived from the phthalimide CRBN recruiters, and the smaller group includes those that are derived from other chemotypes. Thalidomide, and related derivatives, had long been known to be effective in multiple myeloma, but through unknown mechanisms. Significant work by the Tokyo Institute of Technology and Celgene unraveled this mechanism and led to the explosion of interest in CRBN-derived molecular glues. As such, thalidomide was the first approved CRBN-molecular glue, well before it was known to act in this manner. Approvals for lenalidomide and pomalidomide have since been granted. As of the time of writing, a further 16 molecular glues have now entered the clinic . Of these, for those where a structure has been disclosed, only three glues (Indisulam, CQS and E7820) do not display the structural motifs common to CRBN molecular glues, instead recruiting DCAF15 to effect protein degradation of RBM39. This overwhelming focus upon CRBN molecular glues raises several challenges, including the race to discover (and patent) novel chemical space. From a clinical standpoint, it also implies that many of the dozens of molecular glues now in pre-clinical development are likely to be competing for the same disease segment, and thus the same clinical trial populations, potentially limiting recruitment and delaying evaluation. Clearly, exploitation of a wider range of E3 ligases in the pursuit of MGDs is commercially attractive and likely to deliver wider patient benefit. Given their smaller molecular weight and potentially improved physicochemical properties, oral bioavailability remains a key attractive feature of molecular glues, and all the compounds in the clinic which recruit CRBN as the E3 ligase are dosed orally, except for CC-90009 which is dosed via an IV infusion. The reasoning behind this outlier route of administration does not appear to have been publicly disclosed at this time. It is interesting to note that, in addition, all clinical examples of DCAF15 molecular glues are also dosed via an IV infusion, suggesting that oral bioavailability is not necessarily guaranteed for molecular glues outside of the CRBN IMiD-derived agents. TPD is emerging as a promising approach for the treatment of inflammatory diseases, offering a novel therapeutic strategy with potential advantages. Inflammatory diseases, characterized by abnormal immune responses, may involve dysregulated protein expression contributing to pathogenesis, and a TPD approach is suited to address this by selectively removing disease-associated proteins. Another potential benefit lies in the ability to modulate inflammatory signaling pathways by degrading previously un-druggable proteins. An example of these strategies is the development of heterobifunctional degraders for the protein RIPK2. Acting downstream of pattern recognition receptors, RIPK2 activates NF-κB, leading to the production of inflammatory cytokines. Dysregulation of RIPK2 is implicated in various inflammatory diseases, such as Crohn’s Disease and Ulcerative Colitis. Degraders for RIPK2 have been explored pre-clinically as a strategy to improve kinase selectivity and pharmacokinetic properties of inhibitors, and have shown promising anti-inflammatory properties . Further examples of targets in inflammatory pathways where degraders have been developed include TYK2 and BTK , and bifunctional compounds for both are in pre-clinical development for inflammatory indications by Kymera Therapeutics and Nurix Therapeutics, respectively. Currently, the only target where a bifunctional degrader has reached the clinic for an inflammatory indication is IRAK4. As a serine/threonine kinase, IRAK4 functions as a key mediator in the activation of signaling in response to inflammatory stimulation. IRAK4’s central role in inflammatory signaling makes it an attractive target in conditions associated with dysregulated immune activation, and several inhibitors of IRAK4′s kinase activity have entered clinical evaluation . Multiple pre-clinical studies of IRAK4 degraders have highlighted that potent degraders for this kinase target can be generated , and KT-474 by Kymera Therapeutics is now in Phase 2 for treatment of hidradenitis suppurativa (NCT06028230) and atopic dermatitis (NCT06058156). The Phase 1 clinical results have demonstrated that single dosing of 600 mg–1600 mg KT-474 led to a rapid drop in IRAK4 levels in peripheral blood mononuclear cells (PBMCs), reaching nadir by 48 h. The degradation is sustained for at least 14 days, as IRAK4 levels did not return to baseline for these doses at that time. Multiple dosing over 14 days (once daily) showed that a dose as low as 25 mg led to robust IRAK4 degradation (92% at nadir). It is worth noting that at the 100 mg dose, IRAK4 levels were still significantly below baseline at day 28, some 14 days post-dosing. For both hidradenitis suppurativa and atopic dermatitis, there was an improvement in clinical symptoms after treatment with 75 mg KT-474 daily for 28 days. These clinical responses were either maintained or continued to improve in the two weeks that were evaluated after dosing was halted. Overall, the Phase 1 results are promising, and indicate that longer term treatment can be achieved with a relatively low dose of the compound, and still achieve a strong degradation of IRAK4. In addition to Kymera Therapeutics, Nurix Therapeutics are in the IND enabling pre-clinical phase for their IRAK4 degrader for rheumatoid arthritis and other inflammatory conditions. At this time, there are no clinical examples of rationally developed molecular glue degraders for treatment of inflammatory disease. However, in the pre-clinical pipeline, Monte Rosa Therapeutics is in the IND enabling phase for an MGD, MRT-6160, that targets VAV1, a protein implicated in T- and B-cell receptor signaling. Both Monte Rosa and Captor Therapeutics are also in the discovery phases for molecular glue degraders directed to NEK7, an activator of the NLRP3 inflammasome. Whereas targeted protein degradation in oncology has largely exploited targets with matched small-molecule therapeutics, CNS disorders present opportunities for significant differentiation from both small- and large-molecule therapeutic approaches. Misfolded protein aggregates, a hallmark of neurodegenerative disorders, have been considered undruggable using conventional inhibitor approaches, potentially accounting for the failure of compounds in clinical trials targeting protein aggregates in the CNS . At this time, a large number of CNS disorders lack effective treatment, and heterobifunctional degraders represent an attractive therapeutic instrument due to their ability to remove proteins via proteasomal degradation. Despite their potential for degrading a POI in vitro, a major challenge for heterobifunctional degraders is their ability to reach the brain and treat the disease in vivo. Due to their high molecular weight and a large polar surface area, achieving blood brain barrier (BBB) permeability of heterobifunctional degraders is particularly challenging. In this context, degrader–antibody conjugates or encapsulated nanoparticles that can cross the BBB through receptor-mediated transcytosis, have been investigated and may provide an alternative route to access the CNS . Ubiquitin ligases may have tissue-specific expression, such as RNF182, expressed preferentially in the brain; CNS-restricted ligase expression enables the potential for a more specific targeting of the POI within the CNS , with the possible advantage of limiting unwanted effects in tissues not directly involved in disease pathology. Unlike the oncology exemplars described above, PROTACs for neurodegenerative disorders remain in pre-clinical development, largely given the challenges of targeting the brain. Nevertheless, steps have been taken to advance PROTAC molecules in the neuroscience field, with a particular focus on Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). AD The accumulation of mutated tau species into neurofibrillary tangles, both in the intracellular and extracellular space, leads to cellular toxicity and neuronal cell death . Different peptide-based and small-molecule-based PROTACs have been developed for tau degradation. TH006, a peptide-based PROTAC with an ALAPYIP sequence as a VHL ligand, was shown to induce tau degradation in N2a cells overexpressing tau. Whilst the effect of degradation was observed at high concentrations (200 μM), TH006 administration in a mouse model of AD resulted in a reduction in tau levels in the cerebral cortex and hippocampus. TH006 has been administered both intranasally and intravenously, probably due to low BBB permeability, a common feature of these peptides . Similarly, a Keap1-based peptide PROTAC was observed to recruit CUL3 KEAP1 ubiquitin ligase, inducing the degradation of tau through the ubiquitin–proteasome system . QC-01-175, a small-molecule tau-degrading PROTAC based on the PET tracer T807, with a CRBN ligand, was shown to induce Tau degradation in FTD patient-derived neuronal models including the tau-A152T and the tau-P301L variants . Following linker optimization, second-generation CRBN-recruiting degraders (FMF-06-series) delivered a tenfold improvement in degradation potency of total tau and phospho-tau S396 with a tau reduction by 50% at 10 nM concentration . Minimal E3-ligase occupancy was observed in in vitro cellular target engagement assays, indicating low cell permeability of the optimized analogues . C004019, a VHL-based degrader, was demonstrated to lead to tau degradation through the proteasome, both in vitro and in vivo. C004019 has shown a DC 50 of 7.9 nM in a HEK293-hTau overexpressed cell line. Furthermore, intracerebroventricular or subcutaneous administration of C004019 promoted a sustained tau clearance in vivo . Another example is compound I3, a CRBN-based degrader with a THK5105 derivative as a tau ligand, where tau degradation has been demonstrated in vitro using PC12 cells . In the clinical development pipeline, Arvinas claims to have achieved BBB penetration and removal of 95% of pathological tau in vivo after parenteral administration in animal models; the structure of this PROTAC has not been disclosed at the time of writing. PD Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene and in the α-synuclein gene (SNCA) are linked to the onset of PD. The dysfunction of LRRK2 may contribute to the accumulation of α-synuclein, consequent microglia activation, neuroinflammation and ultimately neuronal cell death . Selective degraders targeting LRRK2 have been recently disclosed in a patent by Arvinas, claiming the discovery of potent and selective CRBN-based LRRK2 PROTACs able to degrade LRRK2 in the cerebral cortex after single oral administration in a fPD mouse model with G2019S LRRK2 mutation . In parallel, the Ciulli lab discovered the VHL-based degrader XL01126 that has been shown to be a potent degrader of LRRK2 in multiple cell lines and to pass through the BBB after oral or parenteral administration in mice, exhibiting an oral bioavailability of 15% . These attractive in vitro and in vivo properties of XL01126 represent an intriguing starting point for further drug development. With respect to α-synuclein, a synthetic peptide-based degrader has been shown to degrade intracellular α-synuclein in a recombinant expression system. The degradation of α-synuclein through the proteasome has been shown to rescue mitochondrial defects caused by aberrant α-synuclein accumulation . Moreover, in a recent patent, Arvinas claims the discovery of a series of small-molecule PROTACs, containing a VHL, CRBN, IAP or MDM2 ligand, showing a 65% degradation of α-synuclein at 1 μM in different cell lines . HD The aggregation of mutant huntingtin in HD leads to progressive degeneration of neurons in the striatum and cerebral cortex. Small-molecule-based bifunctional IAP-based degraders have been developed showing ubiquitination and degradation of mutant huntingtin in fibroblasts derived from HD patients . Further studies are needed to fully exploit this approach to treat HD, as the degradation activity has been observed to also involve the wild-type huntingtin . FTD and ALS The TAR DNA-binding protein 43 (TDP-43) is an example of a misfolded protein implicated in FTD and ALS. The successful removal of the toxic C-terminal form using a heterobifunctional degrader has recently been reported . Given the challenges of developing new drugs for targeting mutated proteins in the brain, further in vitro and in vivo validation in independent laboratories is required to further explore the viability of heterobifunctional as an effective therapeutic tool to treat neurodegenerative disorders. The accumulation of mutated tau species into neurofibrillary tangles, both in the intracellular and extracellular space, leads to cellular toxicity and neuronal cell death . Different peptide-based and small-molecule-based PROTACs have been developed for tau degradation. TH006, a peptide-based PROTAC with an ALAPYIP sequence as a VHL ligand, was shown to induce tau degradation in N2a cells overexpressing tau. Whilst the effect of degradation was observed at high concentrations (200 μM), TH006 administration in a mouse model of AD resulted in a reduction in tau levels in the cerebral cortex and hippocampus. TH006 has been administered both intranasally and intravenously, probably due to low BBB permeability, a common feature of these peptides . Similarly, a Keap1-based peptide PROTAC was observed to recruit CUL3 KEAP1 ubiquitin ligase, inducing the degradation of tau through the ubiquitin–proteasome system . QC-01-175, a small-molecule tau-degrading PROTAC based on the PET tracer T807, with a CRBN ligand, was shown to induce Tau degradation in FTD patient-derived neuronal models including the tau-A152T and the tau-P301L variants . Following linker optimization, second-generation CRBN-recruiting degraders (FMF-06-series) delivered a tenfold improvement in degradation potency of total tau and phospho-tau S396 with a tau reduction by 50% at 10 nM concentration . Minimal E3-ligase occupancy was observed in in vitro cellular target engagement assays, indicating low cell permeability of the optimized analogues . C004019, a VHL-based degrader, was demonstrated to lead to tau degradation through the proteasome, both in vitro and in vivo. C004019 has shown a DC 50 of 7.9 nM in a HEK293-hTau overexpressed cell line. Furthermore, intracerebroventricular or subcutaneous administration of C004019 promoted a sustained tau clearance in vivo . Another example is compound I3, a CRBN-based degrader with a THK5105 derivative as a tau ligand, where tau degradation has been demonstrated in vitro using PC12 cells . In the clinical development pipeline, Arvinas claims to have achieved BBB penetration and removal of 95% of pathological tau in vivo after parenteral administration in animal models; the structure of this PROTAC has not been disclosed at the time of writing. Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene and in the α-synuclein gene (SNCA) are linked to the onset of PD. The dysfunction of LRRK2 may contribute to the accumulation of α-synuclein, consequent microglia activation, neuroinflammation and ultimately neuronal cell death . Selective degraders targeting LRRK2 have been recently disclosed in a patent by Arvinas, claiming the discovery of potent and selective CRBN-based LRRK2 PROTACs able to degrade LRRK2 in the cerebral cortex after single oral administration in a fPD mouse model with G2019S LRRK2 mutation . In parallel, the Ciulli lab discovered the VHL-based degrader XL01126 that has been shown to be a potent degrader of LRRK2 in multiple cell lines and to pass through the BBB after oral or parenteral administration in mice, exhibiting an oral bioavailability of 15% . These attractive in vitro and in vivo properties of XL01126 represent an intriguing starting point for further drug development. With respect to α-synuclein, a synthetic peptide-based degrader has been shown to degrade intracellular α-synuclein in a recombinant expression system. The degradation of α-synuclein through the proteasome has been shown to rescue mitochondrial defects caused by aberrant α-synuclein accumulation . Moreover, in a recent patent, Arvinas claims the discovery of a series of small-molecule PROTACs, containing a VHL, CRBN, IAP or MDM2 ligand, showing a 65% degradation of α-synuclein at 1 μM in different cell lines . The aggregation of mutant huntingtin in HD leads to progressive degeneration of neurons in the striatum and cerebral cortex. Small-molecule-based bifunctional IAP-based degraders have been developed showing ubiquitination and degradation of mutant huntingtin in fibroblasts derived from HD patients . Further studies are needed to fully exploit this approach to treat HD, as the degradation activity has been observed to also involve the wild-type huntingtin . The TAR DNA-binding protein 43 (TDP-43) is an example of a misfolded protein implicated in FTD and ALS. The successful removal of the toxic C-terminal form using a heterobifunctional degrader has recently been reported . Given the challenges of developing new drugs for targeting mutated proteins in the brain, further in vitro and in vivo validation in independent laboratories is required to further explore the viability of heterobifunctional as an effective therapeutic tool to treat neurodegenerative disorders. In principle, an MGD approach has distinct advantages for the CNS space as compared to heterobifunctional degraders, largely due to the generally much more attractive physicochemical properties of glues. At this time, no MGDs have been reported for therapeutically relevant CNS targets. Discovery of MGDs here may favor non-aggregating targets, such as LRRK2 described above; however, glues for aggregating proteins may also be possible to discover, since it has been demonstrated that heterobifunctional compounds can function in this area, e.g., for tau. Heterobifunctional degraders and MGDs are both groundbreaking modalities in drug discovery and therapeutics, where both options have gained attention for their ability to selectively degrade disease-causing proteins. A TPD approach offers advantages over traditional inhibition, potentially overcoming drug resistance and providing a more profound and sustained therapeutic effect. Moreover, degraders offer a quicker avenue for investigating the molecular mechanisms underlying essential cellular processes in both physiology and pathology, bypassing the need for time-consuming gene-silencing approaches. The further development of these technologies may pave the way for highly specific and efficient therapeutics, with the potential to address previously undruggable targets and improve the overall efficacy and safety of treatments for different therapeutic areas. This review has captured developments in oncology, neurodegenerative disorders, and inflammation. However, there is clear potential outside of these areas, e.g., for fibrotic disease , anti-infectives , and metabolic disorders . As research activities into new discovery approaches, DMPK strategies and novel applications progress, degraders are likely to play a pivotal role in shaping the future landscape of medicine, helping us break bad proteins to alleviate human disease burden. |
Distinct Effects of Inflammation on Cytochrome P450 Regulation and Drug Metabolism: Lessons from Experimental Models and a Potential Role for Pharmacogenetics | df127c1c-b341-4522-bf76-fa7b15ddd37c | 7766585 | Pharmacology[mh] | The clinical outcome of drug treatments can vary greatly between individuals and even within the same individual. Consequently, certain patients may (suddenly) experience reduced efficacy or exhibit an increased risk for developing adverse events . While part of this variability can be explained by genetic variations in drug-metabolizing enzymes (DMEs)—mainly stemming from the cytochrome P450 (CYP) enzyme family—other non-genetic factors may also greatly contribute to the observed variability in drug response . Inflammation or disease state is shown to have major effects on the metabolism of drugs through downregulation of CYP enzymes and hence contribute to the mismatch between the genotype predicted drug response and the actual phenotype—a phenomenon better known as phenoconversion . However, the impact of inflammation-induced phenoconversion may differ greatly between individual patients and can be dependent on multiple factors. First, the degree of inflammation can significantly influence the extent of CYP suppression . Indeed, signature markers of inflammation are often inversely correlated with drug metabolism . Secondly, the type of inflammation or cytokine profile is an important determinant in the effect of inflammation on drug metabolism. Evidently, interleukin-targeting biologics have shown cytokine-specific successes in reversing the repressing effects of inflammatory cytokines towards CYP proteins . Thirdly, the extent of inflammation-induced phenoconversion might be dependent on the metabolic pathway of a drug since inflammation is shown to downregulate CYP activities in an isoform-specific manner . Lastly, since drug metabolism is also greatly dependent on genetic variability this might be a fourth factor that alters the extent of inflammation-induced phenoconversion in patients . To personalize and optimize drug treatments, a better understanding is needed of how inflammation affects pharmacokinetic behavior and clinical effectiveness of drugs. One major hurdle is that the specific effects of inflammation on pharmacokinetics cannot be easily assessed with in-vivo studies, due to the presence of many interfering covariables (e.g., age, genetic backgrounds, kidney function, co-medication). Therefore, in-vitro liver models may be valuable tools to elucidate the specific effects of inflammation on drug metabolism. Earlier studies with in-vitro models have already demonstrated that various inflammatory mediators associated with inflammation and infection can modulate drug metabolism by reducing the expression of CYPs . However, since the effect of inflammation-induced phenoconversion depends on the degree and type of inflammation as well as the metabolic pathway of the drug, it is necessary to better understand the different effects of various pro-inflammatory mediators and focus on the differential sensitivity between CYP isoforms in response to them. The aim of this literature review is therefore to (1) summarize and update the available evidence on the effects of inflammatory stimuli on CYP expression levels and activity in human in-vitro liver models, with a specific focus on type of inflammation and metabolic pathway of the drug. (2) Provide an overview of our current understanding of the mechanistic pathways via which inflammation in hepatocytes modulates hepatic functions (e.g., transcription factors, enzymes, nuclear receptors) that are critical for drug metabolism. (3) Define how genetic variation in these defined mechanistic pathways may modulate the effect of inflammation on drug metabolism and drug response.
Experimental laboratory studies have been instrumental for our understanding of how inflammation may modulate drug metabolism in the clinic. Through the use of in-vitro hepatocyte models, researchers have investigated which inflammatory mediators can be held responsible for the observed changes in drug metabolism. These studies primarily emphasize the effects of inflammatory stimuli on either the mRNA expression of the major CYPs responsible for drug metabolism or the actual metabolism of probe substrates for these CYPs. Since DMEs show substantial interspecies differences in terms of metabolizing activity and isoform composition, rodent data may not be useful in extrapolation to the clinic . Therefore, we describe the effects of inflammatory stimuli on CYPs in relevant human in-vitro models, summarized in . 2.1. Interleukin-6 (IL-6) IL-6 is the chief stimulator cytokine in activation of innate immunity in the liver to contribute to host defense . Owing to its role as the main cytokine in the acute phase response (APR), multiple studies have focused on investigating the effect of IL-6 on CYP levels in-vitro. 2.1.1. Maximal Effect (E max ) (mRNA) Numerous investigators have confirmed that IL-6 is a potent downregulator of CYP enzymes in both primary human hepatocytes (PHHs) and in the HepaRG cell line, an immortalized human hepatic cell system that retains PHH characteristics but lacks donor variability. Aitken et al. investigated the effect of inflammatory mediators including IL-6 on mRNA expression of CYP2C9, CYP2C19, and CYP3A4 in PHHs . Treatment with IL-6 downregulated mRNA levels for all isoforms studied, but simultaneously revealed profound differences in the magnitude of downregulation, as the expression of CYP3A4 was markedly more reduced than that of CYP2C9 or CYP2C19. A similar observation was made by Dickmann et al. and Klein et al. in PHHs and by Tanner et al. in the HepaRG cell line, who all reported that IL-6 exerted the strongest downregulation on CYP3A4, whereas the effects of IL-6 on other CYPs, most notably CYP2D6, seemed to be more limited. It should be noted from the work of Klein et al. that IL-6 may also induce expression of CYP2E1 in PHHs, which could be relevant for the metabolism of certain anesthetics . Beyond this exception, IL-6 predominantly reduces CYP expression and thus impairs the biotransformation of a wide range of (pro) drugs that are metabolized through CYP enzymes. 2.1.2. Sensitivity between CYPs (mRNA) The strength of the Dickmann study is that it examined the effects of IL-6 at different concentrations, allowing determination of the potency (EC 50 ) and thus rank ordering the responsiveness of the major CYP enzymes following IL-6 exposure . Through this approach this study was able to demonstrate that the exerted effects of IL-6 in PHH occur at physiological relevant concentrations, as similar concentrations of IL-6 have been detected in the circulation of patients with either chronic or acute inflammation . Importantly, these investigations revealed that CYP3A4 was also by potency most sensitive to downregulation by IL-6, as IL-6 downregulated CYP3A4 mRNA with an EC 50 of 0.0032 ng/mL, whereas a 20- to 500-fold higher concentration of IL-6 was needed for downregulation of other CYPs. A similar difference in CYP sensitivity to IL-6 was observed by Rubin et al. in both PHHs and HepaRG cells . Such differences in sensitivity are potentially important as these data suggest that drugs metabolized by CYP3A4 may be affected already at an earlier state during inflammation than drugs that rely on other CYP enzymes. 2.1.3. Sensitivity between PHH Donors Another point of attention is the observed interindividual variability in response to IL-6 between donors in a single experimental setup, excluding inconsistencies observed between studies due to model variations or treatment differences . For example, Dickmann et al. reported EC 50 values for CYP1A2 activity suppression between 0.142 and 4.07 ng/mL (ranging 29-fold) over five donors and a range between 0.0042 and 0.176 ng/mL (ranging 42-fold) for CYP3A4 activity suppression . Evers et al. also reported that CYP3A4 downregulation upon IL-6 stimulation varied largely between donors in one experimental setup, reporting EC 50 suppression values over approximately a 20-fold range between donors. . The observed different susceptibility to inflammation between donors may be a consequence of both genetic variability and differences in disease state or medical history of the studied donors. 2.1.4. Drug-Metabolizing Activity Determination of the cytochrome P450 enzymatic activity is important because beyond the described transcriptional effects, posttranscriptional mechanisms may also contribute to the effects of inflammation on drug metabolism . As can be observed from , effects of inflammation have commonly been assessed by measuring metabolite formation of probe substrates of CYP3A4 (midazolam/testosterone), CYP1A2 (phenacetin), CYP2C9 (tolbutamide), CYP2C19 (S-mephenytoin), and CYP2D6 (propafenone/dextromethorfan). Klein et al. showed in PHHs trends for reduced metabolite formation upon IL-6 treatment but statistical power was lacking, presumably because of the heterogeneity of the donors and potential pharmacogenetic variation in CYP450 enzymes as confounding factors . The HepaRG cell line lacks interindividual variability and showed stable CYP expression in the control group over at least 72 h, increasing the reproducibility of the results. In this model, the highest suppression of activity was noted for CYP3A4 as compared to other CYPs, in line with the observed transcriptional downregulation. Tanner et al. showed decreased downregulation of activity for CYP3A4, CYP1A2, and CYP2C19 but not CYP2C9 and CYP2D6 after 24 h . 2.1.5. Pathways IL-6 may exert its effects in hepatocytes via distinct pathways, as the binding of IL-6 to its receptor initiates cellular signaling pathways via three arms, the Janus kinase (JAK)/STAT protein-3 (STAT3) pathway, the mitogen activated protein kinase (MAPK)/extracellular regulated kinase 1 and 2 (ERK1/2) pathway, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway . Keller et al. found that, using chemical inhibitors in IL-6 treated PHHs, especially the MAPK/ERK and PI3K/AKT signaling pathways—and not the canonical JAK/STAT pathway—were critical for downregulation of CYP enzymes during inflammation . However, it should be noted that the effect of individual kinase inhibitors was tested in only one individual donor. In contrast, Febvre-James et al. found that treatment with the JAK inhibitor ruxolitinib completely reversed the IL-6-mediated suppression of CYP1A2 and CYP3A4 mRNA levels in both HepaRG cells and PHHs, suggesting a prominent role of the JAK/STAT pathway in CYP downregulation . As such, multiple signaling arms of the IL-6 pathways can be held responsible for the observed downregulation of CYP enzymes. 2.1.6. Long-Term Studies Implementing long-term investigation on inflammation-induced CYP suppression in-vitro could aid in a better understanding of the chronic inflammation frequently observed in a clinical setting. Long-term investigations on the effect of inflammatory mediators on CYP expression are scarce, especially in PHHs since CYP expression rapidly declines over time in this model . Long et al. investigated the effect of IL-6 on CYP3A4 activity in a 3D microreactor platform with PHH and Kupffer cells . They tested the effect of tocilizumab, an anti-IL-6 receptor antibody, on inflamed hepatocytes and found that coadministration of tocilizumab with IL-6 after initial 4-day IL-6 treatment prevented the CYP3A4 activity decrease across donors. This highlights that the model is capable of capturing physiological adaptation to inflammation, since CYP3A4 desuppression occurred. Tanner et al. collected data on the long-term effects of IL-6 treatment (14 days) in HepaRG cells, which resulted in more pronounced downregulation of P450 expression as compared to short-term treatment . Still, current studies do not address the impact of long-term low concentrations of cytokines as compared to single high-dose treatment, which leaves an open question. 2.1.7. Clinic Interestingly, the effects of inflammation on drug metabolism in the clinic, most commonly assessed through the IL-6 regulated marker C-reactive protein (CRP), seems to be most reported for CYP3A4 substrates including midazolam, tacrolimus, and/or voriconazole, and less for drugs metabolized through other metabolic pathways. This is in line with data from in-vitro hepatocyte models where IL-6 exerts most profound effects on CYP3A4 . Altogether, these data confirm isoform specific effects of IL-6 and suggest that drugs metabolized via CYP3A4 may be more prone to the effects of inflammation. 2.2. Interleukin 1 (IL-1)-Family: Interleukin-1β and Interleukin-18 The IL-1 family compromises a group of 11 proteins that play a role in the initiation and regulation of inflammatory responses, of which IL-1 β is the most studied member . 2.2.1. Maximal Effect (E max ) (mRNA) In PHHs, IL-1 β treatment reduced CYP3A4 mRNA expression with 95%, but it had no effect on CYP2C9 or CYP2C19 mRNA levels . Protein levels of CYP3A4, but also of CYP2C9, were significantly downregulated after 24 h of treatment with IL-1β. Dickmann et al. showed donor-wide suppression ( n = 5) for CYP3A4/A5, however, IL-1β-mediated suppression of other CYP isoforms (CYP2C9, C19, and 1A2) was not consistently observed among all donors . The observed nonresponse towards IL-1 β of certain CYP isoforms cannot simply be explained by a lack of effect, since IL-1 β consistently reduced CYP3A4 expression by >80% in all donors. Alternatively, because the nonresponsive CYP isoforms (CYP2C9 or CYP2C19) differed between donors, nonresponse to IL-1 β can perhaps be explained by pharmacogenetic variation within these CYP isoforms. IL-18 treatment in HepaRG cells and PHHs did not result in significant downregulation of mRNA levels nor CYP activity . 2.2.2. Sensitivity between Models Interestingly, although Klein et al. showed that the maximal impact of Il-1 β and IL-6 on the mRNA expression of CYP isoforms was comparable in HepaRG cells, IL-1β showed an approximate 100-fold higher potency than IL-6 in inducing the same downregulation . This described difference in potency might be underlined by the fact that the HepaRG cell line displays morphological heterogeneity, including clusters with nonparenchymal cells which could aggravate or sensitize the response to an inflammatory mediator . For example, IL-1 β release is associated with activation of the inflammasome in Kupffer cells , providing a feed-forward stimulus for production of more inflammatory cytokines which could potentially aggravate cytokine-induced downregulation of CYPs. Indeed, coculturing of Kupffer cells increased responsiveness to IL-1 β as compared to monocultures of hepatocytes, as evident from an EC 50 shift from >5 to 0.098 ng/mL for CYP3A4 suppression upon coculturing, an effect not seen with IL-6 treatment . Since IL-18 is also reported to mediate its effect through Kupffer cells , this can explain the lack of effect on CYPs in HepaRG or PHHs cell models described by Rubin et al. Thus, inclusion of nonparenchymal cells in model systems might increase the responsiveness to IL-1 β and IL-18 and hence better reflect the potential effect these inflammatory cytokines may have in an intact human liver. 2.2.3. Sensitivity between PHH Donors Looking at the suppression of activity of CYP3A4 and CYP1A2 in PHHs upon IL-1 β treatment, again large interdonor variation is evident . Dickmann et al. found an average EC 50 value for two donors of 0.450 ng/mL (three donors showed no response) regarding CYP1A2 activity. For CYP3A4, EC 50 values for activity ranged from 0.005 to 1.06 ng/mL over five donors. 2.2.4. Pathways The effects of IL-1β are presumed to be mediated via activation of the nuclear factor kappa B (NF-κB) pathway . Importantly, IL-1 β may also rapidly (within 2–4 h) induce IL-6 expression, which raises the possibility that part of the observed actions of IL-1β are actually mediated by IL-6 . Interestingly, a recent study by Febvre-James et al. found that the IL-1 β repression of CYP enzymes could not be reversed by the JAK inhibitor ruxolitinib, confirming that IL-1 β and IL-6 induce distinct pathways upon inflammation and may complement one another in altering drug metabolism . 2.3. Tumor Necrosis Factor α (TNF-α) TNF- α is another main cytokine involved in inducing the acute phase response in the liver during inflammation. Hepatocytes express the tumor necrosis factor receptor 1 (TNFR1) that upon binding by TNF-α results in the activation of the major NF-κB pathway and the MAPK/ERK pathway . Aitken et al. found that TNF- α treatment induced CYP3A4 mRNA downregulation but not protein downregulation after 24 h . They saw no effect on CYP2C9 and CYP2C19 mRNA levels upon TNF-α treatment, but interestingly the CYP2C9 protein levels were reduced by >95% after 24 h treatment, pointing to a mismatch between the effects on mRNA and protein expression levels. This suggests that post-transcriptional mechanisms, i.e., protein degradation or regulation by miRNAs, are involved in downregulation of CYP protein levels by TNF-α. In line, Dallas et al. reported no effects of TNF- α on CYP2C19 and CYP2C9 mRNA levels, but found significantly downregulated CYP2C19 and CYP2C9 activity . Klein et al. found that TNF-α treatment resulted in similar downregulation of CYP gene expression in HepaRG cells as observed with IL-6 treatment, presuming that part of the effect of TNF-α is mediated via nonparenchymal cells . After 72 h of exposure to TNF- α , all P450 activities were reduced by more than 80%. 2.4. Pathogen Associated Molecular Patterns (PAMPs) PAMPs, such as lipopolysaccharide (LPS), are microbial molecules that can signal immune cells to destroy intruding pathogens associated with infection . Upon LPS recognition, the toll like receptor 4 (TLR4) signaling pathway ultimately activates NF-kB. The study by Aitken et al. found LPS to be the most efficacious inflammatory stimulus in downregulating mRNA levels of CYP3A4, and CYP3A4 protein levels were decreased by about 75% of control 24 h after treatment . Whereas LPS treatment did not influence mRNA levels of CYP2C9 or CYP2C19, CYP2C9 protein levels were reduced by 80% after 24 h of treatment, again indicating a mismatch between mRNA and protein levels. This is in accordance with data presented by Rubin et al. in HepaRG cells and PHHs, where LPS downregulated CYP3A4 and CYP1A2 mRNA levels in both models . LPS showed comparable potency in downregulating CYP3A4 compared to IL-6, but was much less potent in downregulating CYP1A2 levels. 2.5. Other Cytokines: Transforming Growth Factor β (TGF-β), Interferon γ (IFN-γ), Interleukin-22 (IL-22), Interleukin-23 (IL-23), and Interleukin-2 (IL-2) The effect of other pro-inflammatory mediators beyond IL-6, IL-1 β , TNF- α , and PAMPs has also been studied in in-vitro hepatocyte models. TGF- β , an inflammatory mediator linked to fibrosis, caused significant downregulation of CYP3A4, CYP2C9, and CYP2C19 mRNA levels and subsequent protein levels (only shown for CYP3A4 and CYP2C9) . Interestingly, only TGF- β and IL-6 downregulated CYP2C9 mRNA, but protein expression levels of CYP2C9 were strongly downregulated by all inflammatory stimuli tested. IFN-γ, a mediator that is associated with the immune response to viral infections, only reduced mRNA levels of CYP3A4 in PHHs. Conversely, IL-22, a pro-inflammatory mediator found in different auto-immune disorders, was found to repress mRNA levels of CYP1A2, CYP3A4, and CYP2C9 in PHHs and HepaRG cells . Studies investigating the effect of IL-2 on CYP3A4, 1A2, 2C9, 2C19, and 2D6 expression found no suppression of mRNA levels upon treatment in PHHs . Interestingly, when culturing the hepatocytes together with Kupffer cells, a concentration-dependent decrease (50–70%) of CYP3A4 activity was observed with IL-2 at 72 h, suggesting that Kupffer cells are essential for the suppressive effect of IL-2 . IL-12 and IL-23, pro-inflammatory mediators associated with inflammatory autoimmune responses, did not impact CYP3A4 levels and a coculture model did not change this . The effect of other cytokines on CYP expression and activity is yet to be determined. 2.6. Summary The in-vitro data summarized here suggests that direct treatment with inflammatory stimuli can suppress DMEs stemming from the CYP1, CYP2, and CYP3 family. This suppressive effect is most convincingly demonstrated for IL-6, IL-1 β , TNF- α , and LPS. CYP3A4 seems to be most susceptible to cytokine-induced downregulation in human in-vitro hepatocyte models, whereas CYP2D6 seems to be the least sensitive. The enzyme expression of CYP1A2, CYP2C9, and CYP2C19 was also sensitive to the effects of inflammatory mediators, though higher concentrations of cytokines were in general required to downregulate these enzymes and the response was not always conserved among all studied donors. Interestingly, model-dependent responses were observed which could be reliant on the presence of nonparenchymal cells. The effect of inflammatory mediators should therefore be divided into direct effects on hepatocytes and indirect effects through inflammatory signaling in nonparenchymal cells. Importantly, interdonor variation in response to inflammation within the same experimental setup was observed. Translating these findings to the clinic, the consequences of inflammation-induced phenoconversion for drug treatments may differ therefore greatly between individuals and between the metabolic CYP pathways via which drugs are metabolized.
IL-6 is the chief stimulator cytokine in activation of innate immunity in the liver to contribute to host defense . Owing to its role as the main cytokine in the acute phase response (APR), multiple studies have focused on investigating the effect of IL-6 on CYP levels in-vitro. 2.1.1. Maximal Effect (E max ) (mRNA) Numerous investigators have confirmed that IL-6 is a potent downregulator of CYP enzymes in both primary human hepatocytes (PHHs) and in the HepaRG cell line, an immortalized human hepatic cell system that retains PHH characteristics but lacks donor variability. Aitken et al. investigated the effect of inflammatory mediators including IL-6 on mRNA expression of CYP2C9, CYP2C19, and CYP3A4 in PHHs . Treatment with IL-6 downregulated mRNA levels for all isoforms studied, but simultaneously revealed profound differences in the magnitude of downregulation, as the expression of CYP3A4 was markedly more reduced than that of CYP2C9 or CYP2C19. A similar observation was made by Dickmann et al. and Klein et al. in PHHs and by Tanner et al. in the HepaRG cell line, who all reported that IL-6 exerted the strongest downregulation on CYP3A4, whereas the effects of IL-6 on other CYPs, most notably CYP2D6, seemed to be more limited. It should be noted from the work of Klein et al. that IL-6 may also induce expression of CYP2E1 in PHHs, which could be relevant for the metabolism of certain anesthetics . Beyond this exception, IL-6 predominantly reduces CYP expression and thus impairs the biotransformation of a wide range of (pro) drugs that are metabolized through CYP enzymes. 2.1.2. Sensitivity between CYPs (mRNA) The strength of the Dickmann study is that it examined the effects of IL-6 at different concentrations, allowing determination of the potency (EC 50 ) and thus rank ordering the responsiveness of the major CYP enzymes following IL-6 exposure . Through this approach this study was able to demonstrate that the exerted effects of IL-6 in PHH occur at physiological relevant concentrations, as similar concentrations of IL-6 have been detected in the circulation of patients with either chronic or acute inflammation . Importantly, these investigations revealed that CYP3A4 was also by potency most sensitive to downregulation by IL-6, as IL-6 downregulated CYP3A4 mRNA with an EC 50 of 0.0032 ng/mL, whereas a 20- to 500-fold higher concentration of IL-6 was needed for downregulation of other CYPs. A similar difference in CYP sensitivity to IL-6 was observed by Rubin et al. in both PHHs and HepaRG cells . Such differences in sensitivity are potentially important as these data suggest that drugs metabolized by CYP3A4 may be affected already at an earlier state during inflammation than drugs that rely on other CYP enzymes. 2.1.3. Sensitivity between PHH Donors Another point of attention is the observed interindividual variability in response to IL-6 between donors in a single experimental setup, excluding inconsistencies observed between studies due to model variations or treatment differences . For example, Dickmann et al. reported EC 50 values for CYP1A2 activity suppression between 0.142 and 4.07 ng/mL (ranging 29-fold) over five donors and a range between 0.0042 and 0.176 ng/mL (ranging 42-fold) for CYP3A4 activity suppression . Evers et al. also reported that CYP3A4 downregulation upon IL-6 stimulation varied largely between donors in one experimental setup, reporting EC 50 suppression values over approximately a 20-fold range between donors. . The observed different susceptibility to inflammation between donors may be a consequence of both genetic variability and differences in disease state or medical history of the studied donors. 2.1.4. Drug-Metabolizing Activity Determination of the cytochrome P450 enzymatic activity is important because beyond the described transcriptional effects, posttranscriptional mechanisms may also contribute to the effects of inflammation on drug metabolism . As can be observed from , effects of inflammation have commonly been assessed by measuring metabolite formation of probe substrates of CYP3A4 (midazolam/testosterone), CYP1A2 (phenacetin), CYP2C9 (tolbutamide), CYP2C19 (S-mephenytoin), and CYP2D6 (propafenone/dextromethorfan). Klein et al. showed in PHHs trends for reduced metabolite formation upon IL-6 treatment but statistical power was lacking, presumably because of the heterogeneity of the donors and potential pharmacogenetic variation in CYP450 enzymes as confounding factors . The HepaRG cell line lacks interindividual variability and showed stable CYP expression in the control group over at least 72 h, increasing the reproducibility of the results. In this model, the highest suppression of activity was noted for CYP3A4 as compared to other CYPs, in line with the observed transcriptional downregulation. Tanner et al. showed decreased downregulation of activity for CYP3A4, CYP1A2, and CYP2C19 but not CYP2C9 and CYP2D6 after 24 h . 2.1.5. Pathways IL-6 may exert its effects in hepatocytes via distinct pathways, as the binding of IL-6 to its receptor initiates cellular signaling pathways via three arms, the Janus kinase (JAK)/STAT protein-3 (STAT3) pathway, the mitogen activated protein kinase (MAPK)/extracellular regulated kinase 1 and 2 (ERK1/2) pathway, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway . Keller et al. found that, using chemical inhibitors in IL-6 treated PHHs, especially the MAPK/ERK and PI3K/AKT signaling pathways—and not the canonical JAK/STAT pathway—were critical for downregulation of CYP enzymes during inflammation . However, it should be noted that the effect of individual kinase inhibitors was tested in only one individual donor. In contrast, Febvre-James et al. found that treatment with the JAK inhibitor ruxolitinib completely reversed the IL-6-mediated suppression of CYP1A2 and CYP3A4 mRNA levels in both HepaRG cells and PHHs, suggesting a prominent role of the JAK/STAT pathway in CYP downregulation . As such, multiple signaling arms of the IL-6 pathways can be held responsible for the observed downregulation of CYP enzymes. 2.1.6. Long-Term Studies Implementing long-term investigation on inflammation-induced CYP suppression in-vitro could aid in a better understanding of the chronic inflammation frequently observed in a clinical setting. Long-term investigations on the effect of inflammatory mediators on CYP expression are scarce, especially in PHHs since CYP expression rapidly declines over time in this model . Long et al. investigated the effect of IL-6 on CYP3A4 activity in a 3D microreactor platform with PHH and Kupffer cells . They tested the effect of tocilizumab, an anti-IL-6 receptor antibody, on inflamed hepatocytes and found that coadministration of tocilizumab with IL-6 after initial 4-day IL-6 treatment prevented the CYP3A4 activity decrease across donors. This highlights that the model is capable of capturing physiological adaptation to inflammation, since CYP3A4 desuppression occurred. Tanner et al. collected data on the long-term effects of IL-6 treatment (14 days) in HepaRG cells, which resulted in more pronounced downregulation of P450 expression as compared to short-term treatment . Still, current studies do not address the impact of long-term low concentrations of cytokines as compared to single high-dose treatment, which leaves an open question. 2.1.7. Clinic Interestingly, the effects of inflammation on drug metabolism in the clinic, most commonly assessed through the IL-6 regulated marker C-reactive protein (CRP), seems to be most reported for CYP3A4 substrates including midazolam, tacrolimus, and/or voriconazole, and less for drugs metabolized through other metabolic pathways. This is in line with data from in-vitro hepatocyte models where IL-6 exerts most profound effects on CYP3A4 . Altogether, these data confirm isoform specific effects of IL-6 and suggest that drugs metabolized via CYP3A4 may be more prone to the effects of inflammation.
max ) (mRNA) Numerous investigators have confirmed that IL-6 is a potent downregulator of CYP enzymes in both primary human hepatocytes (PHHs) and in the HepaRG cell line, an immortalized human hepatic cell system that retains PHH characteristics but lacks donor variability. Aitken et al. investigated the effect of inflammatory mediators including IL-6 on mRNA expression of CYP2C9, CYP2C19, and CYP3A4 in PHHs . Treatment with IL-6 downregulated mRNA levels for all isoforms studied, but simultaneously revealed profound differences in the magnitude of downregulation, as the expression of CYP3A4 was markedly more reduced than that of CYP2C9 or CYP2C19. A similar observation was made by Dickmann et al. and Klein et al. in PHHs and by Tanner et al. in the HepaRG cell line, who all reported that IL-6 exerted the strongest downregulation on CYP3A4, whereas the effects of IL-6 on other CYPs, most notably CYP2D6, seemed to be more limited. It should be noted from the work of Klein et al. that IL-6 may also induce expression of CYP2E1 in PHHs, which could be relevant for the metabolism of certain anesthetics . Beyond this exception, IL-6 predominantly reduces CYP expression and thus impairs the biotransformation of a wide range of (pro) drugs that are metabolized through CYP enzymes.
The strength of the Dickmann study is that it examined the effects of IL-6 at different concentrations, allowing determination of the potency (EC 50 ) and thus rank ordering the responsiveness of the major CYP enzymes following IL-6 exposure . Through this approach this study was able to demonstrate that the exerted effects of IL-6 in PHH occur at physiological relevant concentrations, as similar concentrations of IL-6 have been detected in the circulation of patients with either chronic or acute inflammation . Importantly, these investigations revealed that CYP3A4 was also by potency most sensitive to downregulation by IL-6, as IL-6 downregulated CYP3A4 mRNA with an EC 50 of 0.0032 ng/mL, whereas a 20- to 500-fold higher concentration of IL-6 was needed for downregulation of other CYPs. A similar difference in CYP sensitivity to IL-6 was observed by Rubin et al. in both PHHs and HepaRG cells . Such differences in sensitivity are potentially important as these data suggest that drugs metabolized by CYP3A4 may be affected already at an earlier state during inflammation than drugs that rely on other CYP enzymes.
Another point of attention is the observed interindividual variability in response to IL-6 between donors in a single experimental setup, excluding inconsistencies observed between studies due to model variations or treatment differences . For example, Dickmann et al. reported EC 50 values for CYP1A2 activity suppression between 0.142 and 4.07 ng/mL (ranging 29-fold) over five donors and a range between 0.0042 and 0.176 ng/mL (ranging 42-fold) for CYP3A4 activity suppression . Evers et al. also reported that CYP3A4 downregulation upon IL-6 stimulation varied largely between donors in one experimental setup, reporting EC 50 suppression values over approximately a 20-fold range between donors. . The observed different susceptibility to inflammation between donors may be a consequence of both genetic variability and differences in disease state or medical history of the studied donors.
Determination of the cytochrome P450 enzymatic activity is important because beyond the described transcriptional effects, posttranscriptional mechanisms may also contribute to the effects of inflammation on drug metabolism . As can be observed from , effects of inflammation have commonly been assessed by measuring metabolite formation of probe substrates of CYP3A4 (midazolam/testosterone), CYP1A2 (phenacetin), CYP2C9 (tolbutamide), CYP2C19 (S-mephenytoin), and CYP2D6 (propafenone/dextromethorfan). Klein et al. showed in PHHs trends for reduced metabolite formation upon IL-6 treatment but statistical power was lacking, presumably because of the heterogeneity of the donors and potential pharmacogenetic variation in CYP450 enzymes as confounding factors . The HepaRG cell line lacks interindividual variability and showed stable CYP expression in the control group over at least 72 h, increasing the reproducibility of the results. In this model, the highest suppression of activity was noted for CYP3A4 as compared to other CYPs, in line with the observed transcriptional downregulation. Tanner et al. showed decreased downregulation of activity for CYP3A4, CYP1A2, and CYP2C19 but not CYP2C9 and CYP2D6 after 24 h .
IL-6 may exert its effects in hepatocytes via distinct pathways, as the binding of IL-6 to its receptor initiates cellular signaling pathways via three arms, the Janus kinase (JAK)/STAT protein-3 (STAT3) pathway, the mitogen activated protein kinase (MAPK)/extracellular regulated kinase 1 and 2 (ERK1/2) pathway, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathway . Keller et al. found that, using chemical inhibitors in IL-6 treated PHHs, especially the MAPK/ERK and PI3K/AKT signaling pathways—and not the canonical JAK/STAT pathway—were critical for downregulation of CYP enzymes during inflammation . However, it should be noted that the effect of individual kinase inhibitors was tested in only one individual donor. In contrast, Febvre-James et al. found that treatment with the JAK inhibitor ruxolitinib completely reversed the IL-6-mediated suppression of CYP1A2 and CYP3A4 mRNA levels in both HepaRG cells and PHHs, suggesting a prominent role of the JAK/STAT pathway in CYP downregulation . As such, multiple signaling arms of the IL-6 pathways can be held responsible for the observed downregulation of CYP enzymes.
Implementing long-term investigation on inflammation-induced CYP suppression in-vitro could aid in a better understanding of the chronic inflammation frequently observed in a clinical setting. Long-term investigations on the effect of inflammatory mediators on CYP expression are scarce, especially in PHHs since CYP expression rapidly declines over time in this model . Long et al. investigated the effect of IL-6 on CYP3A4 activity in a 3D microreactor platform with PHH and Kupffer cells . They tested the effect of tocilizumab, an anti-IL-6 receptor antibody, on inflamed hepatocytes and found that coadministration of tocilizumab with IL-6 after initial 4-day IL-6 treatment prevented the CYP3A4 activity decrease across donors. This highlights that the model is capable of capturing physiological adaptation to inflammation, since CYP3A4 desuppression occurred. Tanner et al. collected data on the long-term effects of IL-6 treatment (14 days) in HepaRG cells, which resulted in more pronounced downregulation of P450 expression as compared to short-term treatment . Still, current studies do not address the impact of long-term low concentrations of cytokines as compared to single high-dose treatment, which leaves an open question.
Interestingly, the effects of inflammation on drug metabolism in the clinic, most commonly assessed through the IL-6 regulated marker C-reactive protein (CRP), seems to be most reported for CYP3A4 substrates including midazolam, tacrolimus, and/or voriconazole, and less for drugs metabolized through other metabolic pathways. This is in line with data from in-vitro hepatocyte models where IL-6 exerts most profound effects on CYP3A4 . Altogether, these data confirm isoform specific effects of IL-6 and suggest that drugs metabolized via CYP3A4 may be more prone to the effects of inflammation.
The IL-1 family compromises a group of 11 proteins that play a role in the initiation and regulation of inflammatory responses, of which IL-1 β is the most studied member . 2.2.1. Maximal Effect (E max ) (mRNA) In PHHs, IL-1 β treatment reduced CYP3A4 mRNA expression with 95%, but it had no effect on CYP2C9 or CYP2C19 mRNA levels . Protein levels of CYP3A4, but also of CYP2C9, were significantly downregulated after 24 h of treatment with IL-1β. Dickmann et al. showed donor-wide suppression ( n = 5) for CYP3A4/A5, however, IL-1β-mediated suppression of other CYP isoforms (CYP2C9, C19, and 1A2) was not consistently observed among all donors . The observed nonresponse towards IL-1 β of certain CYP isoforms cannot simply be explained by a lack of effect, since IL-1 β consistently reduced CYP3A4 expression by >80% in all donors. Alternatively, because the nonresponsive CYP isoforms (CYP2C9 or CYP2C19) differed between donors, nonresponse to IL-1 β can perhaps be explained by pharmacogenetic variation within these CYP isoforms. IL-18 treatment in HepaRG cells and PHHs did not result in significant downregulation of mRNA levels nor CYP activity . 2.2.2. Sensitivity between Models Interestingly, although Klein et al. showed that the maximal impact of Il-1 β and IL-6 on the mRNA expression of CYP isoforms was comparable in HepaRG cells, IL-1β showed an approximate 100-fold higher potency than IL-6 in inducing the same downregulation . This described difference in potency might be underlined by the fact that the HepaRG cell line displays morphological heterogeneity, including clusters with nonparenchymal cells which could aggravate or sensitize the response to an inflammatory mediator . For example, IL-1 β release is associated with activation of the inflammasome in Kupffer cells , providing a feed-forward stimulus for production of more inflammatory cytokines which could potentially aggravate cytokine-induced downregulation of CYPs. Indeed, coculturing of Kupffer cells increased responsiveness to IL-1 β as compared to monocultures of hepatocytes, as evident from an EC 50 shift from >5 to 0.098 ng/mL for CYP3A4 suppression upon coculturing, an effect not seen with IL-6 treatment . Since IL-18 is also reported to mediate its effect through Kupffer cells , this can explain the lack of effect on CYPs in HepaRG or PHHs cell models described by Rubin et al. Thus, inclusion of nonparenchymal cells in model systems might increase the responsiveness to IL-1 β and IL-18 and hence better reflect the potential effect these inflammatory cytokines may have in an intact human liver. 2.2.3. Sensitivity between PHH Donors Looking at the suppression of activity of CYP3A4 and CYP1A2 in PHHs upon IL-1 β treatment, again large interdonor variation is evident . Dickmann et al. found an average EC 50 value for two donors of 0.450 ng/mL (three donors showed no response) regarding CYP1A2 activity. For CYP3A4, EC 50 values for activity ranged from 0.005 to 1.06 ng/mL over five donors. 2.2.4. Pathways The effects of IL-1β are presumed to be mediated via activation of the nuclear factor kappa B (NF-κB) pathway . Importantly, IL-1 β may also rapidly (within 2–4 h) induce IL-6 expression, which raises the possibility that part of the observed actions of IL-1β are actually mediated by IL-6 . Interestingly, a recent study by Febvre-James et al. found that the IL-1 β repression of CYP enzymes could not be reversed by the JAK inhibitor ruxolitinib, confirming that IL-1 β and IL-6 induce distinct pathways upon inflammation and may complement one another in altering drug metabolism .
max ) (mRNA) In PHHs, IL-1 β treatment reduced CYP3A4 mRNA expression with 95%, but it had no effect on CYP2C9 or CYP2C19 mRNA levels . Protein levels of CYP3A4, but also of CYP2C9, were significantly downregulated after 24 h of treatment with IL-1β. Dickmann et al. showed donor-wide suppression ( n = 5) for CYP3A4/A5, however, IL-1β-mediated suppression of other CYP isoforms (CYP2C9, C19, and 1A2) was not consistently observed among all donors . The observed nonresponse towards IL-1 β of certain CYP isoforms cannot simply be explained by a lack of effect, since IL-1 β consistently reduced CYP3A4 expression by >80% in all donors. Alternatively, because the nonresponsive CYP isoforms (CYP2C9 or CYP2C19) differed between donors, nonresponse to IL-1 β can perhaps be explained by pharmacogenetic variation within these CYP isoforms. IL-18 treatment in HepaRG cells and PHHs did not result in significant downregulation of mRNA levels nor CYP activity .
Interestingly, although Klein et al. showed that the maximal impact of Il-1 β and IL-6 on the mRNA expression of CYP isoforms was comparable in HepaRG cells, IL-1β showed an approximate 100-fold higher potency than IL-6 in inducing the same downregulation . This described difference in potency might be underlined by the fact that the HepaRG cell line displays morphological heterogeneity, including clusters with nonparenchymal cells which could aggravate or sensitize the response to an inflammatory mediator . For example, IL-1 β release is associated with activation of the inflammasome in Kupffer cells , providing a feed-forward stimulus for production of more inflammatory cytokines which could potentially aggravate cytokine-induced downregulation of CYPs. Indeed, coculturing of Kupffer cells increased responsiveness to IL-1 β as compared to monocultures of hepatocytes, as evident from an EC 50 shift from >5 to 0.098 ng/mL for CYP3A4 suppression upon coculturing, an effect not seen with IL-6 treatment . Since IL-18 is also reported to mediate its effect through Kupffer cells , this can explain the lack of effect on CYPs in HepaRG or PHHs cell models described by Rubin et al. Thus, inclusion of nonparenchymal cells in model systems might increase the responsiveness to IL-1 β and IL-18 and hence better reflect the potential effect these inflammatory cytokines may have in an intact human liver.
Looking at the suppression of activity of CYP3A4 and CYP1A2 in PHHs upon IL-1 β treatment, again large interdonor variation is evident . Dickmann et al. found an average EC 50 value for two donors of 0.450 ng/mL (three donors showed no response) regarding CYP1A2 activity. For CYP3A4, EC 50 values for activity ranged from 0.005 to 1.06 ng/mL over five donors.
The effects of IL-1β are presumed to be mediated via activation of the nuclear factor kappa B (NF-κB) pathway . Importantly, IL-1 β may also rapidly (within 2–4 h) induce IL-6 expression, which raises the possibility that part of the observed actions of IL-1β are actually mediated by IL-6 . Interestingly, a recent study by Febvre-James et al. found that the IL-1 β repression of CYP enzymes could not be reversed by the JAK inhibitor ruxolitinib, confirming that IL-1 β and IL-6 induce distinct pathways upon inflammation and may complement one another in altering drug metabolism .
TNF- α is another main cytokine involved in inducing the acute phase response in the liver during inflammation. Hepatocytes express the tumor necrosis factor receptor 1 (TNFR1) that upon binding by TNF-α results in the activation of the major NF-κB pathway and the MAPK/ERK pathway . Aitken et al. found that TNF- α treatment induced CYP3A4 mRNA downregulation but not protein downregulation after 24 h . They saw no effect on CYP2C9 and CYP2C19 mRNA levels upon TNF-α treatment, but interestingly the CYP2C9 protein levels were reduced by >95% after 24 h treatment, pointing to a mismatch between the effects on mRNA and protein expression levels. This suggests that post-transcriptional mechanisms, i.e., protein degradation or regulation by miRNAs, are involved in downregulation of CYP protein levels by TNF-α. In line, Dallas et al. reported no effects of TNF- α on CYP2C19 and CYP2C9 mRNA levels, but found significantly downregulated CYP2C19 and CYP2C9 activity . Klein et al. found that TNF-α treatment resulted in similar downregulation of CYP gene expression in HepaRG cells as observed with IL-6 treatment, presuming that part of the effect of TNF-α is mediated via nonparenchymal cells . After 72 h of exposure to TNF- α , all P450 activities were reduced by more than 80%.
PAMPs, such as lipopolysaccharide (LPS), are microbial molecules that can signal immune cells to destroy intruding pathogens associated with infection . Upon LPS recognition, the toll like receptor 4 (TLR4) signaling pathway ultimately activates NF-kB. The study by Aitken et al. found LPS to be the most efficacious inflammatory stimulus in downregulating mRNA levels of CYP3A4, and CYP3A4 protein levels were decreased by about 75% of control 24 h after treatment . Whereas LPS treatment did not influence mRNA levels of CYP2C9 or CYP2C19, CYP2C9 protein levels were reduced by 80% after 24 h of treatment, again indicating a mismatch between mRNA and protein levels. This is in accordance with data presented by Rubin et al. in HepaRG cells and PHHs, where LPS downregulated CYP3A4 and CYP1A2 mRNA levels in both models . LPS showed comparable potency in downregulating CYP3A4 compared to IL-6, but was much less potent in downregulating CYP1A2 levels.
The effect of other pro-inflammatory mediators beyond IL-6, IL-1 β , TNF- α , and PAMPs has also been studied in in-vitro hepatocyte models. TGF- β , an inflammatory mediator linked to fibrosis, caused significant downregulation of CYP3A4, CYP2C9, and CYP2C19 mRNA levels and subsequent protein levels (only shown for CYP3A4 and CYP2C9) . Interestingly, only TGF- β and IL-6 downregulated CYP2C9 mRNA, but protein expression levels of CYP2C9 were strongly downregulated by all inflammatory stimuli tested. IFN-γ, a mediator that is associated with the immune response to viral infections, only reduced mRNA levels of CYP3A4 in PHHs. Conversely, IL-22, a pro-inflammatory mediator found in different auto-immune disorders, was found to repress mRNA levels of CYP1A2, CYP3A4, and CYP2C9 in PHHs and HepaRG cells . Studies investigating the effect of IL-2 on CYP3A4, 1A2, 2C9, 2C19, and 2D6 expression found no suppression of mRNA levels upon treatment in PHHs . Interestingly, when culturing the hepatocytes together with Kupffer cells, a concentration-dependent decrease (50–70%) of CYP3A4 activity was observed with IL-2 at 72 h, suggesting that Kupffer cells are essential for the suppressive effect of IL-2 . IL-12 and IL-23, pro-inflammatory mediators associated with inflammatory autoimmune responses, did not impact CYP3A4 levels and a coculture model did not change this . The effect of other cytokines on CYP expression and activity is yet to be determined.
The in-vitro data summarized here suggests that direct treatment with inflammatory stimuli can suppress DMEs stemming from the CYP1, CYP2, and CYP3 family. This suppressive effect is most convincingly demonstrated for IL-6, IL-1 β , TNF- α , and LPS. CYP3A4 seems to be most susceptible to cytokine-induced downregulation in human in-vitro hepatocyte models, whereas CYP2D6 seems to be the least sensitive. The enzyme expression of CYP1A2, CYP2C9, and CYP2C19 was also sensitive to the effects of inflammatory mediators, though higher concentrations of cytokines were in general required to downregulate these enzymes and the response was not always conserved among all studied donors. Interestingly, model-dependent responses were observed which could be reliant on the presence of nonparenchymal cells. The effect of inflammatory mediators should therefore be divided into direct effects on hepatocytes and indirect effects through inflammatory signaling in nonparenchymal cells. Importantly, interdonor variation in response to inflammation within the same experimental setup was observed. Translating these findings to the clinic, the consequences of inflammation-induced phenoconversion for drug treatments may differ therefore greatly between individuals and between the metabolic CYP pathways via which drugs are metabolized.
The above described findings from in-vitro models show that the sensitivity to inflammation may differ between CYP isoforms and inflammatory stimuli. This implies that distinct mechanisms are involved in the downregulation of CYP enzyme expression and activity. Mechanistically, regulation of hepatic CYP levels and interactions with CYP gene regulators is complicated and includes a wide variety of ligand-activated transcription factors and mediators. Cytokine-mediated alteration of gene transcription is thought to be the main regulatory mechanism accountable for changing CYP450 activity upon inflammation. It is essential to note that no single common pathway is recognized for all the CYP enzymes and underlying mechanisms are cytokine-specific. Here we describe, summarized in , how repression of important CYP enzymes during inflammation may proceed through (1) transcriptional downregulation of transcription factors, (2) interference with dimerization/translocation of (nuclear) transcription factors, (3) altered liver-enriched C/EBP signaling, (4) direct regulation by NF-κB, or (5) post-transcriptional mechanisms. 3.1. Transcriptional Downregulation of Transcription Factors Transcription factors involved in the regulation of CYP mRNA levels, including the nuclear receptors pregnane X receptor (PXR), the constitutive androstane receptor (CAR), their dimerization partner retinoid X receptor (RXR), the aryl hydrocarbon receptor (AhR), as well as human nuclear factors (HNFs) are held responsible for the observed downregulation of DMEs upon inflammation. It is important to distinguish between the role of nuclear transcription factors in the constitutive expression of CYP enzymes versus drug- or inflammation-mediated expression. Here we will focus on the nuclear hormone receptor mechanisms likely to be involved in inflammation-altered CYP expression. 3.1.1. Downregulation of Nuclear Receptors The PXR (gene: NR1I2 ) and the CAR (gene: NR1I3 ) are members of the nuclear receptor superfamily highly expressed in the enterohepatic system of mammals . These ligand activated transcription factors have been identified as key transcriptional regulators of the cytochrome P450 xenobiotic-metabolizing enzymes, mostly for the CYP2C9, CYP2C19, CYP3A4, and CYP3A5 enzyme expression . Upon binding with the RXR, the heterodimer nuclear receptor-RXR complex binds to responsive elements present in the 5′-flanking regions of target genes, usually resulting in an upregulation of gene expression aimed at increased metabolism of drugs. Studies have indeed shown that PXR and CAR increase transcription of the human CYP3A4/5, CYP2C9, CYP2C19, and CYP1A2 genes upon drug treatment . One mechanism by which inflammation changes gene transcription of major DMEs is through repression of the nuclear receptor PXR and CAR. A vast body of evidence shows that inflammation represses PXR levels, leading to downregulation of important CYP enzymes. Pascussi et al. pioneered in showing that IL-6 downregulates PXR mRNA in PHH and inhibits the rifampicine-induced induction of CYP3A4 . Upon LPS treatment in HepG2 cells, the mRNA and protein levels of PXR are reduced . Mechanistically, a decrease in PXR expression within the nucleus was observed, leading to reduced transactivation of the CYP3A4 promotor and subsequent inhibited transcriptional activity of CYP3A4. Additionally, LPS treatment in mice led to functional repression of PXR’s dimerization partner RXR . Yang et al. showed that inhibition of a CYP3A4 promotor reporter after IL-6 treatment in human hepatocytes was greater in the presence of PXR than after its knockdown, suggesting a role for PXR in IL-6-facilitated suppression of CYP3A4 . Knockdown of PXR in human hepatocytes reversed the IL-6-induced CYP3A downregulation. Furthermore, the authors suggest that downregulation of PXR by inflammatory stimuli is causative for decreased transcription of CYP3A4: a continuous decrease in PXR levels was observed already after 1.5 h of treatment, whereas a significant decrease in CYP3A4 mRNA levels occurred only after 3 h. A likely scenario is that the suppressive effect of inflammation on PXR expression is mediated through NF-κB activation, since Zhou X et al. showed that NF-kB directly interacts with a functional binding site in the PXR promotor to suppress its transcriptional expression . Transcriptional downregulation of CAR upon inflammatory stimuli has also been reported. A study by Assenat et al. investigated the negative regulation of CAR via pro-inflammatory cytokines IL-1 β and LPS in human hepatocytes . IL-1 β treatment reduced mRNA levels of CYP2B6, CYP2C9, and CYP3A4 through NF-κB p65 activation. This p65 subunit of the NF-κB complex interfered with the distal glucocorticoid response element present in the CAR promotor, leading to repressed transcription of CAR. In contrast, the AhR is not substantially affected by IL-6 treatment . As such, it appears that the response to inflammation is substantial for PXR and CAR and their dimerization partner RXR, but not for AhR. Still, some debate remains about the role of nuclear receptors in the downregulation of CYP enzymes during inflammation, mostly stemming from conflicting rodent vs. human studies. In the rodent field, a study by Beigneux et al. suggested that downregulation of PXR and CAR was causative for CYP450 downregulation , whereas other experiments suggest that downregulation of important P450 enzymes does not necessitate the nuclear receptor PXR. As an example, Richardson et al. found that downregulation of multiple CYP mRNAs was similar in LPS-treated control and PXR-null mice, suggesting a PXR independent mechanism . For the human situation, transcription factors responsible for the homeostasis of CYPs are evidently downregulated through inflammation. However, up to what extent downregulation of these transcription factors can actually be held responsible for the inflammation driven changes in expression of DMEs and drug metabolism itself remains to be further investigated. 3.1.2. Downregulation of Hepatocyte Nuclear Factors Hepatocyte nuclear factors (HNFs), including HNF-1α and HNF-4 α , form another important family of transcription factors. They can modulate CYP expression in the liver through DNA-binding interactions in CYP promotors or via modulation of PXR and CAR expression . Despite their well-documented role in CYP homeostasis, the contribution of HNFs for the inflammation-induced changes in CYP expression remain, however, scarcely investigated. The binding activities of HNF-1 α and HNF-4 α to DNA were quickly reduced in rat livers treated with LPS in parallel with downregulated hepatic CYP mRNA levels . In HepG2 cells, treatment with IL-6 and IL-1 β resulted in a 10% decrease of HNF-4 α activity as a result of an altered phosphorylation status . Acute and prolonged treatment with IL-6 reduced mRNA levels of HNF-4a in HepaRG cells, but this effect was not seen for HNF-1a and the changes shrink into insignificance compared to the observed downregulation of, e.g., PXR . In contrast, Klein et al. found that mRNA levels of the HNF-4 α were downregulated (≈40%) by IL-6 only at the early time point of 8 h and seemed to have normalized after 24 h . However, a direct link between the fast transcriptional suppression of P450 genes and the reduced mRNA levels/activity of HNFs is still lacking, questioning a prominent role of transcriptional HNF downregulation as a factor in IL-6-induced DME suppression. 3.2. Interference with Dimerization/Nuclear Translocation of (Nuclear) Transcription Factors Impairment of the activity of important transcription factors could, in addition to the above described transcriptional repression of transcription factors, also contribute to repression of CYPs during inflammation. Tanner et al. questioned whether transcriptional downregulation of PXR and CAR mRNA levels itself can fully explain the observed downregulation of CYP enzymes . They suggested that the transactivation potential of PXR and CAR might be simultaneously influenced by inflammation. They found a clear correlation between downregulated PXR and CYP mRNA levels after short-term treatment with IL-6. However, the reduction in PXR expression following prolonged treatment (14-days) with IL-6 was very modest compared to the downregulation observed for the CYP enzymes. As such, downregulation of nuclear receptor target genes (e.g., CYPs) during inflammation could be a consequence of decreased availability of PXR itself, or an impairment of the translocation/activity of the receptor. The existence for such interactions between inflammation and hepatic transcription factors (PXR, CAR, and AhR) have been suggested for both the NF-κB pathway and pathways related to IL-6 signaling. A hypothesized mechanism for this is interference of NF-κB with the dimerization of PXR to RXR and subsequent binding to DNA, thereby inhibiting the activity of PXR. The inhibited transcriptional activity of PXR leads to downregulation of DMEs in HepG2 cells . As NF-κB interferes with the binding of RXR to PXR, this mechanism of repression by NF-κB may also hold true for more nuclear receptor-controlled systems where RXR is the dimerization partner (e.g., CAR), but no experimental evidence exists that can yet support this. AhR-regulated CYP1A2 is likely not regulated by this mechanism. Studies in mouse hepatoma cells have shown that interactions between the P65 subunit of NF-κB and AhR may result in the formation of an inactive complex, with possible consequences for the translocation to the nucleus . In addition, NF-κB has been shown to inhibit transcriptional activity of AhR by reducing histone acetylation of promotors of CYP enzymes (e.g., CYP1A2), thereby altering the accessibility of the DNA for nuclear transcription factors . Thus, activation of the NF-κB pathway may modulate the activity of nuclear transcription factors through changes in dimerization, translocation, or chromatin remodeling. Kinases involved in the IL-6 signaling pathway can also alter the protein status and translocation of nuclear receptors. Cell signaling protein kinases such as Jun-N-terminal kinase (JNK) and protein kinase C (PKC) can repress the activity of the nuclear receptors PXR and CAR, thereby altering their function and impact on downstream transcriptional CYP activity . One hypothesized mechanism is that kinases can alter the phosphorylation status of these nuclear receptor proteins. IL-1β treatment induces JNK expression which can phosphorylate RXR, leading to reduced nuclear binding activity and subsequently inhibited RXR-dependent hepatic gene expression . Additionally, LPS-induced downregulation of P450 genes was attenuated upon treatment with a specific JNK inhibitor in a primary mouse hepatocyte model . Thus, JNK can play a role in inflammation-mediated downregulation of nuclear receptors with RXR as partner. This was backed up by findings from Ghose et al., who showed that an increase in JNK signaling is associated with higher export of RXR out of the nucleus upon low-dose LPS treatment, leading to less RXR-mediated hepatic gene expression . Additionally, ERK signaling has been proven to impair nuclear translocation of CAR in a mouse primary hepatocyte model . Altogether, these findings indicate that kinases play an important role in the regulation of nuclear receptors and their dimerization with RXR, thereby offering a general mechanism for the suppression of genes regulated by nuclear receptors during inflammation. How other important inflammatory cell-signaling components in the IL-6 pathway, such as STAT3, mechanistically regulate CYP repression remains to be investigated. 3.3. Direct Regulation by NF-κB NF-κB can precisely control the expression of CYP1A1, CYP2B1, CYP2C11, CYP2D5, CYP2E1, and CYP3A7 via interaction with the promotors of these genes, leading to downregulation in most cases . For example, Iber et al. reported that the CYP2C11 promotor region contains a low-affinity binding place for NF-κB and mutations in the 3′-end or 5′-end in this NF-κB response element reduced the binding affinity for NF-κB and subsequently suppressed CYP2C11 transcription by IL-1 or LPS in rat hepatocytes . However, experimental evidence for this hypothesis has only been obtained in animal models. Although there is high conservation of CYP enzymes amongst species, the extent and catalytic activity between species differs, highlighting that caution should be taken in extrapolation of results to a human situation . 3.4. Altered Liver-Enriched C/EBP Signaling The expression and DNA binding activity of the transcription factor C/EBPβ is severely enhanced during the acute phase liver response through activation of the NF-κB pathway . One mechanism that is hypothesized to contribute to CYP repression upon IL-6 stimulation is altered balance between two isoforms of the transcription factor C/EBP-β: the liver-enriched transcriptional activating protein (LAP) and the liver-enriched transcriptional inhibitory protein (LIP). The LIP isoform is a shortened variant of C/EBPβ deficient of transactivation activity. Jover et al. found upregulation of the C/EBPβ-LIP protein isoform in HepG2 cells treated with IL-6 . They demonstrated that LIP antagonized transactivation of CYP3A4 by the functional LAP isoform. This altered LAP:LIP ratio correlated with a downregulation of CYP3A4 enzyme levels. Martinez et al. showed a novel enhancer site located in the CYP3A4 gene where the LAP isoform can bind and initiate transcription, whereas the antagonizing action of the truncated LIP isoform on LAP resulted in CYP3A4 gene repression, confirming that the LAP:LIP ratio is of importance in regulation of constitutive expression of CYP3A4 . A C/EBPβ-based mechanism was also found to be involved in transcriptional repression of CYP2A6 . It is yet to be determined whether this mechanism can also explain repression of other CYPs upon IL-6 stimulation in a human model. 3.5. Posttranscriptional Mechanisms (miRNA) The mechanisms behind downregulation of DMEs upon inflammation, as described above, remain an area of intense study. Increasing attention is being given to the potential post-transcriptional mechanisms that could regulate P450 enzymes in inflammation as well. MicroRNAs (miRNAs) can influence the translation and stability of cellular mRNAs at their 3′-UTR side, offering a broad mechanism for gene expression regulation . Previous research has already shown that miRNA activity regulates phase I and II metabolizing enzymes and transcriptional factors through posttranscriptional modification . A recent study by Kugler et al. questions whether the previously observed mechanisms are sufficient to explain the huge downregulation of DMEs observed upon inflammation and investigated the possible role of miRNA in this process . They performed transfections with five inflammation-associated miRNAs in HepaRG cells and looked at the CYP mRNA levels and activity. They found miRNA-dependent downregulation of several CYP mRNA and expression levels after 96 h, where CYP2C19 and CYP3A4 were amongst the top downregulated genes. Thus, miRNAs might be an extra factor in downregulating drug metabolizing capacity during inflammation. Potentially, this could also explain the sometimes observed mismatch between CYP mRNA levels and CYP protein levels after inflammatory stimuli, as was the case for CYP2C9 in the study from Aitken et al. . Since the 3′-UTR region of CYP2C9 can directly be regulated by miR-130b, this could explain the downregulation of CYP2C9 enzyme expression. As such, miRNA regulation could (in part) be responsible for the effects of inflammatory mediators on protein levels in the absence of preceding downregulation of mRNA. Other post-transcriptional mechanisms, such as the role of nitric oxide in the cytokine-mediated regulation of CYPs were excellently reviewed by Morgan et al. . 3.6. Concluding Remark Concluding from previous sections, we hypothesize that the variation in sensitivity of different CYP enzymes for inflammation stems from the distinct mechanisms that regulate them. It seems like PXR- and CAR-regulated CYP enzymes (3A4/5, 2C9, 2C19) are more sensitive to inflammation, whereas the AhR regulated isoform CYP1A2 is less sensitive. CYP2D6 shows to be least sensitive to inflammation, which might be due to the fact that it is not inducible by nuclear receptors and therefore not sensitive to inflammation-induced alterations of the levels of PXR, CAR, and AhR that regulate the expression of other CYPs . Most interestingly, deduction of CYP specific inflammatory mechanisms of downregulation can shed light on the distinct sensitivities towards inflammation.
Transcription factors involved in the regulation of CYP mRNA levels, including the nuclear receptors pregnane X receptor (PXR), the constitutive androstane receptor (CAR), their dimerization partner retinoid X receptor (RXR), the aryl hydrocarbon receptor (AhR), as well as human nuclear factors (HNFs) are held responsible for the observed downregulation of DMEs upon inflammation. It is important to distinguish between the role of nuclear transcription factors in the constitutive expression of CYP enzymes versus drug- or inflammation-mediated expression. Here we will focus on the nuclear hormone receptor mechanisms likely to be involved in inflammation-altered CYP expression. 3.1.1. Downregulation of Nuclear Receptors The PXR (gene: NR1I2 ) and the CAR (gene: NR1I3 ) are members of the nuclear receptor superfamily highly expressed in the enterohepatic system of mammals . These ligand activated transcription factors have been identified as key transcriptional regulators of the cytochrome P450 xenobiotic-metabolizing enzymes, mostly for the CYP2C9, CYP2C19, CYP3A4, and CYP3A5 enzyme expression . Upon binding with the RXR, the heterodimer nuclear receptor-RXR complex binds to responsive elements present in the 5′-flanking regions of target genes, usually resulting in an upregulation of gene expression aimed at increased metabolism of drugs. Studies have indeed shown that PXR and CAR increase transcription of the human CYP3A4/5, CYP2C9, CYP2C19, and CYP1A2 genes upon drug treatment . One mechanism by which inflammation changes gene transcription of major DMEs is through repression of the nuclear receptor PXR and CAR. A vast body of evidence shows that inflammation represses PXR levels, leading to downregulation of important CYP enzymes. Pascussi et al. pioneered in showing that IL-6 downregulates PXR mRNA in PHH and inhibits the rifampicine-induced induction of CYP3A4 . Upon LPS treatment in HepG2 cells, the mRNA and protein levels of PXR are reduced . Mechanistically, a decrease in PXR expression within the nucleus was observed, leading to reduced transactivation of the CYP3A4 promotor and subsequent inhibited transcriptional activity of CYP3A4. Additionally, LPS treatment in mice led to functional repression of PXR’s dimerization partner RXR . Yang et al. showed that inhibition of a CYP3A4 promotor reporter after IL-6 treatment in human hepatocytes was greater in the presence of PXR than after its knockdown, suggesting a role for PXR in IL-6-facilitated suppression of CYP3A4 . Knockdown of PXR in human hepatocytes reversed the IL-6-induced CYP3A downregulation. Furthermore, the authors suggest that downregulation of PXR by inflammatory stimuli is causative for decreased transcription of CYP3A4: a continuous decrease in PXR levels was observed already after 1.5 h of treatment, whereas a significant decrease in CYP3A4 mRNA levels occurred only after 3 h. A likely scenario is that the suppressive effect of inflammation on PXR expression is mediated through NF-κB activation, since Zhou X et al. showed that NF-kB directly interacts with a functional binding site in the PXR promotor to suppress its transcriptional expression . Transcriptional downregulation of CAR upon inflammatory stimuli has also been reported. A study by Assenat et al. investigated the negative regulation of CAR via pro-inflammatory cytokines IL-1 β and LPS in human hepatocytes . IL-1 β treatment reduced mRNA levels of CYP2B6, CYP2C9, and CYP3A4 through NF-κB p65 activation. This p65 subunit of the NF-κB complex interfered with the distal glucocorticoid response element present in the CAR promotor, leading to repressed transcription of CAR. In contrast, the AhR is not substantially affected by IL-6 treatment . As such, it appears that the response to inflammation is substantial for PXR and CAR and their dimerization partner RXR, but not for AhR. Still, some debate remains about the role of nuclear receptors in the downregulation of CYP enzymes during inflammation, mostly stemming from conflicting rodent vs. human studies. In the rodent field, a study by Beigneux et al. suggested that downregulation of PXR and CAR was causative for CYP450 downregulation , whereas other experiments suggest that downregulation of important P450 enzymes does not necessitate the nuclear receptor PXR. As an example, Richardson et al. found that downregulation of multiple CYP mRNAs was similar in LPS-treated control and PXR-null mice, suggesting a PXR independent mechanism . For the human situation, transcription factors responsible for the homeostasis of CYPs are evidently downregulated through inflammation. However, up to what extent downregulation of these transcription factors can actually be held responsible for the inflammation driven changes in expression of DMEs and drug metabolism itself remains to be further investigated. 3.1.2. Downregulation of Hepatocyte Nuclear Factors Hepatocyte nuclear factors (HNFs), including HNF-1α and HNF-4 α , form another important family of transcription factors. They can modulate CYP expression in the liver through DNA-binding interactions in CYP promotors or via modulation of PXR and CAR expression . Despite their well-documented role in CYP homeostasis, the contribution of HNFs for the inflammation-induced changes in CYP expression remain, however, scarcely investigated. The binding activities of HNF-1 α and HNF-4 α to DNA were quickly reduced in rat livers treated with LPS in parallel with downregulated hepatic CYP mRNA levels . In HepG2 cells, treatment with IL-6 and IL-1 β resulted in a 10% decrease of HNF-4 α activity as a result of an altered phosphorylation status . Acute and prolonged treatment with IL-6 reduced mRNA levels of HNF-4a in HepaRG cells, but this effect was not seen for HNF-1a and the changes shrink into insignificance compared to the observed downregulation of, e.g., PXR . In contrast, Klein et al. found that mRNA levels of the HNF-4 α were downregulated (≈40%) by IL-6 only at the early time point of 8 h and seemed to have normalized after 24 h . However, a direct link between the fast transcriptional suppression of P450 genes and the reduced mRNA levels/activity of HNFs is still lacking, questioning a prominent role of transcriptional HNF downregulation as a factor in IL-6-induced DME suppression.
The PXR (gene: NR1I2 ) and the CAR (gene: NR1I3 ) are members of the nuclear receptor superfamily highly expressed in the enterohepatic system of mammals . These ligand activated transcription factors have been identified as key transcriptional regulators of the cytochrome P450 xenobiotic-metabolizing enzymes, mostly for the CYP2C9, CYP2C19, CYP3A4, and CYP3A5 enzyme expression . Upon binding with the RXR, the heterodimer nuclear receptor-RXR complex binds to responsive elements present in the 5′-flanking regions of target genes, usually resulting in an upregulation of gene expression aimed at increased metabolism of drugs. Studies have indeed shown that PXR and CAR increase transcription of the human CYP3A4/5, CYP2C9, CYP2C19, and CYP1A2 genes upon drug treatment . One mechanism by which inflammation changes gene transcription of major DMEs is through repression of the nuclear receptor PXR and CAR. A vast body of evidence shows that inflammation represses PXR levels, leading to downregulation of important CYP enzymes. Pascussi et al. pioneered in showing that IL-6 downregulates PXR mRNA in PHH and inhibits the rifampicine-induced induction of CYP3A4 . Upon LPS treatment in HepG2 cells, the mRNA and protein levels of PXR are reduced . Mechanistically, a decrease in PXR expression within the nucleus was observed, leading to reduced transactivation of the CYP3A4 promotor and subsequent inhibited transcriptional activity of CYP3A4. Additionally, LPS treatment in mice led to functional repression of PXR’s dimerization partner RXR . Yang et al. showed that inhibition of a CYP3A4 promotor reporter after IL-6 treatment in human hepatocytes was greater in the presence of PXR than after its knockdown, suggesting a role for PXR in IL-6-facilitated suppression of CYP3A4 . Knockdown of PXR in human hepatocytes reversed the IL-6-induced CYP3A downregulation. Furthermore, the authors suggest that downregulation of PXR by inflammatory stimuli is causative for decreased transcription of CYP3A4: a continuous decrease in PXR levels was observed already after 1.5 h of treatment, whereas a significant decrease in CYP3A4 mRNA levels occurred only after 3 h. A likely scenario is that the suppressive effect of inflammation on PXR expression is mediated through NF-κB activation, since Zhou X et al. showed that NF-kB directly interacts with a functional binding site in the PXR promotor to suppress its transcriptional expression . Transcriptional downregulation of CAR upon inflammatory stimuli has also been reported. A study by Assenat et al. investigated the negative regulation of CAR via pro-inflammatory cytokines IL-1 β and LPS in human hepatocytes . IL-1 β treatment reduced mRNA levels of CYP2B6, CYP2C9, and CYP3A4 through NF-κB p65 activation. This p65 subunit of the NF-κB complex interfered with the distal glucocorticoid response element present in the CAR promotor, leading to repressed transcription of CAR. In contrast, the AhR is not substantially affected by IL-6 treatment . As such, it appears that the response to inflammation is substantial for PXR and CAR and their dimerization partner RXR, but not for AhR. Still, some debate remains about the role of nuclear receptors in the downregulation of CYP enzymes during inflammation, mostly stemming from conflicting rodent vs. human studies. In the rodent field, a study by Beigneux et al. suggested that downregulation of PXR and CAR was causative for CYP450 downregulation , whereas other experiments suggest that downregulation of important P450 enzymes does not necessitate the nuclear receptor PXR. As an example, Richardson et al. found that downregulation of multiple CYP mRNAs was similar in LPS-treated control and PXR-null mice, suggesting a PXR independent mechanism . For the human situation, transcription factors responsible for the homeostasis of CYPs are evidently downregulated through inflammation. However, up to what extent downregulation of these transcription factors can actually be held responsible for the inflammation driven changes in expression of DMEs and drug metabolism itself remains to be further investigated.
Hepatocyte nuclear factors (HNFs), including HNF-1α and HNF-4 α , form another important family of transcription factors. They can modulate CYP expression in the liver through DNA-binding interactions in CYP promotors or via modulation of PXR and CAR expression . Despite their well-documented role in CYP homeostasis, the contribution of HNFs for the inflammation-induced changes in CYP expression remain, however, scarcely investigated. The binding activities of HNF-1 α and HNF-4 α to DNA were quickly reduced in rat livers treated with LPS in parallel with downregulated hepatic CYP mRNA levels . In HepG2 cells, treatment with IL-6 and IL-1 β resulted in a 10% decrease of HNF-4 α activity as a result of an altered phosphorylation status . Acute and prolonged treatment with IL-6 reduced mRNA levels of HNF-4a in HepaRG cells, but this effect was not seen for HNF-1a and the changes shrink into insignificance compared to the observed downregulation of, e.g., PXR . In contrast, Klein et al. found that mRNA levels of the HNF-4 α were downregulated (≈40%) by IL-6 only at the early time point of 8 h and seemed to have normalized after 24 h . However, a direct link between the fast transcriptional suppression of P450 genes and the reduced mRNA levels/activity of HNFs is still lacking, questioning a prominent role of transcriptional HNF downregulation as a factor in IL-6-induced DME suppression.
Impairment of the activity of important transcription factors could, in addition to the above described transcriptional repression of transcription factors, also contribute to repression of CYPs during inflammation. Tanner et al. questioned whether transcriptional downregulation of PXR and CAR mRNA levels itself can fully explain the observed downregulation of CYP enzymes . They suggested that the transactivation potential of PXR and CAR might be simultaneously influenced by inflammation. They found a clear correlation between downregulated PXR and CYP mRNA levels after short-term treatment with IL-6. However, the reduction in PXR expression following prolonged treatment (14-days) with IL-6 was very modest compared to the downregulation observed for the CYP enzymes. As such, downregulation of nuclear receptor target genes (e.g., CYPs) during inflammation could be a consequence of decreased availability of PXR itself, or an impairment of the translocation/activity of the receptor. The existence for such interactions between inflammation and hepatic transcription factors (PXR, CAR, and AhR) have been suggested for both the NF-κB pathway and pathways related to IL-6 signaling. A hypothesized mechanism for this is interference of NF-κB with the dimerization of PXR to RXR and subsequent binding to DNA, thereby inhibiting the activity of PXR. The inhibited transcriptional activity of PXR leads to downregulation of DMEs in HepG2 cells . As NF-κB interferes with the binding of RXR to PXR, this mechanism of repression by NF-κB may also hold true for more nuclear receptor-controlled systems where RXR is the dimerization partner (e.g., CAR), but no experimental evidence exists that can yet support this. AhR-regulated CYP1A2 is likely not regulated by this mechanism. Studies in mouse hepatoma cells have shown that interactions between the P65 subunit of NF-κB and AhR may result in the formation of an inactive complex, with possible consequences for the translocation to the nucleus . In addition, NF-κB has been shown to inhibit transcriptional activity of AhR by reducing histone acetylation of promotors of CYP enzymes (e.g., CYP1A2), thereby altering the accessibility of the DNA for nuclear transcription factors . Thus, activation of the NF-κB pathway may modulate the activity of nuclear transcription factors through changes in dimerization, translocation, or chromatin remodeling. Kinases involved in the IL-6 signaling pathway can also alter the protein status and translocation of nuclear receptors. Cell signaling protein kinases such as Jun-N-terminal kinase (JNK) and protein kinase C (PKC) can repress the activity of the nuclear receptors PXR and CAR, thereby altering their function and impact on downstream transcriptional CYP activity . One hypothesized mechanism is that kinases can alter the phosphorylation status of these nuclear receptor proteins. IL-1β treatment induces JNK expression which can phosphorylate RXR, leading to reduced nuclear binding activity and subsequently inhibited RXR-dependent hepatic gene expression . Additionally, LPS-induced downregulation of P450 genes was attenuated upon treatment with a specific JNK inhibitor in a primary mouse hepatocyte model . Thus, JNK can play a role in inflammation-mediated downregulation of nuclear receptors with RXR as partner. This was backed up by findings from Ghose et al., who showed that an increase in JNK signaling is associated with higher export of RXR out of the nucleus upon low-dose LPS treatment, leading to less RXR-mediated hepatic gene expression . Additionally, ERK signaling has been proven to impair nuclear translocation of CAR in a mouse primary hepatocyte model . Altogether, these findings indicate that kinases play an important role in the regulation of nuclear receptors and their dimerization with RXR, thereby offering a general mechanism for the suppression of genes regulated by nuclear receptors during inflammation. How other important inflammatory cell-signaling components in the IL-6 pathway, such as STAT3, mechanistically regulate CYP repression remains to be investigated.
NF-κB can precisely control the expression of CYP1A1, CYP2B1, CYP2C11, CYP2D5, CYP2E1, and CYP3A7 via interaction with the promotors of these genes, leading to downregulation in most cases . For example, Iber et al. reported that the CYP2C11 promotor region contains a low-affinity binding place for NF-κB and mutations in the 3′-end or 5′-end in this NF-κB response element reduced the binding affinity for NF-κB and subsequently suppressed CYP2C11 transcription by IL-1 or LPS in rat hepatocytes . However, experimental evidence for this hypothesis has only been obtained in animal models. Although there is high conservation of CYP enzymes amongst species, the extent and catalytic activity between species differs, highlighting that caution should be taken in extrapolation of results to a human situation .
The expression and DNA binding activity of the transcription factor C/EBPβ is severely enhanced during the acute phase liver response through activation of the NF-κB pathway . One mechanism that is hypothesized to contribute to CYP repression upon IL-6 stimulation is altered balance between two isoforms of the transcription factor C/EBP-β: the liver-enriched transcriptional activating protein (LAP) and the liver-enriched transcriptional inhibitory protein (LIP). The LIP isoform is a shortened variant of C/EBPβ deficient of transactivation activity. Jover et al. found upregulation of the C/EBPβ-LIP protein isoform in HepG2 cells treated with IL-6 . They demonstrated that LIP antagonized transactivation of CYP3A4 by the functional LAP isoform. This altered LAP:LIP ratio correlated with a downregulation of CYP3A4 enzyme levels. Martinez et al. showed a novel enhancer site located in the CYP3A4 gene where the LAP isoform can bind and initiate transcription, whereas the antagonizing action of the truncated LIP isoform on LAP resulted in CYP3A4 gene repression, confirming that the LAP:LIP ratio is of importance in regulation of constitutive expression of CYP3A4 . A C/EBPβ-based mechanism was also found to be involved in transcriptional repression of CYP2A6 . It is yet to be determined whether this mechanism can also explain repression of other CYPs upon IL-6 stimulation in a human model.
The mechanisms behind downregulation of DMEs upon inflammation, as described above, remain an area of intense study. Increasing attention is being given to the potential post-transcriptional mechanisms that could regulate P450 enzymes in inflammation as well. MicroRNAs (miRNAs) can influence the translation and stability of cellular mRNAs at their 3′-UTR side, offering a broad mechanism for gene expression regulation . Previous research has already shown that miRNA activity regulates phase I and II metabolizing enzymes and transcriptional factors through posttranscriptional modification . A recent study by Kugler et al. questions whether the previously observed mechanisms are sufficient to explain the huge downregulation of DMEs observed upon inflammation and investigated the possible role of miRNA in this process . They performed transfections with five inflammation-associated miRNAs in HepaRG cells and looked at the CYP mRNA levels and activity. They found miRNA-dependent downregulation of several CYP mRNA and expression levels after 96 h, where CYP2C19 and CYP3A4 were amongst the top downregulated genes. Thus, miRNAs might be an extra factor in downregulating drug metabolizing capacity during inflammation. Potentially, this could also explain the sometimes observed mismatch between CYP mRNA levels and CYP protein levels after inflammatory stimuli, as was the case for CYP2C9 in the study from Aitken et al. . Since the 3′-UTR region of CYP2C9 can directly be regulated by miR-130b, this could explain the downregulation of CYP2C9 enzyme expression. As such, miRNA regulation could (in part) be responsible for the effects of inflammatory mediators on protein levels in the absence of preceding downregulation of mRNA. Other post-transcriptional mechanisms, such as the role of nitric oxide in the cytokine-mediated regulation of CYPs were excellently reviewed by Morgan et al. .
Concluding from previous sections, we hypothesize that the variation in sensitivity of different CYP enzymes for inflammation stems from the distinct mechanisms that regulate them. It seems like PXR- and CAR-regulated CYP enzymes (3A4/5, 2C9, 2C19) are more sensitive to inflammation, whereas the AhR regulated isoform CYP1A2 is less sensitive. CYP2D6 shows to be least sensitive to inflammation, which might be due to the fact that it is not inducible by nuclear receptors and therefore not sensitive to inflammation-induced alterations of the levels of PXR, CAR, and AhR that regulate the expression of other CYPs . Most interestingly, deduction of CYP specific inflammatory mechanisms of downregulation can shed light on the distinct sensitivities towards inflammation.
The available data from in-vitro experiments with PHHs on drug metabolism have indicated that the response to inflammation or its inflammatory mediators may differ substantially between donors under controlled experimental conditions . This raises the question whether the observed distinct response to inflammation between persons is also observed in the clinic. Clinical studies by van Wanrooy et al. and Vet et al. have shown that the metabolism of voriconazole and midazolam at similar concentrations of CRP and corrected for other known confounding factors may still vary considerably between patients . These findings from both in-vitro models and clinical studies suggests the existence of interindividual variability with regards to the effects of inflammation on drug metabolism. This distinct response towards inflammation between subjects may in part be caused by genetic variability in the described pathways via which inflammation modulates the activity of DMEs. By presenting examples from the available literature we illustrate how genetic variability within the different elements presented in can modulate the outcomes of the effect of inflammation on drug metabolism and consequently may contribute to the observed interindividual variability in the effect of inflammation. 4.1. Genetic Variation: Inflammatory Mediators It is well established that genetic variability within inflammatory mediators (e.g., cytokines) can predispose individuals to an altered susceptibility to immune-related disease . For this reason, it is plausible that polymorphisms in cytokine genes could shape the immune response that affects drug metabolism. One prominent example relates to the rs1946518 (-607C/A) variant within the promoter of IL-18 and its effects on the metabolism of the immunosuppressive tacrolimus. Xing et al. and Zhang et al. demonstrated that Han-Chinese patients carrying the AA genotype (19–29% of the patients) exhibited lower concentration/dose (C/D) ratios of tacrolimus within the first month after lung or kidney transplantation than patients with an AC or CC genotype . Interestingly, this relationship for the rs1946518 variant was exclusively shown for patients expressing CYP3A5*1 and functionally linked to lower expression of IL-18 mRNA in the liver. These results imply that the rs1946518 variant reduced the IL-18 driven inflammation in the liver, which prevents the inflammation-induced downregulation of CYP3A5 and consequently reduces the impact of inflammation on drug metabolism in these patients. Importantly, rs1946518 did not modulate C/D ratios in liver transplant patients who were already treated for 1 year with tacrolimus . These results suggest that the variant only affects drug metabolism shortly after transplantation when the immune/inflammatory responses are highest. Altogether, this example illustrates that genetic variability within inflammatory mediators has the potential to modulate the effects of inflammation on drug metabolism. 4.2. Genetic Variation: Inflammatory Receptors As described above, toll-like receptor (TLR) activation by pathogen-associated molecules may downregulate CYP3A4 expression and modulate drug metabolism. However, TLR activation may also be triggered by endogenous molecules (e.g., DNA) that are released during ischemia-reperfusion injury that develops during organ transplantations . Therefore, it has been postulated that genetic variability in TLRs may alter the effect of inflammation and its consequences for drug metabolism. Ou et al. showed that liver transplant patients with the TLR9-rs352139 AA genotype exhibited lower C/D tacrolimus levels than carriers of the AG/GG genotype . Subsequent cellular experiments provided functional support for these observations and demonstrated that the TLR9-rs352139 variant impaired TLR9 expression and consequently reduced NF-κB activation. TLR9-rs352139 AA genotype carriers were thus protected from the effects of ischemia-reperfusion-induced inflammation, which resulted in conservation of their metabolic capacity. The opposite effect was observed for carriers of the TLR4-rs1927907-GG phenotype who exhibited higher tacrolimus C/D ratios than AA/AG carriers, indicating that these patients were more susceptible to the effects of inflammation on their drug-metabolizing capacity . These studies illustrate that genetic variants in receptors can be important modulators of inflammation, which may be particularly relevant for receptors (e.g., IL6R or IL-1R) that are directly involved in the downregulation of CYP enzymes, but this remains to be investigated. 4.3. Genetic Variation: Inflammatory Transcription Factors (NF-κB) Genetic variability within NF-κB is of great interest given its essential role in inflammatory signaling . One common polymorphism in the NFKB1 gene is the promotor -94 ATTG insertion/deletion mutation (rs28362491), with a minor allele frequency of 0.43. Deletion of the ATTG alleles is shown to reduce synthesis of the NF-κB p50 subunit . Zhang et al. showed that patients with the NFKB1 -94 ATTG ins/ins genotype had higher CYP3A4-metabolized dose-adjusted cyclosporine trough concentrations than patients with the -94 ATTG del/del genotype . The impact of the same polymorphism in NFKB1 on the pharmacokinetics of lovastatin, a cholesterol-lowering drug mainly metabolized by CYP3A4, was also investigated . In accordance, the area under the plasma concentration–time curve (AUC) of the metabolite lovastatin lactone was twofold higher in subjects with two copies of the NFKB1 -94 ATTG ins/ins mutation and the plasma clearance was lower as compared to the NFKB1 -94del/del genotype. The NFKB1 -94del/del mutation may thus impair inflammatory signaling and hence attenuate the inflammation-induced downregulation of CYP3A4. Consequently, patients with the NFKB1 -94del/del genotype may perceive milder consequences of inflammation on drug metabolism than people lacking this variant. Since NF-κB is a downstream effector molecule of several inflammatory cytokines, genetic variability has the potential to simultaneously alter the actions of multiple inflammatory mediators on CYP gene expression. The potential impact of genetic variability within NF-κB or within the genes of NF-κB adaptor proteins on the effects of inflammation on drug metabolism is therefore predicted to be greater than genetic variability in the receptors or the mediators themselves. 4.4. Genetic Variation: Nuclear Receptors (PXR, CAR) The nuclear receptors PXR and CAR are, as highlighted earlier, important for the transcriptional regulation of CYP450 enzymes. Pharmacogenetic variations within the genes encoding PXR ( NR1I2 ) or CAR ( NR1I3 ) has therefore been thoroughly investigated in relation to their effects on pharmacokinetics and efficacy of drug treatments, as reviewed comprehensively by Mbatchi et al. . However, the influence of genetic variants within NR1I2 or NR1I3 has primarily been linked to homeostatic regulation of CYP expression in the absence of inflammation. Until now, it remains therefore largely unclear which genetic polymorphisms in NR1I2 or NR1I3 might be candidates for modulating the effects of inflammation on drug metabolism. Since PXR is regulated by NF-κB, either through direct transcriptional repression or via interference with RXR-PXR binding, we hypothesize that polymorphisms within NR1I2 that present themselves in or near NF-κB binding sites might influence the impact of inflammation on drug metabolism . For this reason we used the computational databases “gene transcription regulation database” (GTRD) and “Alggen PROMO database” for identification of polymorphisms in NR1I2 that would be susceptible to the effects of inflammation . Using information on confirmed NF-κB binding sites by chromatin immunoprecipitation-sequencing (CHIP-seq) or predicted NF-κB binding spots, we were able to identify four common variants (minor-allele frequency > 0.01) in NR1I2 that are located in or near NF-κB binding spots, as summarized in . Importantly, the variant NR1I2 -rs3814055 that has initially been linked to a NF-κB binding site was not confirmed by this approach, which is in accordance with observations from Dring et al. who also did not find evidence for a NF-κB binding site positioned at the rs2814055 location . The effects on drug metabolism of these four genetic variants in the NF-kB binding spots in NR1I2 are sparsely reported in the literature. This may suggest that these variants contribute less than other common SNPs within NR1I2 (e.g., rs3814055, rs2472677) to the variability of drug metabolism in the absence of inflammation. However, some data is available from studies conducted in cancer patients. Inflammatory reactions are frequently observed in cancer patients and a common cause of phenoconversion . Interestingly, in a cohort of 109 patients with colon cancer, the “inflammatory” variant NR1I2 rs10934498 (G > A) was identified, from a panel of NR1I2 variants, as one of the main determinants of Irinotecan pharmacokinetics . Irinotecan is a prodrug that is converted into its active metabolite SN-38 and subsequently detoxified into SN-38G. Patient with the rs10934498 AA genotype exhibited reduced SN-38 AUC levels and increased metabolic ratios of SN-38G compared to AG or GG carriers, which indicates that the metabolism of Irinotecan is more conserved in patients with the rs10934498 AA genotype. Based on our observation that rs10934498 is located in an NF-κB binding site, we hypothesize that PXR may no longer be downregulated by inflammation in patients carrying the rs10934498 AA genotype, resulting in a conserved drug-metabolizing activity compared to patients lacking this variant. Altogether, the computational identification of common “inflammatory” variants within NR1I2 suggest that genetic variability may modulate PXR-dependent outcomes of inflammatory signaling. However, further (functional) studies are needed to elucidate the impact of these NR1I2 polymorphisms on drug metabolism in the context of inflammation. 4.5. Genetic Variation: Cytochrome P450 Enzymes Ultimately, the output of the inflammatory signaling cascade regulates CYP expression and subsequent drug metabolic capacity. Even though it is well established that genetic polymorphisms in CYP enzymes contribute to the interindividual variability in pharmacokinetics , it remains uncertain how and to what extent CYP polymorphisms may modulate the impact of inflammation on drug metabolism. Some studies hint towards a genotype-dependent effect of inflammation-induced phenoconversion, as summarized by Klomp et al. . CYP2C19 is highly polymorphic and shown to be affected by inflammation. For example, in a study of 34 patients with an invasive fungal infection receiving voriconazole, it was shown that the effect of inflammation was modulated by the CYP2C19 genotype: the metabolic ratio of voriconazole and its metabolite was more decreased by inflammation in CYP2C19 ultrarapid metabolizers compared to CYP2C19 intermediate metabolizers . Similarly, Ohnishi et al. aimed to investigate the consequences of inflammation for different CYP2C19 genotypes by examining the metabolic ratios of omeprazole and its metabolite in hepatitis C virus (HCV)-positive patients and healthy volunteers . The shift in metabolic ratio between healthy patients and HCV-positive patients was largest for genotype-predicted normal metabolizers (21.1-fold change), followed by intermediate metabolizers (12.4-fold change) and least evident for poor metabolizers. Although these examples only illustrate the effects of inflammation on CYP2C19 mediated drug metabolism, and other CYP isoforms remain to be investigated, they clearly indicate that inflammation-induced changes in CYP450-mediated drug metabolism are affected by an individual’s CYP metabolizer genotype.
It is well established that genetic variability within inflammatory mediators (e.g., cytokines) can predispose individuals to an altered susceptibility to immune-related disease . For this reason, it is plausible that polymorphisms in cytokine genes could shape the immune response that affects drug metabolism. One prominent example relates to the rs1946518 (-607C/A) variant within the promoter of IL-18 and its effects on the metabolism of the immunosuppressive tacrolimus. Xing et al. and Zhang et al. demonstrated that Han-Chinese patients carrying the AA genotype (19–29% of the patients) exhibited lower concentration/dose (C/D) ratios of tacrolimus within the first month after lung or kidney transplantation than patients with an AC or CC genotype . Interestingly, this relationship for the rs1946518 variant was exclusively shown for patients expressing CYP3A5*1 and functionally linked to lower expression of IL-18 mRNA in the liver. These results imply that the rs1946518 variant reduced the IL-18 driven inflammation in the liver, which prevents the inflammation-induced downregulation of CYP3A5 and consequently reduces the impact of inflammation on drug metabolism in these patients. Importantly, rs1946518 did not modulate C/D ratios in liver transplant patients who were already treated for 1 year with tacrolimus . These results suggest that the variant only affects drug metabolism shortly after transplantation when the immune/inflammatory responses are highest. Altogether, this example illustrates that genetic variability within inflammatory mediators has the potential to modulate the effects of inflammation on drug metabolism.
As described above, toll-like receptor (TLR) activation by pathogen-associated molecules may downregulate CYP3A4 expression and modulate drug metabolism. However, TLR activation may also be triggered by endogenous molecules (e.g., DNA) that are released during ischemia-reperfusion injury that develops during organ transplantations . Therefore, it has been postulated that genetic variability in TLRs may alter the effect of inflammation and its consequences for drug metabolism. Ou et al. showed that liver transplant patients with the TLR9-rs352139 AA genotype exhibited lower C/D tacrolimus levels than carriers of the AG/GG genotype . Subsequent cellular experiments provided functional support for these observations and demonstrated that the TLR9-rs352139 variant impaired TLR9 expression and consequently reduced NF-κB activation. TLR9-rs352139 AA genotype carriers were thus protected from the effects of ischemia-reperfusion-induced inflammation, which resulted in conservation of their metabolic capacity. The opposite effect was observed for carriers of the TLR4-rs1927907-GG phenotype who exhibited higher tacrolimus C/D ratios than AA/AG carriers, indicating that these patients were more susceptible to the effects of inflammation on their drug-metabolizing capacity . These studies illustrate that genetic variants in receptors can be important modulators of inflammation, which may be particularly relevant for receptors (e.g., IL6R or IL-1R) that are directly involved in the downregulation of CYP enzymes, but this remains to be investigated.
Genetic variability within NF-κB is of great interest given its essential role in inflammatory signaling . One common polymorphism in the NFKB1 gene is the promotor -94 ATTG insertion/deletion mutation (rs28362491), with a minor allele frequency of 0.43. Deletion of the ATTG alleles is shown to reduce synthesis of the NF-κB p50 subunit . Zhang et al. showed that patients with the NFKB1 -94 ATTG ins/ins genotype had higher CYP3A4-metabolized dose-adjusted cyclosporine trough concentrations than patients with the -94 ATTG del/del genotype . The impact of the same polymorphism in NFKB1 on the pharmacokinetics of lovastatin, a cholesterol-lowering drug mainly metabolized by CYP3A4, was also investigated . In accordance, the area under the plasma concentration–time curve (AUC) of the metabolite lovastatin lactone was twofold higher in subjects with two copies of the NFKB1 -94 ATTG ins/ins mutation and the plasma clearance was lower as compared to the NFKB1 -94del/del genotype. The NFKB1 -94del/del mutation may thus impair inflammatory signaling and hence attenuate the inflammation-induced downregulation of CYP3A4. Consequently, patients with the NFKB1 -94del/del genotype may perceive milder consequences of inflammation on drug metabolism than people lacking this variant. Since NF-κB is a downstream effector molecule of several inflammatory cytokines, genetic variability has the potential to simultaneously alter the actions of multiple inflammatory mediators on CYP gene expression. The potential impact of genetic variability within NF-κB or within the genes of NF-κB adaptor proteins on the effects of inflammation on drug metabolism is therefore predicted to be greater than genetic variability in the receptors or the mediators themselves.
The nuclear receptors PXR and CAR are, as highlighted earlier, important for the transcriptional regulation of CYP450 enzymes. Pharmacogenetic variations within the genes encoding PXR ( NR1I2 ) or CAR ( NR1I3 ) has therefore been thoroughly investigated in relation to their effects on pharmacokinetics and efficacy of drug treatments, as reviewed comprehensively by Mbatchi et al. . However, the influence of genetic variants within NR1I2 or NR1I3 has primarily been linked to homeostatic regulation of CYP expression in the absence of inflammation. Until now, it remains therefore largely unclear which genetic polymorphisms in NR1I2 or NR1I3 might be candidates for modulating the effects of inflammation on drug metabolism. Since PXR is regulated by NF-κB, either through direct transcriptional repression or via interference with RXR-PXR binding, we hypothesize that polymorphisms within NR1I2 that present themselves in or near NF-κB binding sites might influence the impact of inflammation on drug metabolism . For this reason we used the computational databases “gene transcription regulation database” (GTRD) and “Alggen PROMO database” for identification of polymorphisms in NR1I2 that would be susceptible to the effects of inflammation . Using information on confirmed NF-κB binding sites by chromatin immunoprecipitation-sequencing (CHIP-seq) or predicted NF-κB binding spots, we were able to identify four common variants (minor-allele frequency > 0.01) in NR1I2 that are located in or near NF-κB binding spots, as summarized in . Importantly, the variant NR1I2 -rs3814055 that has initially been linked to a NF-κB binding site was not confirmed by this approach, which is in accordance with observations from Dring et al. who also did not find evidence for a NF-κB binding site positioned at the rs2814055 location . The effects on drug metabolism of these four genetic variants in the NF-kB binding spots in NR1I2 are sparsely reported in the literature. This may suggest that these variants contribute less than other common SNPs within NR1I2 (e.g., rs3814055, rs2472677) to the variability of drug metabolism in the absence of inflammation. However, some data is available from studies conducted in cancer patients. Inflammatory reactions are frequently observed in cancer patients and a common cause of phenoconversion . Interestingly, in a cohort of 109 patients with colon cancer, the “inflammatory” variant NR1I2 rs10934498 (G > A) was identified, from a panel of NR1I2 variants, as one of the main determinants of Irinotecan pharmacokinetics . Irinotecan is a prodrug that is converted into its active metabolite SN-38 and subsequently detoxified into SN-38G. Patient with the rs10934498 AA genotype exhibited reduced SN-38 AUC levels and increased metabolic ratios of SN-38G compared to AG or GG carriers, which indicates that the metabolism of Irinotecan is more conserved in patients with the rs10934498 AA genotype. Based on our observation that rs10934498 is located in an NF-κB binding site, we hypothesize that PXR may no longer be downregulated by inflammation in patients carrying the rs10934498 AA genotype, resulting in a conserved drug-metabolizing activity compared to patients lacking this variant. Altogether, the computational identification of common “inflammatory” variants within NR1I2 suggest that genetic variability may modulate PXR-dependent outcomes of inflammatory signaling. However, further (functional) studies are needed to elucidate the impact of these NR1I2 polymorphisms on drug metabolism in the context of inflammation.
Ultimately, the output of the inflammatory signaling cascade regulates CYP expression and subsequent drug metabolic capacity. Even though it is well established that genetic polymorphisms in CYP enzymes contribute to the interindividual variability in pharmacokinetics , it remains uncertain how and to what extent CYP polymorphisms may modulate the impact of inflammation on drug metabolism. Some studies hint towards a genotype-dependent effect of inflammation-induced phenoconversion, as summarized by Klomp et al. . CYP2C19 is highly polymorphic and shown to be affected by inflammation. For example, in a study of 34 patients with an invasive fungal infection receiving voriconazole, it was shown that the effect of inflammation was modulated by the CYP2C19 genotype: the metabolic ratio of voriconazole and its metabolite was more decreased by inflammation in CYP2C19 ultrarapid metabolizers compared to CYP2C19 intermediate metabolizers . Similarly, Ohnishi et al. aimed to investigate the consequences of inflammation for different CYP2C19 genotypes by examining the metabolic ratios of omeprazole and its metabolite in hepatitis C virus (HCV)-positive patients and healthy volunteers . The shift in metabolic ratio between healthy patients and HCV-positive patients was largest for genotype-predicted normal metabolizers (21.1-fold change), followed by intermediate metabolizers (12.4-fold change) and least evident for poor metabolizers. Although these examples only illustrate the effects of inflammation on CYP2C19 mediated drug metabolism, and other CYP isoforms remain to be investigated, they clearly indicate that inflammation-induced changes in CYP450-mediated drug metabolism are affected by an individual’s CYP metabolizer genotype.
Concluding, data from in-vitro models have been instrumental to elucidate that CYP isoforms show distinct susceptibility to downregulation by inflammatory mediators wherein CYP3A4 seems to be most affected by inflammation, supporting clinical observations on CYP3A4 drug substrates. Additionally, the pattern of downregulation of CYP isoforms was dependent on the inflammatory stimulus. Interestingly, interindividual variability in response to inflammation is observed in both in-vitro models and clinical studies. Genetic variability in the described pathways via which inflammation modulates the expression and activity of DMEs might in part explain the distinct response towards inflammation between subjects, but this remains to be further investigated. Ultimately, a better understanding of inflammation-induced phenoconversion may aid in optimizing treatment for the individual patient.
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Increased methane production associated with community shifts towards | 41958499-604e-4a43-9e24-8e3069b7b26c | 11660960 | Microbiology[mh] | Plastic pollution is of growing global concern for its potential to alter the carbon cycling in terrestrial ecosystems . Indeed, a large amount of plastic debris accumulates in soils and terrestrial ecosystems, primarily due to agricultural plastic film degradation, atmospheric fallout, and the use of sewage sludge as fertilizer . For instance, film mulching has become an essential agricultural practice in rice paddies, due to the seasonal arid climate and low precipitation . The accumulation of microplastics in long-term film-mulched paddy soil is estimated to reach 18.1 million particles ha −1 annually in China . The degradation of plastic materials results in the formation of microplastics (MPs < 5 mm) and nanoplastics (NPs < 1 μm). Both MPs and NPs have a significant potential to adversely affect soil ecology . Their adverse effects on the terrestrial carbon and nitrogen cycles may impact soil microbial activities, plant growth, and litter decomposition, and these particles can be toxic for microorganisms in the soil environment . NPs have a larger specific surface area and higher adsorption capacity and mobility than MPs, making them more easily absorbed or ingested by various organisms. The effect of NPs on microbial communities may vary depending on the plastic type investigated and the environmental conditions. On the one hand, NPs have been shown to significantly inhibit CH 4 production in different anaerobic wastewater and sludge digestion systems . On the other hand, there is growing evidence that dissolved organic carbon (DOC) leaching from plastics stimulates microbial activity and directly or indirectly affects carbon sequestration capacity in marine and soil ecosystems . DOC can be directly utilized by bacteria capable of breaking down complex carbon polymers into simpler organic compounds, which involves the expression and activity of carbohydrate-active enzymes (CAZymes) . However, the response of methanogens to the accumulation of NPs in agricultural soils is not yet known. Rice field soils are one of the most important agricultural sources of atmospheric CH 4 . They thus represent an excellent model system for investigating the microbial mechanisms of CH 4 production . The methanogenic degradation pathway of organic matter in submerged rice paddies and anoxic wetlands follows common principles and involves a microbial food web composed of different functional guilds of the domains Bacteria and Archaea . These microbial guilds participate in a cascade of anaerobic degradation steps that involve polymer hydrolysis, fermentation, syntrophic conversion of fatty acids, homoacetogenesis, and methanogenesis . Three different methanogenic pathways, including acetoclastic, hydrogenotrophic, and methylotrophic methanogenesis, are typically active in paddy soils . Acetoclastic methanogens, such as Methanosarcina and Methanothrix , utilize acetate to form CO 2 and CH 4 . Hydrogenotrophic methanogens, including Methanocellales, Methanobacteriales, and Methanomicrobiales, use H 2 and CO 2 to produce CH 4 . Members of the Methanosarcinales and Methanomassiliicoccales are known for their methylotrophic capabilities, able to utilize various methylated compounds, such as methanol, methylamine, and dimethylamine, as carbon and energy sources for CH 4 production . Here, we combined process measurements and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) with functional genome-centric metagenomics and quantitative PCR (qPCR) to disentangle the impact of low-density polyethylene nanoplastics (LDPE NPs) on the methanogenic communities in flooded rice field soil. More specifically, we aimed to elucidate whether LDPE NPs affect the DOC content in anoxic paddy soils and thus CH 4 production, and if so, what is their effect on the metagenomic potential for polymer breakdown and major methanogenesis pathways. LDPE is one of the most produced and discarded synthetic plastics globally and is known to accumulate in various ecosystems, including rice paddies . Despite this environmental threat, the impact of LDPE on the anaerobic microbiota in flooded rice paddies remains largely unexplored. We applied our research strategy to two major soil types widely used for rice farming in China: black and red soil. The organic carbon content in red soil is significantly higher than in black soil (Table S1). Our study sites are known to represent areas of the highest CH 4 production rates among Chinese black and red soils . As a corroborative approach, we also obtained functional gene expression profiles from particular samples. Our research fills a knowledge gap concerning the effects of NPs on DOC and CH 4 metabolism in rice field soils with potentially broad implications for ecosystem fluxes and global climate change. Microcosms setup and soil sampling Soil samples were collected from two typical rice-growing areas that differ in their soil types, defined as black soil (BS) and red soil (RS) in China. BS was collected at the Jiansanjiang Agricultural Experimental Station in Heilongjiang (47°14′N, 132°37′E), while RS was sampled at the Changsha China National Rice Institute in Changsha in Hunan (28°11′N, 112°58′E). Major physicochemical properties of BS and RS are shown in supplementary materials (Additional File 3: Table S1). LDPE (density: 0.91 g/cm 3 ) NPs with a size of 50 nm were purchased from Zhongxin Plastic (Guangdong, China). Nanoplastics were sterilized with methanol, dried at 40 °C, and stored at 4 °C for further use . Four different concentrations of 50-nm LPDE NPs were applied in our BS and RS microcosm experiments. The concentration of nanoplastics refers to the dried paddy soil and is calculated based on its dry weight. The NPs concentrations were 0% (CK), 0.5% (0.1-g NPs), 1% (0.2-g NPs), and 5% (1-g NPs). Although there is not yet a reliable method available to quantify the accumulation of NPs in paddy soils, the amounts are likely in the range of 0 ~ 6.7% microplastics as detected in other soils . Each treatment had four replicates. The microcosms were prepared by adding 20 g of dry soil, 40 mL of autoclaved water, and the appropriate amounts of NPs to sterile 100-mL bottles, followed by thorough mixing (all experimental units experienced the same physical disturbance by mixing, including the controls). The bottles were then sealed with butyl rubber stoppers and aluminum caps and flushed with N 2 for 10 min to establish anoxic conditions. All bottles were incubated in a climate chamber at 25 °C in the dark for up to 160 days. In total, 64 microcosms were set up (2 soils × 4 treatments × 2 time points × 4 replicates). These microcosms were first used for gas measurements (CH 4 , CO 2 ) and then destructively sampled for measurement of metabolites (liquid) and, in addition to dissolved organic carbon (DOC) and matter (DOM), for molecular analysis (soil). The sampling time points reflect our knowledge that (i) hydrolytic decomposition of easily degradable polymer substances occurs over the first 30 days of anaerobic incubation , and (ii) microplastic degradation has long-lasting ecological effects . The detailed experimental setup is shown in Fig. S1 (Additional File 2). Soil samples were taken after 30 and 160 days of incubation. To test whether carbon is abiotically released from LDPE NPs and to what extent, sterilized ( 60 Co γ-radiation at a dose of 25 kGy to kill the soil indigenous microbes) control and NPs-amended (0.5%, 5%) microcosms were incubated in triplicates for 30 days. The carbon released from the LDPE NPs was neglectable. The exact values were 1.83 × 10 −3 mg g −1 and 2.43 × 10 −3 mg g −1 dry paddy soil in the 0.5% and 5% NPs treatments, respectively. LDPE is about 80% carbon . Thus, the total amount of LDPE carbon added per gram dry paddy soil in the 0.5% NPs and 5% NPs treatments was 4 mg and 40 mg, respectively. Process measurements Gas samples (100 µl) were taken from the headspace of the bottles using a Pressure-Lock syringe (VICI). Cumulative gas emissions were measured continuously using a gas chromatography system equipped with a Porapak Q stainless-steel column as previously described (Additional File 2: Fig. S2) . However, due to the highly similar gas measurement results obtained for the 0.5% and 1.0% NPs treatments, our further study was limited to the following three NPs treatments: 0% NPs (CK), 0.5% NPs (0.1 g), and 5% NPs (1 g). The contents of DOC were determined using a total organic carbon analyzer (Elementar, Langenselbold, Germany). The total amount of microbially accessible carbon released by the NPs treatments in the microcosms was estimated by summing up the difference in DOC content between the NPs treatments and the control treatments, as well as the carbon converted into CH 4 and CO 2 (Additional File 3: Table S2). In addition, the calculated CO 2 values may slightly underestimate the released carbon because carbon fixed into cell biomass could not be considered. The solid-phase extraction of dissolved organic matter (DOM) from the CK and 0.5% NPs treatments were conducted using Fourier transform ion cyclotron resonance (FT-ICR-MS) as previously described . The extraction procedure is further detailed in Additional File 1. Targeted metabolomics A 2-mL liquid sample of each microcosm was centrifuged for 15 min at 17,949 × g at 4 °C according to a previous study . Short-chain fatty acids (SCFA) were analyzed using an HP 6890 gas chromatograph (Agilent Technologies). Another 2-mL liquid sample of each microcosm was homogenized with 300 μL of isopropanol/acetonitrile (1:1) and subsequently centrifuged at 17,949 × g for 10 min. Then the supernatant was subjected, in relation to a mixed internal standard, to long-chain fatty acids (LCFAs) analysis using UHPLC-MS (ExionLC™ AD UHPLC-QTRAP® 6500 +). DNA/RNA extraction and quantification of mcrA genes Extraction, purification, and quantification of total soil DNA and RNA were carried out as previously reported (see Additional File 1 for detailed methods description). The numbers of genes encoding methyl coenzyme-M reductase ( mcrA ) were determined using quantitative real-time PCR (qPCR) as described previously . All qPCR reactions were performed in three biological replicates with three technical replicates. Metagenomics and metatranscriptomics Thirty-six metagenomic libraries were generated and sequenced on an Illumina HiSeq 2000 instrument at Novogene Bioinformatics Technology in a 2 × 150 bp paired-end mode. The sequences were quality-checked using Trimmomatic (version 0.35) . The high-quality paired-end reads from each sample were individually assembled into contigs using MEGAHIT (version 1.1.3) and evaluated using QUAST 2.3. Metagenomic contigs were queried in Prokka and BLAST against the NCBI nonredundant (nr) protein database and the clusters of orthologous groups (COG) database using MEGAN6 Ultimate Edition (version 6.20.5) . Functions related to carbon metabolic categories were classified into aromatic and carbohydrate carbon classes (Additional File 3: Table S3), as described in a previous study . Taxonomic assignment of the H 2 evolving hydrogenases genes was achieved by extracting their sequences from the metagenomic contigs. The extracted sequences were then blasted against NCBI’s nonredundant protein database using Diamond with default settings. Genome binning of the assembled contigs was carried out using metaWRAP . The completeness and contamination of the metagenome-assembled genomes (MAGs) were evaluated using CheckM (Version 1.1.2) . MAGs were annotated using Prokka (version 1.14.6) and searched against NCBI-nr and KEGG databases . The maximum-likelihood phylogenomic trees were constructed from the multiple sequence alignments (MSAs) generated by GTDB-Tk software and visualized in the online iTol platform ( https://itol.embl.de/ ) . CoverM and the average nucleotide identity (ANI) of MAGs were calculated to determine their abundances and similarities . The detailed procedure of carbon annotation, genome binning, and annotation is described in Additional File 1. Furthermore, total RNA extracted from the three replicate microcosms of a given treatment after 160 days of incubation was mixed to produce composite samples for cDNA library preparation. Metatranscriptomic libraries could be created for the following three experimental treatments: red soil with 0% NPs (RS-CK), red soil with 0.5% NPs (RS-0.5% NPs), and black soil with 0.5% NPs (BS-0.5% NPs). Total RNA extraction from the BS control treatment was attempted but failed. Sequencing was done using Illumina MiSeq in a 2 × 250 bp paired-end mode as described previously . The detailed procedure of cDNA library preparation and metatranscriptomic data analysis is described in Additional File 1. Statistical analyses All statistical analyses were conducted in R (Version 4.0.1). Principal coordinate analysis (PCoA) based on Bray‒Curtis distances of carbon functional gene profiles was carried out to compare the variance in beta diversity across samples. Analysis of similarities (ANOSIM) based on Bray‒Curtis distances was performed to estimate the effect of NPs on carbon functional gene diversity. In addition, we applied one-way ANOVA followed by post hoc multiple comparisons using the Tukey HSD test to assess the significant difference in DOC levels, mcrA gene copy numbers, NPs-induced metagenomic abundance changes of the methanogen-bacteria ratio, and the genes encoding the degradation of aromatics and complex carbohydrates. The relative metagenomic abundance refers to the annotated counts per million reads. Statistical significance was established at a FDR-corrected P -value < 0.05. LEfse (linear discriminant analysis effect size) analysis was used to investigate the metagenomic abundance of MAGs that exhibited significant enrichment in specific treatment groups. Soil samples were collected from two typical rice-growing areas that differ in their soil types, defined as black soil (BS) and red soil (RS) in China. BS was collected at the Jiansanjiang Agricultural Experimental Station in Heilongjiang (47°14′N, 132°37′E), while RS was sampled at the Changsha China National Rice Institute in Changsha in Hunan (28°11′N, 112°58′E). Major physicochemical properties of BS and RS are shown in supplementary materials (Additional File 3: Table S1). LDPE (density: 0.91 g/cm 3 ) NPs with a size of 50 nm were purchased from Zhongxin Plastic (Guangdong, China). Nanoplastics were sterilized with methanol, dried at 40 °C, and stored at 4 °C for further use . Four different concentrations of 50-nm LPDE NPs were applied in our BS and RS microcosm experiments. The concentration of nanoplastics refers to the dried paddy soil and is calculated based on its dry weight. The NPs concentrations were 0% (CK), 0.5% (0.1-g NPs), 1% (0.2-g NPs), and 5% (1-g NPs). Although there is not yet a reliable method available to quantify the accumulation of NPs in paddy soils, the amounts are likely in the range of 0 ~ 6.7% microplastics as detected in other soils . Each treatment had four replicates. The microcosms were prepared by adding 20 g of dry soil, 40 mL of autoclaved water, and the appropriate amounts of NPs to sterile 100-mL bottles, followed by thorough mixing (all experimental units experienced the same physical disturbance by mixing, including the controls). The bottles were then sealed with butyl rubber stoppers and aluminum caps and flushed with N 2 for 10 min to establish anoxic conditions. All bottles were incubated in a climate chamber at 25 °C in the dark for up to 160 days. In total, 64 microcosms were set up (2 soils × 4 treatments × 2 time points × 4 replicates). These microcosms were first used for gas measurements (CH 4 , CO 2 ) and then destructively sampled for measurement of metabolites (liquid) and, in addition to dissolved organic carbon (DOC) and matter (DOM), for molecular analysis (soil). The sampling time points reflect our knowledge that (i) hydrolytic decomposition of easily degradable polymer substances occurs over the first 30 days of anaerobic incubation , and (ii) microplastic degradation has long-lasting ecological effects . The detailed experimental setup is shown in Fig. S1 (Additional File 2). Soil samples were taken after 30 and 160 days of incubation. To test whether carbon is abiotically released from LDPE NPs and to what extent, sterilized ( 60 Co γ-radiation at a dose of 25 kGy to kill the soil indigenous microbes) control and NPs-amended (0.5%, 5%) microcosms were incubated in triplicates for 30 days. The carbon released from the LDPE NPs was neglectable. The exact values were 1.83 × 10 −3 mg g −1 and 2.43 × 10 −3 mg g −1 dry paddy soil in the 0.5% and 5% NPs treatments, respectively. LDPE is about 80% carbon . Thus, the total amount of LDPE carbon added per gram dry paddy soil in the 0.5% NPs and 5% NPs treatments was 4 mg and 40 mg, respectively. Gas samples (100 µl) were taken from the headspace of the bottles using a Pressure-Lock syringe (VICI). Cumulative gas emissions were measured continuously using a gas chromatography system equipped with a Porapak Q stainless-steel column as previously described (Additional File 2: Fig. S2) . However, due to the highly similar gas measurement results obtained for the 0.5% and 1.0% NPs treatments, our further study was limited to the following three NPs treatments: 0% NPs (CK), 0.5% NPs (0.1 g), and 5% NPs (1 g). The contents of DOC were determined using a total organic carbon analyzer (Elementar, Langenselbold, Germany). The total amount of microbially accessible carbon released by the NPs treatments in the microcosms was estimated by summing up the difference in DOC content between the NPs treatments and the control treatments, as well as the carbon converted into CH 4 and CO 2 (Additional File 3: Table S2). In addition, the calculated CO 2 values may slightly underestimate the released carbon because carbon fixed into cell biomass could not be considered. The solid-phase extraction of dissolved organic matter (DOM) from the CK and 0.5% NPs treatments were conducted using Fourier transform ion cyclotron resonance (FT-ICR-MS) as previously described . The extraction procedure is further detailed in Additional File 1. A 2-mL liquid sample of each microcosm was centrifuged for 15 min at 17,949 × g at 4 °C according to a previous study . Short-chain fatty acids (SCFA) were analyzed using an HP 6890 gas chromatograph (Agilent Technologies). Another 2-mL liquid sample of each microcosm was homogenized with 300 μL of isopropanol/acetonitrile (1:1) and subsequently centrifuged at 17,949 × g for 10 min. Then the supernatant was subjected, in relation to a mixed internal standard, to long-chain fatty acids (LCFAs) analysis using UHPLC-MS (ExionLC™ AD UHPLC-QTRAP® 6500 +). mcrA genes Extraction, purification, and quantification of total soil DNA and RNA were carried out as previously reported (see Additional File 1 for detailed methods description). The numbers of genes encoding methyl coenzyme-M reductase ( mcrA ) were determined using quantitative real-time PCR (qPCR) as described previously . All qPCR reactions were performed in three biological replicates with three technical replicates. Thirty-six metagenomic libraries were generated and sequenced on an Illumina HiSeq 2000 instrument at Novogene Bioinformatics Technology in a 2 × 150 bp paired-end mode. The sequences were quality-checked using Trimmomatic (version 0.35) . The high-quality paired-end reads from each sample were individually assembled into contigs using MEGAHIT (version 1.1.3) and evaluated using QUAST 2.3. Metagenomic contigs were queried in Prokka and BLAST against the NCBI nonredundant (nr) protein database and the clusters of orthologous groups (COG) database using MEGAN6 Ultimate Edition (version 6.20.5) . Functions related to carbon metabolic categories were classified into aromatic and carbohydrate carbon classes (Additional File 3: Table S3), as described in a previous study . Taxonomic assignment of the H 2 evolving hydrogenases genes was achieved by extracting their sequences from the metagenomic contigs. The extracted sequences were then blasted against NCBI’s nonredundant protein database using Diamond with default settings. Genome binning of the assembled contigs was carried out using metaWRAP . The completeness and contamination of the metagenome-assembled genomes (MAGs) were evaluated using CheckM (Version 1.1.2) . MAGs were annotated using Prokka (version 1.14.6) and searched against NCBI-nr and KEGG databases . The maximum-likelihood phylogenomic trees were constructed from the multiple sequence alignments (MSAs) generated by GTDB-Tk software and visualized in the online iTol platform ( https://itol.embl.de/ ) . CoverM and the average nucleotide identity (ANI) of MAGs were calculated to determine their abundances and similarities . The detailed procedure of carbon annotation, genome binning, and annotation is described in Additional File 1. Furthermore, total RNA extracted from the three replicate microcosms of a given treatment after 160 days of incubation was mixed to produce composite samples for cDNA library preparation. Metatranscriptomic libraries could be created for the following three experimental treatments: red soil with 0% NPs (RS-CK), red soil with 0.5% NPs (RS-0.5% NPs), and black soil with 0.5% NPs (BS-0.5% NPs). Total RNA extraction from the BS control treatment was attempted but failed. Sequencing was done using Illumina MiSeq in a 2 × 250 bp paired-end mode as described previously . The detailed procedure of cDNA library preparation and metatranscriptomic data analysis is described in Additional File 1. All statistical analyses were conducted in R (Version 4.0.1). Principal coordinate analysis (PCoA) based on Bray‒Curtis distances of carbon functional gene profiles was carried out to compare the variance in beta diversity across samples. Analysis of similarities (ANOSIM) based on Bray‒Curtis distances was performed to estimate the effect of NPs on carbon functional gene diversity. In addition, we applied one-way ANOVA followed by post hoc multiple comparisons using the Tukey HSD test to assess the significant difference in DOC levels, mcrA gene copy numbers, NPs-induced metagenomic abundance changes of the methanogen-bacteria ratio, and the genes encoding the degradation of aromatics and complex carbohydrates. The relative metagenomic abundance refers to the annotated counts per million reads. Statistical significance was established at a FDR-corrected P -value < 0.05. LEfse (linear discriminant analysis effect size) analysis was used to investigate the metagenomic abundance of MAGs that exhibited significant enrichment in specific treatment groups. Impact of the NPs treatments on DOC and DOM Scanning electron micrographs revealed that NPs had a strong capacity to form rod-shaped aggregates (Additional File 2: Fig. S3). The addition of NPs to the microcosms significantly increased the DOC content in the black soil and the red soil by 80% and 60%, respectively. No significant difference in DOC increase was observed between the 30-day and 160-day incubation periods (Fig. a). Concomitantly to the NPs-induced increase in DOC after 30 days of incubation, the relative proportion of recalcitrant DOM molecules in both the black soil [molecular lability boundary (MLB L ) ck = 0.144, (MLB L ) NPs = 0.115)] and the red soil [(MLB L ) ck = 0.134, (MLB L ) NPs = 0.121)] increased due to a decrease in labile DOM (Additional File 2: Fig. S4; Additional File 3: Table S4). Fatty acid profiles and CH 4 production In the black soil, all the metabolites, including acetate, propionate, valerate, and lactate, showed a transient peak concentration after 30-day incubation. The greatest transient concentrations were observed for acetate (2 mM [5% NPs]), valerate (0.4 mM [0.5%, 5% NPs], and lactate (0.8 mM [CK]). Compared to the black soil, the metabolite turnover patterns markedly differed in the red soil. In particular, acetate exhibited its transient peak concentration already after 9-day incubation. The concentration of all metabolites had decreased to low levels in both soils after 160-day incubation but was still detectable in some cases (e.g., acetate and propionate in the 5% NPs treatment in the black soil) (Additional File 2: Fig. S5). The concentration of LCFAs in the black soil had increased with increasing LDPE NPs concentration after 30-day incubation but was decreased after 160-day incubation. This was most obviously for the monounsaturated C18 fatty acids oleic acid and cis-vaccenic acid ( P < 0.05) (Additional File 2: Fig. S6). Relative to the control, the addition of LDPE NPs induced a change in the CH 4 production rate of up to 10.1-fold in the black soil and 4.5-fold in the red soil (Fig. b; Additional File 2: Figs. S2, S7). However, relative to the red soil, the black soil had an extended lag phase of approximately 20 days until CH 4 production was detectable. Consequently, the amount of CH 4 produced was significantly lower in the black soil after 30-day incubation than in the red soil. Although similar amounts of CH 4 were measured in the 5% NPs treatments of both soils after 160 days of incubation, CH 4 production in the black soil remained significantly lower over the complete 160-day incubation period than in the red soil (Fig. b; Additional File 2: Fig. S2). In the black soil, the total excess amounts of microbially accessible carbon released in the 5% NPs treatments relative to the control treatments were 18.69 mg (30 days) and 39.3 mg (160 days). The corresponding values for the red soil were 12.76 mg (30 days) and 43.84 mg (160 days). The values calculated for the 5% NPs treatments were significantly higher than those calculated for the 0.5% NPs treatments, primarily due to the increased amount of carbon converted into CH 4 (Additional File 3: Table S2). The CH 4 production rate was significantly and positively correlated with the DOC content across both NPs treatments (0.5%, 5%) relative to CK for both sampling time points (30 days, 160 days). This correlation was highly significant for both the black soil ( R 2 = 0.296, P < 0.012) and the red soil ( R 2 = 0.562, P < 0.001) (Fig. b). Furthermore, the copy numbers of the mcrA gene significantly increased ( P < 0.001) after the addition of NPs (Fig. c; Additional File 2: Fig. S8), indicating a positive correlation between methanogen abundance and CH 4 production in both the black soil ( R 2 = 0.639, P < 0.001) and the red soil ( R 2 = 0.479, P < 0.001) (Fig. c). Metagenomics and enriched MAGs Shotgun metagenomic sequencing was performed for 36 soil samples, producing more than 593 GB of Illumina sequence data. A total of 1190 metagenome-assembled genomes (MAGs) were recovered. Among them, 391 MAGs were identified to be of high quality (completeness > 70% and contamination < 10%) (Additional File 2: Fig. S9). Among the bacterial MAGs, the relative abundance of 45 MAGs was significantly and positively correlated with DOC content. Most of these MAGs belonged to Syntrophomonadia (21), Lentimicrobiaceae (6), and Ignavibacteriaceae (4). In addition, a total of 38 high-quality methanogen MAGs were obtained (Additional File 2: Fig. S10; Additional File 3: Table S5), which belonged to the Methanocellaceae (17), Methanobacteriaceae (11), Methanotrichaceae (6), Methanosarcinaceae (3), and Methanomassiliicoccaceae (1). Among these MAGs, the relative abundance of 12 methanogen MAGs was significantly and positively correlated with CH 4 production. These were affiliated with Methanocella (9) and Methanobacterium (3). Most of the MAGs affiliated with Syntrophomonadaceae and Methanocellaceae were found in both the black and red soils to be significantly enriched in the NPs treatments relative to the control (Fig. a; Additional File 2: Fig. S10). In both soils, we indeed observed a significant correlation between the NPs-induced changes in the metagenomic abundance of Syntrophomondaceae and Methanocellaceae MAGs ( P < 0.001) (Fig. b). The NPs-induced enrichment of the Syntrophomonadaceae was also highly evident in the family-level profiles obtained for the total metagenomic data (from 0.46% up to 2.42%) ( P < 0.001) and the community-wide composition of hydrogenase genes (from undetectable levels to a range from 8.55% to 20.13%) ( P < 0.001) (Additional File 2: Figs. S11, S12), with the latter being significantly related to an increase in the total hydrogenase gene abundance (Additional File 2: Fig. S12). In the black soil, the NPs-induced abundance increases were observed for various MAGs belonging to Syntrophomondaceae (12), Lentimicrobiaceae (6), Ignavibacteriaceae (4), Desulfomonilia (3), Coriobacteriia (3), Bacteroidetes (1), Acetivibrionales (1), Actinobacteriota (1), Bacillaceae (1), Clostridia (1), Methanosarcinaceae (1), Methanobacteriaceae (2), and Methanocellaceae (10). In the red soil, 10 Syntrophomondaceae MAGs were significantly enriched in the NPs treatments. In addition, MAGs belonging to Magnetospirillaceae were detected with increased abundance but only in the 0.5% NPs treatment. Among methanogens, MAGs affiliated with Methanosarcinaceae (B15_bin_34), Methanobacteriaceae, and Methanocellaceae were significantly enriched in the NPs treatments after 30-day incubation. Taxonomic and functional profiles of carbohydrate and aromatic C utilization The addition of LDPE NPs significantly affected the taxonomic and functional profiles of genes involved in polymer breakdown. PCoA indicated that in both the black soil ( P < 0.001) and the red soil ( P < 0.01), the incubation time had a more significant impact on the beta diversity of genes encoding the degradation of complex carbohydrates and aromatic C than the NPs treatments (Additional File 2: Fig. S13). However, the NPs treatments had in both soil types a significant effect on the functional composition of genes encoding the degradation of aromatic C but not on those involved in utilizing complex carbohydrates (BS: R Treatment = 0.192, P < 0.05; RS: R Treatment = 0.169, P < 0.05) (Additional File 2: Fig. S13). In addition, the relative metagenomic abundance of genes encoding aromatics degradation was significantly correlated with DOC content in both soils after 160-day incubation, but not after 30-day incubation (Additional File 2: Fig. S14). The genes encoding the hydrolysis of complex carbohydrates exhibited a higher metagenomic abundance than those encoding the degradation of aromatic C in both the black soil and the red soil (Fig. a). Relative to CK, their metagenomic abundance had consecutively and significantly increased with the concentration of NPs after the 160-day incubation period, but their abundance was significantly lower than after 30 days of incubation (Fig. a; Additional File 2: Fig. S15). Furthermore, in black and red soils, the relative metagenomic abundance of genes encoding the degradation of carbohydrates and aromatic C was significantly correlated with both the log copy number of the mcrA genes and the CH 4 production rate on day 160, but not on day 30 (Fig. b; Additional File 2: Figs. S16, S17). The taxonomic assignment of genes encoding the degradation of carbohydrates and aromatic C showed that the bacterial communities were dominated by species affiliated to the Actinobacteria, Firmicutes, Bacteroidetes, and Proteobacteria (Additional File 2: Fig. S18). Among the genes encoding carbohydrate degradation, Syntrophomonadaceae, Peptococcaceae, Marinilabiliaceae, and Paenibacillaceae were significantly enriched by the NPs treatments in the black soil, while Mycobacteriaceae, Oxalobacteraceae, and Comamonadaceae showed a significant enrichment by the NPs treatments in the red soil (Additional File 2: Fig. S19). Among the genes encoding aromatic C decomposition, Clostridiaceae, Peptococcaceae, and Paenibacillaceae were significantly enriched by the NPs treatment in the black soil, while unclassified Proteobacteria showed an increased relative abundance in NPs-treated red soil (Additional File 2: Fig. S20). The methanogen community The metagenomic abundance of the methanogens relative to bacteria increased with both the concentration of NPs and the incubation time (Fig. a). In addition, the increase in the metagenomic methanogen-to-bacteria abundance ratio showed a highly significant correlation ( P < 0.001) with CH 4 production in both the black soil and the red soil (Fig. b). Likewise, the methanogen-to-bacteria transcript ratio and the expression level of mRNA affiliated to the KEGG level 3 category “methane metabolism” had, relative to the control, markedly increased in the red soil 0.5% NPs treatment after the 160-day incubation period. Both the methanogen-to-bacteria abundance ratio and the expression level of the methane metabolism-affiliated mRNA were comparable between the black soil and the red soil (Additional File 3: Table S6). Metagenomic analysis and taxonomic classification of the methanogen MAGs collectively confirmed that Methanosarcinaceae, Methanotrichaceae, Methanocellaceae, and Methanobacteriaceae were the dominant methanogenic families (Fig. ; Additional File 2: Fig. S21; Additional File 3: Table S7). In black soil, Methanosarcinaceae was the most abundant methanogen group, but the addition of NPs induced a shift towards an increase in the relative abundance of Methanocellaceae. In particular, the relative abundance of Methanocellaceae exceeded that of Methanosarcinaceae in the 5% NPs treatment after 160-day incubation, but not after 30-day incubation. A strong NPs-induced increase in Methanocellaceae abundance after 160 days of incubation was also well evidenced by the assembled MAGs (Fig. ). In red soil, Methanocellaceae was the predominant family-level group, while both Methanosarcinaceae and Methanotrichaceae were of lower abundance. The addition of 0.5% and 5% NPs induced, relative to the control, a significant increase in the relative metagenomic abundance of the Methanocellaceae after an incubation period of 30 and 160 days, while no treatment effect was observed for Methanosarcinaceae and Methanotrichaceae. The strong increase in Methanocellaceae abundance at both incubation times was further corroborated by the assembled MAGs (Fig. ). Transcript analysis of methanogenic mRNA showed that the addition of NPs induced predominant activity of the Methanosarcinaceae and Methanocellaceae, accompanied by a relative abundance shift in the expression of genes involved in methylotrophic methanogenesis from Methanomassiliicoccaceae towards Methanosarcinaceae in the red soil (Additional File 2: Figs. S22, S23). Analysis of the functional potential revealed that among the three methanogenic pathways, genes encoding acetoclastic methanogenesis were most abundant. However, their relative proportion decreased with increasing NPs concentration in both black and red soils (Fig. ; Additional File 2: Figs. S24, S25). Concomitantly, the relative metagenomic abundance of genes encoding hydrogenotrophic methanogenesis significantly increased (Fig. ; Additional File 2: Fig. S24, S25). Notably, the relative metagenomic abundance of genes encoding hydrogenotrophic methanogenesis was greater in the red soil across all the experimental treatments, which agrees well with the predominance of Methanocellaceae in this soil type (compare Figs. and ). The genetic potential for methylotrophic methanogenesis was increased in both soil types only after 160 days of incubation, and this increase was more pronounced in the red soil (Fig. ). The NPs-induced increase in the relative metagenomic abundance of genes encoding hydrogenotrophic (R 2 BS = 0.591, P < 0.001; R 2 RS = 0.45, P < 0.05) and methylotrophic (R 2 BS = 0.458, P < 0.05; R 2 RS = 0.577, P < 0.05) methanogenesis showed a significant and positive correlation with DOC after 160 days of incubation, whereas the genes encoding acetoclastic methanogenesis did not display a significant correlation (Additional File 2: Fig. S27). Further, functional KEEG-based annotation of the methane metabolism-affiliated mRNA agreed well with the metagenomic results. The mRNA transcripts highly specific for one of the three methanogenesis pathways revealed prevalent expression of acetoclastic methanogenesis. However, the expression level of hydrogenotrophic and methylotrophic methanogenesis increased relative to acetoclastic methanogenesis in the red soil 0.5% NPs treatment compared to the control treatment (Additional File 3: Table S6). Transcript mapping of methanogenic mRNA onto the pooled 38 methanogen MAGs showed that in both the control treatment and the 0.5% NPs treatment, the methanogen populations expressed all three methanogenic (acetoclastic, hydrogenotrophic, methylotrophic) pathways after 160 days of incubation (Additional File 2: Figs. S28, S29). The methylotrophic pathway was characterized by an exclusive expression of mtaBC (Additional File 2: Fig. S29). These two genes encode the methyltransferase/methanol corrinoid protein, a specific biomarker for methanol-dependent methanogenesis. Scanning electron micrographs revealed that NPs had a strong capacity to form rod-shaped aggregates (Additional File 2: Fig. S3). The addition of NPs to the microcosms significantly increased the DOC content in the black soil and the red soil by 80% and 60%, respectively. No significant difference in DOC increase was observed between the 30-day and 160-day incubation periods (Fig. a). Concomitantly to the NPs-induced increase in DOC after 30 days of incubation, the relative proportion of recalcitrant DOM molecules in both the black soil [molecular lability boundary (MLB L ) ck = 0.144, (MLB L ) NPs = 0.115)] and the red soil [(MLB L ) ck = 0.134, (MLB L ) NPs = 0.121)] increased due to a decrease in labile DOM (Additional File 2: Fig. S4; Additional File 3: Table S4). 4 production In the black soil, all the metabolites, including acetate, propionate, valerate, and lactate, showed a transient peak concentration after 30-day incubation. The greatest transient concentrations were observed for acetate (2 mM [5% NPs]), valerate (0.4 mM [0.5%, 5% NPs], and lactate (0.8 mM [CK]). Compared to the black soil, the metabolite turnover patterns markedly differed in the red soil. In particular, acetate exhibited its transient peak concentration already after 9-day incubation. The concentration of all metabolites had decreased to low levels in both soils after 160-day incubation but was still detectable in some cases (e.g., acetate and propionate in the 5% NPs treatment in the black soil) (Additional File 2: Fig. S5). The concentration of LCFAs in the black soil had increased with increasing LDPE NPs concentration after 30-day incubation but was decreased after 160-day incubation. This was most obviously for the monounsaturated C18 fatty acids oleic acid and cis-vaccenic acid ( P < 0.05) (Additional File 2: Fig. S6). Relative to the control, the addition of LDPE NPs induced a change in the CH 4 production rate of up to 10.1-fold in the black soil and 4.5-fold in the red soil (Fig. b; Additional File 2: Figs. S2, S7). However, relative to the red soil, the black soil had an extended lag phase of approximately 20 days until CH 4 production was detectable. Consequently, the amount of CH 4 produced was significantly lower in the black soil after 30-day incubation than in the red soil. Although similar amounts of CH 4 were measured in the 5% NPs treatments of both soils after 160 days of incubation, CH 4 production in the black soil remained significantly lower over the complete 160-day incubation period than in the red soil (Fig. b; Additional File 2: Fig. S2). In the black soil, the total excess amounts of microbially accessible carbon released in the 5% NPs treatments relative to the control treatments were 18.69 mg (30 days) and 39.3 mg (160 days). The corresponding values for the red soil were 12.76 mg (30 days) and 43.84 mg (160 days). The values calculated for the 5% NPs treatments were significantly higher than those calculated for the 0.5% NPs treatments, primarily due to the increased amount of carbon converted into CH 4 (Additional File 3: Table S2). The CH 4 production rate was significantly and positively correlated with the DOC content across both NPs treatments (0.5%, 5%) relative to CK for both sampling time points (30 days, 160 days). This correlation was highly significant for both the black soil ( R 2 = 0.296, P < 0.012) and the red soil ( R 2 = 0.562, P < 0.001) (Fig. b). Furthermore, the copy numbers of the mcrA gene significantly increased ( P < 0.001) after the addition of NPs (Fig. c; Additional File 2: Fig. S8), indicating a positive correlation between methanogen abundance and CH 4 production in both the black soil ( R 2 = 0.639, P < 0.001) and the red soil ( R 2 = 0.479, P < 0.001) (Fig. c). Shotgun metagenomic sequencing was performed for 36 soil samples, producing more than 593 GB of Illumina sequence data. A total of 1190 metagenome-assembled genomes (MAGs) were recovered. Among them, 391 MAGs were identified to be of high quality (completeness > 70% and contamination < 10%) (Additional File 2: Fig. S9). Among the bacterial MAGs, the relative abundance of 45 MAGs was significantly and positively correlated with DOC content. Most of these MAGs belonged to Syntrophomonadia (21), Lentimicrobiaceae (6), and Ignavibacteriaceae (4). In addition, a total of 38 high-quality methanogen MAGs were obtained (Additional File 2: Fig. S10; Additional File 3: Table S5), which belonged to the Methanocellaceae (17), Methanobacteriaceae (11), Methanotrichaceae (6), Methanosarcinaceae (3), and Methanomassiliicoccaceae (1). Among these MAGs, the relative abundance of 12 methanogen MAGs was significantly and positively correlated with CH 4 production. These were affiliated with Methanocella (9) and Methanobacterium (3). Most of the MAGs affiliated with Syntrophomonadaceae and Methanocellaceae were found in both the black and red soils to be significantly enriched in the NPs treatments relative to the control (Fig. a; Additional File 2: Fig. S10). In both soils, we indeed observed a significant correlation between the NPs-induced changes in the metagenomic abundance of Syntrophomondaceae and Methanocellaceae MAGs ( P < 0.001) (Fig. b). The NPs-induced enrichment of the Syntrophomonadaceae was also highly evident in the family-level profiles obtained for the total metagenomic data (from 0.46% up to 2.42%) ( P < 0.001) and the community-wide composition of hydrogenase genes (from undetectable levels to a range from 8.55% to 20.13%) ( P < 0.001) (Additional File 2: Figs. S11, S12), with the latter being significantly related to an increase in the total hydrogenase gene abundance (Additional File 2: Fig. S12). In the black soil, the NPs-induced abundance increases were observed for various MAGs belonging to Syntrophomondaceae (12), Lentimicrobiaceae (6), Ignavibacteriaceae (4), Desulfomonilia (3), Coriobacteriia (3), Bacteroidetes (1), Acetivibrionales (1), Actinobacteriota (1), Bacillaceae (1), Clostridia (1), Methanosarcinaceae (1), Methanobacteriaceae (2), and Methanocellaceae (10). In the red soil, 10 Syntrophomondaceae MAGs were significantly enriched in the NPs treatments. In addition, MAGs belonging to Magnetospirillaceae were detected with increased abundance but only in the 0.5% NPs treatment. Among methanogens, MAGs affiliated with Methanosarcinaceae (B15_bin_34), Methanobacteriaceae, and Methanocellaceae were significantly enriched in the NPs treatments after 30-day incubation. The addition of LDPE NPs significantly affected the taxonomic and functional profiles of genes involved in polymer breakdown. PCoA indicated that in both the black soil ( P < 0.001) and the red soil ( P < 0.01), the incubation time had a more significant impact on the beta diversity of genes encoding the degradation of complex carbohydrates and aromatic C than the NPs treatments (Additional File 2: Fig. S13). However, the NPs treatments had in both soil types a significant effect on the functional composition of genes encoding the degradation of aromatic C but not on those involved in utilizing complex carbohydrates (BS: R Treatment = 0.192, P < 0.05; RS: R Treatment = 0.169, P < 0.05) (Additional File 2: Fig. S13). In addition, the relative metagenomic abundance of genes encoding aromatics degradation was significantly correlated with DOC content in both soils after 160-day incubation, but not after 30-day incubation (Additional File 2: Fig. S14). The genes encoding the hydrolysis of complex carbohydrates exhibited a higher metagenomic abundance than those encoding the degradation of aromatic C in both the black soil and the red soil (Fig. a). Relative to CK, their metagenomic abundance had consecutively and significantly increased with the concentration of NPs after the 160-day incubation period, but their abundance was significantly lower than after 30 days of incubation (Fig. a; Additional File 2: Fig. S15). Furthermore, in black and red soils, the relative metagenomic abundance of genes encoding the degradation of carbohydrates and aromatic C was significantly correlated with both the log copy number of the mcrA genes and the CH 4 production rate on day 160, but not on day 30 (Fig. b; Additional File 2: Figs. S16, S17). The taxonomic assignment of genes encoding the degradation of carbohydrates and aromatic C showed that the bacterial communities were dominated by species affiliated to the Actinobacteria, Firmicutes, Bacteroidetes, and Proteobacteria (Additional File 2: Fig. S18). Among the genes encoding carbohydrate degradation, Syntrophomonadaceae, Peptococcaceae, Marinilabiliaceae, and Paenibacillaceae were significantly enriched by the NPs treatments in the black soil, while Mycobacteriaceae, Oxalobacteraceae, and Comamonadaceae showed a significant enrichment by the NPs treatments in the red soil (Additional File 2: Fig. S19). Among the genes encoding aromatic C decomposition, Clostridiaceae, Peptococcaceae, and Paenibacillaceae were significantly enriched by the NPs treatment in the black soil, while unclassified Proteobacteria showed an increased relative abundance in NPs-treated red soil (Additional File 2: Fig. S20). The metagenomic abundance of the methanogens relative to bacteria increased with both the concentration of NPs and the incubation time (Fig. a). In addition, the increase in the metagenomic methanogen-to-bacteria abundance ratio showed a highly significant correlation ( P < 0.001) with CH 4 production in both the black soil and the red soil (Fig. b). Likewise, the methanogen-to-bacteria transcript ratio and the expression level of mRNA affiliated to the KEGG level 3 category “methane metabolism” had, relative to the control, markedly increased in the red soil 0.5% NPs treatment after the 160-day incubation period. Both the methanogen-to-bacteria abundance ratio and the expression level of the methane metabolism-affiliated mRNA were comparable between the black soil and the red soil (Additional File 3: Table S6). Metagenomic analysis and taxonomic classification of the methanogen MAGs collectively confirmed that Methanosarcinaceae, Methanotrichaceae, Methanocellaceae, and Methanobacteriaceae were the dominant methanogenic families (Fig. ; Additional File 2: Fig. S21; Additional File 3: Table S7). In black soil, Methanosarcinaceae was the most abundant methanogen group, but the addition of NPs induced a shift towards an increase in the relative abundance of Methanocellaceae. In particular, the relative abundance of Methanocellaceae exceeded that of Methanosarcinaceae in the 5% NPs treatment after 160-day incubation, but not after 30-day incubation. A strong NPs-induced increase in Methanocellaceae abundance after 160 days of incubation was also well evidenced by the assembled MAGs (Fig. ). In red soil, Methanocellaceae was the predominant family-level group, while both Methanosarcinaceae and Methanotrichaceae were of lower abundance. The addition of 0.5% and 5% NPs induced, relative to the control, a significant increase in the relative metagenomic abundance of the Methanocellaceae after an incubation period of 30 and 160 days, while no treatment effect was observed for Methanosarcinaceae and Methanotrichaceae. The strong increase in Methanocellaceae abundance at both incubation times was further corroborated by the assembled MAGs (Fig. ). Transcript analysis of methanogenic mRNA showed that the addition of NPs induced predominant activity of the Methanosarcinaceae and Methanocellaceae, accompanied by a relative abundance shift in the expression of genes involved in methylotrophic methanogenesis from Methanomassiliicoccaceae towards Methanosarcinaceae in the red soil (Additional File 2: Figs. S22, S23). Analysis of the functional potential revealed that among the three methanogenic pathways, genes encoding acetoclastic methanogenesis were most abundant. However, their relative proportion decreased with increasing NPs concentration in both black and red soils (Fig. ; Additional File 2: Figs. S24, S25). Concomitantly, the relative metagenomic abundance of genes encoding hydrogenotrophic methanogenesis significantly increased (Fig. ; Additional File 2: Fig. S24, S25). Notably, the relative metagenomic abundance of genes encoding hydrogenotrophic methanogenesis was greater in the red soil across all the experimental treatments, which agrees well with the predominance of Methanocellaceae in this soil type (compare Figs. and ). The genetic potential for methylotrophic methanogenesis was increased in both soil types only after 160 days of incubation, and this increase was more pronounced in the red soil (Fig. ). The NPs-induced increase in the relative metagenomic abundance of genes encoding hydrogenotrophic (R 2 BS = 0.591, P < 0.001; R 2 RS = 0.45, P < 0.05) and methylotrophic (R 2 BS = 0.458, P < 0.05; R 2 RS = 0.577, P < 0.05) methanogenesis showed a significant and positive correlation with DOC after 160 days of incubation, whereas the genes encoding acetoclastic methanogenesis did not display a significant correlation (Additional File 2: Fig. S27). Further, functional KEEG-based annotation of the methane metabolism-affiliated mRNA agreed well with the metagenomic results. The mRNA transcripts highly specific for one of the three methanogenesis pathways revealed prevalent expression of acetoclastic methanogenesis. However, the expression level of hydrogenotrophic and methylotrophic methanogenesis increased relative to acetoclastic methanogenesis in the red soil 0.5% NPs treatment compared to the control treatment (Additional File 3: Table S6). Transcript mapping of methanogenic mRNA onto the pooled 38 methanogen MAGs showed that in both the control treatment and the 0.5% NPs treatment, the methanogen populations expressed all three methanogenic (acetoclastic, hydrogenotrophic, methylotrophic) pathways after 160 days of incubation (Additional File 2: Figs. S28, S29). The methylotrophic pathway was characterized by an exclusive expression of mtaBC (Additional File 2: Fig. S29). These two genes encode the methyltransferase/methanol corrinoid protein, a specific biomarker for methanol-dependent methanogenesis. Here, we investigated the microbiome-driven effects of LDPE NPs on the DOC content and CH 4 production in two distinct paddy soil types, the black soil and the red soil. Through simulating the accumulation of LDPE NPs in soil microcosms, we particularly aimed to assess whether paddy soils majorly differing in their microbiome composition (see Additional File 1 for further details) show a common response pattern to the accumulation of LDPE NPs (Additional File 2: Fig. S11). Although the methanogenic communities in both soil types showed a marked difference in the duration of their lag phase for CH 4 production (Fig. b; Additional File 2: Fig. S2) and related activities (Fig. a; Additional File 2: Figs. S5, S6), we observed a common response pattern primarily characterized by a significant NPs-induced increase in soil DOC. The increased soil DOC subsequently triggered a correlated increase in the methanogen community (determined via qPCR of mcrA gene copy numbers) and CH 4 production (Fig. ; Additional File 2: Figs. S7, S8). Correspondingly, the metagenomic methanogen-to-bacteria abundance ratio shifted in both soils towards a significant increase in the methanogen community (Fig. ), which is further corroborated by the mRNA patterns obtained for the red soil after 160 days of incubation (Additional File 3: Table S6). Stimulative effect of LDPE NPs on the bacterial activity Light (UV)-induced aging and deterioration of LDPE after extended exposure time has been repeatedly reported , but the occurrence of such effects can be excluded from our study due to the incubation of the soil microcosms under anoxic conditions in the dark. The lack of a significant carbon release from the pristine NPs in the sterile microcosms after 30-day incubation already provides unambiguous evidence that the significant increase in soil DOC is due to a LDPE NPs-induced increase in microbial activity . While neglectable amounts of carbon were released abiotically from the LDPE NPs, soil DOC had — relative to the control — significantly increased in the LDPE NPs treatments in both the black soil and the red soil after the 30-day incubation period (Fig. a). Various bacteria and fungi have been demonstrated to be able to degrade and utilize polyethylene , such as Rhodococcus spp., Cladosporium spp., and Fusarium spp. . In addition, soil protists, as major consumers of bacteria and fungi, may play a critical role in mitigating the impacts of microplastics pollution . However, all of them degrade polyethylene only under aerobic conditions . The introduction of oxygen into the alkane structure and depolymerization are the two key limiting steps for its biodegradation . Indeed, previous studies have shown that polyethylene is not biodegradable under anaerobic conditions. For example, no degradation of polyethylene was observed in a liquid waste disposal bioreactor operated under anaerobic conditions for over 500 days, even at temperatures as high as 50 °C . Furthermore, we observed no significant change in the metagenomic abundance of genes described to be involved in the aerobic degradation of the polyethylene, such as the flavin-binding monooxygenase ( almA ) and alkane 1-monooxygenase ( alkB ) (Additional File 2: Fig. S30). Nonetheless, given the complexity and emerging nature of the research on nanoplastics, we admit that the anaerobic degradation of LDPE NPs by a yet unknown mechanism cannot be completely ruled out. This, however, would have to be a highly efficient mechanism, given that, for example, the observed NPs-induced carbon flux observed already after 30 days of incubation in the black soil corresponds to an equivalent of 16.2% of the total carbon added via nanoplastics to the 0.5% LDPE treatments (Additional File 3: Table S2). The NPs-induced increase in DOC is most likely a stimulative effect on the hydrolytic microbiota activity, leading to an increased transformation of complex polymeric carbon into DOC that the soil microbiota could utilize. This view is strongly supported by the significant NPs-induced increase in the microbially accessible carbon that with incubation time was detectable as DOC or had already been converted into CH 4 and CO 2 (Additional File 3: Table S2). In particular, the strong and positive correlation between the metagenomic abundance of genes involved in degrading aromatic C and the DOC contents suggests that complex aromatic compounds were a major source for the NPs-induced increase in DOC levels (Additional File 2: Fig. S14), a conclusion further supported by the observed increase in the DOM recalcitrance after the 30-day incubation period (Additional File 2: Fig. S4; Additional File 3: Table S4). Furthermore, both the NPs treatments and the incubation time had a significant effect on the functional composition of the aromatic genes in the black soil and the red soil but only the incubation time on the genes encoding the decomposition of complex carbohydrates. Thus, in addition to soil lipids, the most likely sources for the NPs-induced increase in soil DOC are plant-derived humic substances and lignin. The three polymers share similar functional groups, such as carboxyl, phenolic/aliphatic hydroxyl, and methoxyl groups but, most importantly, aromatic moieties . Concomitantly, the metagenomic abundance of genes encoding the decomposition of complex carbohydrates and aromatics was positively and significantly correlated with both the mcrA gene copy numbers and the CH 4 production (Fig. b; Additional File 2: Figs. S16, S17). This finding suggests that the NPs-induced increase in the genetic potential for polymer hydrolysis significantly contributed to CH 4 production. Specifically, the tenfold increase in the NPs concentration, from 0.5 to 5%, resulted in a 1.5-fold increase in CH 4 production in red soil and a threefold increase in black soil, following the 160-day incubation period (Fig. b; Additional File 3: Table S2). LDPE NPs significantly enriched for Syntrophomonadaceae and Methanocellaceae Despite significant differences in the bacterial taxa responding to the NPs (Additional File 2: Fig. S11), the methanogen community showed a highly similar response pattern between the two paddy soil types. Both the black soil and the red soil shared a significant shift in the metagenomic potential from acetoclastic methanogenesis towards hydrogenotrophic methanogenesis (Fig. ) and, at the taxonomic level, a specific abundance increase in Methanocella spp. (Fig. ). While this common community response was highly significant at the DNA level, the mRNA profiles obtained for the control and 0.5% NPs treatments of the red soil further corroborated the metagenomic results (Additional File 2: Fig. S29; Additional File 3: Table S6). Concomitantly, the LDPE NPs induced a significant metagenomic abundance increase in Syntrophomonas -affiliated MAGs (Additional File 2: Fig. S10) and, even more evident, their hydrogenase genes (Additional File 2: Fig. S12). The correlated abundance increases in Syntrophomonadaceae and Methanocellaceae MAGs in response to the NPs treatments were highly significant for both black and red soils (Fig. ; Additional File 2: Fig. S10). Syntrophomonas is known to be a keystone taxon for the anaerobic oxidation of fatty acids of four (butyrate) or more carbons by β -oxidation. Indeed, Syntrophomonas spp. are able to degrade saturated and unsaturated monocarboxylic fatty acids of up to 18 carbons by syntrophic association with hydrogen- or formate-utilizing partner organisms and depend on this association for thermodynamic reasons. To become thermodynamically feasible in our study, the β -oxidation of butyrate, valerate, or longer fatty acids, such as oleic acid and cis-vaccenic acid (Additional File 2: Figs. S5, S6), had to be syntrophically coupled to the activity of a hydrogenotrophic methanogen partner. While these two fatty acids are typical molecular marker for plant-derived SOC , the high valerate concentrations may result from the ongoing syntrophic oxidation of LCFAs, which is most evident for the black soil (Additional File 2: Fig. S31). Methanocella has been shown to be intrinsically adaptive to low H 2 concentrations. Their higher affinity to hydrogen allows these methanogens to outcompete Methanobacterium under substrate-limiting conditions . By contrast, Methanobacterium is adapted to survive in high hydrogen conditions . Indeed, the metagenomic abundance of Methanobacteriaceae was depleted in our NPs treatments. In particular, Methanocellaceae outcompeted Methanobacteriaceae during the later incubation period, likely because the partial H 2 pressure fell below the level thatMethanobacteriaceae can effectively utilize . Thus, it is reasonable to conclude that in both soil types, the syntrophy between Syntrophomonas and Methanocella played a major role in the conversion of SCFAs (Fig. S5) and LCFAs (Additional File 2: Fig. S6) to acetate. Notably, the genomic composition of the Syntrophomonas assemblages clearly differed between the black and red soils. Their differences in soil characteristics and microbiome composition, but also the varying length range of fatty acids degraded by different Syntrophomonas spp., may well explain the differing genomic composition . By contrast, the genomic composition of Methanocella spp. was similar, with the same MAGs being specifically enriched in both soil types (e.g., A28_bin_31 and A13_bin_23) (Additional File 2: Fig. S10). Although the metagenomic abundance of genes encoding methylotrophic methanogenesis showed no significant difference between control and NPs treatments, their relative abundance in the NPs treatments was significantly and positively correlated to soil DOC after the extended 160-day incubation period (Additional File 2: Fig. S27). This correlation was accompanied in the red soil by a shift in the pathway expression from hydrogen-dependent methylotrophy operated by Methanomassiliicoccaceae to hydrogen-independent methylotrophy operated by Methanosarcinaceae (Additional File 2: Figs. S22, S23). Given this shift, LDPE NPs induced a relative decrease in the expression of the Methanosarcina -affiliated acetoclastic pathway but relative increase in the expression of Methanosarcina -affiliated methylotrophy. This was related to an exclusive expression of the methanol-specific mtaBC genes (Additional File 2: Fig. S29) . Certain amounts of methanol will be released during the decomposition of lignin . The view of lignin as the possible source of methanol agrees well with the fact that the metagenomic abundance of genes involved in degrading aromatic C showed a strong and positive correlation with DOC ( P < 0.05) and CH 4 production ( P < 0.05) (Fig. b; Additional File 2: Figs. S14, S17). The mRNA profiles also confirmed that Methanocella were the dominant player in hydrogenotrophic methanogenesis (Additional File 2: Figs. S22, S23). Light (UV)-induced aging and deterioration of LDPE after extended exposure time has been repeatedly reported , but the occurrence of such effects can be excluded from our study due to the incubation of the soil microcosms under anoxic conditions in the dark. The lack of a significant carbon release from the pristine NPs in the sterile microcosms after 30-day incubation already provides unambiguous evidence that the significant increase in soil DOC is due to a LDPE NPs-induced increase in microbial activity . While neglectable amounts of carbon were released abiotically from the LDPE NPs, soil DOC had — relative to the control — significantly increased in the LDPE NPs treatments in both the black soil and the red soil after the 30-day incubation period (Fig. a). Various bacteria and fungi have been demonstrated to be able to degrade and utilize polyethylene , such as Rhodococcus spp., Cladosporium spp., and Fusarium spp. . In addition, soil protists, as major consumers of bacteria and fungi, may play a critical role in mitigating the impacts of microplastics pollution . However, all of them degrade polyethylene only under aerobic conditions . The introduction of oxygen into the alkane structure and depolymerization are the two key limiting steps for its biodegradation . Indeed, previous studies have shown that polyethylene is not biodegradable under anaerobic conditions. For example, no degradation of polyethylene was observed in a liquid waste disposal bioreactor operated under anaerobic conditions for over 500 days, even at temperatures as high as 50 °C . Furthermore, we observed no significant change in the metagenomic abundance of genes described to be involved in the aerobic degradation of the polyethylene, such as the flavin-binding monooxygenase ( almA ) and alkane 1-monooxygenase ( alkB ) (Additional File 2: Fig. S30). Nonetheless, given the complexity and emerging nature of the research on nanoplastics, we admit that the anaerobic degradation of LDPE NPs by a yet unknown mechanism cannot be completely ruled out. This, however, would have to be a highly efficient mechanism, given that, for example, the observed NPs-induced carbon flux observed already after 30 days of incubation in the black soil corresponds to an equivalent of 16.2% of the total carbon added via nanoplastics to the 0.5% LDPE treatments (Additional File 3: Table S2). The NPs-induced increase in DOC is most likely a stimulative effect on the hydrolytic microbiota activity, leading to an increased transformation of complex polymeric carbon into DOC that the soil microbiota could utilize. This view is strongly supported by the significant NPs-induced increase in the microbially accessible carbon that with incubation time was detectable as DOC or had already been converted into CH 4 and CO 2 (Additional File 3: Table S2). In particular, the strong and positive correlation between the metagenomic abundance of genes involved in degrading aromatic C and the DOC contents suggests that complex aromatic compounds were a major source for the NPs-induced increase in DOC levels (Additional File 2: Fig. S14), a conclusion further supported by the observed increase in the DOM recalcitrance after the 30-day incubation period (Additional File 2: Fig. S4; Additional File 3: Table S4). Furthermore, both the NPs treatments and the incubation time had a significant effect on the functional composition of the aromatic genes in the black soil and the red soil but only the incubation time on the genes encoding the decomposition of complex carbohydrates. Thus, in addition to soil lipids, the most likely sources for the NPs-induced increase in soil DOC are plant-derived humic substances and lignin. The three polymers share similar functional groups, such as carboxyl, phenolic/aliphatic hydroxyl, and methoxyl groups but, most importantly, aromatic moieties . Concomitantly, the metagenomic abundance of genes encoding the decomposition of complex carbohydrates and aromatics was positively and significantly correlated with both the mcrA gene copy numbers and the CH 4 production (Fig. b; Additional File 2: Figs. S16, S17). This finding suggests that the NPs-induced increase in the genetic potential for polymer hydrolysis significantly contributed to CH 4 production. Specifically, the tenfold increase in the NPs concentration, from 0.5 to 5%, resulted in a 1.5-fold increase in CH 4 production in red soil and a threefold increase in black soil, following the 160-day incubation period (Fig. b; Additional File 3: Table S2). Despite significant differences in the bacterial taxa responding to the NPs (Additional File 2: Fig. S11), the methanogen community showed a highly similar response pattern between the two paddy soil types. Both the black soil and the red soil shared a significant shift in the metagenomic potential from acetoclastic methanogenesis towards hydrogenotrophic methanogenesis (Fig. ) and, at the taxonomic level, a specific abundance increase in Methanocella spp. (Fig. ). While this common community response was highly significant at the DNA level, the mRNA profiles obtained for the control and 0.5% NPs treatments of the red soil further corroborated the metagenomic results (Additional File 2: Fig. S29; Additional File 3: Table S6). Concomitantly, the LDPE NPs induced a significant metagenomic abundance increase in Syntrophomonas -affiliated MAGs (Additional File 2: Fig. S10) and, even more evident, their hydrogenase genes (Additional File 2: Fig. S12). The correlated abundance increases in Syntrophomonadaceae and Methanocellaceae MAGs in response to the NPs treatments were highly significant for both black and red soils (Fig. ; Additional File 2: Fig. S10). Syntrophomonas is known to be a keystone taxon for the anaerobic oxidation of fatty acids of four (butyrate) or more carbons by β -oxidation. Indeed, Syntrophomonas spp. are able to degrade saturated and unsaturated monocarboxylic fatty acids of up to 18 carbons by syntrophic association with hydrogen- or formate-utilizing partner organisms and depend on this association for thermodynamic reasons. To become thermodynamically feasible in our study, the β -oxidation of butyrate, valerate, or longer fatty acids, such as oleic acid and cis-vaccenic acid (Additional File 2: Figs. S5, S6), had to be syntrophically coupled to the activity of a hydrogenotrophic methanogen partner. While these two fatty acids are typical molecular marker for plant-derived SOC , the high valerate concentrations may result from the ongoing syntrophic oxidation of LCFAs, which is most evident for the black soil (Additional File 2: Fig. S31). Methanocella has been shown to be intrinsically adaptive to low H 2 concentrations. Their higher affinity to hydrogen allows these methanogens to outcompete Methanobacterium under substrate-limiting conditions . By contrast, Methanobacterium is adapted to survive in high hydrogen conditions . Indeed, the metagenomic abundance of Methanobacteriaceae was depleted in our NPs treatments. In particular, Methanocellaceae outcompeted Methanobacteriaceae during the later incubation period, likely because the partial H 2 pressure fell below the level thatMethanobacteriaceae can effectively utilize . Thus, it is reasonable to conclude that in both soil types, the syntrophy between Syntrophomonas and Methanocella played a major role in the conversion of SCFAs (Fig. S5) and LCFAs (Additional File 2: Fig. S6) to acetate. Notably, the genomic composition of the Syntrophomonas assemblages clearly differed between the black and red soils. Their differences in soil characteristics and microbiome composition, but also the varying length range of fatty acids degraded by different Syntrophomonas spp., may well explain the differing genomic composition . By contrast, the genomic composition of Methanocella spp. was similar, with the same MAGs being specifically enriched in both soil types (e.g., A28_bin_31 and A13_bin_23) (Additional File 2: Fig. S10). Although the metagenomic abundance of genes encoding methylotrophic methanogenesis showed no significant difference between control and NPs treatments, their relative abundance in the NPs treatments was significantly and positively correlated to soil DOC after the extended 160-day incubation period (Additional File 2: Fig. S27). This correlation was accompanied in the red soil by a shift in the pathway expression from hydrogen-dependent methylotrophy operated by Methanomassiliicoccaceae to hydrogen-independent methylotrophy operated by Methanosarcinaceae (Additional File 2: Figs. S22, S23). Given this shift, LDPE NPs induced a relative decrease in the expression of the Methanosarcina -affiliated acetoclastic pathway but relative increase in the expression of Methanosarcina -affiliated methylotrophy. This was related to an exclusive expression of the methanol-specific mtaBC genes (Additional File 2: Fig. S29) . Certain amounts of methanol will be released during the decomposition of lignin . The view of lignin as the possible source of methanol agrees well with the fact that the metagenomic abundance of genes involved in degrading aromatic C showed a strong and positive correlation with DOC ( P < 0.05) and CH 4 production ( P < 0.05) (Fig. b; Additional File 2: Figs. S14, S17). The mRNA profiles also confirmed that Methanocella were the dominant player in hydrogenotrophic methanogenesis (Additional File 2: Figs. S22, S23). Our results clearly demonstrate that the accumulation of LDPE NPs in anoxic paddy soils leads to a significant increase in DOC and, in consequence, CH 4 production. The presence of 5% NPs triggered the highest carbon flux and CH 4 production, with a 1.5-fold to threefold increase in total CH 4 production relative to the 0.5% NPs treatments after the 160-day incubation period. However, relative to the total amount of NPs added to the paddy soil, 0.5% NPs had a greater effect on the carbon flux and CH 4 production than 5% NPs, thereby indicating that even smaller quantities of NPs can substantially influence CH 4 production in rice field soils. Experimental evidence suggests that humic substances, lignin, and soil lipids are major sources for the NPs-induced increase in microbially accessible carbon. Although greatly differing in microbiome composition and the initial microbial response to NPs’ presence, both soil types exhibited a remarkably similar methanogen response. The specific enrichment of Syntrophomonas and Methanocella indicates that LDPE NPs stimulate the syntrophic oxidation of SCFAs and LCFAs, with Methanocella acting as the hydrogenotrophic methanogen partner. Methanocella has previously been shown to play a key role in H 2 consumption during the syntrophic oxidation of SCFAs in Italian and Chinese rice paddy soils . While our research primarily focused on the effects of LDPE NPs on the methanogenic community and CH 4 production in the anoxic bulk soil, the rice rhizosphere is more complex due to the oxygen diffusion facilitated by rice roots in agricultural settings. The aerenchyma in rice plants allows oxygen to diffuse into the rhizosphere, creating a mosaic of oxic and anoxic zones . This oxygen availability could promote the aerobic degradation of LDPE NPs, particularly through microbial processes that introduce oxygen into the alkane structure, a critical limiting step in NP depolymerization . Therefore, LDPE may be degraded by aerobic bacteria associated with rice roots, potentially providing “fresh carbon” that could further stimulate CH 4 production in nearby micro-oxic and anoxic zones. Certain oxygen-tolerant methanogens, such as Methanocella , may utilize the carbon derived from LDPE NPs for CH 4 production, in addition to plant-derived carbon. Undoubtedly, our results have important implications for the production and release of methane in LDPE-contaminated paddy soils and, given the major contribution of this ecosystem to atmospheric methane, for global climate change. Further research is required to determine whether the common methanogenic response observed in black and red soils is similarly triggered by LDPE NPs in geographically diverse anthropogenic and natural wetlands. Additional File 1: Supplemental materials and methods; Supplemental discussion. Additional File 2: Supplemental Fig. S1 to S31. Additional File 3: Supplemental Tables S1 to S7. |
Can patient education initiatives in primary care increase patient knowledge of appropriate antibiotic use and decrease expectations for unnecessary antibiotic prescriptions? | 44b8b5f5-a4f2-4dab-a652-5747a0913e77 | 11878379 | Patient Education as Topic[mh] | The World Health Organisation has described antibiotic resistance as a global crisis where we are heading towards a “post-antibiotic era” in which common infections and minor injuries will become deadly once again . Antibiotic resistance is hastened by misuse and overuse and requires interventions at all levels of society . Around 80% of UK antibiotic prescriptions in humans are issued in primary care settings, and it is estimated that rates are similar worldwide . Furthermore, a 2014 study revealed that 55% of GPs reported pressure from patients to prescribe antibiotics, with 45% admitting to prescribing unnecessary antibiotics for a viral infection due to patient demand . The same study found that 4% of adults expect to have antibiotics prescribed on every visit to primary care, and 6% expect antibiotics on most occasions . Butler et al . concluded patients associate antibiotic prescriptions with treatment, even when unnecessary, and patients who leave without a prescription feel disappointed in their care, which threatens the doctor-patient relationship . Therefore, primary care settings are an appropriate target for initial patient education attempts due to significant patient demand for antibiotic therapy. Antibiotic misuse is a complex problem requiring a multi-faceted response. Therefore, this systematic review aims to synthesize the available data on the impact of various forms of patient education on patient knowledge and understanding of appropriate antibiotic use to assess whether patient education has a positive impact on reducing unnecessary antibiotic prescriptions. Search strategy This study is a systematic review aiming to synthesize and analyse available research to identify whether patient education can have a significant effect on antibiotic awareness and prescriptions and, if so, establishing the most effective methods of achieving this. This study design was chosen to allow for an unbiased synthesis of all currently available evidence to provide a robust answer to the research question. This review is registered, and the review protocol can be accessed via author correspondence. A database search of Embase, Medline, Web of Science, PubMed, and Cochrane Library was performed using the following MeSH terms: Patient Education, Drug Prescriptions, General Practice, Antibiotic Resistance, and Anti-bacterial Agents. The following free terms were searched with the previous MeSH headings: Patient Information, Practice Patterns, Drug Utilization, Prescri*, Drug Resistance, Microbials, Antibiotics. Inclusion and exclusion criteria Following the database search, a primary screen of the title and abstract of each article was carried out against the inclusion and exclusion criteria. Inclusion and exclusion criteria, outlined in , were chosen to allow the review to examine patient education initiatives in isolation. It was decided to exclude papers that were published prior to 2000 due to the technological advances that have allowed for multiple methods of education to become more mainstream and readily accessible, such as online resources and interactive web-based resources. It was also decided to limit included papers to those published in English only, as it was found that this restriction allowed for studies from across four continents to be included but avoided issues of translation. Next, a secondary screen was carried out where the remaining full papers were read and compared with the same inclusion and exclusion criteria. The reference lists of the selected studies were screened for additional studies according to the same criteria. All eligible studies were appraised using the Mixed Methods Appraisal Tool . To ensure the validity of the results, the entire search process was repeated by the original reviewer 3 weeks after the initial search. Where there was uncertainty, these studies were discussed with a second reviewer. Data extraction A data extraction table was used to collate the relevant findings from each study, using the headings: Author, Year, Title, Country, Type of Study, Sample Size, Methodology, Intervention, Primary Outcomes, and Secondary Outcomes. The primary and secondary outcomes included the impact of patient education on patient awareness, knowledge, and attitudes towards antibiotics, and the impact of the intervention on antibiotic prescriptions or reported expectations of antibiotics. A meta-analysis of the studies was not performed due to the heterogenous nature of the reported data. This study is a systematic review aiming to synthesize and analyse available research to identify whether patient education can have a significant effect on antibiotic awareness and prescriptions and, if so, establishing the most effective methods of achieving this. This study design was chosen to allow for an unbiased synthesis of all currently available evidence to provide a robust answer to the research question. This review is registered, and the review protocol can be accessed via author correspondence. A database search of Embase, Medline, Web of Science, PubMed, and Cochrane Library was performed using the following MeSH terms: Patient Education, Drug Prescriptions, General Practice, Antibiotic Resistance, and Anti-bacterial Agents. The following free terms were searched with the previous MeSH headings: Patient Information, Practice Patterns, Drug Utilization, Prescri*, Drug Resistance, Microbials, Antibiotics. Following the database search, a primary screen of the title and abstract of each article was carried out against the inclusion and exclusion criteria. Inclusion and exclusion criteria, outlined in , were chosen to allow the review to examine patient education initiatives in isolation. It was decided to exclude papers that were published prior to 2000 due to the technological advances that have allowed for multiple methods of education to become more mainstream and readily accessible, such as online resources and interactive web-based resources. It was also decided to limit included papers to those published in English only, as it was found that this restriction allowed for studies from across four continents to be included but avoided issues of translation. Next, a secondary screen was carried out where the remaining full papers were read and compared with the same inclusion and exclusion criteria. The reference lists of the selected studies were screened for additional studies according to the same criteria. All eligible studies were appraised using the Mixed Methods Appraisal Tool . To ensure the validity of the results, the entire search process was repeated by the original reviewer 3 weeks after the initial search. Where there was uncertainty, these studies were discussed with a second reviewer. A data extraction table was used to collate the relevant findings from each study, using the headings: Author, Year, Title, Country, Type of Study, Sample Size, Methodology, Intervention, Primary Outcomes, and Secondary Outcomes. The primary and secondary outcomes included the impact of patient education on patient awareness, knowledge, and attitudes towards antibiotics, and the impact of the intervention on antibiotic prescriptions or reported expectations of antibiotics. A meta-analysis of the studies was not performed due to the heterogenous nature of the reported data. Study selection The database search identified 449 papers, of which 135 were duplicates, leaving 314 papers. The primary screen of titles and abstracts excluded 256 papers, leaving 58 papers to be read in full. Following the second screen, 17 papers remained eligible. An additional 2 papers were identified during a reference list screen. A total of 18 studies met the inclusion criteria for this review: 1 qualitative, 1 mixed methods, and 16 quantitative studies. Study characteristics A table of study characteristics comprising of authors, date, location, study design, intervention, sample size, and outcome measures was created and is shown in Supplementary . Quality To assess the quality of the selected papers and identify potential weaknesses or biases, the Mixed Methods Appraisal Tool was used. The full quality assessment table is shown in Supplementary . Study findings To compare the results, the studies were grouped based on the intervention examined. Six categories were identified: public health campaigns, leaflets, posters, videos, mixed methods, and other. As the methodology, interventions, and results were too heterogenic to accurately compare, a meta-analysis was not performed. Data were extracted on patient knowledge and awareness of antibiotic use and the effect of the intervention on patient use or expectation of antibiotics, or the effect of the intervention on antibiotic prescription rates. The full data extraction table is shown in Supplementary . The database search identified 449 papers, of which 135 were duplicates, leaving 314 papers. The primary screen of titles and abstracts excluded 256 papers, leaving 58 papers to be read in full. Following the second screen, 17 papers remained eligible. An additional 2 papers were identified during a reference list screen. A total of 18 studies met the inclusion criteria for this review: 1 qualitative, 1 mixed methods, and 16 quantitative studies. A table of study characteristics comprising of authors, date, location, study design, intervention, sample size, and outcome measures was created and is shown in Supplementary . To assess the quality of the selected papers and identify potential weaknesses or biases, the Mixed Methods Appraisal Tool was used. The full quality assessment table is shown in Supplementary . To compare the results, the studies were grouped based on the intervention examined. Six categories were identified: public health campaigns, leaflets, posters, videos, mixed methods, and other. As the methodology, interventions, and results were too heterogenic to accurately compare, a meta-analysis was not performed. Data were extracted on patient knowledge and awareness of antibiotic use and the effect of the intervention on patient use or expectation of antibiotics, or the effect of the intervention on antibiotic prescription rates. The full data extraction table is shown in Supplementary . Public health campaigns Overall, the three public health campaigns studied were largely ineffective in changing public understanding and attitudes towards antibiotics. McNulty et al . and Parsons et al . examined antibiotic campaigns in England and concluded there was no significant change in public understanding of antibiotic use. Similarly, Curry et al . examined a campaign in New Zealand and concluded that there was “no change” in public understanding of the use of antibiotics. Each campaign used similar methods of education, such as radio broadcasts, posters, and leaflets, and each study reported low levels of public familiarity with the campaigns. However, Curry et al . achieved responses from 200 people in the pre- and post-intervention surveys. Although the response rate was sufficient for the survey, a sample size of 200 people may not be adequate to assess the impact of a country-wide public health campaign. Parsons et al . achieved responses from 442 people in the pre-intervention survey and 815 in the post-intervention survey when analysing a specific borough, which appears a more reliable sample size to adequately assess the effect of a local campaign. Leaflets Five studies examined the effect of an information leaflet . Of these, four found an overall positive effect of the information leaflet, and two demonstrated limited results. Min Lee et al . reported that whilst patients stated the pamphlet increased their understanding of antibiotics, 20.6% of intervention patients received unnecessary antibiotics for their symptoms compared to 17.7% of control patients. However, the study found when comparing ethnic groups, Indian intervention patients received significantly fewer antibiotics (OR 0.28, 95% CI 0.09–0.93). This study was carried out in Singapore, and participants were from Chinese, Malay, or Indian backgrounds. However, the information leaflet was published in English only, leading the authors to suggest that language barriers and varying English language proficiency may have affected the results, particularly as a positive effect was seen in one ethnic group. Posters Two studies examined the effect of posters . One study found a significant positive effect, whereas the second found the intervention had no effect. Ritchie et al . carried out a pre-and post-intervention survey after showing patients a randomly allocated poster, which found viewing posters halved patient expectations to receive antibiotics for a “bad cold” from 27% pre-intervention to 13% post-intervention . Contrastingly, Ashe et al . examined the effect of a waiting room poster on antibiotic use and found no significant difference in antibiotic prescribing rates between intervention and control months, concluding the poster was ineffective in reducing paediatric antibiotic prescriptions . Videos Three studies examined the impact of videos . Of these, one reported significant positive effects on patient expectations of antibiotics, one reported mixed effects and one study reported a modest impact. Lecky et al . examined the impact of five 30-second-long video animations on patient awareness of antibiotics and attitude towards their use . This mixed-methods study reported that patients found the animations memorable and informative, with quotes from patients demonstrating understanding of the messages in the animations, and saw significant positive effects on adult patient’s intentions to use antibiotics . However, this intervention had a limited effect on parent’s intentions to consult for their children with similar symptoms. Bauchner et al . saw no overall difference between intervention and control groups, however, subgroup analysis revealed an improvement in knowledge in intervention groups in an urban clinic compared to little difference in test scores in the suburban clinic . Contrastingly, Wheeler et al . examined the impact of a waiting room video message on parental attitudes towards antibiotic use in children and found that parents who viewed the intervention were significantly less likely to seek antibiotics for viral infections . This video intervention was eight minutes long and featured local doctors and nurses with a segment delivered by an infectious disease expert . This intervention may be seen as more trustworthy by parents than brief, humorous animations, as the intervention was delivered by healthcare professionals known to the participants which could improve the effectiveness of the intervention. Furthermore, the sample size of 771 used by Wheeler et al . was greater than the sample size of 56 used by Lecky et al . , and consisted solely of parents, therefore this study could have greater validity when applied to paediatric patients compared to Lecky et al . . Mixed interventions Four studies used multiple interventions to assess the impact of patient education on antibiotic awareness and use . McNicholas and Hooper used posters, GIFs, and memes displayed in examination rooms . This study found the rate of total and repeat consultation prescriptions for antibiotics decreased significantly after introducing the patient education materials . Gonzales et al . provided educational materials for primary care settings, consisting of waiting room and examination room posters and reference cards, and household educational materials consisting of bilingual brochures, reference cards, and a letter explaining the Be S.M.A.R.T campaign . This study found the campaign had a considerable effect on antibiotic prescribing for adults with acute bronchitis, but a negligible effect on prescribing for paediatric pharyngitis, in keeping with the apparent trend of patient education initiatives seemingly having a limited impact on paediatric prescribing . Taylor et al . carried out an RTC to evaluate the effectiveness of an educational pamphlet and video on parental attitudes about antibiotic use in children and found a significant difference in parental opinion on the correct use of antibiotics post-intervention . Using the same data, Taylor et al. evaluated the effectiveness of the same intervention in reducing antibiotic use in children and found no statistically significant decrease in antibiotic prescription between the intervention and control arms . Therefore, while the educational materials improved parents’ understanding of antibiotic use, the materials did not reduce consultations or prescriptions for unnecessary antibiotics for viral infections in children. Other Perera et al . carried out an RCT to assess the impact of a six-slide presentation on patient expectations of antibiotics for upper respiratory tract infections . The study found that viewing one of the intervention presentations halved the reported patient expectation for antibiotics . This intervention also demonstrated a reduction in expectations for antibiotics when the results were restricted to examining the 91 child participants, demonstrating an overall positive effect . Overall, the three public health campaigns studied were largely ineffective in changing public understanding and attitudes towards antibiotics. McNulty et al . and Parsons et al . examined antibiotic campaigns in England and concluded there was no significant change in public understanding of antibiotic use. Similarly, Curry et al . examined a campaign in New Zealand and concluded that there was “no change” in public understanding of the use of antibiotics. Each campaign used similar methods of education, such as radio broadcasts, posters, and leaflets, and each study reported low levels of public familiarity with the campaigns. However, Curry et al . achieved responses from 200 people in the pre- and post-intervention surveys. Although the response rate was sufficient for the survey, a sample size of 200 people may not be adequate to assess the impact of a country-wide public health campaign. Parsons et al . achieved responses from 442 people in the pre-intervention survey and 815 in the post-intervention survey when analysing a specific borough, which appears a more reliable sample size to adequately assess the effect of a local campaign. Five studies examined the effect of an information leaflet . Of these, four found an overall positive effect of the information leaflet, and two demonstrated limited results. Min Lee et al . reported that whilst patients stated the pamphlet increased their understanding of antibiotics, 20.6% of intervention patients received unnecessary antibiotics for their symptoms compared to 17.7% of control patients. However, the study found when comparing ethnic groups, Indian intervention patients received significantly fewer antibiotics (OR 0.28, 95% CI 0.09–0.93). This study was carried out in Singapore, and participants were from Chinese, Malay, or Indian backgrounds. However, the information leaflet was published in English only, leading the authors to suggest that language barriers and varying English language proficiency may have affected the results, particularly as a positive effect was seen in one ethnic group. Two studies examined the effect of posters . One study found a significant positive effect, whereas the second found the intervention had no effect. Ritchie et al . carried out a pre-and post-intervention survey after showing patients a randomly allocated poster, which found viewing posters halved patient expectations to receive antibiotics for a “bad cold” from 27% pre-intervention to 13% post-intervention . Contrastingly, Ashe et al . examined the effect of a waiting room poster on antibiotic use and found no significant difference in antibiotic prescribing rates between intervention and control months, concluding the poster was ineffective in reducing paediatric antibiotic prescriptions . Three studies examined the impact of videos . Of these, one reported significant positive effects on patient expectations of antibiotics, one reported mixed effects and one study reported a modest impact. Lecky et al . examined the impact of five 30-second-long video animations on patient awareness of antibiotics and attitude towards their use . This mixed-methods study reported that patients found the animations memorable and informative, with quotes from patients demonstrating understanding of the messages in the animations, and saw significant positive effects on adult patient’s intentions to use antibiotics . However, this intervention had a limited effect on parent’s intentions to consult for their children with similar symptoms. Bauchner et al . saw no overall difference between intervention and control groups, however, subgroup analysis revealed an improvement in knowledge in intervention groups in an urban clinic compared to little difference in test scores in the suburban clinic . Contrastingly, Wheeler et al . examined the impact of a waiting room video message on parental attitudes towards antibiotic use in children and found that parents who viewed the intervention were significantly less likely to seek antibiotics for viral infections . This video intervention was eight minutes long and featured local doctors and nurses with a segment delivered by an infectious disease expert . This intervention may be seen as more trustworthy by parents than brief, humorous animations, as the intervention was delivered by healthcare professionals known to the participants which could improve the effectiveness of the intervention. Furthermore, the sample size of 771 used by Wheeler et al . was greater than the sample size of 56 used by Lecky et al . , and consisted solely of parents, therefore this study could have greater validity when applied to paediatric patients compared to Lecky et al . . Four studies used multiple interventions to assess the impact of patient education on antibiotic awareness and use . McNicholas and Hooper used posters, GIFs, and memes displayed in examination rooms . This study found the rate of total and repeat consultation prescriptions for antibiotics decreased significantly after introducing the patient education materials . Gonzales et al . provided educational materials for primary care settings, consisting of waiting room and examination room posters and reference cards, and household educational materials consisting of bilingual brochures, reference cards, and a letter explaining the Be S.M.A.R.T campaign . This study found the campaign had a considerable effect on antibiotic prescribing for adults with acute bronchitis, but a negligible effect on prescribing for paediatric pharyngitis, in keeping with the apparent trend of patient education initiatives seemingly having a limited impact on paediatric prescribing . Taylor et al . carried out an RTC to evaluate the effectiveness of an educational pamphlet and video on parental attitudes about antibiotic use in children and found a significant difference in parental opinion on the correct use of antibiotics post-intervention . Using the same data, Taylor et al. evaluated the effectiveness of the same intervention in reducing antibiotic use in children and found no statistically significant decrease in antibiotic prescription between the intervention and control arms . Therefore, while the educational materials improved parents’ understanding of antibiotic use, the materials did not reduce consultations or prescriptions for unnecessary antibiotics for viral infections in children. Perera et al . carried out an RCT to assess the impact of a six-slide presentation on patient expectations of antibiotics for upper respiratory tract infections . The study found that viewing one of the intervention presentations halved the reported patient expectation for antibiotics . This intervention also demonstrated a reduction in expectations for antibiotics when the results were restricted to examining the 91 child participants, demonstrating an overall positive effect . The results show that patient education is an effective method of increasing knowledge and reducing antibiotic prescriptions in adults, if an effective method is chosen. However, in paediatric prescribing, the results demonstrate that patient education is less effective. The interventions which demonstrated the most significant effects in both adult and paediatric populations involved active forms of education, such as interactive leaflets and animations, where the participants were engaged with the intervention and often discussed the intervention with either their doctor or the researchers. Research supports that “active learning” techniques improve student performance when compared to traditional lecture-style teaching . “Active learning” is “any instructional method that engages students in the learning process” as opposed to passively receiving information . Therefore, patients should also be encouraged to take an active role in education interventions. Supporting this, a systematic review of effective strategies for patient education concluded that verbal education alone is the least effective strategy, whereas written materials, videotapes, and multiple strategies were more effective, with 62% of patients who received patient education using multiple strategies having better outcomes than those who received standard care . This, therefore, helps explain the varying results of the studies examined in this review. For example, Ashe et al . and Ritchie et al . both examined the impact of posters as a form of patient education. However, Ashe et al . made no attempt to encourage patients to view the poster, and it is unclear whether patients viewed the poster, affecting the validity of the results. Contrastingly, the methodology used by Ritchie et al . involved specifically handing patients different posters and encouraging them to read and discuss the content with the researchers, therefore engaging and involving the patients in the intervention. This is similarly seen in the four successful leaflet interventions , as each of these interventions involved the patient being directed to an educative resource and taking an active role in the discussion. Similarly, when examining health beliefs and behavioural change, the Health Belief Model (HBM) and the Transtheoretical Model of Behavioural Change (TMBC) can help identify how to best target patient education to maximize the effectiveness of education interventions. The HBM explains how a person’s action depends on their perception of the benefits and barriers related to the health behaviour . In this case, a person must understand the risks of antibiotic misuse and the benefits of appropriate antibiotic use, alongside recognizing the threat of antibiotic resistance and the side effects of unnecessary antibiotic prescriptions, compared to a potential belief that antibiotics are necessary for viral symptoms. Similarly, the TMBC outlines the stages that a person undergoes when making a change. In order to enact behavioural change, a person must enter the “contemplation” stage, where they identify a problem and start to seek a solution. A study found that 47.8% of respondents incorrectly identified antibiotics as being effective in treating viral infections . Therefore, it is reasonable to suggest that this population would not enter this “contemplation” stage as they do not see antibiotic misuse as a problem that applies to them, as they believe they are seeking antibiotics for a genuine need. This may further explain why the passive interventions outlined in this review had limited impact, as these interventions relied on people not only engaging with the intervention independently, but being able to apply the intervention to their circumstances and recognize it as being applicable to their situation in order to begin a cycle of behavioural change. As previously explained, the three public health campaigns studied proved largely ineffective. Despite their broad range of interventions, such as broadcasts, adverts, and posters, these interventions required people to independently engage with and consider the messages. Contrastingly, the more effective interventions, such as the interactive presentation studied by Perera et al ., specifically linked the patient’s symptoms and the futility of antibiotic treatment, whilst also providing information on suitable alternative treatments . This enables patients to make the connection between the symptoms they are experiencing and the need to change their expectations for antibiotics, allowing them to start the process of behavioural change. This demonstrates the importance of delivering patient education interventions in a manner where the patient is actively involved in the intervention, to allow them to recognize the issue, apply it to their situation, and modify their behaviour. Interestingly, studies involving paediatric patients proved largely ineffective, with the exceptions of Francis et al . and Johnson et al . . The design of these studies allowed the participants to receive education on appropriate antibiotic use and alternative remedies during a consultation, and consolidate this with discussion and educational leaflets. In these examples, the participants are actively shown how their symptoms do not need antibiotics through education and discussion. Contrastingly, the interventions designed by Ashe et al . and Taylor et al . required participants to independently engage with and apply the interventions, demonstrating a passive form of education with limited effectiveness. Furthermore, the studies that demonstrated a positive effect allowed parents to discuss their concerns with a doctor, which may increase trust in the intervention as it is supplemented with support from a trusted healthcare professional. For example, Taylor et al . posted their educational intervention to parents, and doctors were blinded as to participation status, removing the ability to use the intervention in a consultation, unlike the methodology of Johnson et al . . Interestingly, the results of Taylor et al . and Taylor et al . demonstrated a positive change in parental attitudes towards antibiotic use, but no change to prescribing or consultation rates, meaning it is unclear whether the posted leaflet intervention was sufficient to allow the parents to associate the information provided with the symptoms experienced by their child. Similarly, Min Lee et al . used medical students to hand out leaflets to patients independently of their consultation, whereas the four leaflet interventions with positive effects incorporated their leaflets into the consultation. Therefore, these studies further demonstrate the benefit of an active approach to patient education and suggest that more education and resources are needed to be effective in paediatric consults to reassure parents. While this review grouped studies to allow for effective comparison of the results, it is clear that one common characteristic unites the most effective interventions—the extent to which the patient is involved in the intervention. Studies that proved entirely ineffective, such as Ashe et al . from the poster category, McNulty et al . from the public health campaign category, and Min Lee et al . from the leaflet category, all demonstrated passive methodologies, with each study relying on the patient taking the initiative to independently engage with the resource provided. The studies that saw significant effects, such as Ritchie et al . from the poster category, Perera et al . from the mixed interventions category, and Johnson et al . from the leaflet category, all directed patients to view specific educative initiatives which were relevant to them, engaged them in discussion and allowed patients to take an active role in their learning and be fully involved in the delivery of the intervention. Studies that had more moderate effects, such as Bauchner et al . from the video category, did attempt to engage patients in targeted video interventions, but did not also engage the patients in discussion or provide further information to consult at a later date. This demonstrates that whilst these patients were directed to watch a specific, targeted video, they were not offered the opportunity to consolidate this with discussion or further resources, limiting the involvement of the patient in the intervention, and thus limiting the effectiveness. Therefore, the most effective patient education initiatives provide opportunities for active learning and seek to actively involve the patient in the process. Comparisons To the best of our knowledge, this is the first review to synthesize the effectiveness of multiple patient education initiatives on the understanding and use of antibiotics, however, many studies investigating the efficacy of patient education materials on common conditions, management options, and health promotion were identified during the initial literature search. A systematic review on providing patient education materials for non-specific lower back pain found a high degree of variability across outcomes but concluded providing materials is favourable . Similarly, a one-year prospective study found a patient education course improved asthma control and decreased exacerbations in patients with severe uncontrolled asthma . With regards to antibiotics, a systematic review by de Bont et al . concluded that patient information leaflets are effective in reducing antibiotic prescriptions, actual antibiotic use, and intentions to reconsult for future similar symptoms . These studies further demonstrate that patient education is an effective and valuable tool, as found in this review, and support the suggestion that patient education is an effective and useful tool to implement in the strategy against antibiotic resistance. Practical and theoretical implications This review demonstrates patient education is a useful tool to improve patient understanding and awareness of antibiotic use, which can be used to further inform antibiotic awareness campaigns and support antibiotic resistance strategies. In practice, educative initiatives have been shown to be useful with minimal impacts on patient satisfaction, indicating these interventions should be introduced into primary care more widely. Strengths and limitations The main strength of this review is the search strategy, as five databases were searched, allowing for a thorough literature review. However, this review is limited as the studies included were conducted in Western populations, particularly the USA. Therefore, the results may not be culturally applicable worldwide. This review is further limited by the heterogeneity of the data, as differences in population samples, primary and secondary outcomes, and interventions make statistical analysis more difficult. Finally, due to limited resources, only one reviewer carried out the search and data extraction. Although this was repeated to ensure the validity of the results, a secondary reviewer would have been beneficial. Future work As this review demonstrates patient education is an effective tool in improving antibiotic awareness and use, it would be useful to carry out further trials directly comparing education interventions to determine the most effective and cost-effective interventions. To the best of our knowledge, this is the first review to synthesize the effectiveness of multiple patient education initiatives on the understanding and use of antibiotics, however, many studies investigating the efficacy of patient education materials on common conditions, management options, and health promotion were identified during the initial literature search. A systematic review on providing patient education materials for non-specific lower back pain found a high degree of variability across outcomes but concluded providing materials is favourable . Similarly, a one-year prospective study found a patient education course improved asthma control and decreased exacerbations in patients with severe uncontrolled asthma . With regards to antibiotics, a systematic review by de Bont et al . concluded that patient information leaflets are effective in reducing antibiotic prescriptions, actual antibiotic use, and intentions to reconsult for future similar symptoms . These studies further demonstrate that patient education is an effective and valuable tool, as found in this review, and support the suggestion that patient education is an effective and useful tool to implement in the strategy against antibiotic resistance. This review demonstrates patient education is a useful tool to improve patient understanding and awareness of antibiotic use, which can be used to further inform antibiotic awareness campaigns and support antibiotic resistance strategies. In practice, educative initiatives have been shown to be useful with minimal impacts on patient satisfaction, indicating these interventions should be introduced into primary care more widely. The main strength of this review is the search strategy, as five databases were searched, allowing for a thorough literature review. However, this review is limited as the studies included were conducted in Western populations, particularly the USA. Therefore, the results may not be culturally applicable worldwide. This review is further limited by the heterogeneity of the data, as differences in population samples, primary and secondary outcomes, and interventions make statistical analysis more difficult. Finally, due to limited resources, only one reviewer carried out the search and data extraction. Although this was repeated to ensure the validity of the results, a secondary reviewer would have been beneficial. As this review demonstrates patient education is an effective tool in improving antibiotic awareness and use, it would be useful to carry out further trials directly comparing education interventions to determine the most effective and cost-effective interventions. Patient education initiatives are an effective way to improve patient awareness of antibiotic misuse and reduce antibiotic prescriptions, if they are delivered in an effective manner. Not all forms of education are equal, and the most significant results were demonstrated by initiatives that sought to involve and engage the patient in the educative intervention. Supplementary material is available at Family Practice online. cmae047_suppl_Supplementary_Appendix |
Effect of exogenous treatment with zaxinone and its mimics on rice root microbiota across different growth stages | a6aaa982-3a64-41d4-a81f-4bfb8933f3c8 | 11682185 | Microbiology[mh] | Ensuring food security for the world population is challenged by a variety of factors, including climate change, environmental pollution, and, in particular, the rapidly escalating demand to address the expanding human population . According to the United Nations Food and Agriculture Organization (FAO) estimates, agriculture will need to increase food production by nearly 70% by 2050. There is a projected need for a 112% increase in food production to meet anticipated caloric requirements in specific regions such as South Asia and sub-Saharan Africa . Rice ( Oryza sativa L.), a member of the Poaceae family, is a global major food crop, supplying staple sustenance to nearly half of the world’s population . Approximately 60% of the world’s rice is cultivated in Southeast Asia, and its production and consumption are on the rise in Africa as well . Currently, the productivity of rice is threatened by pests, soil degradation , , diminishing water , and environmental pollution . Weeds (37.02%), insects (27.9%), and fungal pests (15.6%) are recognized as primary contributors to yield losses . In sub-Saharan Africa, parasitic weeds of the genus Striga cause significant yield reductions , a situation expected to worsen with the influence of climate change . Given that modeling projections for rice production indicate an emerging constraint on yields , global adaptation and mitigation strategies are imperative. A promising solution is the use of growth-promoting biostimulants that include molecules and/or microorganisms enhancing plant fitness in terms of plant growth, productivity, and nutrient utilization efficiency. Additionally, biostimulants may have the capacity to bolster tolerance against a broad spectrum of abiotic and biotic stresses – . The employment of plant-associated microorganisms (plant microbiota) represents a particularly promising, long-term solution to the challenges of attaining food security and preserving the environment . The plant microbiota is shaped by eco-evolutionary processes driven by the metabolic affinity between partners and chemical signals released by plant roots into the rhizosphere to screen the microbial community , . Besides beneficial microbes, the application of phytohormones or hormone-like compounds, such as auxins and cytokinins or sterols and polyamines, respectively, showed positive effects on plants, including the promotion of plant growth and productivity . The plant pigments carotenoids are a source of a series of regulatory metabolites. Oxidative cleavage of these carotenoids leads to a class of compounds called apocarotenoids that encompass precursors for the phytohormones abscisic acid (ABA) and strigolactones (SLs), as well as bioactive metabolites and growth regulators, such as β-cyclocitral, anchorene, and zaxinone . Indeed, apocarotenoids play a role in nearly all aspects of plant physiology and development, contribute to the plant response to both abiotic and biotic stresses, and mediate plant-plant and plant-microbe interactions . The carotenoid-derived hormone SLs regulates various aspects of plant development, including shoot branching, root architecture, and leaf senescence, and modulates plant responses to both abiotic and biotic stress – . Additionally, SLs play a pivotal role in rhizospheric communications, manifesting both negative and positive effects , . On one hand, they induce the germination of seeds of root parasitic plants, which is followed by infestation that causes substantial yield losses in numerous crops , . On the other hand, they act as chemical signals attracting arbuscular mycorrhizal (AM) fungi and facilitating the establishment of beneficial AM symbiosis . Recent studies have indicated that SLs also influence the composition of the rhizosphere microbial community , and regulate plant-pathogen interactions , . Zaxinone is emerging as a crucial regulator of rice growth, metabolism, hormone homeostasis, and AM symbiosis , . Its plant growth-promoting effect is mediated by an enhancement of root sugar uptake and metabolism, and a modulation of SL and cytokinin content , . The limited availability of zaxinone, due to a complex labor-intensive organic synthesis, has been overcome by the development of easily synthesizable and highly efficient zaxinone mimics (MiZax) . MiZax3 and MiZax5 exhibit zaxinone-like activities, such as rescuing root growth in zaxinone-deficient rice mutants, promoting overall growth, and reducing SL content in wild-type plants. Exogenous applications of zaxinone, MiZax3, and MiZax5 demonstrated their utility and growth-promoting effects on rice and various horticultural crops under both normal and desert conditions , . Additionally, these compounds have the ability to alleviate the infestation by the root parasitic plant Striga by decreasing SL biosynthesis , , . Interestingly, MiZax compounds were at least as efficient as zaxinone in reducing Striga infestation and had no negative impact on mycorrhization . These data highlight that zaxinone, and in particular, the highly efficient MiZax are excellent biostimulants and helpful tools for establishing sustainable agriculture and alleviating the infestation by parasitic plants. However, their impact on soil microbial community composition is still unknown. With the aim to promote the use of these novel growth-promoting compounds as biostimulants, we investigated whether the exogenous application of zaxinone or MiZax(s) on the soil could influence soil microbiota communities, the recruitment of rice root-associated microbes, and shoot and grain metabolism. Our results show that treatment with zaxinone and MiZax mostly impacted the prokaryotic component of the root endosphere. However, network analysis highlighted a partial perturbation of taxa-taxa interactions at the vegetative stage (tillering), followed by a full recovery of a complex network, structured by relevant beneficial microbial hubs, during the fruit set (milky stage). Using microbial ecology tools, we provide here new insights into the role of zaxinone and MiZax in the interplay between plants and rice root-associated microbiota. Plant growth conditions, hormonal treatments, and sampling The impact of zaxinone, MiZax3, and MiZax5 on native paddy soil and rice rhizomicrobiota was studied in a greenhouse mesocosm experiment. Four soil treatments were considered, namely zaxinone, MiZax3, MiZax5, and the solvent acetone as control (ACE), for both rice plants and unplanted soil. Plants were sampled at three phenological stages, the tillering stage (60 days after transplanting, T1) the milky-stage maturation (120 days after transplanting, T2), and the over-ripe stage (180 days after transplanting, T3). For each treatment a total of 33 plants were grown: 15 for phenotyping sampled at T3 and 18 for microbiota profiling (sampled at T1 and T2, 9 biological replicates each). For the unplanted soil treatment, 18 replicates were collected (9 for each sampling point). Mesocosm systems were set up using native paddy soil harvested from the experimental fields of the CREA-CI research center (Vercelli, Italy) which was used in previous studies , . Soil physico-chemical parameters measured on a representative batch used for this study are reported in Table . Rice seeds ( Oryza sativa cv. ‘Nipponbare’) were sown in alveolar trays filled with soil. After 1 month of growth under controlled conditions, plants were transferred to the final plastic pots (10 × 9 × 17 cm) filled with the same soil. For unplanted soil treatment, one alveolar tray was left unsown and the resulting soil cores were transferred into pots with fresh soils (as for rice seedlings) for the unplanted soil conditions. Plants and unplanted soils were grown in the greenhouse at the Department of Life Sciences and Systems Biology of the University of Torino from June 2021 to October 2021 (rice growing season) without monitoring light, temperature and humidity. Plants were watered once a week with tap water and once with distilled water containing zaxinone, MiZax3, and MiZax5 molecules dissolved individually to reach the final concentration of 5µM (10 −6 ), which has already been shown to promote growth activity in rice plant and to alleviate infestation by the root parasitic plant Striga , . Fifty mL of the solution was poured into the soil of each pot once every two weeks for about 5 months (10 treatments) to cover the vegetative and rice reproductive growth stages. Compartment isolation and microbiota profiling Plants were sampled for microbiota profiling at the tillering stage (T1) and at the milky-stage maturation (T2). At sampling, plants were removed from pots, vigorously shaken, and 10–15 g of roots collected within 3–4 cm from the base of the stem into a 50-mL Falcon tube. Unplanted soil samples were collected using a sterile spoon from the middle core of the pot, discarding edges that were in contact with plastic or any other portions where plant roots were visible. Samples were stored at + 4 °C and processed within 24 h to separate plant root compartments under sterile conditions. Samples were then processed to isolate the rhizosphere from the root endosphere according to the protocol by Bulgarelli et al. with minor modifications. Roots fragments were first washed into 10 mM sterile phosphate-buffer saline with 0.02% Tween-80 added (PBS-T), under continuous stirring on a horizontal shaker (15 min, 70 rpm). To obtain the rhizosphere soil slurry, roots were removed and tubes were centrifuged (4000 g, 10 min). The rhizosphere was then resuspended in 2 mL PBS-T and snap-freezed in liquid nitrogen. Roots were enriched in the endospheric compartment by two washes of 10 sonication cycles (30 s pulses, 30 s rest each) in PBS-T, discarding and replacing the buffer after each wash. Samples were finally rinsed in 50 mL of sterile dH 2 0, blotted on sterile filter paper, and stored at −80 °C until DNA isolation. For each time point, at least two aliquots of the same PBS-T buffer used to wash samples were collected and further processed along samples as blanks. DNA was extracted under sterile conditions from 0.5 g of unplanted soil or 500 µL of rhizospheric soil slurry with the NucleoSpin Soil kit (Macherey-Nagel, Düren, Germany) and from 20 mg freeze-dried root material using the NucleoSpin Plant II Mini kit (Macherey-Nagel) following manufacturer’s recommendations. DNA quantity and purity were assessed using a Nanodrop-1000 instrument (Thermo Scientific, Wilmington, Germany). DNA materials were sent for gene marker amplification and sequencing to IGA Technology Services (Udine, Italy; http://igatechnology.com/ ). For Prokaryotic communities profiling the V4 16S region was selected using primers pairs 515F (5’-GTGYCAGCMGCCGCGGTAA-3’) and 806R (5’-GACTACNVGGGTWTCTAAT-3’) , linked with the Illumina adapters overhang. Amplification on organellar rDNA was prevented by peptide nucleic acids (PNAs) clamping using universal pPNA and mPNA clamps for plastidial and mitochondrial sequences following the manufacturer’s protocol (PNA Bio Inc, Newbury Park, CA). For fungi, the ITS2 region of the rRNA gene was adopted as marker using primers pair fTIS7 (5’-GTGARTCATCGAATCTTTG-3’) and ITS4 (5’-TCCTCCGCTTATTGATATGC-3’) . Libraries from both target regions (16 S and ITS2) were then constructed and sequenced on an Illumina NovaSeq6000 platform (Illumina, San Diego, CA, USA) with a 2 × 250 bp sequencing layout. Bioinformatics Amplicon libraries were inspected for quality using FastQC v0.11.9 and multiQC v1.11 software and raw reads imported into QIIME 2 (Quantitative Insights Into Microbial Ecology) v2022.02 for denoising, Amplicon Sequence Variants (ASVs) detection and taxonomy mapping. First, primers were fully removed from reads using the cutadapt ‘trim-paired’ plugin discarding untrimmed sequences. For ITS2 libraries the full-length ITS2 region was selected using ITSxpress plugin with the built-in fungal database to increase taxonomic resolution . Clean reads were then denoised and merged into ASVs using DADA2 plugin in ‘pooled’ chimera method detection and applying a reads truncation of 180 and 160 bp based on quality profiles for R1 and R2 sequences, respectively. No reads truncation was applied for ITS2 libraries (--p-trunc-len 0). Variants were then taxonomically annotated using a Naïve-Bayes classifier via the ‘feature-classifier classify-sklearn’ plugin . The SILVA v138 database (99% clustering) pre-formatted for QIIME , and the UNITE + INSDC v8.3 database in developer and dynamic mode were used as reference databases for 16S and ITS2 libraries, respectively. Tables were further taxonomy-filtered to obtain the final feature table analyzed. For the 16S dataset, ASVs matching organellar (mitochondria and chloroplast) rDNA, or without any match (unassigned at the domain level) were removed while for ITS2 libraries non-fungal sequences were discarded. The obtained feature tables was imported into R v4.2.1 environment (R Core Team, 2023) and contaminants were removed using the extraction-blank samples with the microDecon package . Alpha-and beta-diversity analyses were performed using ‘phyloseq’ v1.40.0 , ‘vegan’ v2.6-2 , and ‘QsRutils’ v0.1.5 . The ASVs count table was first filtered by removing low-abundance ASVs using ‘HTSFilter’ v1.36.0 and then normalized with a rarefaction-free approach using DEseq2 v1.36.0 , . Analyses of β- diversity were performed on the resulting normalized table. PERMANOVA and pairwise PERMANOVA analyses were performed using the adonis function of the R package ‘vegan’ and the package ‘pairwiseAdonis’ v0.4.1 , respectively. Principal coordinate analysis (PCoA) was performed by multidimensional scaling (MDS) of Bray–Curtis distance matrices using cmdscale R function. Constrained ordination (cPCoA) were computed using the ‘vegan’ capscale function (which implements CAP (Canonical analysis of principal coordinates) by constraining the factor of interest. Significance of constraints was assessed using the ANOVA-like permutation test implemented in the anova.cca function from the vegan package (999 permutations, P < 0.05). Compartment enrichment and differential abundance analyses were performined using DESeq2 package applying a zero-tolerant geometric mean formula, as detailed in phyloseq package vignettes, and adopting an FDR threshold of 0.05 to define enriched/depleted taxa. Phylogenetic heatmaps were obtained using the ggtreeExtra R package keeping only highly-abundant taxa (relative abundance > 5%) annotated at least at family level. Briefly, ASV sequences of differentially abundant taxa were aligned using MUSCLE (default parameters), and approximately-ML phylogenetic trees were obtained using FastTree v2.1.11 using the GTR model and enabling ‘-no2nd’ option and setting SPRs number as 4. Graphical elaborations were performed using ‘ggtern’ v3.3.5 and ggplot2 v3.3.6 packages. Network analysis Co-abundance networks of the root endosphere prokaryotic community for each treatment and time points were inferred using network analysis. The most abundant taxa (occurring in > 50% of the samples with at least 350 reads across all the considered samples) were selected for each of the subsampled tables and co-abundance networks inferred using the SPIEC-EASI (Sparse Inverse Covariance Estimation for Ecological Association and Statistical Inference) algorithm in SpiecEasi R package v1.1.2 using the Meinshausen and Bühlmann neighborhood selection model, a lambda path of 100 and other parameters at default values. The final model was selected by random subsampling and interaction re-estimation using stability Approach to Regularization Selection (StARS) and pulsar packages using 100 random subsamples at 0.05% variability threshold. The obtained adjacency matrices were imported into igraph objects and networks plotted using ggraph R package v2.1.0 . Network statistics and node’s topological parameters were calculated using igraph R package v1.5.1 and differences across conditions were assessed using the Student’s t -test ( P < 0.05). For each of the obtained networks, 1000 re-wired random networks (same number of nodes and edges as the real ones) were obtained using the Erdős–Rényi model with the ‘sample_gnm’ function in igraph and metrics calculated as detailed above. Differences of the topological metrics between random and real networks were assessed using the Z-test ( p < 0.05) within the BSDA v1.2.2 R package . Keystone species (hubs-taxa) were identified as the top 5% ASVs showing maximum closeness centrality and betweenness centrality metrics according to a log-normal distribution , . Gas chromatography-mass spectrometry (GC-MS) analysis Powdered shoot and root material (50 mg ± 10%) was extracted in 700 µL of methanol by adding 10 µg/mL of methyl α-D-glucopyranoside as internal standard. The samples were homogenized by vortexing and by using a Ball Mill (Retsch, MM 300) with 5 mm zirconia balls (3 min, 20 Hz) and then centrifuged (10 min, 21000 g) recovering 600 µL of the resulting supernatant. The sample was mixed by vortexing with 300 µL of chloroform and 750 µL of water and centrifuged (10 min, 21000 g ). Aliquots of 100 µL and 300 µL from the polar phase were dried in a SpeedVac™ concentrator for GC-MS analysis, respectively. Samples for GC-MS were derivatized according to Lisec et al. . The samples were re-suspended in 40 µL of methoxyaminhydrochloride (20 mg/mL in pyridine) and shaked for 2 h (37 C°, 900 rpm). After that, 70 µL MSTFA were added, and the samples were mixed for additional 30 min (37 C°) and transferred to a glass vial for GC-MS analysis. GC-MS analysis was performed on an Agilent 7890A GC system coupled to a Pegasus HT high throughput TOF/MS (LECO). 1 µL of the sample was injected at 230 °C in splitless mode with He as a carrier gas (2 mL/min). The flow rate was kept constant with electronic pressure control enabled. Chromatography was performed in a 30 m MDN-35 capillary column, with the following temperature program: isothermal for 2 min at 80 °C, followed by a 15 °C per min ramp to 330 °C, and isothermal for 6 min at 330 °C. Transfer line and ion source temperatures were set to 250 °C. The recorded mass range was set from m/z 70 to m/z 600 at 20 scans per second. The remaining monitored chromatography time was preceded by a 170 s solvent delay with filaments turned off. The manual mass defect was set to filament bias current to − 70 V, and detector voltage to ~ 1700–1850 V. The obtained chromatograms were converted to .raw file format and analyzed using the Xcalibur 2.2 software (Thermo Fisher). GC-MS peaks were annotated by comparing retention indexes relative to a mixture of fatty acid methyl esters (FAMES) and spectra similarity against metabolites from the Golm metabolome database (GMD) . Statistical analysis was conducted using MetaboAnalyst software. Five different biological replicates were analyzed for each condition. Biochemical analyses Sample extraction The Pereira-Caro et al. method was adapted to simultaneously extract the target lipophilic components from rice seeds, with some modifications. Dehulled rice seeds collected from panicles were grounded using a TissueLyser (Retsch) machine (25 Hz, 2 min) to obtain 2 g for each genotype of rice flour from whole grain (brown rice) and extracted for 1 h in an ultrasonicator with 10 mL of ethanol/hexane (4:3, v/v) mixture containing 0.1% ascorbic acid (w/v). After homogenization, samples were centrifuged for 15 min (9000 rpm at 20 °C). The obtained pellets were re-extracted twice using 5 mL hexane, mixed by vortexing, sonicated for 1 h and centrifuged as described above. The resuspended pellet was pooled and washed first with 10 mL distilled water and 5 mL of 10% NaCl solution. The organic phase was retained and reduced to almost dryness using a rotary vacuum evaporator at 35 °C. A small amount of 90% ethanol was added to remove adhering residues on the wall. The concentrated extract was frozen at −20 °C, freeze-dried for 24 h and stored in the dark at 4 °C for further analyses. Three different biological replicates were analyzed for each condition. Antioxidant analysis The antioxidant assays such as DPPH (2,2-Diphenyl-1-picrylhydrazyl), FRAP (Ferric Reducing Antioxidant Power), and ABTS (2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) were performed using the previous method . Briefly, Trolox in ethanol (serial dilutions) was used as a positive control, and a blank control was prepared. DPPH, FRAP, and ABTS are measured in 515 nm, 620 nm, and 734 nm, respectively. All antioxidant values were expressed as Trolox equivalents/100 g rice (µmol TE/100 g). Three different biological replicates were analyzed for each condition. Total starch quantification The rice seeds were dehulled and milled as described before and total starch spectrophotometrically-quantified using the Total Starch (AA/AMG) Assay Kit (Megazyme Ltd., Ireland), following the manufacturer’s instructions. Three different biological replicates were analyzed for each condition. Mineral determination The minerals were quantified in the rice seed samples using the Inductively Coupled Plasma Optical Emission spectroscopy (ICP-OES) following a previously published method . From the digested samples of rice, twelve minerals such as Al, Ca, Cu, Fe, K, Mg, Mn, Mo, Na, P, S, and Zn were quantified. Statistical analysis All the statistical analyses were performed in the R statistical environment (R Core Team, 2023). Data normality and homoscedasticity were tested using Shapiro–Wilk and Levene’s test using the ‘stats’ and ‘car’ v3.1–2packages , respectively (P < 0.05). According to data distributions, ANOVA for normal homoscedastic data or Kruskal–Wallis test for non-normal homoscedastic data were applied (P < 0.05) using custom base R function or the ‘agricolae’ package . Multiple comparisons between treatments were performed using Tukey’s HSD or Dunn’s post-hoc tests after ANOVA or Kruskal-Wallis respectively (p < 0.05), using the package ‘agricolae’ v1.3 or ‘rstatix’ 0.7.2 . When comparing two experimental groups the Welch t-test was applied as implemented in package ‘ggpubr’ v0.6.0 . All data visualizations were performed in R using ‘ggplot2’ v3.3.6 . The impact of zaxinone, MiZax3, and MiZax5 on native paddy soil and rice rhizomicrobiota was studied in a greenhouse mesocosm experiment. Four soil treatments were considered, namely zaxinone, MiZax3, MiZax5, and the solvent acetone as control (ACE), for both rice plants and unplanted soil. Plants were sampled at three phenological stages, the tillering stage (60 days after transplanting, T1) the milky-stage maturation (120 days after transplanting, T2), and the over-ripe stage (180 days after transplanting, T3). For each treatment a total of 33 plants were grown: 15 for phenotyping sampled at T3 and 18 for microbiota profiling (sampled at T1 and T2, 9 biological replicates each). For the unplanted soil treatment, 18 replicates were collected (9 for each sampling point). Mesocosm systems were set up using native paddy soil harvested from the experimental fields of the CREA-CI research center (Vercelli, Italy) which was used in previous studies , . Soil physico-chemical parameters measured on a representative batch used for this study are reported in Table . Rice seeds ( Oryza sativa cv. ‘Nipponbare’) were sown in alveolar trays filled with soil. After 1 month of growth under controlled conditions, plants were transferred to the final plastic pots (10 × 9 × 17 cm) filled with the same soil. For unplanted soil treatment, one alveolar tray was left unsown and the resulting soil cores were transferred into pots with fresh soils (as for rice seedlings) for the unplanted soil conditions. Plants and unplanted soils were grown in the greenhouse at the Department of Life Sciences and Systems Biology of the University of Torino from June 2021 to October 2021 (rice growing season) without monitoring light, temperature and humidity. Plants were watered once a week with tap water and once with distilled water containing zaxinone, MiZax3, and MiZax5 molecules dissolved individually to reach the final concentration of 5µM (10 −6 ), which has already been shown to promote growth activity in rice plant and to alleviate infestation by the root parasitic plant Striga , . Fifty mL of the solution was poured into the soil of each pot once every two weeks for about 5 months (10 treatments) to cover the vegetative and rice reproductive growth stages. Plants were sampled for microbiota profiling at the tillering stage (T1) and at the milky-stage maturation (T2). At sampling, plants were removed from pots, vigorously shaken, and 10–15 g of roots collected within 3–4 cm from the base of the stem into a 50-mL Falcon tube. Unplanted soil samples were collected using a sterile spoon from the middle core of the pot, discarding edges that were in contact with plastic or any other portions where plant roots were visible. Samples were stored at + 4 °C and processed within 24 h to separate plant root compartments under sterile conditions. Samples were then processed to isolate the rhizosphere from the root endosphere according to the protocol by Bulgarelli et al. with minor modifications. Roots fragments were first washed into 10 mM sterile phosphate-buffer saline with 0.02% Tween-80 added (PBS-T), under continuous stirring on a horizontal shaker (15 min, 70 rpm). To obtain the rhizosphere soil slurry, roots were removed and tubes were centrifuged (4000 g, 10 min). The rhizosphere was then resuspended in 2 mL PBS-T and snap-freezed in liquid nitrogen. Roots were enriched in the endospheric compartment by two washes of 10 sonication cycles (30 s pulses, 30 s rest each) in PBS-T, discarding and replacing the buffer after each wash. Samples were finally rinsed in 50 mL of sterile dH 2 0, blotted on sterile filter paper, and stored at −80 °C until DNA isolation. For each time point, at least two aliquots of the same PBS-T buffer used to wash samples were collected and further processed along samples as blanks. DNA was extracted under sterile conditions from 0.5 g of unplanted soil or 500 µL of rhizospheric soil slurry with the NucleoSpin Soil kit (Macherey-Nagel, Düren, Germany) and from 20 mg freeze-dried root material using the NucleoSpin Plant II Mini kit (Macherey-Nagel) following manufacturer’s recommendations. DNA quantity and purity were assessed using a Nanodrop-1000 instrument (Thermo Scientific, Wilmington, Germany). DNA materials were sent for gene marker amplification and sequencing to IGA Technology Services (Udine, Italy; http://igatechnology.com/ ). For Prokaryotic communities profiling the V4 16S region was selected using primers pairs 515F (5’-GTGYCAGCMGCCGCGGTAA-3’) and 806R (5’-GACTACNVGGGTWTCTAAT-3’) , linked with the Illumina adapters overhang. Amplification on organellar rDNA was prevented by peptide nucleic acids (PNAs) clamping using universal pPNA and mPNA clamps for plastidial and mitochondrial sequences following the manufacturer’s protocol (PNA Bio Inc, Newbury Park, CA). For fungi, the ITS2 region of the rRNA gene was adopted as marker using primers pair fTIS7 (5’-GTGARTCATCGAATCTTTG-3’) and ITS4 (5’-TCCTCCGCTTATTGATATGC-3’) . Libraries from both target regions (16 S and ITS2) were then constructed and sequenced on an Illumina NovaSeq6000 platform (Illumina, San Diego, CA, USA) with a 2 × 250 bp sequencing layout. Amplicon libraries were inspected for quality using FastQC v0.11.9 and multiQC v1.11 software and raw reads imported into QIIME 2 (Quantitative Insights Into Microbial Ecology) v2022.02 for denoising, Amplicon Sequence Variants (ASVs) detection and taxonomy mapping. First, primers were fully removed from reads using the cutadapt ‘trim-paired’ plugin discarding untrimmed sequences. For ITS2 libraries the full-length ITS2 region was selected using ITSxpress plugin with the built-in fungal database to increase taxonomic resolution . Clean reads were then denoised and merged into ASVs using DADA2 plugin in ‘pooled’ chimera method detection and applying a reads truncation of 180 and 160 bp based on quality profiles for R1 and R2 sequences, respectively. No reads truncation was applied for ITS2 libraries (--p-trunc-len 0). Variants were then taxonomically annotated using a Naïve-Bayes classifier via the ‘feature-classifier classify-sklearn’ plugin . The SILVA v138 database (99% clustering) pre-formatted for QIIME , and the UNITE + INSDC v8.3 database in developer and dynamic mode were used as reference databases for 16S and ITS2 libraries, respectively. Tables were further taxonomy-filtered to obtain the final feature table analyzed. For the 16S dataset, ASVs matching organellar (mitochondria and chloroplast) rDNA, or without any match (unassigned at the domain level) were removed while for ITS2 libraries non-fungal sequences were discarded. The obtained feature tables was imported into R v4.2.1 environment (R Core Team, 2023) and contaminants were removed using the extraction-blank samples with the microDecon package . Alpha-and beta-diversity analyses were performed using ‘phyloseq’ v1.40.0 , ‘vegan’ v2.6-2 , and ‘QsRutils’ v0.1.5 . The ASVs count table was first filtered by removing low-abundance ASVs using ‘HTSFilter’ v1.36.0 and then normalized with a rarefaction-free approach using DEseq2 v1.36.0 , . Analyses of β- diversity were performed on the resulting normalized table. PERMANOVA and pairwise PERMANOVA analyses were performed using the adonis function of the R package ‘vegan’ and the package ‘pairwiseAdonis’ v0.4.1 , respectively. Principal coordinate analysis (PCoA) was performed by multidimensional scaling (MDS) of Bray–Curtis distance matrices using cmdscale R function. Constrained ordination (cPCoA) were computed using the ‘vegan’ capscale function (which implements CAP (Canonical analysis of principal coordinates) by constraining the factor of interest. Significance of constraints was assessed using the ANOVA-like permutation test implemented in the anova.cca function from the vegan package (999 permutations, P < 0.05). Compartment enrichment and differential abundance analyses were performined using DESeq2 package applying a zero-tolerant geometric mean formula, as detailed in phyloseq package vignettes, and adopting an FDR threshold of 0.05 to define enriched/depleted taxa. Phylogenetic heatmaps were obtained using the ggtreeExtra R package keeping only highly-abundant taxa (relative abundance > 5%) annotated at least at family level. Briefly, ASV sequences of differentially abundant taxa were aligned using MUSCLE (default parameters), and approximately-ML phylogenetic trees were obtained using FastTree v2.1.11 using the GTR model and enabling ‘-no2nd’ option and setting SPRs number as 4. Graphical elaborations were performed using ‘ggtern’ v3.3.5 and ggplot2 v3.3.6 packages. Co-abundance networks of the root endosphere prokaryotic community for each treatment and time points were inferred using network analysis. The most abundant taxa (occurring in > 50% of the samples with at least 350 reads across all the considered samples) were selected for each of the subsampled tables and co-abundance networks inferred using the SPIEC-EASI (Sparse Inverse Covariance Estimation for Ecological Association and Statistical Inference) algorithm in SpiecEasi R package v1.1.2 using the Meinshausen and Bühlmann neighborhood selection model, a lambda path of 100 and other parameters at default values. The final model was selected by random subsampling and interaction re-estimation using stability Approach to Regularization Selection (StARS) and pulsar packages using 100 random subsamples at 0.05% variability threshold. The obtained adjacency matrices were imported into igraph objects and networks plotted using ggraph R package v2.1.0 . Network statistics and node’s topological parameters were calculated using igraph R package v1.5.1 and differences across conditions were assessed using the Student’s t -test ( P < 0.05). For each of the obtained networks, 1000 re-wired random networks (same number of nodes and edges as the real ones) were obtained using the Erdős–Rényi model with the ‘sample_gnm’ function in igraph and metrics calculated as detailed above. Differences of the topological metrics between random and real networks were assessed using the Z-test ( p < 0.05) within the BSDA v1.2.2 R package . Keystone species (hubs-taxa) were identified as the top 5% ASVs showing maximum closeness centrality and betweenness centrality metrics according to a log-normal distribution , . Powdered shoot and root material (50 mg ± 10%) was extracted in 700 µL of methanol by adding 10 µg/mL of methyl α-D-glucopyranoside as internal standard. The samples were homogenized by vortexing and by using a Ball Mill (Retsch, MM 300) with 5 mm zirconia balls (3 min, 20 Hz) and then centrifuged (10 min, 21000 g) recovering 600 µL of the resulting supernatant. The sample was mixed by vortexing with 300 µL of chloroform and 750 µL of water and centrifuged (10 min, 21000 g ). Aliquots of 100 µL and 300 µL from the polar phase were dried in a SpeedVac™ concentrator for GC-MS analysis, respectively. Samples for GC-MS were derivatized according to Lisec et al. . The samples were re-suspended in 40 µL of methoxyaminhydrochloride (20 mg/mL in pyridine) and shaked for 2 h (37 C°, 900 rpm). After that, 70 µL MSTFA were added, and the samples were mixed for additional 30 min (37 C°) and transferred to a glass vial for GC-MS analysis. GC-MS analysis was performed on an Agilent 7890A GC system coupled to a Pegasus HT high throughput TOF/MS (LECO). 1 µL of the sample was injected at 230 °C in splitless mode with He as a carrier gas (2 mL/min). The flow rate was kept constant with electronic pressure control enabled. Chromatography was performed in a 30 m MDN-35 capillary column, with the following temperature program: isothermal for 2 min at 80 °C, followed by a 15 °C per min ramp to 330 °C, and isothermal for 6 min at 330 °C. Transfer line and ion source temperatures were set to 250 °C. The recorded mass range was set from m/z 70 to m/z 600 at 20 scans per second. The remaining monitored chromatography time was preceded by a 170 s solvent delay with filaments turned off. The manual mass defect was set to filament bias current to − 70 V, and detector voltage to ~ 1700–1850 V. The obtained chromatograms were converted to .raw file format and analyzed using the Xcalibur 2.2 software (Thermo Fisher). GC-MS peaks were annotated by comparing retention indexes relative to a mixture of fatty acid methyl esters (FAMES) and spectra similarity against metabolites from the Golm metabolome database (GMD) . Statistical analysis was conducted using MetaboAnalyst software. Five different biological replicates were analyzed for each condition. Sample extraction The Pereira-Caro et al. method was adapted to simultaneously extract the target lipophilic components from rice seeds, with some modifications. Dehulled rice seeds collected from panicles were grounded using a TissueLyser (Retsch) machine (25 Hz, 2 min) to obtain 2 g for each genotype of rice flour from whole grain (brown rice) and extracted for 1 h in an ultrasonicator with 10 mL of ethanol/hexane (4:3, v/v) mixture containing 0.1% ascorbic acid (w/v). After homogenization, samples were centrifuged for 15 min (9000 rpm at 20 °C). The obtained pellets were re-extracted twice using 5 mL hexane, mixed by vortexing, sonicated for 1 h and centrifuged as described above. The resuspended pellet was pooled and washed first with 10 mL distilled water and 5 mL of 10% NaCl solution. The organic phase was retained and reduced to almost dryness using a rotary vacuum evaporator at 35 °C. A small amount of 90% ethanol was added to remove adhering residues on the wall. The concentrated extract was frozen at −20 °C, freeze-dried for 24 h and stored in the dark at 4 °C for further analyses. Three different biological replicates were analyzed for each condition. Antioxidant analysis The antioxidant assays such as DPPH (2,2-Diphenyl-1-picrylhydrazyl), FRAP (Ferric Reducing Antioxidant Power), and ABTS (2,2’-Azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) were performed using the previous method . Briefly, Trolox in ethanol (serial dilutions) was used as a positive control, and a blank control was prepared. DPPH, FRAP, and ABTS are measured in 515 nm, 620 nm, and 734 nm, respectively. All antioxidant values were expressed as Trolox equivalents/100 g rice (µmol TE/100 g). Three different biological replicates were analyzed for each condition. Total starch quantification The rice seeds were dehulled and milled as described before and total starch spectrophotometrically-quantified using the Total Starch (AA/AMG) Assay Kit (Megazyme Ltd., Ireland), following the manufacturer’s instructions. Three different biological replicates were analyzed for each condition. Mineral determination The minerals were quantified in the rice seed samples using the Inductively Coupled Plasma Optical Emission spectroscopy (ICP-OES) following a previously published method . From the digested samples of rice, twelve minerals such as Al, Ca, Cu, Fe, K, Mg, Mn, Mo, Na, P, S, and Zn were quantified. All the statistical analyses were performed in the R statistical environment (R Core Team, 2023). Data normality and homoscedasticity were tested using Shapiro–Wilk and Levene’s test using the ‘stats’ and ‘car’ v3.1–2packages , respectively (P < 0.05). According to data distributions, ANOVA for normal homoscedastic data or Kruskal–Wallis test for non-normal homoscedastic data were applied (P < 0.05) using custom base R function or the ‘agricolae’ package . Multiple comparisons between treatments were performed using Tukey’s HSD or Dunn’s post-hoc tests after ANOVA or Kruskal-Wallis respectively (p < 0.05), using the package ‘agricolae’ v1.3 or ‘rstatix’ 0.7.2 . When comparing two experimental groups the Welch t-test was applied as implemented in package ‘ggpubr’ v0.6.0 . All data visualizations were performed in R using ‘ggplot2’ v3.3.6 . Zaxinone and its mimics shape soil and root prokaryotic communities but not mycobiota assembly To investigate the impact of exogenous treatment with zaxinone and its mimic molecules (MiZax3 and MiZax5) on soil and plant-associated microbial communities, deep 16S and ITS2 rRNA gene amplicon sequencing on unplanted soil and rice rhizosphere and endosphere collected at two timepoints (tillering and milky stage) were performed. A total of ~ 40 and ~ 50 M high-quality reads for the 16S and ITS2 markers, were obtained respectively. After primers removal, sequence denoising, ASV calling, and removal of non-target sequences (plant organellar DNA and non-fungal sequences), a total of 20,875,118 and 20,600,037 fragments were retained and used for subsequent analyses for 16S and ITS2 markers, respectively (Dataset S1). A total of 31,797 16S ASVs (bASVs) and 2712 ITS2 ASVs (fASVs) were obtained, optimally covering diversity for both markers (Figure - ). The root endospheric prokaryotic community was dominated by Proteobacteria, Myxococcota, Chloroflexi, Actinobacteriota, and Bacteroidota, while in rhizosphere and soil, a higher abundance of Acidobacteria and Planctomycetes was detected (Fig. A); this trend is in line with literature data describing the rice microbiota , . The root endophytic fungal community was dominated by Sordariomycetes and Dothideomycetes class (Ascomycota), while in rhizosphere and soil, there was a prevalence of Agaricomycetes (Basidiomycota) and Mortierellomycetes (Mortierellomycotina, Fig. B). Principal Coordinate Analysis (PCoA) on both datasets showed that the influence of zaxinone and MiZax treatments was less marked compared to the effect of compartment factors, validating the robustness of the protocol used to collect rhizocompartments (Figure , Table ). However, at least for prokaryotic communities, PERMANOVA analysis indicated a significant effect of treatments ( P < 0.05, 9999 permutations; Table ). Indeed, constraining PCoA ordinations by treatment factor using canonical analysis of principal coordinates in all compartments and timepoints, a clear separation of bacterial communities across treatments emerged ( P < 0.05; Fig. C) with a closer clustering of Prokaryotic communities in plants/soils treated with MiZax3 and MiZax5 and a neat separation of zaxinone-treated samples at both timepoints, with the two mimics exerting a less marked influence compared with the acetone control. By contrast, the treatments had a lower impact on fungal communities with a less clear separation between conditions and a non-significant effect on β-diversity (PERMANOVA, P > 0.05) (Fig. D). Since all the factors as well as their interactions showed a high impact on prokaryotic community assembly, PERMANOVA was performed testing of the impact of treatments at individual time points/compartments combinations (Table ). Treatments had a significant impact on bacterial communities at T1 in both root endosphere and unplanted soil but not on rhizosphere. At T2, treatments significantly influenced the assembly of prokaryotic communities in all rhizo-compartments with the highest effect on the root endosphere (29.36% of explained variance). Still, no treatment effect was detected in fungal communities. In pairwise PERMANOVA analysis (Table ), it was evident that the individual contribution of the different molecules influences the prokaryotic community abundance: the influence of zaxinone and MiZax5 treatments was significant in the unplanted soil, compared to the control, and in endosphere, especially at T2, all the tested molecules gave a significant impact. Such variations in community assembly were evident when comparing relative abundances of the most abundant bacterial orders. For example, zaxinone treatment decreased the relative abundance of Pedospherales in the endosphere, while MiZax3 promoted their abundance in the rhizosphere at T1. Both MiZax molecules significantly decreased the amount of Polyangiales in the soil at T1 while at T2 MiZax5 decreased Rhizobiales levels. Besides, at T2, zaxinone significantly lowered the relative abundance of Anaerolinales in soil, while MiZax3 increased Chitinophagales in the endosphere (Figure A-B). As reflected in previous PERMANOVA analysis, minor variations occurred in mycobiota at T1: at this time point, MiZax5 led to significantly higher Pleosporales levels in the root endosphere (Figure S5 A-B). No effect of the treatments was observed on bacterial and fungal Shannon index ( α - diversity) (Fig. E and Figure S6) at both time points for both soil and rhizosphere samples. A discernible trend toward an increase in diversity was evident in the root endosphere during the reproductive stage (T2) of the 16S rDNA amplicon dataset irrespective of the treatments (Figure S6C). Furthermore, looking at the Shannon diversity index, differences between T1 and T2 within each treatment emerged indicating that zaxinone and MiZax can influence microbiota dynamics across plant phenological stages (Fig. E-F and S6). In more detail, in the endosphere the prokaryotic -diversity increased across time points for all the treatments considered, including the acetone control (Fig. E and S6). Regarding the fungal communities, zaxinone and MiZax5 elicited a substantial elevation in -diversity from T1 to T2 (Fig. F) while no effect emerged in the control. This trend is also detectable in the rhizosphere, where zaxinone increased fungal -diversity across time points (Figure S6B). Notably, no discernible alterations in α -diversity were noted in the unplanted soil samples among T1 and T2, when compared with the trend of the acetone control, except for an increase in MiZax5 treatment for the prokaryotic community (Figure S6A). Overall, these results indicate that zaxinone and MiZax treatments exerted a mild effect on the prokaryotic community assembly with variations mainly related to compartments and time points while having a minor impact on the fungal community. Nevertheless, when comparing time points within the same treatment, it was found that zaxinone increased fungal α -diversity in root endosphere and rhizosphere in T2 vs. T1 compared to the control acetone condition, while MiZax5 had the same effect in unplanted soil considering the prokaryotic communities. This highlights the possible role of Zaxinone and its mimics in shaping root and soil communities across different plant life stages. Zaxinone and MiZax modulate microbial recruitment dynamics along the soil-root interface To investigate the recruitment of microbiota by rice plants along the soil-rhizosphere-endosphere continuum and to assess the potential interference of zaxinone and MiZax treatments in this process, compartment-specific ASVs, defined as those occurring in higher abundance in a particular compartment compared to others across treatments and time points were analyzed. The results revealed distinct patterns of bacterial taxa enrichment across compartments in the various treatments, exhibiting a pronounced timepoint-dependent trend. Specifically, at T1, there was an increase in the number of rhizosphere-enriched taxa under zaxinone, MiZax3, and MiZax5 treatments (Fig. ). Concurrently, there was an increase in root endosphere-enriched taxa compared to the acetone control in all treatments except for the zaxinone treatment. At T2, a decrease in rhizosphere- and root-enriched ASVs upon the treatment with zaxinone and MiZax3 was observed, whereas the application of MiZax5 caused an increase in root- and rhizosphere-enriched taxa (Fig. ). Overall, MiZax5 treatment proved most effective in increasing the number of highly specific rhizosphere taxa at both time points. Notably, treatments had also an effect on soil-enriched ASVs. With the exception of MiZax5, all the treatments reduced and increased soil-enriched ASVs at T1 and T2, respectively (Fig. ). At each time point, all treatments showed a shared core of root-enriched taxa which included Comamonadaceae, Rhizobiaceae, Chloroflexaceae, and Microscillaceae at T1 with the addition of a Novosphingobium sp. at T2. Among this root-specific set of taxa, MiZax treatments consistently recruited specific Acidibacter sp., Devosia sp., and Comamonadaceae ASVs at T1 (Figure S7). Altogether, these data suggest that zaxinone and MiZax treatments exert different effects on microbiota recruitment according to the timepoint considered. Remarkably, during the 15 days following the application of treatments (T1 sampling), plants exhibited the recruitment of distinct endosphere and rhizosphere communities. Nevertheless, by T2, the bacterial community assemblies in both compartments displayed increased homogeneity, marked by a reduction in compartment-specific taxa and an augmentation of taxa shared among different compartments. The sole exception to this trend was observed in MiZax5, which consistently maintained highly compartment-exclusive communities at both time points and across compartments (Fig. and S8). Zaxinone and MiZax modulate bacterial and fungal taxa in the root endosphere The analysis of differential abundance (Fig. ) at the ASV level revealed that zaxinone and MiZax molecules exerted the most substantial impacts on root endosphere communities, evidenced by a higher number of differentially abundant taxa at both T1 and T2, for both prokaryotic and fungal communities. In contrast, the rhizosphere and soil exhibited a lower number of taxa with altered abundance following treatments. This pattern was notably pronounced in prokaryotic communities (Fig. A), and a comparable trend was observed in Fungi, albeit with a limited number of differentially abundant taxa across conditions in the latter case (Fig. C). Furthermore, our observations indicate that at T1, the majority of taxa exhibited a negative response to almost all treatments in the root, rhizosphere, and soil. In the root endosphere, the number of enriched/depleted prokaryotic taxa at T2 diverged upon zaxinone and MiZax3 treatments. In particular, upon MiZax3 treatment an increase of depleted taxa was identified while the MiZax5 treatment resulted in a higher number of enriched taxa compared to the other treatments (Fig. A). Considering the taxonomic diversity of differentially abundant taxa in the root endosphere, it was observed that depleted taxa spanned across the bacterial phylogeny, with the exception of Actinobacteriota which mostly increased in their abundance in all treatments at T1 (Fig. B). The phyla Acidobacteriota and Proteobacteria are generally depleted. In particular, within Proteobacteria the family Nitrosomonadaceae (genus Ellin6067 ) is decreased in our dataset after the treatments at the first timepoint, while the relative abundance of Comamonadaceae (Proteobacteria) increased with MiZax5 treatment. The application of the molecules was consistently linked to a reduction in Chloroflexi abundance both in the vegetative and in reproductive plant stages. Among depleted taxa, Fimbriimonadaceae (Armatimonadota phylum) emerged especially upon zaxinone and MiZax5 treatments. This taxon is usually detected in ANAMMOX (ANaerobic AMMonium OXidation) consortia, implying that the Fimbriimonadaceae family either contains ammonia-oxidizing taxa or has positive interactions with ammonia-oxidizing bacteria, favoring the ammonia-oxidizing processes . Additionally, a diminished abundance of sulfate-reducing bacteria, such as Geobacteraceae, was observed across all treatments at T2. Notably, treatments significantly influenced Archaeal taxa, with methanogens (primarily Methanosarcina , Methanobacterium , Methanosaeta , and Methanocella genera) generally exhibiting increased abundance in treated samples compared to the control, particularly at T1. Notably, an increase in the abundance of Actinobacteriota, particularly at T1 was detected. This group encompasses taxa well-known to establish beneficial interactions with plants, acting both in the rhizosphere and as endophytes, stimulating plant growth and enhancing disease resistance . Conversely, other groups well-acknowledged to include plant-beneficial species including Sphingomonadaceae (Proteobacteria) and Bacillaceae (Firmicutes), decreased in abundance suggesting a treatment-induced shift of these components. Considering Fungi, our findings revealed no distinct phylogeny-related differences, as the taxa depleted in the root endosphere were distributed across all major phyla, with only a few exceptions. In particular, almost all the ASVs belonging to Helotiales (namely Talaromyces , Dimorphospora , Meliniomyces , and Hyaloscypha ASV) were enriched across treatments (Fig. D). This group includes soil fungi with marked organic matter degradation abilities that are known to associate with plant roots as endophytes and symbionts . Within Mortierellomycota, Glomeromycotina formerly Glomeromycota, genera such as Funneliformis and Claroideoglomus -related ASVs in Fig. D ) and Mortierellomycotina (formerly Mortierellomycota), seem to be mostly depleted in this compartment, with the exception of zaxinone- and MiZax5-treated plants at T2, which show an increment of different taxa, especially the genera Funneliformis and Mortierella . However, these changes do not reflect any significant changes in the whole AMF community at higher taxonomic level such as families, which is mainly composed of Glomeraceae, Paraglomeraceae, and Claroideoglomeraceae at variable abundances according to the phenological stage and additionally being slightly affected by treatment (Figure S8). Lastly, two ASVs pointing to the Trichoderma genus showed an increase in its abundance at T2 upon both Zaxinone and Mizax5 treatment. This fungus is known to exert plant-beneficial abilities, being particularly active as a biocontrol agent and increasing yield in rice . Taken together, these data suggest an overall impact of zaxinone and its mimicking molecules on the abundances of numerous microbial groups, which turned out to be mostly decreased at the first time point, with some exceptions. At T2, the influence of the treatments seems to be globally less pronounced. Zaxinone and MiZax treatment impact microbiota network dynamics more at the vegetative than at the reproductive stage To track for changes in co-occurrence dynamics determined by treatments on the bacterial endosphere community and to identify hubs-taxa (i.e. ’keystone microbes which drive the structure of the community), co-occurrence networks were constructed using Sparse Inverse Covariance estimation (SPIEC-EASI) for each timepoint and treatment considered (Fig. ). Globally, structures of the community in each treatment at each timepoint showed comparable network-level metrics, with a higher ratio of positive correlations between taxa (mean 61.1% positive edges) and an overall similar modularity, centrality metrics, and cohesion (Table S6). Notably, at the milky-stage (T2), communities showed increased connectivity, nodes degree, and number of hubs-taxa identified, indicating a higher community complexity. However, a treatment-dependent modulation was observed in most of the node-level metrics analyzed (Figure S9). At T1 all the treatments significantly decreased the degree distribution (number of connections, i.e . edges, established by each node). Zaxinone and MiZax5 treatments significantly increased betweenness i.e . the extent to which a node lies in the shortest path connecting other nodes and decreased closeness centrality i.e . the average distance to all other nodes. Further, the eigenvector-centrality and the HUB score, which both indicate the amount of connections towards highly influential taxa, were positively impacted by the treatments with the exception of MiZax5. In addition, in both zaxinone and MiZax5 the betweenness centrality significantly increased while closeness centrality decreased (Figure S9). Altogether, these metrics indicate that treatments increased distance between taxa and increased the occurrences of more isolated sub-communities, in terms of connections while decreasing the overall connections between taxa (lower degree). At T2, the degree distribution became more uniform across treatments, with the exception of MiZax3, where significantly fewer connections emerged. Concurrently, at the same timepoint, all treatments led to an increase in node closeness, and, except for MiZax5, also in betweenness centrality. Interestingly, by comparing the inferred network metrics with those of randomly generated graphs (see methods; Table S6), it was found that at both time points network structures were not casual, highlighting that reconstructed community dynamics were meaningful. To offer a more detailed insight into the impact of treatments on the community network structure, hub-taxa, i.e. the nodes characterized by higher closeness and betweenness centrality (top 5% of the distribution, Fig. ) were identified. At T1 most of the hubs-taxa detected across treatments belong to Proteobacteria, Myxococcota, and Acidobacteria including Sphingomonas , Haliangium , Vicinamibacter , and Tahibacter genera. Most of them were already known as keystone species in root- or plant-associated communities and hold plant-growth-promoting capacities. The analysis indicated that treatments resulted in a reduction of hub-taxa at T1 (from 6 to 1–2 hub-taxa in the control and treatments, respectively), while minor to no differences were detected at T2. In the control (acetone), hub-taxa primarily consisted of Chloroflexi (A4b family), Acidobacteriota, Firmicutes, Actinobacteriota, and Bacteroidota members, with the inclusion of Proteobacteria (Comamonadaceae) at T2. Moreover, in the examination of the node’s closeness distribution, a notable shift towards lower values was observed in zaxinone and MiZax5 at T1, reflecting the reduced number of established edges (degree metrics, Fig. A). At T2, keystone taxa increased compared to T1 in all treatments. Several Comamonadaceae ASVs (proteobacteria), acknowledged for their prevalence in rice-associated root communities , were identified as keystone taxa in all treatments as well as in the control. Under MiZax5 treatment, Novosphingobium and Streptomyces , two well-acknowledged PGP species, emerged as hub-taxa. Interestingly, in both MiZax3 and MiZax5 treatments, Haliangium occurred as a keystone species. Overall, analysis of co-occurrences indicated that all the treatments decreased the overall network complexity promoting the isolation of sub-communities and decreasing the number of hubs at the vegetative stage (T1), while at the reproductive stage (T2), in treated plants and in particular upon MiZax5 application, significant interactions between taxa were re-established in a similar manner to the acetone control, though with an array of hub-taxa that seems to be specific for each condition considered. Zaxinone and MiZax treatment induce alterations in plant’s primary metabolism and grain nutrient content At the metabolomic level, the effects of zaxinone-related compounds and the associated root microbiota composition on treated and non-treated rice plants were determined by collecting shoots from the same rice plants used for the metabarcoding analysis at T1 and T2. Through targeted GC-MS analysis, approximately 40 primary metabolites, including amino acids, organic acids, and sugars, were identified as differentially accumulated metabolites (Fig. ). Noteworthy alterations in metabolite levels were observed across various metabolite classes in green tissues. During the vegetative stage (T1), MiZax3 and MiZax5 treatments induce a trend of increase in the sugar content. In particular, threitol and myoinositol are significantly more abundant in the shoots upon MiZax3 treatment. Conversely, zaxinone exhibited a contrasting trend in sugar content at T1 compared to its synthetic mimics. As the plants progressed to the reproductive stage (T2), a higher trend in sugar content (glucose, glycerol, myoinositol, and fructose) has been reported under zaxinone treatment, whereas the same compounds appeared rather reduced following MiZax5 treatments, though none of the detected changes turned out to be statistically significant. A general accumulation of amino acids was observed upon treatments: in particular, an increase in the levels of different free amino acids (alanine, threonine, and GABA) was observed at T1 upon MiZax treatment. At the same timepoint, zaxinone treatment induced an accumulation of isoleucine, proline, and threonine while at T2 an increase in alanine was observed upon MiZax5. While the effect of the treatments on sugar and amino acid accumulation seems to be limited, the organic acid pattern turned out to be more influenced, especially at T1. At that time point, MiZax3 induced TCA cycle intermediates, including glycerate, pyruvate, and (2)-oxoglutarate. Similarly, at both time points MiZax5 increased glycerate and (2)-oxoglutarate content. While at T1 malate and citrate showed a statistically-supported lower abundance in shoot treated with MiZax3 and zaxinone, a slight decrease in shoot treated with MiZax5 was observed. Ribonic acid was also negatively affected mainly by both MiZax. A substantial reduction in phosphoric acid levels in the shoots after all zaxinone-related compounds treatments was also observed at T1. By contrast, an increase in salicylate levels in the shoots was observed at T2 following zaxinone treatment, whereas MiZax3 and MiZax5 exhibited an opposite trend. To a certain extent, the metabolomic profiles are in agreement with the results obtained by Wang et al. , which reported an increased concentration of free amino acids and succinate in the shoot of rice plants treated with zaxinone. However, there are some discrepancies in other metabolic pathways, namely sugar metabolism and organic acids. This may be ascribed to differences in the experimental set-up ( i.e. plant’s phenological stage and compound applications in hydroponic or soil system). Furthermore, our findings indicate that MiZax3 is the most effective compound in modulating the plant metabolome, particularly at T1. In order to determine the impact of zaxinone and MiZax compounds and the relative root-associated microbiota community on seed nutrient content, the starch content, the antioxidant capacity, and the mineral nutrient profile were evaluated. While the antioxidant activity and the starch content did not change across treatments, some differences in grain mineral nutrition were observed. Indeed, a higher content of zinc (33.87 ppm) and copper (5.73 ppm) in seeds of plants treated with zaxinone compared to control acetone plants was detected. Conversely, a decrease in manganese content was observed in seeds of plants treated with both MiZax3 and MiZax5 (Figure S10). To investigate the impact of exogenous treatment with zaxinone and its mimic molecules (MiZax3 and MiZax5) on soil and plant-associated microbial communities, deep 16S and ITS2 rRNA gene amplicon sequencing on unplanted soil and rice rhizosphere and endosphere collected at two timepoints (tillering and milky stage) were performed. A total of ~ 40 and ~ 50 M high-quality reads for the 16S and ITS2 markers, were obtained respectively. After primers removal, sequence denoising, ASV calling, and removal of non-target sequences (plant organellar DNA and non-fungal sequences), a total of 20,875,118 and 20,600,037 fragments were retained and used for subsequent analyses for 16S and ITS2 markers, respectively (Dataset S1). A total of 31,797 16S ASVs (bASVs) and 2712 ITS2 ASVs (fASVs) were obtained, optimally covering diversity for both markers (Figure - ). The root endospheric prokaryotic community was dominated by Proteobacteria, Myxococcota, Chloroflexi, Actinobacteriota, and Bacteroidota, while in rhizosphere and soil, a higher abundance of Acidobacteria and Planctomycetes was detected (Fig. A); this trend is in line with literature data describing the rice microbiota , . The root endophytic fungal community was dominated by Sordariomycetes and Dothideomycetes class (Ascomycota), while in rhizosphere and soil, there was a prevalence of Agaricomycetes (Basidiomycota) and Mortierellomycetes (Mortierellomycotina, Fig. B). Principal Coordinate Analysis (PCoA) on both datasets showed that the influence of zaxinone and MiZax treatments was less marked compared to the effect of compartment factors, validating the robustness of the protocol used to collect rhizocompartments (Figure , Table ). However, at least for prokaryotic communities, PERMANOVA analysis indicated a significant effect of treatments ( P < 0.05, 9999 permutations; Table ). Indeed, constraining PCoA ordinations by treatment factor using canonical analysis of principal coordinates in all compartments and timepoints, a clear separation of bacterial communities across treatments emerged ( P < 0.05; Fig. C) with a closer clustering of Prokaryotic communities in plants/soils treated with MiZax3 and MiZax5 and a neat separation of zaxinone-treated samples at both timepoints, with the two mimics exerting a less marked influence compared with the acetone control. By contrast, the treatments had a lower impact on fungal communities with a less clear separation between conditions and a non-significant effect on β-diversity (PERMANOVA, P > 0.05) (Fig. D). Since all the factors as well as their interactions showed a high impact on prokaryotic community assembly, PERMANOVA was performed testing of the impact of treatments at individual time points/compartments combinations (Table ). Treatments had a significant impact on bacterial communities at T1 in both root endosphere and unplanted soil but not on rhizosphere. At T2, treatments significantly influenced the assembly of prokaryotic communities in all rhizo-compartments with the highest effect on the root endosphere (29.36% of explained variance). Still, no treatment effect was detected in fungal communities. In pairwise PERMANOVA analysis (Table ), it was evident that the individual contribution of the different molecules influences the prokaryotic community abundance: the influence of zaxinone and MiZax5 treatments was significant in the unplanted soil, compared to the control, and in endosphere, especially at T2, all the tested molecules gave a significant impact. Such variations in community assembly were evident when comparing relative abundances of the most abundant bacterial orders. For example, zaxinone treatment decreased the relative abundance of Pedospherales in the endosphere, while MiZax3 promoted their abundance in the rhizosphere at T1. Both MiZax molecules significantly decreased the amount of Polyangiales in the soil at T1 while at T2 MiZax5 decreased Rhizobiales levels. Besides, at T2, zaxinone significantly lowered the relative abundance of Anaerolinales in soil, while MiZax3 increased Chitinophagales in the endosphere (Figure A-B). As reflected in previous PERMANOVA analysis, minor variations occurred in mycobiota at T1: at this time point, MiZax5 led to significantly higher Pleosporales levels in the root endosphere (Figure S5 A-B). No effect of the treatments was observed on bacterial and fungal Shannon index ( α - diversity) (Fig. E and Figure S6) at both time points for both soil and rhizosphere samples. A discernible trend toward an increase in diversity was evident in the root endosphere during the reproductive stage (T2) of the 16S rDNA amplicon dataset irrespective of the treatments (Figure S6C). Furthermore, looking at the Shannon diversity index, differences between T1 and T2 within each treatment emerged indicating that zaxinone and MiZax can influence microbiota dynamics across plant phenological stages (Fig. E-F and S6). In more detail, in the endosphere the prokaryotic -diversity increased across time points for all the treatments considered, including the acetone control (Fig. E and S6). Regarding the fungal communities, zaxinone and MiZax5 elicited a substantial elevation in -diversity from T1 to T2 (Fig. F) while no effect emerged in the control. This trend is also detectable in the rhizosphere, where zaxinone increased fungal -diversity across time points (Figure S6B). Notably, no discernible alterations in α -diversity were noted in the unplanted soil samples among T1 and T2, when compared with the trend of the acetone control, except for an increase in MiZax5 treatment for the prokaryotic community (Figure S6A). Overall, these results indicate that zaxinone and MiZax treatments exerted a mild effect on the prokaryotic community assembly with variations mainly related to compartments and time points while having a minor impact on the fungal community. Nevertheless, when comparing time points within the same treatment, it was found that zaxinone increased fungal α -diversity in root endosphere and rhizosphere in T2 vs. T1 compared to the control acetone condition, while MiZax5 had the same effect in unplanted soil considering the prokaryotic communities. This highlights the possible role of Zaxinone and its mimics in shaping root and soil communities across different plant life stages. To investigate the recruitment of microbiota by rice plants along the soil-rhizosphere-endosphere continuum and to assess the potential interference of zaxinone and MiZax treatments in this process, compartment-specific ASVs, defined as those occurring in higher abundance in a particular compartment compared to others across treatments and time points were analyzed. The results revealed distinct patterns of bacterial taxa enrichment across compartments in the various treatments, exhibiting a pronounced timepoint-dependent trend. Specifically, at T1, there was an increase in the number of rhizosphere-enriched taxa under zaxinone, MiZax3, and MiZax5 treatments (Fig. ). Concurrently, there was an increase in root endosphere-enriched taxa compared to the acetone control in all treatments except for the zaxinone treatment. At T2, a decrease in rhizosphere- and root-enriched ASVs upon the treatment with zaxinone and MiZax3 was observed, whereas the application of MiZax5 caused an increase in root- and rhizosphere-enriched taxa (Fig. ). Overall, MiZax5 treatment proved most effective in increasing the number of highly specific rhizosphere taxa at both time points. Notably, treatments had also an effect on soil-enriched ASVs. With the exception of MiZax5, all the treatments reduced and increased soil-enriched ASVs at T1 and T2, respectively (Fig. ). At each time point, all treatments showed a shared core of root-enriched taxa which included Comamonadaceae, Rhizobiaceae, Chloroflexaceae, and Microscillaceae at T1 with the addition of a Novosphingobium sp. at T2. Among this root-specific set of taxa, MiZax treatments consistently recruited specific Acidibacter sp., Devosia sp., and Comamonadaceae ASVs at T1 (Figure S7). Altogether, these data suggest that zaxinone and MiZax treatments exert different effects on microbiota recruitment according to the timepoint considered. Remarkably, during the 15 days following the application of treatments (T1 sampling), plants exhibited the recruitment of distinct endosphere and rhizosphere communities. Nevertheless, by T2, the bacterial community assemblies in both compartments displayed increased homogeneity, marked by a reduction in compartment-specific taxa and an augmentation of taxa shared among different compartments. The sole exception to this trend was observed in MiZax5, which consistently maintained highly compartment-exclusive communities at both time points and across compartments (Fig. and S8). The analysis of differential abundance (Fig. ) at the ASV level revealed that zaxinone and MiZax molecules exerted the most substantial impacts on root endosphere communities, evidenced by a higher number of differentially abundant taxa at both T1 and T2, for both prokaryotic and fungal communities. In contrast, the rhizosphere and soil exhibited a lower number of taxa with altered abundance following treatments. This pattern was notably pronounced in prokaryotic communities (Fig. A), and a comparable trend was observed in Fungi, albeit with a limited number of differentially abundant taxa across conditions in the latter case (Fig. C). Furthermore, our observations indicate that at T1, the majority of taxa exhibited a negative response to almost all treatments in the root, rhizosphere, and soil. In the root endosphere, the number of enriched/depleted prokaryotic taxa at T2 diverged upon zaxinone and MiZax3 treatments. In particular, upon MiZax3 treatment an increase of depleted taxa was identified while the MiZax5 treatment resulted in a higher number of enriched taxa compared to the other treatments (Fig. A). Considering the taxonomic diversity of differentially abundant taxa in the root endosphere, it was observed that depleted taxa spanned across the bacterial phylogeny, with the exception of Actinobacteriota which mostly increased in their abundance in all treatments at T1 (Fig. B). The phyla Acidobacteriota and Proteobacteria are generally depleted. In particular, within Proteobacteria the family Nitrosomonadaceae (genus Ellin6067 ) is decreased in our dataset after the treatments at the first timepoint, while the relative abundance of Comamonadaceae (Proteobacteria) increased with MiZax5 treatment. The application of the molecules was consistently linked to a reduction in Chloroflexi abundance both in the vegetative and in reproductive plant stages. Among depleted taxa, Fimbriimonadaceae (Armatimonadota phylum) emerged especially upon zaxinone and MiZax5 treatments. This taxon is usually detected in ANAMMOX (ANaerobic AMMonium OXidation) consortia, implying that the Fimbriimonadaceae family either contains ammonia-oxidizing taxa or has positive interactions with ammonia-oxidizing bacteria, favoring the ammonia-oxidizing processes . Additionally, a diminished abundance of sulfate-reducing bacteria, such as Geobacteraceae, was observed across all treatments at T2. Notably, treatments significantly influenced Archaeal taxa, with methanogens (primarily Methanosarcina , Methanobacterium , Methanosaeta , and Methanocella genera) generally exhibiting increased abundance in treated samples compared to the control, particularly at T1. Notably, an increase in the abundance of Actinobacteriota, particularly at T1 was detected. This group encompasses taxa well-known to establish beneficial interactions with plants, acting both in the rhizosphere and as endophytes, stimulating plant growth and enhancing disease resistance . Conversely, other groups well-acknowledged to include plant-beneficial species including Sphingomonadaceae (Proteobacteria) and Bacillaceae (Firmicutes), decreased in abundance suggesting a treatment-induced shift of these components. Considering Fungi, our findings revealed no distinct phylogeny-related differences, as the taxa depleted in the root endosphere were distributed across all major phyla, with only a few exceptions. In particular, almost all the ASVs belonging to Helotiales (namely Talaromyces , Dimorphospora , Meliniomyces , and Hyaloscypha ASV) were enriched across treatments (Fig. D). This group includes soil fungi with marked organic matter degradation abilities that are known to associate with plant roots as endophytes and symbionts . Within Mortierellomycota, Glomeromycotina formerly Glomeromycota, genera such as Funneliformis and Claroideoglomus -related ASVs in Fig. D ) and Mortierellomycotina (formerly Mortierellomycota), seem to be mostly depleted in this compartment, with the exception of zaxinone- and MiZax5-treated plants at T2, which show an increment of different taxa, especially the genera Funneliformis and Mortierella . However, these changes do not reflect any significant changes in the whole AMF community at higher taxonomic level such as families, which is mainly composed of Glomeraceae, Paraglomeraceae, and Claroideoglomeraceae at variable abundances according to the phenological stage and additionally being slightly affected by treatment (Figure S8). Lastly, two ASVs pointing to the Trichoderma genus showed an increase in its abundance at T2 upon both Zaxinone and Mizax5 treatment. This fungus is known to exert plant-beneficial abilities, being particularly active as a biocontrol agent and increasing yield in rice . Taken together, these data suggest an overall impact of zaxinone and its mimicking molecules on the abundances of numerous microbial groups, which turned out to be mostly decreased at the first time point, with some exceptions. At T2, the influence of the treatments seems to be globally less pronounced. To track for changes in co-occurrence dynamics determined by treatments on the bacterial endosphere community and to identify hubs-taxa (i.e. ’keystone microbes which drive the structure of the community), co-occurrence networks were constructed using Sparse Inverse Covariance estimation (SPIEC-EASI) for each timepoint and treatment considered (Fig. ). Globally, structures of the community in each treatment at each timepoint showed comparable network-level metrics, with a higher ratio of positive correlations between taxa (mean 61.1% positive edges) and an overall similar modularity, centrality metrics, and cohesion (Table S6). Notably, at the milky-stage (T2), communities showed increased connectivity, nodes degree, and number of hubs-taxa identified, indicating a higher community complexity. However, a treatment-dependent modulation was observed in most of the node-level metrics analyzed (Figure S9). At T1 all the treatments significantly decreased the degree distribution (number of connections, i.e . edges, established by each node). Zaxinone and MiZax5 treatments significantly increased betweenness i.e . the extent to which a node lies in the shortest path connecting other nodes and decreased closeness centrality i.e . the average distance to all other nodes. Further, the eigenvector-centrality and the HUB score, which both indicate the amount of connections towards highly influential taxa, were positively impacted by the treatments with the exception of MiZax5. In addition, in both zaxinone and MiZax5 the betweenness centrality significantly increased while closeness centrality decreased (Figure S9). Altogether, these metrics indicate that treatments increased distance between taxa and increased the occurrences of more isolated sub-communities, in terms of connections while decreasing the overall connections between taxa (lower degree). At T2, the degree distribution became more uniform across treatments, with the exception of MiZax3, where significantly fewer connections emerged. Concurrently, at the same timepoint, all treatments led to an increase in node closeness, and, except for MiZax5, also in betweenness centrality. Interestingly, by comparing the inferred network metrics with those of randomly generated graphs (see methods; Table S6), it was found that at both time points network structures were not casual, highlighting that reconstructed community dynamics were meaningful. To offer a more detailed insight into the impact of treatments on the community network structure, hub-taxa, i.e. the nodes characterized by higher closeness and betweenness centrality (top 5% of the distribution, Fig. ) were identified. At T1 most of the hubs-taxa detected across treatments belong to Proteobacteria, Myxococcota, and Acidobacteria including Sphingomonas , Haliangium , Vicinamibacter , and Tahibacter genera. Most of them were already known as keystone species in root- or plant-associated communities and hold plant-growth-promoting capacities. The analysis indicated that treatments resulted in a reduction of hub-taxa at T1 (from 6 to 1–2 hub-taxa in the control and treatments, respectively), while minor to no differences were detected at T2. In the control (acetone), hub-taxa primarily consisted of Chloroflexi (A4b family), Acidobacteriota, Firmicutes, Actinobacteriota, and Bacteroidota members, with the inclusion of Proteobacteria (Comamonadaceae) at T2. Moreover, in the examination of the node’s closeness distribution, a notable shift towards lower values was observed in zaxinone and MiZax5 at T1, reflecting the reduced number of established edges (degree metrics, Fig. A). At T2, keystone taxa increased compared to T1 in all treatments. Several Comamonadaceae ASVs (proteobacteria), acknowledged for their prevalence in rice-associated root communities , were identified as keystone taxa in all treatments as well as in the control. Under MiZax5 treatment, Novosphingobium and Streptomyces , two well-acknowledged PGP species, emerged as hub-taxa. Interestingly, in both MiZax3 and MiZax5 treatments, Haliangium occurred as a keystone species. Overall, analysis of co-occurrences indicated that all the treatments decreased the overall network complexity promoting the isolation of sub-communities and decreasing the number of hubs at the vegetative stage (T1), while at the reproductive stage (T2), in treated plants and in particular upon MiZax5 application, significant interactions between taxa were re-established in a similar manner to the acetone control, though with an array of hub-taxa that seems to be specific for each condition considered. At the metabolomic level, the effects of zaxinone-related compounds and the associated root microbiota composition on treated and non-treated rice plants were determined by collecting shoots from the same rice plants used for the metabarcoding analysis at T1 and T2. Through targeted GC-MS analysis, approximately 40 primary metabolites, including amino acids, organic acids, and sugars, were identified as differentially accumulated metabolites (Fig. ). Noteworthy alterations in metabolite levels were observed across various metabolite classes in green tissues. During the vegetative stage (T1), MiZax3 and MiZax5 treatments induce a trend of increase in the sugar content. In particular, threitol and myoinositol are significantly more abundant in the shoots upon MiZax3 treatment. Conversely, zaxinone exhibited a contrasting trend in sugar content at T1 compared to its synthetic mimics. As the plants progressed to the reproductive stage (T2), a higher trend in sugar content (glucose, glycerol, myoinositol, and fructose) has been reported under zaxinone treatment, whereas the same compounds appeared rather reduced following MiZax5 treatments, though none of the detected changes turned out to be statistically significant. A general accumulation of amino acids was observed upon treatments: in particular, an increase in the levels of different free amino acids (alanine, threonine, and GABA) was observed at T1 upon MiZax treatment. At the same timepoint, zaxinone treatment induced an accumulation of isoleucine, proline, and threonine while at T2 an increase in alanine was observed upon MiZax5. While the effect of the treatments on sugar and amino acid accumulation seems to be limited, the organic acid pattern turned out to be more influenced, especially at T1. At that time point, MiZax3 induced TCA cycle intermediates, including glycerate, pyruvate, and (2)-oxoglutarate. Similarly, at both time points MiZax5 increased glycerate and (2)-oxoglutarate content. While at T1 malate and citrate showed a statistically-supported lower abundance in shoot treated with MiZax3 and zaxinone, a slight decrease in shoot treated with MiZax5 was observed. Ribonic acid was also negatively affected mainly by both MiZax. A substantial reduction in phosphoric acid levels in the shoots after all zaxinone-related compounds treatments was also observed at T1. By contrast, an increase in salicylate levels in the shoots was observed at T2 following zaxinone treatment, whereas MiZax3 and MiZax5 exhibited an opposite trend. To a certain extent, the metabolomic profiles are in agreement with the results obtained by Wang et al. , which reported an increased concentration of free amino acids and succinate in the shoot of rice plants treated with zaxinone. However, there are some discrepancies in other metabolic pathways, namely sugar metabolism and organic acids. This may be ascribed to differences in the experimental set-up ( i.e. plant’s phenological stage and compound applications in hydroponic or soil system). Furthermore, our findings indicate that MiZax3 is the most effective compound in modulating the plant metabolome, particularly at T1. In order to determine the impact of zaxinone and MiZax compounds and the relative root-associated microbiota community on seed nutrient content, the starch content, the antioxidant capacity, and the mineral nutrient profile were evaluated. While the antioxidant activity and the starch content did not change across treatments, some differences in grain mineral nutrition were observed. Indeed, a higher content of zinc (33.87 ppm) and copper (5.73 ppm) in seeds of plants treated with zaxinone compared to control acetone plants was detected. Conversely, a decrease in manganese content was observed in seeds of plants treated with both MiZax3 and MiZax5 (Figure S10). The microbiota analysis reveals a community typical of paddy soils Rice fields represent a peculiar environment for the microbial soil communities. Due to the periodic flooding, this habitat is characterized by oxygen-limited conditions that shape the microbiota assembly. Bacterial communities typically include both aerobic and anaerobic taxa . The overall microbiota assembly from unplanted soil revealed a prokaryotic composition typical of paddy environments, including Gemmatimonadetes, Chloroflexi, Acidobacteria and Actinobacteria, and the archaeal phylum Crenarchaeota – . On the fungal side, our analysis revealed a relevant proportion of Leotiomycetes in all the conditions considered. This group of fungi includes good organic matter decomposers that can tolerate high levels of heavy metal contaminants usually found in paddy soils , and can associate with plant roots living as endophytes. Impact of zaxinone and its mimics on rhizomicrobiome diversity and composition So far, the effects of exogenous treatment with zaxinone and its mimics (MiZax3 and MiZax5) were investigated considering the growth promotion activity, the regulation of SLs biosynthesis, and the AM symbiosis , . Here, we provide comprehensively new information about the impact of these compounds on paddy soil and rice root-associated microbes and how these effects systemically influence rice metabolomic and grain nutrient profiles considering different developmental stages. The metabarcoding analysis highlighted that rice microbiome assembly is mainly influenced by compartment niche and developmental stage as already reported for rice and other plants – , regardless of zaxinone and MiZax treatments. In contrast to the findings reported by Zangh and colleagues , which observed a reduction in root microbial community richness in the later stage of the rice life cycle, our data reveals a general increase in α -diversity at T2 compared to T1 across the three considered compartments (unplanted soil, rhizosphere, and endosphere), regardless of the treatments. This increment was evident in the endosphere particularly for the prokaryotic community while the α -diversity of the fungal community increased over time only under zaxinone and MiZax5 treatments. Notwithstanding the compartment and developmental stage, zaxinone and MiZax treatments significantly influenced the β -diversity of prokaryotic microbial communities. Notably, we highlighted a shared pattern between MiZax3 and MiZax5 more similar to the acetone control, whereas a clear separation was evident for samples treated with zaxinone. Studies focused on plant traits demonstrated that MiZax3 and MiZax5 exhibit zaxinone-like activity by rescuing the root growth of a zaxinone-deficient rice mutant. They also promote overall growth and decrease SLs content in both roots and root exudates of wild-type plants . However, contrasting results were observed when mycorrhization was considered. Specifically, the application of 5 µM MiZax did not negatively impact AM fungal root colonization, whereas zaxinone treatment markedly reduced AM mycorrhization , . These findings suggested that zaxinone and MiZax compounds can be interchanged when plant traits are concerned but more caution is needed considering plant-microbe interactions. Our metabarcoding data are consistent with these observations. As shown by the analysis of compartment-specific taxa, the different pattern between MiZax and zaxinone treatment seems to be more evident at T1. Herein, a stronger polarization between root and rhizosphere prokaryotic communities occurs in MiZax3 and MiZax5 compared to the acetone control. Conversely, in the zaxinone treatment, a higher overlap between these two compartments is detected at both developmental stages. In particular, in the endosphere at T1, we identified an increased number of ASVs which are key soil-beneficial bacterial taxa, such as Comamonadaceae, Acidibacter , and Devosia , enriched under MiZax3 and MiZax5 treatments. Acidibacter and Comamonadaceae have normally high phosphorus solubilizing activity , and in addition, Comamonadaceae has also the ability to solubilize potassium, zinc, and nitrogen and its abundance has been related to disease-suppressive soil , . Devosia has been reported as nitrogen-fixing bacteria which also alleviate abiotic stress and recently has been reported to be enriched on AM extraradical hyphae and mycorrhizal root . Furthermore, two novel Devosia species recently isolated from the rice rhizosphere have been demonstrated to produce IAA and siderophores . Further, in the rhizosphere MiZax3 and MiZax5 shared the accumulation of keystone rhizobacteria taxa such as Pedosphaeraceae , and Nitrosarchaeum which is predicted to be an anaerobic hydrocarbon-degrading bacteria in the subsurface soil . By contrast, at T2 in both zaxinone and MiZax3, rhizosphere and endosphere prokaryotic communities were more similar, while MiZax5 still maintained the pattern shown at T1. By contrast, the impact of the treatments on soil communities was detectable but negligible in term of the amount of regulated taxa. It is plausible to hypothesize that the soil environment more effectively buffers exogenous environmental changes, potentially due to its higher microbial abundance compared to root tissues. As an alternative, we can hypothesize that the applied molecules only exert a limited direct effect on the microbial communities, such an outcome being magnified by the plant. Zaxinone and its mimics are in fact perceived by the plant, which might undertake modification of its hormonal balance and/or rhizodeposition that could result in a differential recruitment of endosphere/rhizosphere microbiota. Coupled with the evidence that the application of MiZax3 and MiZax5 differentially modulated the abundances of bacterial ASVs both in the endosphere and in the rhizosphere, this data suggests that each molecule has a specific impact on shaping the bacterial community. Compared with the acetone control, at T1, all the molecules exerted the most significant impact on the root endosphere bacterial and fungal communities with a widespread depletion of taxa, while an opposite pattern was observed in the rhizosphere where the compounds supply incremented the number of enriched taxa, at least for prokaryotic communities. At T2 a higher ratio of depleted prokaryotic taxa was observed in the endosphere following treatment with zaxinone and MiZax3 while MiZax5 has a milder effect, with enriched taxa prevailing on the depleted ones. The endosphere mycobiota was slightly less impacted by treatments compared to T1. In the rhizosphere and in the unplanted soil, all the treatments displayed a limited impact in terms of enriched/depleted taxa, irrespective of the timepoint. These findings suggest that zaxinone and MiZax treatments exert the highest impact on microbial communities in the root endosphere, suggesting once again that these dynamics are likely influenced by plant-mediated processes. In the analysis of the taxonomic diversity of differentially abundant taxa in the root endosphere, it was observed that depleted taxa were widely distributed across the bacterial phylogeny. Notably, Actinobacteriota was an exception, mostly showing an increase in their abundance in all treatments at T1. This phylum is recognized as the producer of many bioactive metabolites in agriculture, such as insecticides, herbicides, fungicides, and growth-promoting substances for plants . By contrast, the abundance of Acidobacteria decreased drastically, overall. Interestingly, a lower abundance of Acidobacteria was also found in rice d17 mutant lines defective for SLs biosynthesis , suggesting that the decreased Acidobacteria abundance in the endosphere of zaxinone and MiZax treated plants could be dependent on the negative impact of these compounds on SLs biosynthesis. At the same time, we observed an enrichment of Chitinophagaceae upon MiZax3 treatment. Since Chitinophagaceae was negatively associated with orobanchol , their higher abundance could be related to the negative impact of MiZax on SLs biosynthesis. Regarding the fungal community, we observed a depletion of Mucoromycota phylum. It is worth noting that different Funneliformis ASVs belonging to Glomeromycotina subphylum were depleted by zaxinone treatment at T1 while enriched at T2. By contrast, MiZax3 and MiZax5 have a mild impact at both time points. These findings are in line with our previous reports which displayed at early time points a strong reduction of AM symbiosis colonization in rice root treated with zaxinone while no negative effects were reported upon MiZax treatment , . The decrease of these taxa at a very early sampling time may be attributed to the lower SL content in root exudates induced by zaxinone treatment . The SLs reduction potentially delays the mycorrhization process, which however was fully recovered over time. The analysis of prokaryotic community interactions in the endosphere, revealed in zaxinone and MiZax-treated rice roots at T1 a decrease in network complexity and in a number of keystone taxa compared to the control, with the most pronounced effects for zaxinone and MiZax5 treatments, although few but significant plant-beneficial microbes emerged as hubs-taxa. However, at T1 all the network metrics indicated for most of the treatments a decentralization of microbe-microbe interactions compared to the control, with few but wider connections spanning through the network and possibly resulting in a community less dependent on a few hub species. These features suggest that at T1 the community may be more resilient to external perturbations, but further experiments are needed to confirm these speculations. At T2, in all treated plants and in particular, upon MiZax5, significant interactions between taxa were re-established in a similar way to the acetone control, with a shift in microbes potentially holding plant-beneficial traits among the identified keystone taxa. Overall, our results indicate that all the treatments, to different extents, induce significant changes in root-associated rice microbial communities particularly at T1, with a stronger effect on prokaryotes. Notably, our data indicate that these changes modify the community network structure involving keystone taxa. However, at T2 the microbial communities dynamics were re-established suggesting a temporary delay in the microbial interaction established by treated plants compared to the control ones. Despite these changes, under most of the tested conditions, the hub taxa still include genera with well-acknowledged plant-beneficial traits such as Sphingomonas , Streptomyces , and Haliangium . This last species has been already recognized as a hub taxon in rice paddies, being very sensitive to external solicitations such as abiotic stresses (negative correlation) or biofertilization (positive correlation) , and to be enriched in the rice root endosphere under the disturbance of barnyard grass ( Echinochloa crus-galli ). Shoot metabolome and its correlation with the rhizomicrobiome In the current study, we found that the soil treatment with zaxinone and its synthetic mimics systematically promote different metabolic pathways in the shoot of rice plants. Notwithstanding the treatment with zaxinone and MiZax exert comparable activity in the plant , the impact on shoot metabolites and grain nutrient content display some differences that may be also attributed to the different rhizomicrobiota composition. It was determined in different host plants that different rhizomicrobiota communities play a significant role in metabolic profiles and mineral nutrient uptake at local and systemic level – . The main metabolic differences in sugar, organic acid, and amino acid content have been detected at T1 upon MiZax3 treatment, while at T2 few differences have been observed between all treatments. Wang et al. demonstrated that the growth-promoting effect of zaxinone is strongly linked with an increase in sugar metabolism in rice shoot at 24 h after treatment. In our conditions, differences in sugar content were not detected in the shoot of rice plants treated with zaxinone. In contrast, MiZax3 at T1 exhibited an increase in myoinositol and threitol content. Concerning the organic acids content, we observed at T1 an accumulation of oxoglutarate, pyruvate, dehydroascorbate, and glycerate in the shoot of MiZax3 treated plants, the content of some of them (oxoglutarate and glycerate) increased also upon MiZax5 treatment and as a general trend we observed an accumulation of these metabolites in shoots of plants treated with zaxinone. Interestingly, Wang et al. previously demonstrated the early accumulation of 2-oxoglutaric acid and glyceric acid in shoot as a response to zaxinone treatment, suggesting that also MiZax compounds play a role in organic acid metabolism. However, we measured a lower content of citrate and malate. Since both organic acids contribute to the acquisition of phosphorus in soils , the reduced accumulation of these acids may be associated with the lower content of phosphoric acid observed in the shoots of all treated plants. Concerning amino acid content, we identified an increment of GABA, alanine, and threonine content in both MiZax at T1. It is worth noting that upon these treatments at T1, we observed an increase of nitrogen-fixing bacteria such as Comamonadaceae and Devosia . Given their known ability to enhance plant nitrogen uptake and to produce amino acids, these bacteria may be accountable for the enhanced amino acid content in these plants . In line with this hypothesis, Rahmoune and colleagues (2019) demonstrated that the inoculation of plant growth-promoting rhizobacteria (PGPR) in Datura stramonium affected significantly the amino acid content in both organs (root and shoot), highlighting a consistent increment of alanine in the shoot of inoculated plants. Impact of zaxinone and its mimics on grain nutrient content Since it has been reported that zaxinone and MiZax also promoted the growth and yield of horticultural crops under open-field conditions – , we, therefore, investigated their impact on grain nutritional content. Regarding the mineral nutrients profile, we observed that zaxinone increased Zinc (Zn) and Cu content, while Mn was reduced under both MiZax treatments. Notably, elevated Zn concentration has been reported in rice grains of plants inoculated with β and ɣ-proteobacteria (i.e. Sphingomonas sp., Burkholderia cepacia , Pantoea rodasii , and Enterobacter sp.) indicating a key role of rice-associated microbes in mineral grain content , . Zinc deficiency is a major constraint to rice production and Zn is also often deficient in humans with rice-based diets . The increase in Zn in the seeds of plants treated with zaxinone validates the use of this metabolite not only for improving rice growth but also for enhancing the nutritional aspect of the grain. Concerning Mn and Cu, both are considered essential elements for the growth and development of plants participating in many metabolic processes, including oxidation-reduction (redox), and photosynthesis . The lower amount of Mn in grains of MiZax treated plants could be related to the increase in the level of chlorophyll and in the enhancement of photosynthetic activities reported in rice that could affect Mn homeostasis and translocation from shoot to the grains. Rice fields represent a peculiar environment for the microbial soil communities. Due to the periodic flooding, this habitat is characterized by oxygen-limited conditions that shape the microbiota assembly. Bacterial communities typically include both aerobic and anaerobic taxa . The overall microbiota assembly from unplanted soil revealed a prokaryotic composition typical of paddy environments, including Gemmatimonadetes, Chloroflexi, Acidobacteria and Actinobacteria, and the archaeal phylum Crenarchaeota – . On the fungal side, our analysis revealed a relevant proportion of Leotiomycetes in all the conditions considered. This group of fungi includes good organic matter decomposers that can tolerate high levels of heavy metal contaminants usually found in paddy soils , and can associate with plant roots living as endophytes. So far, the effects of exogenous treatment with zaxinone and its mimics (MiZax3 and MiZax5) were investigated considering the growth promotion activity, the regulation of SLs biosynthesis, and the AM symbiosis , . Here, we provide comprehensively new information about the impact of these compounds on paddy soil and rice root-associated microbes and how these effects systemically influence rice metabolomic and grain nutrient profiles considering different developmental stages. The metabarcoding analysis highlighted that rice microbiome assembly is mainly influenced by compartment niche and developmental stage as already reported for rice and other plants – , regardless of zaxinone and MiZax treatments. In contrast to the findings reported by Zangh and colleagues , which observed a reduction in root microbial community richness in the later stage of the rice life cycle, our data reveals a general increase in α -diversity at T2 compared to T1 across the three considered compartments (unplanted soil, rhizosphere, and endosphere), regardless of the treatments. This increment was evident in the endosphere particularly for the prokaryotic community while the α -diversity of the fungal community increased over time only under zaxinone and MiZax5 treatments. Notwithstanding the compartment and developmental stage, zaxinone and MiZax treatments significantly influenced the β -diversity of prokaryotic microbial communities. Notably, we highlighted a shared pattern between MiZax3 and MiZax5 more similar to the acetone control, whereas a clear separation was evident for samples treated with zaxinone. Studies focused on plant traits demonstrated that MiZax3 and MiZax5 exhibit zaxinone-like activity by rescuing the root growth of a zaxinone-deficient rice mutant. They also promote overall growth and decrease SLs content in both roots and root exudates of wild-type plants . However, contrasting results were observed when mycorrhization was considered. Specifically, the application of 5 µM MiZax did not negatively impact AM fungal root colonization, whereas zaxinone treatment markedly reduced AM mycorrhization , . These findings suggested that zaxinone and MiZax compounds can be interchanged when plant traits are concerned but more caution is needed considering plant-microbe interactions. Our metabarcoding data are consistent with these observations. As shown by the analysis of compartment-specific taxa, the different pattern between MiZax and zaxinone treatment seems to be more evident at T1. Herein, a stronger polarization between root and rhizosphere prokaryotic communities occurs in MiZax3 and MiZax5 compared to the acetone control. Conversely, in the zaxinone treatment, a higher overlap between these two compartments is detected at both developmental stages. In particular, in the endosphere at T1, we identified an increased number of ASVs which are key soil-beneficial bacterial taxa, such as Comamonadaceae, Acidibacter , and Devosia , enriched under MiZax3 and MiZax5 treatments. Acidibacter and Comamonadaceae have normally high phosphorus solubilizing activity , and in addition, Comamonadaceae has also the ability to solubilize potassium, zinc, and nitrogen and its abundance has been related to disease-suppressive soil , . Devosia has been reported as nitrogen-fixing bacteria which also alleviate abiotic stress and recently has been reported to be enriched on AM extraradical hyphae and mycorrhizal root . Furthermore, two novel Devosia species recently isolated from the rice rhizosphere have been demonstrated to produce IAA and siderophores . Further, in the rhizosphere MiZax3 and MiZax5 shared the accumulation of keystone rhizobacteria taxa such as Pedosphaeraceae , and Nitrosarchaeum which is predicted to be an anaerobic hydrocarbon-degrading bacteria in the subsurface soil . By contrast, at T2 in both zaxinone and MiZax3, rhizosphere and endosphere prokaryotic communities were more similar, while MiZax5 still maintained the pattern shown at T1. By contrast, the impact of the treatments on soil communities was detectable but negligible in term of the amount of regulated taxa. It is plausible to hypothesize that the soil environment more effectively buffers exogenous environmental changes, potentially due to its higher microbial abundance compared to root tissues. As an alternative, we can hypothesize that the applied molecules only exert a limited direct effect on the microbial communities, such an outcome being magnified by the plant. Zaxinone and its mimics are in fact perceived by the plant, which might undertake modification of its hormonal balance and/or rhizodeposition that could result in a differential recruitment of endosphere/rhizosphere microbiota. Coupled with the evidence that the application of MiZax3 and MiZax5 differentially modulated the abundances of bacterial ASVs both in the endosphere and in the rhizosphere, this data suggests that each molecule has a specific impact on shaping the bacterial community. Compared with the acetone control, at T1, all the molecules exerted the most significant impact on the root endosphere bacterial and fungal communities with a widespread depletion of taxa, while an opposite pattern was observed in the rhizosphere where the compounds supply incremented the number of enriched taxa, at least for prokaryotic communities. At T2 a higher ratio of depleted prokaryotic taxa was observed in the endosphere following treatment with zaxinone and MiZax3 while MiZax5 has a milder effect, with enriched taxa prevailing on the depleted ones. The endosphere mycobiota was slightly less impacted by treatments compared to T1. In the rhizosphere and in the unplanted soil, all the treatments displayed a limited impact in terms of enriched/depleted taxa, irrespective of the timepoint. These findings suggest that zaxinone and MiZax treatments exert the highest impact on microbial communities in the root endosphere, suggesting once again that these dynamics are likely influenced by plant-mediated processes. In the analysis of the taxonomic diversity of differentially abundant taxa in the root endosphere, it was observed that depleted taxa were widely distributed across the bacterial phylogeny. Notably, Actinobacteriota was an exception, mostly showing an increase in their abundance in all treatments at T1. This phylum is recognized as the producer of many bioactive metabolites in agriculture, such as insecticides, herbicides, fungicides, and growth-promoting substances for plants . By contrast, the abundance of Acidobacteria decreased drastically, overall. Interestingly, a lower abundance of Acidobacteria was also found in rice d17 mutant lines defective for SLs biosynthesis , suggesting that the decreased Acidobacteria abundance in the endosphere of zaxinone and MiZax treated plants could be dependent on the negative impact of these compounds on SLs biosynthesis. At the same time, we observed an enrichment of Chitinophagaceae upon MiZax3 treatment. Since Chitinophagaceae was negatively associated with orobanchol , their higher abundance could be related to the negative impact of MiZax on SLs biosynthesis. Regarding the fungal community, we observed a depletion of Mucoromycota phylum. It is worth noting that different Funneliformis ASVs belonging to Glomeromycotina subphylum were depleted by zaxinone treatment at T1 while enriched at T2. By contrast, MiZax3 and MiZax5 have a mild impact at both time points. These findings are in line with our previous reports which displayed at early time points a strong reduction of AM symbiosis colonization in rice root treated with zaxinone while no negative effects were reported upon MiZax treatment , . The decrease of these taxa at a very early sampling time may be attributed to the lower SL content in root exudates induced by zaxinone treatment . The SLs reduction potentially delays the mycorrhization process, which however was fully recovered over time. The analysis of prokaryotic community interactions in the endosphere, revealed in zaxinone and MiZax-treated rice roots at T1 a decrease in network complexity and in a number of keystone taxa compared to the control, with the most pronounced effects for zaxinone and MiZax5 treatments, although few but significant plant-beneficial microbes emerged as hubs-taxa. However, at T1 all the network metrics indicated for most of the treatments a decentralization of microbe-microbe interactions compared to the control, with few but wider connections spanning through the network and possibly resulting in a community less dependent on a few hub species. These features suggest that at T1 the community may be more resilient to external perturbations, but further experiments are needed to confirm these speculations. At T2, in all treated plants and in particular, upon MiZax5, significant interactions between taxa were re-established in a similar way to the acetone control, with a shift in microbes potentially holding plant-beneficial traits among the identified keystone taxa. Overall, our results indicate that all the treatments, to different extents, induce significant changes in root-associated rice microbial communities particularly at T1, with a stronger effect on prokaryotes. Notably, our data indicate that these changes modify the community network structure involving keystone taxa. However, at T2 the microbial communities dynamics were re-established suggesting a temporary delay in the microbial interaction established by treated plants compared to the control ones. Despite these changes, under most of the tested conditions, the hub taxa still include genera with well-acknowledged plant-beneficial traits such as Sphingomonas , Streptomyces , and Haliangium . This last species has been already recognized as a hub taxon in rice paddies, being very sensitive to external solicitations such as abiotic stresses (negative correlation) or biofertilization (positive correlation) , and to be enriched in the rice root endosphere under the disturbance of barnyard grass ( Echinochloa crus-galli ). In the current study, we found that the soil treatment with zaxinone and its synthetic mimics systematically promote different metabolic pathways in the shoot of rice plants. Notwithstanding the treatment with zaxinone and MiZax exert comparable activity in the plant , the impact on shoot metabolites and grain nutrient content display some differences that may be also attributed to the different rhizomicrobiota composition. It was determined in different host plants that different rhizomicrobiota communities play a significant role in metabolic profiles and mineral nutrient uptake at local and systemic level – . The main metabolic differences in sugar, organic acid, and amino acid content have been detected at T1 upon MiZax3 treatment, while at T2 few differences have been observed between all treatments. Wang et al. demonstrated that the growth-promoting effect of zaxinone is strongly linked with an increase in sugar metabolism in rice shoot at 24 h after treatment. In our conditions, differences in sugar content were not detected in the shoot of rice plants treated with zaxinone. In contrast, MiZax3 at T1 exhibited an increase in myoinositol and threitol content. Concerning the organic acids content, we observed at T1 an accumulation of oxoglutarate, pyruvate, dehydroascorbate, and glycerate in the shoot of MiZax3 treated plants, the content of some of them (oxoglutarate and glycerate) increased also upon MiZax5 treatment and as a general trend we observed an accumulation of these metabolites in shoots of plants treated with zaxinone. Interestingly, Wang et al. previously demonstrated the early accumulation of 2-oxoglutaric acid and glyceric acid in shoot as a response to zaxinone treatment, suggesting that also MiZax compounds play a role in organic acid metabolism. However, we measured a lower content of citrate and malate. Since both organic acids contribute to the acquisition of phosphorus in soils , the reduced accumulation of these acids may be associated with the lower content of phosphoric acid observed in the shoots of all treated plants. Concerning amino acid content, we identified an increment of GABA, alanine, and threonine content in both MiZax at T1. It is worth noting that upon these treatments at T1, we observed an increase of nitrogen-fixing bacteria such as Comamonadaceae and Devosia . Given their known ability to enhance plant nitrogen uptake and to produce amino acids, these bacteria may be accountable for the enhanced amino acid content in these plants . In line with this hypothesis, Rahmoune and colleagues (2019) demonstrated that the inoculation of plant growth-promoting rhizobacteria (PGPR) in Datura stramonium affected significantly the amino acid content in both organs (root and shoot), highlighting a consistent increment of alanine in the shoot of inoculated plants. Since it has been reported that zaxinone and MiZax also promoted the growth and yield of horticultural crops under open-field conditions – , we, therefore, investigated their impact on grain nutritional content. Regarding the mineral nutrients profile, we observed that zaxinone increased Zinc (Zn) and Cu content, while Mn was reduced under both MiZax treatments. Notably, elevated Zn concentration has been reported in rice grains of plants inoculated with β and ɣ-proteobacteria (i.e. Sphingomonas sp., Burkholderia cepacia , Pantoea rodasii , and Enterobacter sp.) indicating a key role of rice-associated microbes in mineral grain content , . Zinc deficiency is a major constraint to rice production and Zn is also often deficient in humans with rice-based diets . The increase in Zn in the seeds of plants treated with zaxinone validates the use of this metabolite not only for improving rice growth but also for enhancing the nutritional aspect of the grain. Concerning Mn and Cu, both are considered essential elements for the growth and development of plants participating in many metabolic processes, including oxidation-reduction (redox), and photosynthesis . The lower amount of Mn in grains of MiZax treated plants could be related to the increase in the level of chlorophyll and in the enhancement of photosynthetic activities reported in rice that could affect Mn homeostasis and translocation from shoot to the grains. Taken together, soil application of zaxinone and MiZax exerted a temporary strong effect on the endosphere microbial communities, particularly prokaryotes, while a minor impact on fungal communities was observed. Moreover, if the T1 showed a general depletion of the prokaryotes communities and a reduction of hub-taxa at T2 all treated plants, especially those treated with MiZax5, re-established significant interactions between taxa at a level comparable to the acetone control. This recovery can be due to the difference in the plant phenological stage or to enhanced resilience of the rhizomicrobiota community to tolerate exogenous treatments over time. Among the communities impacted by treatments, a number of taxa potentially holding plant-beneficial traits were observed. However, since plant-growth promoting capacities cannot be confirmed by our metabarcoding approach, this evidence needs further validation by isolating strains or by in vitro tests. Interestingly, the differences in microbial communities assembly highlighted at T1 among treatments and between the control are also partially mirrored in the metabolites profiles which displayed changes in sugar, organic acid, and amino acid content depending on the condition considered, while few differences between shoot of treated and control plants are observed at T2. Furthermore, the grain biochemical characterization revealed that these compounds are not only beneficial for increasing plant biomass and yield – , but also hold promise for enhancing the accumulation of zinc content in rice seeds. With the adopted experimental set-up it was not possible to disentangle the effects of the treatments themselves on plant-associated communities from the changes arising from the different SLs exudation pattern exerted by MiZax application – . However, even to a much lower extent, treatments also impacted the soil prokaryotic community in absence of the plant suggesting a role for these molecules in shaping plant-associated microbial assemblages in a direct manner. This evidence opens new research questions, such as the understanding of contribution of the plant-mediated signaling on the changes observed here and whether these occur in a similar way across different crop plant models. Overall, our results reinforce the practical use of zaxinone and MiZax application in the field as ecologically friendly biostimulants to enhance crop productivity without causing permanent disruption to the native rice root-associated microbiota, thereby paving the way for new strategies towards sustainable agriculture worldwide. Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 |
Validation Study of a Distress Screener | 521003cd-4ba1-4426-b0eb-bb43d3f35239 | 2712065 | Preventive Medicine[mh] | The prevalence of common mental disorders (CMDs) in employees on sick leave is reported to be over 30% in the Netherlands in 2007. This prevalence is high compared with other countries . Adjustment disorders account for most psychopathology giving rise to inability to work in the Netherlands, whereas psychiatric illnesses, such as major depression, anxiety disorders, psychoses, and personality disorders, account for only a small minority of cases . The societal and financial costs of disfunctioning in terms of (long term) sickness absence due to CMDs are extensive . With the increase of mental workload over the past decades, the fraction of psychological problems related to occupational stress has increased rapidly . Dutch studies revealed that about 20% of patients with CMDs stayed on sick leave for more than 1 year . Within the context of Dutch occupational health care, distress is commonly experienced by employees and frequently related to sickness absence . In case of distress-related sickness absence early identification is important to prevent long-term sick leave and to enable early interventions, because it is known that long-lasting work disability reduces the chance of return to work . Terluin developed the four-dimensional symptom questionnaire (4DSQ) which is a self-report questionnaire of 50 items that measures non-specific general distress, depression, anxiety and somatisation. The 4DSQ is incorporated in the guideline for psychological problems of the Dutch association of occupational medicine and is frequently applied by occupational physicians (OPs) among employees on sick leave. A disadvantage of the 4DSQ is the relatively long time that it takes to be filled in (5–10 min). In that way precious time is lost during a consultation. Consequently, occupational physicians often request their patients to fill it in at home and hand it in at the next consultation. So, there is a need for a short questionnaire, which identifies distress in an early stage of sick leave. In this study a 3-item version of the 4DSQ distress subscale was developed and tested. The purpose of this study was to assess an optimal cut-off point and to validate this so-called Distress Screener.
Research Population The research population consisted of employees on sick leave of three Dutch companies: an academic hospital, an university and a steel company. A diversity of job functions were included in this study. The specific inclusion criteria were: full or part-time on sick leave, duration of sick leave shorter than 8 weeks and no period of sick leave with the same reason within 1 month before the current episode to select only incident cases of work disability. Recruitment Study Population All employees who were on sick leave for more than 1 week received the Distress Screener together with an explanatory letter from the OP. The respondents who met the inclusion criteria and were willing to participate, were divided in two groups according to the score of the Distress Screener with cut-off point four. This cut-off point was based on a required level of specificity, calculated in a group of non-selected primary care patients ( N = 2127) and was used for the intervention study: the ADAPT study. The research population in the current paper is based in part on the population of the ADAPT study. The ADAPT study is a randomized controlled trial evaluating the cost-effectiveness of a participatory workplace intervention compared with usual care for sick-listed employees with distress . The workplace intervention is a stepwise approach in which an employee and supervisor identify and prioritize obstacles and solutions for a return to work guided by a mediator. The intervention is aimed to reach consensus between a sick-listed employee and his or her supervisor about a plan for return to work. In the period between April 2006 and May 2007, respondents who were screened positive according to the Distress Screener were recruited for the ADAPT study . In addition, a sample of non-distressed (screened negative) employees on sick leave were recruited from the same three companies in the period January till May 2007. Permission was obtained from the Medical Ethics committee and all respondents provided informed consent. Within one till 2 weeks after filling in the Distress Screener, the respondents filled in the 4DSQ. In addition, data of OPs diagnoses were obtained from the medical file of each employee. These diagnoses were a proportional breakdown of the types of health problems that were typical for this population and which led to extended sickness absence. OPs in the Netherlands classify diagnoses according to the international classification of diseases (CAS) which is based on the ICD-10. Measurement Instruments The Distress Screener is a short questionnaire which comprises three items of the 4DSQ distress subscale: “During the past week, did you suffer from worry?”, “During the past week, did you suffer from listlessness?” and “During the past week, did you feel tense?”. The selection of items was made a priori from a dataset consisting of 2,127 primary care patients. The three items were chosen based on their factor loadings and ‘difficulties’, so as to maximize the discrimination between subjects with 4DSQ distress-scores ≤10 and subjects with 4DSQ distress-scores >10. The response scale contains three options: “no” (0), “sometimes” (1), and “regularly or more often” (2). A total score was constructed by summing up the answers on the three items. The cut-off point that discriminates between ‘screened positive’ and ‘screened negative’ was established on a score of 4 or higher. A positive score means that the person involved is scored as distressed according to the Distress Screener. The 4DSQ is a questionnaire comprising 50 items distributed over four scales: the distress scale contains 16 items (range 0–32), the depression scale contains 6 items (range 0–12), the anxiety scale contains 12 items (range 0–24) and the somatisation scale contains 16 items (range 0–32) . The reference period is “the past week”. The response scale contains five categories: “no” (0), “sometimes” (1), “regularly” (2), “often” (2), “very often or constantly” (2). The item scores are summated to scale scores. Discrimination between ‘cases’ and ‘non-cases’ were established for distress score >10, somatisation score >10, depression score >2, and anxiety score >7 . Measuring distress with the 4DSQ has been shown to be a valid and reliable measurement . According to Van Rhenen et al. the distress score of >10 is appropriate for use in studies of distress in working populations and therefore used as reference standard in this study. OPs diagnoses [CAS-codes based on the ICD-10 and developed by the Dutch Association of Occupational Medicine (NVAB) and the Employed Persons’ Insurance Administration Agency (UWV)] were classified into six categories of CMDs. Four categories of diagnoses were related to the subscales of the 4DSQ, ‘Distress’ (‘Stress-related complaints’), ‘Somatisation’, ‘Depression’ and ‘Anxiety’, plus the categories of ‘Other psychological complaints’ and ‘Other complaints’ (see Table ). Analyses In order to adjust for the stratified sampling procedure, we used weight factors for all analyses (0.666 for screen-positive and 1.308 for screen-negative employees) to ensure that the population reflected the composition of the source population of incident sick-leave cases. Using the 4DSQ distress score >10 as reference standard, the receiver operator characteristic (ROC) curve of the Distress Screener was obtained for a range of seven cut-off values (0–6). Sensitivity and specificity were calculated for each cut-off value. With regard to this study, identification of distress by the Distress Screener in an early stage of sick leave, it was important to select a high number of true-positively classified distressed persons and restrict the number of false-positively classified healthy persons. Therefore, determination of the optimal cut-off point was based on a high sensitivity value with the most appropriate specificity value. To examine the validity of the Distress Screener the Pearson correlation coefficients were calculated between the total score of the Distress Screener and the total score of each 4DSQ subscale. We compared correlated correlation coefficients, according to the method described by Meng et al. , including a Bonferroni correction. The degree of similarity between two repeated measurements, the test–retest (12-day) reliability, was obtained by computing the Pearson correlation coefficient of the total score of the three items of the Distress screener with the total score of the same three items of the 4DSQ distress subscale. Furthermore, the validity was examined by comparing the outcomes of the Distress Screener (screened negative and screened positive) with OPs diagnoses (categorized CAS-codes). Both relations of the Distress Screener with OPs diagnoses and the 4DSQ distress subscale with OPs diagnoses were compared. Sensitivity and specificity values and positive and negative predictive values were determined from the established outcomes. Outcomes of both the Distress Screener and the 4DSQ distress subscale were dichotomised.
The research population consisted of employees on sick leave of three Dutch companies: an academic hospital, an university and a steel company. A diversity of job functions were included in this study. The specific inclusion criteria were: full or part-time on sick leave, duration of sick leave shorter than 8 weeks and no period of sick leave with the same reason within 1 month before the current episode to select only incident cases of work disability.
All employees who were on sick leave for more than 1 week received the Distress Screener together with an explanatory letter from the OP. The respondents who met the inclusion criteria and were willing to participate, were divided in two groups according to the score of the Distress Screener with cut-off point four. This cut-off point was based on a required level of specificity, calculated in a group of non-selected primary care patients ( N = 2127) and was used for the intervention study: the ADAPT study. The research population in the current paper is based in part on the population of the ADAPT study. The ADAPT study is a randomized controlled trial evaluating the cost-effectiveness of a participatory workplace intervention compared with usual care for sick-listed employees with distress . The workplace intervention is a stepwise approach in which an employee and supervisor identify and prioritize obstacles and solutions for a return to work guided by a mediator. The intervention is aimed to reach consensus between a sick-listed employee and his or her supervisor about a plan for return to work. In the period between April 2006 and May 2007, respondents who were screened positive according to the Distress Screener were recruited for the ADAPT study . In addition, a sample of non-distressed (screened negative) employees on sick leave were recruited from the same three companies in the period January till May 2007. Permission was obtained from the Medical Ethics committee and all respondents provided informed consent. Within one till 2 weeks after filling in the Distress Screener, the respondents filled in the 4DSQ. In addition, data of OPs diagnoses were obtained from the medical file of each employee. These diagnoses were a proportional breakdown of the types of health problems that were typical for this population and which led to extended sickness absence. OPs in the Netherlands classify diagnoses according to the international classification of diseases (CAS) which is based on the ICD-10.
The Distress Screener is a short questionnaire which comprises three items of the 4DSQ distress subscale: “During the past week, did you suffer from worry?”, “During the past week, did you suffer from listlessness?” and “During the past week, did you feel tense?”. The selection of items was made a priori from a dataset consisting of 2,127 primary care patients. The three items were chosen based on their factor loadings and ‘difficulties’, so as to maximize the discrimination between subjects with 4DSQ distress-scores ≤10 and subjects with 4DSQ distress-scores >10. The response scale contains three options: “no” (0), “sometimes” (1), and “regularly or more often” (2). A total score was constructed by summing up the answers on the three items. The cut-off point that discriminates between ‘screened positive’ and ‘screened negative’ was established on a score of 4 or higher. A positive score means that the person involved is scored as distressed according to the Distress Screener. The 4DSQ is a questionnaire comprising 50 items distributed over four scales: the distress scale contains 16 items (range 0–32), the depression scale contains 6 items (range 0–12), the anxiety scale contains 12 items (range 0–24) and the somatisation scale contains 16 items (range 0–32) . The reference period is “the past week”. The response scale contains five categories: “no” (0), “sometimes” (1), “regularly” (2), “often” (2), “very often or constantly” (2). The item scores are summated to scale scores. Discrimination between ‘cases’ and ‘non-cases’ were established for distress score >10, somatisation score >10, depression score >2, and anxiety score >7 . Measuring distress with the 4DSQ has been shown to be a valid and reliable measurement . According to Van Rhenen et al. the distress score of >10 is appropriate for use in studies of distress in working populations and therefore used as reference standard in this study. OPs diagnoses [CAS-codes based on the ICD-10 and developed by the Dutch Association of Occupational Medicine (NVAB) and the Employed Persons’ Insurance Administration Agency (UWV)] were classified into six categories of CMDs. Four categories of diagnoses were related to the subscales of the 4DSQ, ‘Distress’ (‘Stress-related complaints’), ‘Somatisation’, ‘Depression’ and ‘Anxiety’, plus the categories of ‘Other psychological complaints’ and ‘Other complaints’ (see Table ).
In order to adjust for the stratified sampling procedure, we used weight factors for all analyses (0.666 for screen-positive and 1.308 for screen-negative employees) to ensure that the population reflected the composition of the source population of incident sick-leave cases. Using the 4DSQ distress score >10 as reference standard, the receiver operator characteristic (ROC) curve of the Distress Screener was obtained for a range of seven cut-off values (0–6). Sensitivity and specificity were calculated for each cut-off value. With regard to this study, identification of distress by the Distress Screener in an early stage of sick leave, it was important to select a high number of true-positively classified distressed persons and restrict the number of false-positively classified healthy persons. Therefore, determination of the optimal cut-off point was based on a high sensitivity value with the most appropriate specificity value. To examine the validity of the Distress Screener the Pearson correlation coefficients were calculated between the total score of the Distress Screener and the total score of each 4DSQ subscale. We compared correlated correlation coefficients, according to the method described by Meng et al. , including a Bonferroni correction. The degree of similarity between two repeated measurements, the test–retest (12-day) reliability, was obtained by computing the Pearson correlation coefficient of the total score of the three items of the Distress screener with the total score of the same three items of the 4DSQ distress subscale. Furthermore, the validity was examined by comparing the outcomes of the Distress Screener (screened negative and screened positive) with OPs diagnoses (categorized CAS-codes). Both relations of the Distress Screener with OPs diagnoses and the 4DSQ distress subscale with OPs diagnoses were compared. Sensitivity and specificity values and positive and negative predictive values were determined from the established outcomes. Outcomes of both the Distress Screener and the 4DSQ distress subscale were dichotomised.
Subjects A total of 5,845 Distress Screeners were sent to employees on sick leave (see Fig. ). About 2,562 screeners came back, in which 1,620 employees were still sick-listed and 942 resumed work. Respectively, 517 employees screened positive and 328 employees screened negative were divided into two subgroups based on cut-off point 4 of the Distress Screener. Eventually, 171 employees (resp. 82 and 89) met the inclusion criteria and gave their informed consent. Causes of dropping out were: employees did not meet the inclusion criteria (resp. 31 and 3), employees were not sick-listed anymore (resp. 162 and 51), and employees were eventually not willing to participate (resp. 112 and 61). From 74 screened positive employees (90%) and 62 screened negative employees (70%) the first diagnosis in the medical file was available. The remaining 35 employees were not consulted by the OP and therefore medical diagnoses were not available. On average there were 12 days between filling in the Distress Screener and the 4DSQ (SD = 7.42; median = 10). Optimal Cut-Off Point Table shows the weighted sensitivity and specificity values of each cut-off point. From the ROC-curve the score four or higher was derived as the optimal cut-off point of the Distress Screener because, it had the highest sensitivity value with the most appropriate specificity value. The area under the curve (AUC) had a value of 0.762 (95% CI 0.639–0.885). Correlations Between Distress Screener and 4DSQ Subscales Table shows correlations between the Distress Screener and the four subscales of the 4DSQ. The Distress Screener and the 4DSQ distress subscale had a high correlation of 0.82. The Distress Screener correlated higher with the 4DSQ distress subscale compared with the other 4DSQ subscales. Furthermore, this corrected correlated correlation coefficient was significantly different from the three correlations of the Distress Screener with the other 4DSQ subscales. The test–retest (12-day) reliability had a high correlation of 0.83. Comparison of Distress Score and OPs Diagnoses Table presents the prevalence of distress according to the Distress Screener and the prevalence of distress according to the 4DSQ distress subscale compared to the medical diagnoses. ‘Anxiety’ and ‘Somatisation’ were not diagnosed by the OPs and therefore not presented in Table . When comparing OPs diagnoses with positive and negative Distress Screener scores it can be seen that 21 out of 26 employees (80.8%) with the diagnosis ‘Stress-related complaints’, were screened positive. All employees with the diagnosis ‘Depression’ or ‘Other psychological complaints’, scored positive on the Distress Screener. Furthermore, 76 out of 98 cases (77.6%) with OPs diagnosis ‘Other complaints’ scored negative on the Distress Screener. This resulted in a sensitivity value of the Distress Screener for detecting any psychological problem as diagnosed by the OPs of 0.85 (28/28 + 5) and a specificity value of 0.78 (76/76 + 22). The positive predictive value (PPV) and negative predictive value (NPV) of the Distress Screener were respectively, 0.56 (28/50) and 0.94 (76/81). When comparing OPs diagnoses with the 4DSQ distress subscale scores it can be seen that 20 out of 25 employees (80%) who were diagnosed as having ‘Stress related complaints’ had a positive score (i.e. distressed) on the 4DSQ distress subscale. All employees with the diagnosis ‘Depression’ and ‘Other psychological complaints’ had positive scores (i.e. distressed) and 69 out of 97 cases (71.1%) with the diagnosis ‘Other complaints’ had a negative score (i.e. non-distressed). This resulted in a sensitivity value of 0.84 (27/27 + 5) and a specificity value of 0.71 (69/69 + 28) of the 4DSQ distress subscale. The PPV and NPV of the 4DSQ distress subscale were respectively, 0.49 (27/55) and 0.93 (69/74).
A total of 5,845 Distress Screeners were sent to employees on sick leave (see Fig. ). About 2,562 screeners came back, in which 1,620 employees were still sick-listed and 942 resumed work. Respectively, 517 employees screened positive and 328 employees screened negative were divided into two subgroups based on cut-off point 4 of the Distress Screener. Eventually, 171 employees (resp. 82 and 89) met the inclusion criteria and gave their informed consent. Causes of dropping out were: employees did not meet the inclusion criteria (resp. 31 and 3), employees were not sick-listed anymore (resp. 162 and 51), and employees were eventually not willing to participate (resp. 112 and 61). From 74 screened positive employees (90%) and 62 screened negative employees (70%) the first diagnosis in the medical file was available. The remaining 35 employees were not consulted by the OP and therefore medical diagnoses were not available. On average there were 12 days between filling in the Distress Screener and the 4DSQ (SD = 7.42; median = 10).
Table shows the weighted sensitivity and specificity values of each cut-off point. From the ROC-curve the score four or higher was derived as the optimal cut-off point of the Distress Screener because, it had the highest sensitivity value with the most appropriate specificity value. The area under the curve (AUC) had a value of 0.762 (95% CI 0.639–0.885).
Table shows correlations between the Distress Screener and the four subscales of the 4DSQ. The Distress Screener and the 4DSQ distress subscale had a high correlation of 0.82. The Distress Screener correlated higher with the 4DSQ distress subscale compared with the other 4DSQ subscales. Furthermore, this corrected correlated correlation coefficient was significantly different from the three correlations of the Distress Screener with the other 4DSQ subscales. The test–retest (12-day) reliability had a high correlation of 0.83.
Table presents the prevalence of distress according to the Distress Screener and the prevalence of distress according to the 4DSQ distress subscale compared to the medical diagnoses. ‘Anxiety’ and ‘Somatisation’ were not diagnosed by the OPs and therefore not presented in Table . When comparing OPs diagnoses with positive and negative Distress Screener scores it can be seen that 21 out of 26 employees (80.8%) with the diagnosis ‘Stress-related complaints’, were screened positive. All employees with the diagnosis ‘Depression’ or ‘Other psychological complaints’, scored positive on the Distress Screener. Furthermore, 76 out of 98 cases (77.6%) with OPs diagnosis ‘Other complaints’ scored negative on the Distress Screener. This resulted in a sensitivity value of the Distress Screener for detecting any psychological problem as diagnosed by the OPs of 0.85 (28/28 + 5) and a specificity value of 0.78 (76/76 + 22). The positive predictive value (PPV) and negative predictive value (NPV) of the Distress Screener were respectively, 0.56 (28/50) and 0.94 (76/81). When comparing OPs diagnoses with the 4DSQ distress subscale scores it can be seen that 20 out of 25 employees (80%) who were diagnosed as having ‘Stress related complaints’ had a positive score (i.e. distressed) on the 4DSQ distress subscale. All employees with the diagnosis ‘Depression’ and ‘Other psychological complaints’ had positive scores (i.e. distressed) and 69 out of 97 cases (71.1%) with the diagnosis ‘Other complaints’ had a negative score (i.e. non-distressed). This resulted in a sensitivity value of 0.84 (27/27 + 5) and a specificity value of 0.71 (69/69 + 28) of the 4DSQ distress subscale. The PPV and NPV of the 4DSQ distress subscale were respectively, 0.49 (27/55) and 0.93 (69/74).
Main Findings The present study examined the validity and the optimal cut-off point of the Distress Screener. According to the results cut-off point ≥4 is most optimal. With regard to early identification of distress in employees on sick leave it is important to select a high number of true-positively classified distressed persons. Thus, in this study and the ADAPT study the optimal cut-off point was correctly chosen. The results confirmed a high validity of the Distress Screener. In line with our expectations the Distress Screener was only significantly related to the 4DSQ distress subscale and not to the other three 4DSQ subscales. Furthermore the results indicated a high validity of the Distress Screener and the 4DSQ distress subscale when comparing them to OPs diagnoses. Both the Distress Screener and the 4DSQ distress subscale showed high agreement with OPs diagnosis ‘Stress-related complaints’ and other psychological problems as assessed by the OPs. The sensitivity and specificity, and the PPV and NPV of the Distress Screener were comparable to those of the 4DSQ distress subscale. Explanation of Results As only five employees were diagnosed with ‘Depression’ by the OPs, it is not possible to draw up conclusions of outcomes of the positive score of the Distress Screener and the 4DSQ distress subscale with OPs diagnosis ‘Depression’. Therefore, it should be cautioned to interpret these results. Literature suggests that psychological distress overlaps with various symptoms of depression and burnout, and contains psycho-physiological and behavioural symptoms that are not specific to a given pathology . In line with the nature of distress as the general, most basic dimension of psychopathology, it is to be expected that distress symptoms also are present when depression is diagnosed. The relation between OPs diagnosis ‘Other complaints’ and distress can be explained in several ways. First, it is reasonable that the OPs did not recognize the symptoms of distress in some cases. And secondly, it is reasonable that OPs were more focused on diagnosing the somatic complaint, distress was not the main diagnosis at that moment. ‘Anxiety’ and ‘Somatisation’ were not diagnosed by the OPs. It is imaginable that symptoms of anxiety and somatisation are more difficult to recognize and will be recorded often as stress-related mental disorders. Literature confirms that anxiety disorders encompass a combination of distress and depression, or distress and anxiety symptoms , along with a variable degree of somatisation symptoms . Furthermore, symptoms like back pain, neck pain and painful muscles were quite often diagnosed according to the medical files. We classified these diagnoses into the category of ‘Other complaints’. It is plausible that these complaints were not immediately recognised by the OPs as somatisation symptoms and were recorded as physical problems. The PPVs of both the Distress Screener and the 4DSQ distress subscale were relatively low values. These low PPVs were directly proportional to the low prevalence percentages of 25% of ‘any psychological problem’ diagnosed by the OP. ‘Any psychological problem’ was compared with the positive and negative scores of both the Distress Screener and the 4DSQ distress subscale (33/(98 + 33) and 32/(97 + 32)). Furthermore, it is plausible that the OPs overlooked distress and other psychological problems (the employee does not mention it). The PPV also decreases through these false-positives, which becomes not false-positive by a false (positive) outcome of the Distress Screener, but through a false (negative) outcome of the reference standard (the OP). Study Limitations The following limitations in this study were present. First, the Dutch registration system of CAS codes is focused on reporting one diagnosis of sickness absence by the OP. This diagnosis is directly linked with the reason of sick leave of the employee. This may explain high numbers of the diagnosis ‘Other complaints’. The second limitation of this study was the average of 12 days between completing the Distress Screener and the 4DSQ. Within these 12 days the psychological state of a person can change, especially in this early stage of sick leave. The longer the time between completing the Distress Screener and the 4DSQ, the higher the chance that the situation or psychological state changes. Distress symptoms can decrease over time or the cause of distress can disappear. Third, selection bias might have occurred while in the screened positive group eight participants and in the screened negative group 27 participants were not diagnosed by the OPs. Probably, participants without a diagnosis recovered and returned to work so quickly, that the OP did not have the opportunity to establish a diagnosis. Within the current analyses of the data these participants were classified as ‘missing’. Fourth, It is debatable to use OPs diagnoses as external criterion as there are differences between diagnoses of the OP/General Practitioner and outcomes of validated questionnaires . Alternatives were the 4DSQ or other validated questionnaires. In the guideline for psychological problems applied by OPs, the 4DSQ is also one of the diagnostic tools. Finally, generalizing the results of this study should be cautioned as only three companies were involved in this study. Moreover, the population was limited to a primary occupational healthcare population of employees on sick leave. Implications for Practice and Research The Distress Screener can be used by the OP during consulting time as a quick scan for the early identification of distress in employees on sick leave. In other words, the Distress Screener can be used by the OP for detecting employees on sick leave who need additional attention for their emotional state, whatever the reason of sick leave might be. Filling in the Distress Screener takes considerably less time than filling in the 4DSQ distress subscale and is at the same time as valid as the 4DSQ distress subscale. When physical complaints are present the Distress Screener is able to identify quickly additional distress. But, when using the Distress Screener only, lack of relevant information can occur. Considering obtaining a diagnosis, application of treatments and additional costs, the OPs should decide to fill in the whole 4DSQ (by the employee) during the first consultation if an employee scores four or higher on the Distress Screener. It is relevant and valid for OPs to screen during consulting time. When a psychological problem emerged through screening by the 4DSQ, this will be discussed with the employee. If the employee agrees with the recommended actions the guideline for psychological problems of the Dutch association of occupational medicine will be applied by the OP. The Distress Screener can also be used for research purposes. The optimal cut-off point should then be adjusted to the objectives of the research. At last, further research is needed within the working population, wherein the Distress Screener can be tested as a tool for predicting absenteeism. However, screening of populations should be performed carefully and an appropriate intervention should be available to justify screening.
The present study examined the validity and the optimal cut-off point of the Distress Screener. According to the results cut-off point ≥4 is most optimal. With regard to early identification of distress in employees on sick leave it is important to select a high number of true-positively classified distressed persons. Thus, in this study and the ADAPT study the optimal cut-off point was correctly chosen. The results confirmed a high validity of the Distress Screener. In line with our expectations the Distress Screener was only significantly related to the 4DSQ distress subscale and not to the other three 4DSQ subscales. Furthermore the results indicated a high validity of the Distress Screener and the 4DSQ distress subscale when comparing them to OPs diagnoses. Both the Distress Screener and the 4DSQ distress subscale showed high agreement with OPs diagnosis ‘Stress-related complaints’ and other psychological problems as assessed by the OPs. The sensitivity and specificity, and the PPV and NPV of the Distress Screener were comparable to those of the 4DSQ distress subscale.
As only five employees were diagnosed with ‘Depression’ by the OPs, it is not possible to draw up conclusions of outcomes of the positive score of the Distress Screener and the 4DSQ distress subscale with OPs diagnosis ‘Depression’. Therefore, it should be cautioned to interpret these results. Literature suggests that psychological distress overlaps with various symptoms of depression and burnout, and contains psycho-physiological and behavioural symptoms that are not specific to a given pathology . In line with the nature of distress as the general, most basic dimension of psychopathology, it is to be expected that distress symptoms also are present when depression is diagnosed. The relation between OPs diagnosis ‘Other complaints’ and distress can be explained in several ways. First, it is reasonable that the OPs did not recognize the symptoms of distress in some cases. And secondly, it is reasonable that OPs were more focused on diagnosing the somatic complaint, distress was not the main diagnosis at that moment. ‘Anxiety’ and ‘Somatisation’ were not diagnosed by the OPs. It is imaginable that symptoms of anxiety and somatisation are more difficult to recognize and will be recorded often as stress-related mental disorders. Literature confirms that anxiety disorders encompass a combination of distress and depression, or distress and anxiety symptoms , along with a variable degree of somatisation symptoms . Furthermore, symptoms like back pain, neck pain and painful muscles were quite often diagnosed according to the medical files. We classified these diagnoses into the category of ‘Other complaints’. It is plausible that these complaints were not immediately recognised by the OPs as somatisation symptoms and were recorded as physical problems. The PPVs of both the Distress Screener and the 4DSQ distress subscale were relatively low values. These low PPVs were directly proportional to the low prevalence percentages of 25% of ‘any psychological problem’ diagnosed by the OP. ‘Any psychological problem’ was compared with the positive and negative scores of both the Distress Screener and the 4DSQ distress subscale (33/(98 + 33) and 32/(97 + 32)). Furthermore, it is plausible that the OPs overlooked distress and other psychological problems (the employee does not mention it). The PPV also decreases through these false-positives, which becomes not false-positive by a false (positive) outcome of the Distress Screener, but through a false (negative) outcome of the reference standard (the OP).
The following limitations in this study were present. First, the Dutch registration system of CAS codes is focused on reporting one diagnosis of sickness absence by the OP. This diagnosis is directly linked with the reason of sick leave of the employee. This may explain high numbers of the diagnosis ‘Other complaints’. The second limitation of this study was the average of 12 days between completing the Distress Screener and the 4DSQ. Within these 12 days the psychological state of a person can change, especially in this early stage of sick leave. The longer the time between completing the Distress Screener and the 4DSQ, the higher the chance that the situation or psychological state changes. Distress symptoms can decrease over time or the cause of distress can disappear. Third, selection bias might have occurred while in the screened positive group eight participants and in the screened negative group 27 participants were not diagnosed by the OPs. Probably, participants without a diagnosis recovered and returned to work so quickly, that the OP did not have the opportunity to establish a diagnosis. Within the current analyses of the data these participants were classified as ‘missing’. Fourth, It is debatable to use OPs diagnoses as external criterion as there are differences between diagnoses of the OP/General Practitioner and outcomes of validated questionnaires . Alternatives were the 4DSQ or other validated questionnaires. In the guideline for psychological problems applied by OPs, the 4DSQ is also one of the diagnostic tools. Finally, generalizing the results of this study should be cautioned as only three companies were involved in this study. Moreover, the population was limited to a primary occupational healthcare population of employees on sick leave.
The Distress Screener can be used by the OP during consulting time as a quick scan for the early identification of distress in employees on sick leave. In other words, the Distress Screener can be used by the OP for detecting employees on sick leave who need additional attention for their emotional state, whatever the reason of sick leave might be. Filling in the Distress Screener takes considerably less time than filling in the 4DSQ distress subscale and is at the same time as valid as the 4DSQ distress subscale. When physical complaints are present the Distress Screener is able to identify quickly additional distress. But, when using the Distress Screener only, lack of relevant information can occur. Considering obtaining a diagnosis, application of treatments and additional costs, the OPs should decide to fill in the whole 4DSQ (by the employee) during the first consultation if an employee scores four or higher on the Distress Screener. It is relevant and valid for OPs to screen during consulting time. When a psychological problem emerged through screening by the 4DSQ, this will be discussed with the employee. If the employee agrees with the recommended actions the guideline for psychological problems of the Dutch association of occupational medicine will be applied by the OP. The Distress Screener can also be used for research purposes. The optimal cut-off point should then be adjusted to the objectives of the research. At last, further research is needed within the working population, wherein the Distress Screener can be tested as a tool for predicting absenteeism. However, screening of populations should be performed carefully and an appropriate intervention should be available to justify screening.
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null | af6a7732-0a78-410c-8346-f7f8763772f7 | 9571880 | Pharmacology[mh] | Polygonum capitatum is a well-known and large-scale Miao medicinal plant with a long history of economic and medicinal value. Amongst Chinese people, especially in Guizhou province, P. capitatum is commonly named TouHuaLiao . It is often named Gastrochilus panduratum RIDL., Kaempferia pandurata Roxb., Curcuma rotunda L., and Boesenbergia rotunda Linn . At present, P. capitatum shows a variety of pharmacological activities, including anti-inflammatory, antioxidant, antimicrobial, anticancer, analgesic, hypothermic, diuretic and other pharmacological effects . These pharmacological activities are attributed to the chemical constituents and extracts of P. capitatum . So far, more than 90 compounds have been isolated from P. capitatum . Phenolic acids and flavonoids are believed to be responsible for the bioactivities of P. capitatum . With recently increasing levels of research into P. capitatum , it is especially valuable to review its current status in order to provide reference for a deep exploration of its ethnic medicinal potential. This review summarized progress in the chemical study of P. capitatum , mainly covering the classes of flavonoids, lignanoids, phenols, and other components. Moreover, we systematically organized the development of the medicinal flora into traditional usages, botany, and pharmacology. Qualitative and quantitative chemical analyses were also covered. Furthermore, a number of P. capitatum -based drugs (Relinqing Granule and Milin Capsule) have been approved by the State Food and Drug Administration. The other P. capitatum -based drugs, Relinqing ® Granule and Milin ® Capsule, have also been approved by the China Food and Drug Administration . In addition, research directions for the future and prospects of P. capitatum were also discussed in this article. 1.1. The Traditional and Ethnical Uses of P. Capitatum in China P. capitatum first appeared in the “ Guangxi Traditional Chinese Medicine Annals ”, as a method to dispel wind, disperse blood stasis and relieve pain . Contemporary among the works of “ Guangxi Chinese Herbal Medicine ”, it possessed the effects of detoxification and inflammation, and was chiefly used for the treatment of dysentery, skin ulcers, and unspecified poisonous swelling . Furthermore, it was recorded in the masterworks of “ Yunnan Chinese Herbal medicine ”; it had the pharmacological effect of clear heat diuresis drenching . The literature was consistent with the present P. capitatum . In the 2010 edition of the Chinese Pharmacopoeia (Appendix), the name of the medicinal material was Polygonum capitatum Buch. -Ham. ex D. Don was given as the name of the herb . The medicinal parts were collected as whole dry herbs or aerial parts. P. capitatum exhibits heat- and damp-clearing functions as a medicinal diuretic . Moreover, in folk medicine it was frequently decocted with water, the therapeutic effect was more obvious, but it was inconvenient to take . In recent years, various pharmaceutical factories in Guizhou province have made full use of and developed P. capitatum resources, together with their diversified preparation products that have appeared successively. Among them, Relinqing Granule is the most representative prescription, and has the functions of heat-clearing and detoxifying, diuresis and dredging stranguria. They are used for hot stranguria caused by damp-heat in the lower energizer . 1.2. Botanical Description P. capitatum, is derived from the dried herbs of Polygonaceae species (Polygonaceae family), and is a perennial herb, 10–15 cm tall, with stolons, rooting at its nodes, annual branches ascending upward, and a red surface. Leaves are alternately oval-, base-, and wedge-shaped, sometimes with “V”-shaped markings on the leaf surface, inflorescent, terminal, perianth reddish, five-parted, and flowering from June to October each year. It is worth noting that the stem of the transverse section is composed of one to two rows of epidermis cells. The outermost part has glandular hairs where the cortex is narrow and composed of many rows of tightly arranged parenchyma cells that contain more clusters of calcium oxalate crystals. In addition, the leaf of P. capitatum is a heterofacial leaf. That is to say, the upper epidermis of the leaf of the main vein protrudes slightly upward, semicircularly, and the parenchyma cells of the protruding part are small and dense with glandular hairs often growing in the lower epidermis. Furthermore, the vascular bundles in the middle of the main veins are arranged in a ring; they are externally tough vascular bundles. Parenchyma cells are round, scattered calcium oxalate clusters. The palisade tissue is generally composed of two to three rows of long oval cells, which are closely arranged with scattered clusters of calcium oxalate crystals . 1.3. Geographic Distribution P. capitatum is generally distributed in the southwest of China, mainly in Jiangxi, Guizhou, Hunan, Hubei, Sichuan, Guangxi, Yunnan, and Tibet provinces. It is also found in other Asian countries, including India, Nepal, Bhutan, Myanmar and Vietnam. The plants of P. capitatum are fond of growing in cool and moist places, they are suitable for growing in the sandy loam of sunny valleys with good air permeability and mild acidic soil without water shortages . P. capitatum first appeared in the “ Guangxi Traditional Chinese Medicine Annals ”, as a method to dispel wind, disperse blood stasis and relieve pain . Contemporary among the works of “ Guangxi Chinese Herbal Medicine ”, it possessed the effects of detoxification and inflammation, and was chiefly used for the treatment of dysentery, skin ulcers, and unspecified poisonous swelling . Furthermore, it was recorded in the masterworks of “ Yunnan Chinese Herbal medicine ”; it had the pharmacological effect of clear heat diuresis drenching . The literature was consistent with the present P. capitatum . In the 2010 edition of the Chinese Pharmacopoeia (Appendix), the name of the medicinal material was Polygonum capitatum Buch. -Ham. ex D. Don was given as the name of the herb . The medicinal parts were collected as whole dry herbs or aerial parts. P. capitatum exhibits heat- and damp-clearing functions as a medicinal diuretic . Moreover, in folk medicine it was frequently decocted with water, the therapeutic effect was more obvious, but it was inconvenient to take . In recent years, various pharmaceutical factories in Guizhou province have made full use of and developed P. capitatum resources, together with their diversified preparation products that have appeared successively. Among them, Relinqing Granule is the most representative prescription, and has the functions of heat-clearing and detoxifying, diuresis and dredging stranguria. They are used for hot stranguria caused by damp-heat in the lower energizer . P. capitatum, is derived from the dried herbs of Polygonaceae species (Polygonaceae family), and is a perennial herb, 10–15 cm tall, with stolons, rooting at its nodes, annual branches ascending upward, and a red surface. Leaves are alternately oval-, base-, and wedge-shaped, sometimes with “V”-shaped markings on the leaf surface, inflorescent, terminal, perianth reddish, five-parted, and flowering from June to October each year. It is worth noting that the stem of the transverse section is composed of one to two rows of epidermis cells. The outermost part has glandular hairs where the cortex is narrow and composed of many rows of tightly arranged parenchyma cells that contain more clusters of calcium oxalate crystals. In addition, the leaf of P. capitatum is a heterofacial leaf. That is to say, the upper epidermis of the leaf of the main vein protrudes slightly upward, semicircularly, and the parenchyma cells of the protruding part are small and dense with glandular hairs often growing in the lower epidermis. Furthermore, the vascular bundles in the middle of the main veins are arranged in a ring; they are externally tough vascular bundles. Parenchyma cells are round, scattered calcium oxalate clusters. The palisade tissue is generally composed of two to three rows of long oval cells, which are closely arranged with scattered clusters of calcium oxalate crystals . P. capitatum is generally distributed in the southwest of China, mainly in Jiangxi, Guizhou, Hunan, Hubei, Sichuan, Guangxi, Yunnan, and Tibet provinces. It is also found in other Asian countries, including India, Nepal, Bhutan, Myanmar and Vietnam. The plants of P. capitatum are fond of growing in cool and moist places, they are suitable for growing in the sandy loam of sunny valleys with good air permeability and mild acidic soil without water shortages . To date, there are a total of 91 compounds ( 1 – 91 ) with the phytochemical composition of P. capitatum . They can be classified into four classes: 30 flavonoids, 10 lignanoids, 25 phenols, and 26 other compounds. Each phytochemical is numbered ( 1 – 91 ) and their names, formulas, molecular weights, and the parts of plant used in these compounds, are cited in the . 2.1. Flavonoids Flavonoids are large secondary metabolites found in P. capitatum . More than 30 flavonoid compounds from P. capitatum have been isolated and their structures confirmed. The main flavonoids are flavanones, flavones, flavonol glycosides, and dihydroflavone alcohol glycosides. However, some of these flavonoids also exist in other plants. Most of them show a unique structure with an acylated monosacchride residue integrated in their main skeleton. Thirty flavonoids have been separated from P. capitatum and their chemical structures are displayed in . In 2001, 3’,4’-methylenedioxy-3,5,6,7,8,5’-hexamethylflavone ( 1 ) was first isolated from P. capitatum , which is an unusual flavone of P. capitatum . After that, quercetin ( 2 ) , kaempferol ( 3 ) , kaempferol-3-methyl ether ( 4 ) , and taxifolin ( 5 ) were separated and purified from P. capitatum . Furthermore, the flavonoids and their glycosides are a widespread occurrence in P. capitatum . Among them, glycosylation at C-3 of the nucleus has been found to be the most commonly present, and rhamnose, glucose, arabinose, and rhamnosyl-rhamnose are the most common sugars found as glycones of this flavonol glycoside, including quercitrin ( 6 ) , quertin-3-O-(4’’-methoxy)-α-L-rhamnopyranosyl ( 7 ) , kaempferol-3-O-α-L-rhamnopyranoside ( 8 ) , myricetrin ( 9 ) , hirsutrin/quercetin-3-O-β-D-glucopyranoside ( 10 ) , kaempferol-3-O-β-D-glucopyranoside ( 11 ) , 2’’-O-galloyl quercitrin ( 12 ) , 2’’-O-galloyl hirsutrin ( 13 ) , luteoloside/luteolin-7-O-glucoside/cymaroside ( 14 ) , daidzin ( 15 ) , rutin ( 16 ) , quercetin-3-O-(4’’-O-acetyl)-α-L-rhamnoside ( 17 ) , quercetin-3-O-α-L- rhamnoside-2’’-gallte ( 6 ) , quercetin-3-O-α-L-rhamnoside-3’’-gallate ( 19 ) , quercetin-3-O-(2’’-O-rhamnoside)-β-D-glucopyranoside ( 20 ) , querctin-3-O-(3’’-O-rhamnoside)-β-D-glucopyranoside ( 21 ) , 2,7,4’-trihydroxyflavanone-5-O-β- D-glucopyranoside ( 24 ) , and epicatechin-3-O-gallate ( 30 ) . Most of these were separated from P. capitatum for the first time. In particular, some new styles of flavonol glycoside ( 12 – 13 , 18 – 21 ) , combined with a substituent of the gallic acid group, were first isolated from it, which may play an important role in their pharmacoactivity. Meanwhile, a new chromone glycoside (7-O-(6-galloyl)-β-D-glucopyranosyl-5-hydroxychromone ( 23 ) and one known chromone (5,7-dihydroxychromone ( 22 ) were isolated. Moreover, the isolation of four flavonoid lignans of silymarin, for which the structure was the condensation of flavanonol and phenyl propanoid derivatives, including silybin ( 25 ) , isosilybin ( 26 ) , 2,3-dehydrosilybin ( 27 ) and 2,3-dehydrosilychristin ( 28 ) from P. capitatum, were new styles of lignans. In addition, a common flavanone catechin ( 29 ) was found from this plant. 2.2. Lignanoids Ten lignanoids were isolated and identified from P. capitatum . The structures of these compounds are shown in . Moreover, it belongs to isolariciresinol ( 31 ) , −isolariciresinol-3a-O-β-dxylopyranoside ( 32 ) , -5’-Methoxyisolariciresinol-9-O-β-D-Xylopyranoside ( 33 ) , −isolariciresinol-3a-O-β-D-glucopyranoside ( 34 ) , nudiposide lyoniresinol 3α-O-β-D-xylopyranoside ( 35 ) , isolariciresinol-2a-O-β-D-xylopyranoside ( 36 ) , lyoniside/ lyoniresinol-3α-O-β-D-xylopyranoside ( 37 ) , 5’-methoxyisolariciresinol-2a-O-β-D-xylopyranoside ( 38 ) , schizandriside ( 39 ) , and lyoniresinol-2a-O-[6-O-(4-hydroxy-3,5-dimethoxy)-benzoyl]-β-D-glucopyranoside ( 40 ) . For them, nudiposide and lyoniresinol 3α-O-β-D-xylopyranoside, lyoniside and lyoniresinol 3α-O-β-D-xylopyranoside, are the same compound, respectively. Furthermore, −isolariciresinol-3a-O-β-dxylopyranoside/isolariciresinol-2a-O-β-D-xylopyranoside and nudiposide/lyoniside are two pairs of absolute configuration, and were isolated and identified from the herbs of P. capitatum . 2.3. Phenolics According to the literature, phenolic compounds are the secondary abundant constituents in P. capitatum. So far, a total of 25 phenolic compounds ( 41 – 65 ) have been separated from this plant . Among them, gallic acid ( 41 ) , vanillic acid ( 42 ) and protocatechuic acid ( 43 ) are the major ones and have been confirmed to possess various pharmacological activities. Moreover, 2-methoxyl-1,4-benzenediol-1-O-β-D-glucopyranoside/2-methoxy-4-hydroxyphenol-1-O-β-D-glucopyranoside/isotachioside and 1,3-dimethoxyl-2,5-benzenediol-5-O-β-D-glucopyranoside/3,5-dimethoxy-4-hydro-xyphenol-1-O-β-D-glucopyranoside, were the same compounds, respectively. It should be noted that, phenolic glycosides ( 48 – 56 , 58 – 62 ) were reported for the first time from P. capitatum and the family Polygonaceae. 2.4. Other Compounds Other compounds have also been isolated and identified from P. capitatum , and their structures are shown in . Sixteen organic acids, alcohols, esters and aldehydes, including palmitic acid ( 66 ) , linoleic acid ( 67 ) , hexadecanoic acid-2,3-dihydroxypropyl ester ( 68 ) , 24-hydroxy-24-alkane-3 ( 69 ) , pentacosanol ( 70 ) , 28 alkyl-1,27-diene ( 71 ) , 29-hydroxy-29-alkanone-3 ( 72 ) , tricosane ( 73 ) , behenic acid ( 74 ) , tricosanol ( 75 ) , lignoceric acid ( 76 ) , docanoic acid -2,3-dihydroxypropyl ester ( 77 ) , docosyl ferulate ( 78 ) ,5-hydroxymethylfurfural ( 79 ) , succinic acid/butanedioic acid ( 80 ) and tetracosane-1,3-diol ( 81 ) were identified from the petroleum ether extracts of P. capitatum . Furthermore, four terpenoids have been isolated from this ethnic medicine, including ursolic acid ( 82 ) , oleanolic acid ( 83 ) , β-sitosterol ( 84 ) and β-daucosterol ( 85 ) . Only one anthraquinone component, emodin ( 86 ) , has been separated from it. Of note, 1,5,7-trihydroxy-3-methylanthraquinone (Yu was isolated from P. capitatum in 2008) and emodin were found to be the same component. Two amino acids have been identified from the n -butanol fraction of the ethanol extract of P. capitatum , including L-tryptophan ( 87 ) and L-phenylalanine ( 88 ) . Quite recently, two ellagitannins, davidiin ( 89 ) and FR429 ( 90 ) , were discovered from it. In addition, one alkaloid, flazine ( 91 ) , was also identified in P. capitatum . Flavonoids are large secondary metabolites found in P. capitatum . More than 30 flavonoid compounds from P. capitatum have been isolated and their structures confirmed. The main flavonoids are flavanones, flavones, flavonol glycosides, and dihydroflavone alcohol glycosides. However, some of these flavonoids also exist in other plants. Most of them show a unique structure with an acylated monosacchride residue integrated in their main skeleton. Thirty flavonoids have been separated from P. capitatum and their chemical structures are displayed in . In 2001, 3’,4’-methylenedioxy-3,5,6,7,8,5’-hexamethylflavone ( 1 ) was first isolated from P. capitatum , which is an unusual flavone of P. capitatum . After that, quercetin ( 2 ) , kaempferol ( 3 ) , kaempferol-3-methyl ether ( 4 ) , and taxifolin ( 5 ) were separated and purified from P. capitatum . Furthermore, the flavonoids and their glycosides are a widespread occurrence in P. capitatum . Among them, glycosylation at C-3 of the nucleus has been found to be the most commonly present, and rhamnose, glucose, arabinose, and rhamnosyl-rhamnose are the most common sugars found as glycones of this flavonol glycoside, including quercitrin ( 6 ) , quertin-3-O-(4’’-methoxy)-α-L-rhamnopyranosyl ( 7 ) , kaempferol-3-O-α-L-rhamnopyranoside ( 8 ) , myricetrin ( 9 ) , hirsutrin/quercetin-3-O-β-D-glucopyranoside ( 10 ) , kaempferol-3-O-β-D-glucopyranoside ( 11 ) , 2’’-O-galloyl quercitrin ( 12 ) , 2’’-O-galloyl hirsutrin ( 13 ) , luteoloside/luteolin-7-O-glucoside/cymaroside ( 14 ) , daidzin ( 15 ) , rutin ( 16 ) , quercetin-3-O-(4’’-O-acetyl)-α-L-rhamnoside ( 17 ) , quercetin-3-O-α-L- rhamnoside-2’’-gallte ( 6 ) , quercetin-3-O-α-L-rhamnoside-3’’-gallate ( 19 ) , quercetin-3-O-(2’’-O-rhamnoside)-β-D-glucopyranoside ( 20 ) , querctin-3-O-(3’’-O-rhamnoside)-β-D-glucopyranoside ( 21 ) , 2,7,4’-trihydroxyflavanone-5-O-β- D-glucopyranoside ( 24 ) , and epicatechin-3-O-gallate ( 30 ) . Most of these were separated from P. capitatum for the first time. In particular, some new styles of flavonol glycoside ( 12 – 13 , 18 – 21 ) , combined with a substituent of the gallic acid group, were first isolated from it, which may play an important role in their pharmacoactivity. Meanwhile, a new chromone glycoside (7-O-(6-galloyl)-β-D-glucopyranosyl-5-hydroxychromone ( 23 ) and one known chromone (5,7-dihydroxychromone ( 22 ) were isolated. Moreover, the isolation of four flavonoid lignans of silymarin, for which the structure was the condensation of flavanonol and phenyl propanoid derivatives, including silybin ( 25 ) , isosilybin ( 26 ) , 2,3-dehydrosilybin ( 27 ) and 2,3-dehydrosilychristin ( 28 ) from P. capitatum, were new styles of lignans. In addition, a common flavanone catechin ( 29 ) was found from this plant. Ten lignanoids were isolated and identified from P. capitatum . The structures of these compounds are shown in . Moreover, it belongs to isolariciresinol ( 31 ) , −isolariciresinol-3a-O-β-dxylopyranoside ( 32 ) , -5’-Methoxyisolariciresinol-9-O-β-D-Xylopyranoside ( 33 ) , −isolariciresinol-3a-O-β-D-glucopyranoside ( 34 ) , nudiposide lyoniresinol 3α-O-β-D-xylopyranoside ( 35 ) , isolariciresinol-2a-O-β-D-xylopyranoside ( 36 ) , lyoniside/ lyoniresinol-3α-O-β-D-xylopyranoside ( 37 ) , 5’-methoxyisolariciresinol-2a-O-β-D-xylopyranoside ( 38 ) , schizandriside ( 39 ) , and lyoniresinol-2a-O-[6-O-(4-hydroxy-3,5-dimethoxy)-benzoyl]-β-D-glucopyranoside ( 40 ) . For them, nudiposide and lyoniresinol 3α-O-β-D-xylopyranoside, lyoniside and lyoniresinol 3α-O-β-D-xylopyranoside, are the same compound, respectively. Furthermore, −isolariciresinol-3a-O-β-dxylopyranoside/isolariciresinol-2a-O-β-D-xylopyranoside and nudiposide/lyoniside are two pairs of absolute configuration, and were isolated and identified from the herbs of P. capitatum . According to the literature, phenolic compounds are the secondary abundant constituents in P. capitatum. So far, a total of 25 phenolic compounds ( 41 – 65 ) have been separated from this plant . Among them, gallic acid ( 41 ) , vanillic acid ( 42 ) and protocatechuic acid ( 43 ) are the major ones and have been confirmed to possess various pharmacological activities. Moreover, 2-methoxyl-1,4-benzenediol-1-O-β-D-glucopyranoside/2-methoxy-4-hydroxyphenol-1-O-β-D-glucopyranoside/isotachioside and 1,3-dimethoxyl-2,5-benzenediol-5-O-β-D-glucopyranoside/3,5-dimethoxy-4-hydro-xyphenol-1-O-β-D-glucopyranoside, were the same compounds, respectively. It should be noted that, phenolic glycosides ( 48 – 56 , 58 – 62 ) were reported for the first time from P. capitatum and the family Polygonaceae. Other compounds have also been isolated and identified from P. capitatum , and their structures are shown in . Sixteen organic acids, alcohols, esters and aldehydes, including palmitic acid ( 66 ) , linoleic acid ( 67 ) , hexadecanoic acid-2,3-dihydroxypropyl ester ( 68 ) , 24-hydroxy-24-alkane-3 ( 69 ) , pentacosanol ( 70 ) , 28 alkyl-1,27-diene ( 71 ) , 29-hydroxy-29-alkanone-3 ( 72 ) , tricosane ( 73 ) , behenic acid ( 74 ) , tricosanol ( 75 ) , lignoceric acid ( 76 ) , docanoic acid -2,3-dihydroxypropyl ester ( 77 ) , docosyl ferulate ( 78 ) ,5-hydroxymethylfurfural ( 79 ) , succinic acid/butanedioic acid ( 80 ) and tetracosane-1,3-diol ( 81 ) were identified from the petroleum ether extracts of P. capitatum . Furthermore, four terpenoids have been isolated from this ethnic medicine, including ursolic acid ( 82 ) , oleanolic acid ( 83 ) , β-sitosterol ( 84 ) and β-daucosterol ( 85 ) . Only one anthraquinone component, emodin ( 86 ) , has been separated from it. Of note, 1,5,7-trihydroxy-3-methylanthraquinone (Yu was isolated from P. capitatum in 2008) and emodin were found to be the same component. Two amino acids have been identified from the n -butanol fraction of the ethanol extract of P. capitatum , including L-tryptophan ( 87 ) and L-phenylalanine ( 88 ) . Quite recently, two ellagitannins, davidiin ( 89 ) and FR429 ( 90 ) , were discovered from it. In addition, one alkaloid, flazine ( 91 ) , was also identified in P. capitatum . As a folk medicine, the whole of the P. capitatum plant has been used to treat urinary tract infections, dysentery, eczema, urolithiasis and pyelonephritis by the Hmong residents from China. It has long been conceived that gallic acid is the only composition underwriting the pharmacological effects of P. capitatum . However, the anti-inflammatory effect of P. capitatum extract has been ascribed to gallic acid-free fractions abounding in flavonoids. Thus, the phenolics and flavonoids are both considered as crucial bioactive constituents of P. capitatum . Plenty of investigations have been reported on the pharmacological activities of P. capitatum extracts and its major compounds. In the past two decades, pharmacological studies on P. capitatum have indicated diverse biological activities, including anti-inflammatory, antioxidant, anti-hepatocellular carcinoma, antibacterial, antitumor, analgesic, hypothermic, and diuretic activity. This research is summarized here with special focus on flavonoids and phenolic acids with medicinal potential . 3.1. Anti-Inflammatory Activities The pharmacological effects of P. capitatum on anti-inflammatory activity have been fully summarized. The aqueous and ethanol extract of P. capitatum exhibits anti-inflammatory effects by inhibiting the levels of inflammatory cytokines NO and TNF-α in RAW 264.7 macrophages . The largest study was reported by Liao, the total flavonoid fractions were tested on Kunming mice (18–22 g), administrated orally through gavage in a single dose of 0.6 g/kg, 0.3 g/kg, and 0.15 g/kg per day for seven consecutive days. The results showed significant anti-inflammatory activity with inhibition rates of 86.15 % at 0.6 g/kg . Furthermore, treatment with flavonoid-rich extract of P. capitatum (the major constituents were luteolin-7-O-glucoside, rutin, and quercitrin) at 90 and 180 mg/kg body weight in rats for 6 weeks remarkably decreased serum TNF-α, and interleukin-6 (IL-6) levels, which mechanism implied that total flavonoids suppressed the development of atherosclerosis, possibly by inhibiting inflammatory response . Later, the anti-inflammation effects of total flavonoids of both wild and cultivated P. capitatum were also observed in mouse abdominal cavity capillary permeability, the xylene-induced ear swelling model and carrageenan-induced mouse pedal swelling test, and the results showed an inhibitory effect in the same dose . To screen effective anti-inflammatory extracts from P. capitatum , they reported that the aqueous extract and the protein-free water extract of P. capitatum could significantly inhibit the release of NO, TNF-α and IL-6 in LPS-induced RAW264.7 cells. In particular, the protein-free water extract of P. capitatum had the best effect on NO, TNF-α and IL-6 inhibition and was the main effective anti-inflammatory ingredient . Recently, quercetin, one flavonoid, was isolated from P. capitatum , and regulated the balance of gastric cell proliferation and apoptosis to protect against gastritis. Its mechanism was that quercetin protects against gastric inflammation and apoptosis associated with Helicobacter pylori infection by affecting the levels of p38MAPK, BCL-2 and BAX genes . At the same time, flavonoid glycosides of P. capitatum protect against inflammation associated with Helicobacter pylori infection, and the results suggested that flavonoid glycoside has repairing functions for gastric injuries . In addition, the P. capitatum extract powder (1.58 g/kg body weight, DW) in CMC-Na solution, was orally administered for SD rats once daily for 14 consecutive days. The results proved P. capitatum could inhibit the activation of the AKT/PI3K pathway by upregulating PTEN expression; thus, gastric mucosal inflammation induced by H. pylori can be improved . P. capitatum has a significant therapeutic effect on allergic contact dermatitis, which may be related to suppression of levels of IL-4 and TNF-α . In particular, Relinqing granules (14.4, 7.2 g/kg DW) promisingly inhibited dimethylbenzene-induced auricle tumefaction of mice. Relinqing granules (3.6, 7.2 g/kg DW) significantly inhibited granuloma with cotton ball in rats. Relinqing granules (7.2 g/kg DW) significantly decreased the number of white blood cells in rat urine with chronic urinary tract infections, and improved kidney function and pathological changes . The search for a better model system to explore the effective constituents and the mechanism of action of anti-inflammatory P. capitatum was studied through the method of network pharmacology. The results showed a total of 6 active compounds, and 41 potential targets and 76 signal pathways were screened and obtained . 3.2. Anti-Oxidant Activities The anti-oxidant activities of P. capitatum and its flavonoids have been studied extensively using different anti-oxidant models. These models were induced 2-20-azinobis-3-ethylben-zthia zoline-6-sulphonate (ABTS), 1,1-diphenyl-2-picrylhydraz-yl (DPPH), hydrogen peroxide (H 2 O 2 ). The proposed situation/mechanisms are summarized in . P. capitatum extract has demonstrated obvious anti-oxidant activity in vitro. Experimental studies have shown that an 80% methanol extract of leaves and stems from P. capitatum demonstrate strong antioxidant activities against ABTS + /OH − (23.08%) and Fe 2+ chelating capacity activities (17.3% EDTA/g DW) . Some flavonoids isolated from P. capitatum , quercitrin, protocatechuic acid, quercetin and kaempferol possessed strong scavenging free radical capacity against H 2 O 2 , with an IC 50 of 0.044 μM, 0.276 μM, 0.098 μM and 0.029 μM, respectively . For in vitro experiments, the ethanol extract revealed stronger anti-oxidant activities than the aqueous extracts of P. capitatum ; its IC 50 values were 1.71 mg/mL and 0.15 mg/mL, respectively . The same result was shown in another study; the methanol extract of P. capitatum showed higher scavenging activity against DPPH radical and ABTS radical Particularly, the methanol extract exhibited more significant antioxidant activity than that of positive drug BHT . In addition, the EtOAc extract of P. capitatum exhibited remarkable scavenging activity against DPPH radical and ABTS radical. The results further elucidate that EtOAc extract could be used as an important part of antioxidant substances, and that polyphends were the major active ingredients of antioxidant activity for P. capitatum . However, it is of great importance to note that only a small part of the research conducted into anti-oxidant activity has employed in vitro based methods and that further in vivo verifications should be encouraged. 3.3. Antimicrobial Activities Plenty of investigations have been reported on the antimicrobial activities of P. capitatum extracts, and the major compounds P. capitatum possesses and their promising antibacterial activities . Previous studies have reported that crude extracts of P. capitatum significantly inhibit the growth of the bacteria Listeria monocytogenes and Salmonella anatum , at the minimum inhibitory concentration (MIC) of 6.25 mg/mL . Liu et al. reported that the 60% ethanol extract (250 μg/disc) displayed a better antibacterial activity against the multidrug-resistant Staphylococcus aureus . Moreover, in another study, plant extracts and fractions of P. capitatum demonstrated antimicrobial properties against bacterial strains, and through the determination of the MIC and the minimum bactericidal concentration (MBC), the results showed that the crude extracts or fractions FV (flavonoid-enriched fraction) and TN (tannin-enriched fraction) have antibacterial and bactericidal properties . Additionally, in an in vitro antibacterial test, 40 μg/mL or higher concentrations of extracts (flavonoid glycosides) of P. capitatum inhibited the growth of H. pylori ; the resistance of MIC was regarded as >40.0 μg/mL, while the resistance of MIC of amoxicillin was regarded as >1.0 μg/mL . Simultaneously, P. capitatum inhibits H. pylori growth via interfering with and inhibiting the expression of Helicobacter pylori protein . Moreover, four effective parts of the alcohol extract of P. capitatum were found to have outstanding potential antimicrobial activities; the main antibacterial components could be 6-galacyl glucose, 3, 6-digalacyl glucose, 1, 3, 6-trigalacyl glucose and Davidiin . Moreover, the different polar of seven fractions in the 70% ethanol extract of P. capitatum had high antibacterial activity against EScherichia coli , the MIC was 0.20 mg/mL, and the MBC was 0.78 mg/mL . These findings show that antimicrobial activity is an essential property of P. capitatum and that this flora should be a fundamental source of preservatives for the pharmaceutical industry. 3.4. Anti-Tumor Activities Some pharmacological studies have shown that different extract and compound prescriptions derived from P. capitatum have significant antineoplastic effects against diseases. In 2013, Wang et al. showed that emodin at doses of 10–120 mΜ could effectively inhibit production with a dose-dependent manner of HCC cell lines. The possible mechanism of action inhibited the expression of the proteasome-dependence of EZH2 . It was also found that intraperitoneal administration (single dose of 10 mg/kg/day, sp) significantly inhibits tumor progression in hepatoma xenograft mice . It is well known that davidiin displays extensive antitumor activity. Davidiin, a natural product isolated from P. capitatum , has an antitumor mechanism of changing the metabolism of sphingolipids. When HepG2 cells were treated with 50 μM davidian for 72 h, the levels of several types of sphingolipids significantly changed, including Cer, LacCer and So; they decreased markedly to 26.2%, 27.8% and 19.7%, respectively . 3.5. Other Biological Activities Apart from anti-inflammatory, anti-oxidant, antimicrobial and anti-tumor activities, P. capitatum has a remarkable effect on anti-atherosclerosis, a hypoglycemic effect, and defervescence and analgesic action. Wang et al. reported that luteolin-7-O-glucoside, rutin and quercitrin total flavonoids, separated from P. capitatum , exerted an anti-atherosclerosis effect in hyperlipidemia rats through regulating blood lipid metabolism, and modulating a proinflammatory profile . At the same time, the lignans (isoidulinol, 5’-methoxy-isolaridosin-9-O-β-D-xylopyranoside) isolated from P. capitatum showed significant hypoglycemic activity against type two diabetes . Later, it was reported that aqueous extract of P. capitatum at a dose of 450 mg/kg DW significantly reduced the body temperature of rabbits with a fever induced by an intravenous injection of typhoid fever and Paratyphoid bacillus . Furthermore, the alcohol and water extracts of P. capitatum exhibited a prominent analgesic effect on the writhing response induced by acetic acid in mice . In addition, P. capitatum extracts (5 g/kg, 10 g/kg, 20 g/kg DW, 4 weeks) demonstrated a hypoglycemic effect. This mechanism may be related to the expression of AMPK and GLUT4 genes up-regulated in the liver to further promote the uptake of glucose by the liver tissue . The pharmacological effects of P. capitatum on anti-inflammatory activity have been fully summarized. The aqueous and ethanol extract of P. capitatum exhibits anti-inflammatory effects by inhibiting the levels of inflammatory cytokines NO and TNF-α in RAW 264.7 macrophages . The largest study was reported by Liao, the total flavonoid fractions were tested on Kunming mice (18–22 g), administrated orally through gavage in a single dose of 0.6 g/kg, 0.3 g/kg, and 0.15 g/kg per day for seven consecutive days. The results showed significant anti-inflammatory activity with inhibition rates of 86.15 % at 0.6 g/kg . Furthermore, treatment with flavonoid-rich extract of P. capitatum (the major constituents were luteolin-7-O-glucoside, rutin, and quercitrin) at 90 and 180 mg/kg body weight in rats for 6 weeks remarkably decreased serum TNF-α, and interleukin-6 (IL-6) levels, which mechanism implied that total flavonoids suppressed the development of atherosclerosis, possibly by inhibiting inflammatory response . Later, the anti-inflammation effects of total flavonoids of both wild and cultivated P. capitatum were also observed in mouse abdominal cavity capillary permeability, the xylene-induced ear swelling model and carrageenan-induced mouse pedal swelling test, and the results showed an inhibitory effect in the same dose . To screen effective anti-inflammatory extracts from P. capitatum , they reported that the aqueous extract and the protein-free water extract of P. capitatum could significantly inhibit the release of NO, TNF-α and IL-6 in LPS-induced RAW264.7 cells. In particular, the protein-free water extract of P. capitatum had the best effect on NO, TNF-α and IL-6 inhibition and was the main effective anti-inflammatory ingredient . Recently, quercetin, one flavonoid, was isolated from P. capitatum , and regulated the balance of gastric cell proliferation and apoptosis to protect against gastritis. Its mechanism was that quercetin protects against gastric inflammation and apoptosis associated with Helicobacter pylori infection by affecting the levels of p38MAPK, BCL-2 and BAX genes . At the same time, flavonoid glycosides of P. capitatum protect against inflammation associated with Helicobacter pylori infection, and the results suggested that flavonoid glycoside has repairing functions for gastric injuries . In addition, the P. capitatum extract powder (1.58 g/kg body weight, DW) in CMC-Na solution, was orally administered for SD rats once daily for 14 consecutive days. The results proved P. capitatum could inhibit the activation of the AKT/PI3K pathway by upregulating PTEN expression; thus, gastric mucosal inflammation induced by H. pylori can be improved . P. capitatum has a significant therapeutic effect on allergic contact dermatitis, which may be related to suppression of levels of IL-4 and TNF-α . In particular, Relinqing granules (14.4, 7.2 g/kg DW) promisingly inhibited dimethylbenzene-induced auricle tumefaction of mice. Relinqing granules (3.6, 7.2 g/kg DW) significantly inhibited granuloma with cotton ball in rats. Relinqing granules (7.2 g/kg DW) significantly decreased the number of white blood cells in rat urine with chronic urinary tract infections, and improved kidney function and pathological changes . The search for a better model system to explore the effective constituents and the mechanism of action of anti-inflammatory P. capitatum was studied through the method of network pharmacology. The results showed a total of 6 active compounds, and 41 potential targets and 76 signal pathways were screened and obtained . The anti-oxidant activities of P. capitatum and its flavonoids have been studied extensively using different anti-oxidant models. These models were induced 2-20-azinobis-3-ethylben-zthia zoline-6-sulphonate (ABTS), 1,1-diphenyl-2-picrylhydraz-yl (DPPH), hydrogen peroxide (H 2 O 2 ). The proposed situation/mechanisms are summarized in . P. capitatum extract has demonstrated obvious anti-oxidant activity in vitro. Experimental studies have shown that an 80% methanol extract of leaves and stems from P. capitatum demonstrate strong antioxidant activities against ABTS + /OH − (23.08%) and Fe 2+ chelating capacity activities (17.3% EDTA/g DW) . Some flavonoids isolated from P. capitatum , quercitrin, protocatechuic acid, quercetin and kaempferol possessed strong scavenging free radical capacity against H 2 O 2 , with an IC 50 of 0.044 μM, 0.276 μM, 0.098 μM and 0.029 μM, respectively . For in vitro experiments, the ethanol extract revealed stronger anti-oxidant activities than the aqueous extracts of P. capitatum ; its IC 50 values were 1.71 mg/mL and 0.15 mg/mL, respectively . The same result was shown in another study; the methanol extract of P. capitatum showed higher scavenging activity against DPPH radical and ABTS radical Particularly, the methanol extract exhibited more significant antioxidant activity than that of positive drug BHT . In addition, the EtOAc extract of P. capitatum exhibited remarkable scavenging activity against DPPH radical and ABTS radical. The results further elucidate that EtOAc extract could be used as an important part of antioxidant substances, and that polyphends were the major active ingredients of antioxidant activity for P. capitatum . However, it is of great importance to note that only a small part of the research conducted into anti-oxidant activity has employed in vitro based methods and that further in vivo verifications should be encouraged. Plenty of investigations have been reported on the antimicrobial activities of P. capitatum extracts, and the major compounds P. capitatum possesses and their promising antibacterial activities . Previous studies have reported that crude extracts of P. capitatum significantly inhibit the growth of the bacteria Listeria monocytogenes and Salmonella anatum , at the minimum inhibitory concentration (MIC) of 6.25 mg/mL . Liu et al. reported that the 60% ethanol extract (250 μg/disc) displayed a better antibacterial activity against the multidrug-resistant Staphylococcus aureus . Moreover, in another study, plant extracts and fractions of P. capitatum demonstrated antimicrobial properties against bacterial strains, and through the determination of the MIC and the minimum bactericidal concentration (MBC), the results showed that the crude extracts or fractions FV (flavonoid-enriched fraction) and TN (tannin-enriched fraction) have antibacterial and bactericidal properties . Additionally, in an in vitro antibacterial test, 40 μg/mL or higher concentrations of extracts (flavonoid glycosides) of P. capitatum inhibited the growth of H. pylori ; the resistance of MIC was regarded as >40.0 μg/mL, while the resistance of MIC of amoxicillin was regarded as >1.0 μg/mL . Simultaneously, P. capitatum inhibits H. pylori growth via interfering with and inhibiting the expression of Helicobacter pylori protein . Moreover, four effective parts of the alcohol extract of P. capitatum were found to have outstanding potential antimicrobial activities; the main antibacterial components could be 6-galacyl glucose, 3, 6-digalacyl glucose, 1, 3, 6-trigalacyl glucose and Davidiin . Moreover, the different polar of seven fractions in the 70% ethanol extract of P. capitatum had high antibacterial activity against EScherichia coli , the MIC was 0.20 mg/mL, and the MBC was 0.78 mg/mL . These findings show that antimicrobial activity is an essential property of P. capitatum and that this flora should be a fundamental source of preservatives for the pharmaceutical industry. Some pharmacological studies have shown that different extract and compound prescriptions derived from P. capitatum have significant antineoplastic effects against diseases. In 2013, Wang et al. showed that emodin at doses of 10–120 mΜ could effectively inhibit production with a dose-dependent manner of HCC cell lines. The possible mechanism of action inhibited the expression of the proteasome-dependence of EZH2 . It was also found that intraperitoneal administration (single dose of 10 mg/kg/day, sp) significantly inhibits tumor progression in hepatoma xenograft mice . It is well known that davidiin displays extensive antitumor activity. Davidiin, a natural product isolated from P. capitatum , has an antitumor mechanism of changing the metabolism of sphingolipids. When HepG2 cells were treated with 50 μM davidian for 72 h, the levels of several types of sphingolipids significantly changed, including Cer, LacCer and So; they decreased markedly to 26.2%, 27.8% and 19.7%, respectively . Apart from anti-inflammatory, anti-oxidant, antimicrobial and anti-tumor activities, P. capitatum has a remarkable effect on anti-atherosclerosis, a hypoglycemic effect, and defervescence and analgesic action. Wang et al. reported that luteolin-7-O-glucoside, rutin and quercitrin total flavonoids, separated from P. capitatum , exerted an anti-atherosclerosis effect in hyperlipidemia rats through regulating blood lipid metabolism, and modulating a proinflammatory profile . At the same time, the lignans (isoidulinol, 5’-methoxy-isolaridosin-9-O-β-D-xylopyranoside) isolated from P. capitatum showed significant hypoglycemic activity against type two diabetes . Later, it was reported that aqueous extract of P. capitatum at a dose of 450 mg/kg DW significantly reduced the body temperature of rabbits with a fever induced by an intravenous injection of typhoid fever and Paratyphoid bacillus . Furthermore, the alcohol and water extracts of P. capitatum exhibited a prominent analgesic effect on the writhing response induced by acetic acid in mice . In addition, P. capitatum extracts (5 g/kg, 10 g/kg, 20 g/kg DW, 4 weeks) demonstrated a hypoglycemic effect. This mechanism may be related to the expression of AMPK and GLUT4 genes up-regulated in the liver to further promote the uptake of glucose by the liver tissue . LC/MS or HPLC are currently the most powerful techniques for global chemical analysis of TCM. They have been extensively used for the analysis of chemical constituents of P. capitatum . The previous literature has reported flavonoids and phenolic acids were considered to be the vital active constituents of P. capitatum . In the 2003 edition of the “Quality standards of Chinese medicinal materials and ethnic medicinal materials in Guizhou Province”, only gallic acid (the content > 0.05%) was included as a standard for the evaluation of P. capitatum quality . Zhang et al. reported an HPLC method to analyze the herbs of P. capitatum ; the average content of gallic acid was 0.2% . Over the past few years, the use of reversed-phase HPLC has been developed for the analysis of flavonoids; quercitrin, derived from P. capitatum , was linear and ranged from 0.082–0.408 μg . In 2010, a scientist established a simple HPLC method for the characterization of quercetin from three parts (flower, stem and leaf) of P. capitatum . The results showed that the quercetins ranged from 0.25% to 0.62%, and the highest content of quercetin was found in leaves . Recently, the Beijing Institute of Materia Medica, Chinese Academy of Medical Sciences, has completed the quality standard of P. capitatum . The content of gallic acid and quercetin should not be less than 0.015 g/100 g DW and 0.1 g/100 g DW, respectively . A comparative pharmacokinetic study of crude herb from P. capitatum was carried out. Several research groups have studied the metabolism of gallic acid (GA) and protocatechuic acid (PCA) in the aqueous extract of P. capitatum . Administration of aqueous extract of P. capitatum was at oral doses of 60 mg/kg (equivalent to 12 mg/kg DW of GA and 0.9 mg/kg DW of PCA) to rats; after 1 h, the concentration of GA and PCA in kidney tissue, respectively, reached 1218.62 ng/g and 43.98 ng/g, indicating that extensive metabolism of GA and PCA occurred after ingestion . He et al. studied the material metabolism of the bioactive extracts of P. capitatum . The results showed that the metabolic pathways of intestinal flora in P. capitatum were hydrolysis, reduction and oxidation . After that, the metabolic characteristics of FR429 were evaluated in male Wistar rats (260–280 g), a total of eight metabolites were detected from bile and urine. It was deduced that the main metabolic pathway of FR429 in rats was methylation and subsequent glucuronidation . Recently, the extract of P. capitatum 700 mg/kg DW (equivalent to gallic acid 21.35 mg/kg DW, quercetin 2.17 mg/kg DW, quercetin content of 0.392 mg/kg DW, respectively,) was orally administered to rats. As a result, gallic acid and quercitrin were detected in plasma, but quercetin was not detected . Similarly, ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to determine the plasma levels of P. capitatum extracts. Compared with the normal group, the absorption of GA, PCA and quercetin (QR) in pyelonephritis rats was increased, and excretion was decreased . P. capitatum is a traditional medicinal plant of the Miao people and has been used to treat a variety of urological disorders in China over a long history, such as dysentery, pyelonephritis, cystitis, urolithiasis, pelvic inflammation and rheumatic pain. In this work, we reviewed the available information concerning the traditional uses, phytochemistry, pharmacology and quality control of P. capitatum . In total, 91 compounds from P. capitatum were isolated, including 30 flavonoids, 10 lignanoids, 25 phenols, and 26 other constituents. Furthermore, P. capitatum has clear pharmacological properties such as antibacterial, anti-inflammatory, antioxidant, antitumor, antipyretic and analgesic effects, and has potential hypoglycemic development prospects. These research results could provide a referential merit for the processing, quality control and clinical medication guidance of P. capitatum . In addition, some drugs have been derived from P. capitatum and are presently used in clinic such as Relinqing granule and Milins capsules, but the development of its related medical products is still very limited. However, it is also necessary to further study the drug-forming properties and pharmacokinetics of the active constituents of P. capitatum , as well as to establish quality control standards for different areas of P. capitatum , to investigate their safety evaluation, adverse reactions and toxicity, and to carry out research at the cellular and molecular levels. We hope that this review highlights the important value of P. capitatum and promotes its all-round development. |
Parental leave, childcare policies, and workplace bias for hepatology professionals: A national survey | 36a620a2-4142-4545-a044-908bba12826f | 10461944 | Internal Medicine[mh] | There is a broad evidence base supporting the health, well-being, and economic benefits of adequate parental leave for both children and parents, and consequently, multiple medical societies recommend an adequate duration of paid parental leave. – However, there is a discrepancy between the duration of parental leave that is recommended by medical societies and those available in practice. , , A lack of adequate parental leave has been hypothesized as a major barrier to sex equity in medicine. , , – No prior studies have examined the availability and duration of parental leave and impact on child-rearing for hepatologists. There are several factors of the hepatology workforce and work environment that make issues of workplace equity and parental leave germane to our field. Hepatology is a clinically rigorous specialty and frequently requires a heavy inpatient load and high-intensity outpatient management. Furthermore, hepatologists in the United States are often required to complete gastroenterology fellowship and hepatology training. Gastroenterology requires performing procedures, which can be physically demanding, particularly in late term pregnancy. The field is also predominantly male, which means that most people in leadership roles have not personally experienced the physical demands of being pregnant. Studies of physicians in gastroenterology suggest that inadequate parental leave policies and bias against parental leave and child-rearing contribute to sex-based disparities across all career stages, including training, hiring, retention, mentorship, sponsorship, promotion, and advancement. – In addition to impacting careers, insufficient parental leave has also disproportionately affected female physicians’ family planning given the long duration of advanced training. , , Furthermore, insufficient leave impacts the gastroenterology pipeline, as trainees reported that a major deterrent to pursuing specialty fellowship was concerns about incompatibility with pregnancy and child-rearing. , The upcoming shortage of hepatology providers makes addressing this barrier urgent. Beyond parental leave, there are also no studies in hepatology on work environments designed to accommodate pregnancy and parenthood. Frequent overnight calls and higher procedural volumes have been found in other specialties to be linked to adverse pregnancy outcomes but have not yet been studied in hepatology. There are also no studies about accommodations for parents, including time and space for breast milk pumping, as well as the availability of childcare. In addition, there is also a gap in the knowledge about implicit and explicit bias against pregnancy, parenthood, and parental leave in hepatology. While maternity bias has been documented in other areas of medicine, it has not yet been studied in hepatology. , , – Bias and harassment are present throughout medical education for Black physicians and other races underrepresented in medicine; while we did not find published data on racial disparities around maternity leave for physicians, compounding bias for women with intersectional identities may exacerbate existing disparities. , To address these knowledge gaps, we conducted a national survey among trainee and faculty physicians within the AASLD to evaluate the impact of parental leave, child-rearing, and maternity bias.
Survey population The survey was delivered through electronic mail (email) by the AASLD to their email database of 5402 contacts. The initial email was distributed on January 4, 2021, and one reminder email was sent on January 11, 2021. The database includes providers, industry personnel, and donors; however, the survey aimed to solicit responses only from physicians. The survey was anonymous and voluntary, and no incentives were offered for participation. The population of interest for this study was physicians though the listserv data do not allow differentiation between physicians and nonphysician providers. The distribution list classified members by “primary role,” which includes a provider category: physician (38.0%), surgeon (2.9%), physician-scientist (13.4%), trainee (resident, fellow, nurse practitioner, physician assistant, or postdoctoral fellow) (16.0%), and student (medical school, nursing school, or undergraduate) (13.0%). People in these categories are not necessarily physicians but provide the most inclusive estimate to ensure that we are encapsulating all possible physicians into our response rate denominator. Survey design The survey included 33 total items, utilizing skip logic to tailor relevant questions appropriately (Supplement 1, http://links.lww.com/HC9/A408 ). Survey content captured demographics and career stage at childbirth(s), perceived workplace bias, need for modified training or career pathways, family planning, weeks of paid and unpaid leave, workload modifications during pregnancy or child-rearing, childcare services, and pregnancy outcomes. These topics were selected through discussion among AASLD’s Women’s Initiatives Committee based on prior studies of workforce gender equity in medicine and of the committee members’ lived experiences. Questions were then written by the first author who has training in quantitative methodology and survey instrument writing. For demographic questions, respondents were requested to select all ethnicities that they identify with. The survey was written by the first author and edited with input from coauthors with expertise in gender equity research. The survey was then transferred to RedCap 10.5.2 (Vanderbilt University), a secure web platform for building and managing online surveys. After drafting the web-based survey, the survey was piloted with hepatologists to assess clarity and ease of use. Feedback from pilot testers was then incorporated. The study was submitted to the University of Washington Institutional Review Board and deemed exempt (STUDY00011576). All research was conducted in accordance with both the Declarations of Helsinki and Istanbul. Written consent was given electronically by all subjects. Statistical analysis Data were analyzed by IBM SPSS Statistics Version 26, and Descriptive statistics tests, Chi-squared, and Mann-Whitney U test were employed where appropriate with statistical significance considered as p < 0.05.
The survey was delivered through electronic mail (email) by the AASLD to their email database of 5402 contacts. The initial email was distributed on January 4, 2021, and one reminder email was sent on January 11, 2021. The database includes providers, industry personnel, and donors; however, the survey aimed to solicit responses only from physicians. The survey was anonymous and voluntary, and no incentives were offered for participation. The population of interest for this study was physicians though the listserv data do not allow differentiation between physicians and nonphysician providers. The distribution list classified members by “primary role,” which includes a provider category: physician (38.0%), surgeon (2.9%), physician-scientist (13.4%), trainee (resident, fellow, nurse practitioner, physician assistant, or postdoctoral fellow) (16.0%), and student (medical school, nursing school, or undergraduate) (13.0%). People in these categories are not necessarily physicians but provide the most inclusive estimate to ensure that we are encapsulating all possible physicians into our response rate denominator.
The survey included 33 total items, utilizing skip logic to tailor relevant questions appropriately (Supplement 1, http://links.lww.com/HC9/A408 ). Survey content captured demographics and career stage at childbirth(s), perceived workplace bias, need for modified training or career pathways, family planning, weeks of paid and unpaid leave, workload modifications during pregnancy or child-rearing, childcare services, and pregnancy outcomes. These topics were selected through discussion among AASLD’s Women’s Initiatives Committee based on prior studies of workforce gender equity in medicine and of the committee members’ lived experiences. Questions were then written by the first author who has training in quantitative methodology and survey instrument writing. For demographic questions, respondents were requested to select all ethnicities that they identify with. The survey was written by the first author and edited with input from coauthors with expertise in gender equity research. The survey was then transferred to RedCap 10.5.2 (Vanderbilt University), a secure web platform for building and managing online surveys. After drafting the web-based survey, the survey was piloted with hepatologists to assess clarity and ease of use. Feedback from pilot testers was then incorporated. The study was submitted to the University of Washington Institutional Review Board and deemed exempt (STUDY00011576). All research was conducted in accordance with both the Declarations of Helsinki and Istanbul. Written consent was given electronically by all subjects.
Data were analyzed by IBM SPSS Statistics Version 26, and Descriptive statistics tests, Chi-squared, and Mann-Whitney U test were employed where appropriate with statistical significance considered as p < 0.05.
The initial email (January 4, 2021) was sent to 5402 contacts, with a 40% open rate and a 4% click through rate (221 contacts). The second email (January 11, 2021) was sent to 5412 contacts, with a 38% open rate and a 2% click through rate (105 contacts). Overall, there were 308 unique clicks on the survey link. Cohort characteristics An inclusive estimate of possible physicians on the listserv includes 83.32% of the contacts, a total of 4509 contacts. Our survey was completed by 349 respondents, with a response rate of 7.7%. The survey was answered by 199 US-based respondents with an MD or DO credential. There was a wide distribution of respondents across 30 states (Figure ). Demographic characteristics are listed in Table . Respondent gender included 130 women (65.3%) and 69 men (34.7%), with no respondents selecting gender nonbinary. The age range was between 29 and 84 years old, with a mean of 43.9 ± 11.3. The ethnicity of respondents is reported in Table . Current practice settings include academic—primarily clinical practice (69.8%, n = 139), academic—primarily research (19.6%, n = 39) and private practice (5.5%, n = 11), industry (0.5%, n = 1), and other (4.5%, n = 9). Respondents were asked their years in practice since they completed clinical training (either gastroenterology fellowship or transplant hepatology fellowship, whichever was completed most recently) (Table ). Bias Three-quarters (75.2%) of women reported having experienced workplace discrimination compared with one-third (37.3%) of men (Figure ). Regarding differences by race/ethnicity, Black, and Hispanic women more frequently reported types of workplace discrimination compared with White counterparts. Overall, 83.3% of Black women and 62.5% of Hispanic women reported discrimination. Types of discrimination more frequently reported by Black and Hispanic women included unequal pay or benefits (50.0% Black women, 50.0% Hispanic women, and 41.1% White women) and unfair lack of consideration for promotion or management (50.0% Black women, 25.0% Hispanic women, and 17.8% White women). Participants were also asked specifically if they have perceived negative bias from colleagues or supervisors regarding child-rearing or parental leave. Forty-six percent of all respondents (46.5%) had perceived bias about either their own parental leave or child-rearing, or that of others. Of respondents with children, almost half of women reported experiencing bias about their own parental leave or child-rearing (43.4% of women versus 9.8% of men) and experienced bias about the parental leave or child-rearing of others (39.4% of women vs. 18.0% of men) (Figure ). Of respondents without children, 46.7% of women experienced bias about the parental leave or child-rearing of others compared with zero men. We assessed the frequency with which respondents were asked about their pregnancy intentions or child-rearing plans during interviews. One out of 5 (20.0%) women and 4.4% of men reported being asked about their or their partners’ pregnancy intentions or child-rearing plans during interviews for training programs. During interviews for attending positions, 13.8% of women and 5.9% of men reported being asked about their or their partners’ pregnancy intentions or child-rearing plans. Training and career plans Respondents were asked if they altered their career plans or their training because of child-rearing, pregnancy, or adoption. Significantly more women than men altered their career plans because of child-rearing, pregnancy, or adoption (30.0% of women vs. 15.9% of men, p = 0.030 Table ). If respondents were a trainee during pregnancy, adoption, or birth of a child, they were asked whether they adjusted their training because of pregnancy or child-rearing plans. Men were significantly more likely to report that their training path did not change due to pregnancy or child-rearing (women 35.1% vs. men 57.6%; p = 0.006). Respondents were asked about specific ways in which training was changed due to pregnancy or child-rearing (Figure ). Many women reported “my training was extended (eg, I completed training later than planned)” (women: 13.4%; men 0%), “my research time was reduced (women 21.6%; men 5.1%),” and “my ability to pursue an additional degree was affected” (women 3.1%; men 1.7%). Many respondents reported that this was not applicable since pregnancy/adoption did not occur during training (women 27.8%; men 35.6%). Excluding those for whom this was not applicable (pregnancy/adoption did not occur during training), over half (52.9%) of women reported that their training was changed due to pregnancy or child-rearing plans, including 30.0% reporting that their research time was reduced. Promotion and career advancement Many women reported their choice to have children negatively impacted promotion or career advancement. Of women who were pregnant and/or had children, 41.8% believed that having children had a negative impact, 55.1% believed that it had a neutral impact, and 3.1% believed that it had a positive impact (Figure ). Of men whose partner was pregnant and/or had children, 9.8% stated they believed that it had a negative impact, 88.5% believed that it was neutral, and 1.6% believed that it had a positive impact. The majority of respondents without children thought that their decision to not have children had a neutral impact on their promotion (96.8% women; 100% men). Family planning When asked if they had in the past delayed, or are currently delaying, having children, 69.5% of women and 35.9% of men reported that they had delayed or were currently delaying having children (Figure ). Two-thirds (65.6%) of men selected that they have not delayed having children compared with less than one-third (31.3%) of women. For current trainees, the most common reasons for delaying having children included “career concerns” (69.6% of women; 71.4% of men) and “concern about lack of parental leave or lack of sufficient parental leave” (39.1% of women; 28.6% of men). Respondents were asked if job-related stressors or responsibilities contributed to an adverse outcome of pregnancy or in getting pregnant. One-third of women (35.4%) reported yes, and 16.9% said that this was not applicable since they or their partner have not been pregnant or tried to become pregnant. Ten percent of men reported yes, and 13.0% reported not applicable. Parental leave and child-rearing Child-rearing The majority of respondents (77.9%) currently had children, and additional 2.5% were pregnant or their partner was pregnant, without current children. Men were significantly more likely to have children, and/or they/their partner were currently pregnant (88.4% of men, compared with 76.2% of women; p = 0.038). Of respondents with children, the average number of children was 2.1 ± 0.8, and men had a significantly higher number of children than women (men: mean 2.4 ±0.9 vs. women mean 1.9 ±0.7; p = < .001). Of respondents without children, 56.4% plan to have a child, and 50.0% were actively trying to have a child. Respondents with children were asked about their age, career stage, and practice setting at the birth of each child. Women hepatologists were older than their male counterparts when having children, with a nonsignificant trend for the average age at birth of their first child (mean for women: 33.2 y vs. men: 32.8 y), and statistical significance for their second child (women: 35.9 y vs. men: 34.0; p = 0.013 (full results in Table ). For the first child of women, the highest percentage had their first child during fellowship (43.3%), followed by an attending (30.9%), then residency (24.7%), and then medical school (1.0%). For the first child of men, the highest percentage had their first child as an attending (36.2%), followed by during fellowship (32.8%), then residency (25.9%), and then medical school (5.2%). Parental leave weeks, paid and unpaid Respondents were asked about their parental leave, including paid leave, unpaid leave, and weeks taken from other protected time off. For women’s first child, the average leave included a mean of 7.5 ± 3.5 weeks of paid leave and 3.7 ± 4.5 weeks of unpaid leave. Mean 4.1 ± 2.8 weeks were taken from other protected time (eg, vacation, sick days, or research time). For men’s first child, the average leave included 1.7 ±2.4 weeks of paid leave and 0.8 ±1.8 weeks of unpaid leave. A mean of 1.1 ±2.3 weeks was taken from other protected times. For women’s second child, the average leave included a mean of 8.3 ±3.7 weeks of paid leave and 4.0 ±4.8 weeks of unpaid leave, with 4.4 ±3.5 weeks taken away from other protected time. For men’s second child, average leave included 1.7 ±2.8 weeks of paid leave and 0.5 ±1.0 weeks of unpaid leave, with 0.9 ±1.2 weeks taken from other protected time. The duration of paid leave was significantly longer for women in primarily research academic positions (mean 9.1 wk) than those in primarily clinical academic positions (mean 7.1 wk), p = 0.02. For all women who provided their parental leave length, 79.3% had fewer paid weeks than the American Academy of Pediatrics recommended 12 weeks of leave. When the number of weeks taken away from other protected time (such as research and vacation) was subtracted from the number of weeks of paid parental leave, 90.9% had fewer than 12 weeks of dedicated paid parental leave. Health and pregnancy/child-rearing accommodations Health issues Respondents with children who were pregnant partners were asked about health issues during pregnancy and delivery. For their first child, 15.8% reported health issues during pregnancy, and 18.9% reported health issues during delivery. Two-thirds (67.4%) reported no health issues. For their second child, 22.9% reported health issues during pregnancy, and 7.1% reported health issues during delivery. Over two-thirds (72.9%) reported no health issues. Overnight call Respondents were asked how often they had overnight call responsibilities in their third trimester of pregnancy. For their first child, only one-fifth of women pregnant with their first child did not have any overnight calls in their third trimester of pregnancy (19.6%), while all the others had an increasing number of overnight calls. For subsequent children, the frequency of overnight calls during the third trimester decreased, with a quarter reporting no call for their second (26.5%) and third (26.3%) child. Weekly calls decreased to just over half for their second child (51.5%) and third child (52.6%). A higher percentage of those who worked 6 or more overnight calls per month in their third trimester reported health issues during pregnancy (22.2%, compared with 13.8%) and in delivery (22.2%, compared with 18.5%). Changes to call or work schedule before and after birth Respondents were asked if they changed their call or work schedule because of pregnancy and child-rearing. Over half of women changed their schedule before birth, during pregnancy (55.2%, compared with 18.6% of men). Of those who changed their schedule during pregnancy, they were asked what changes were made. Analysis of these open responses shows that, for women, over half (56.0%) increased the difficulty of their schedule to “front-load,” meaning that they would decrease calls during birth or delivery, or for some in their third trimester. This increased their call and service burden during pregnancy compared with their original schedule. A third (32.0%) reduced their call or endoscopy burden, and for 12%, changes were made but without a clear impact on the difficulty of their schedule. After the birth of their child, one-third of women (33.3%) and one-fifth of men (22.4%) reported changing their schedule. Respondents were also asked about changes to procedural volume and type if they performed procedures during their pregnancy. One-fifth decreased their procedural volume (21.3%), while two-thirds did not make changes to procedural volume (69.7%), and none reported increasing their procedural volume. Fifteen percent (15.7%) made changes to the types of procedures they performed, such as decreased procedures with fluoroscopy. Breastfeeding and pumping Respondents reported whether or not they breastfed and their breastfeeding duration. Of those who breastfed, one-fifth breastfed for <6 months (21.6%), one-third breastfed between 6 months and 11 months (33.0%), 40% between 1 and 2 years (40.9%), and 4.5% breastfed for 2 years or more. Only half of the women who breastfed reported adequate space for pumping breast milk (50.0%), with 20.7% reporting no space and 29.3% having inadequate space. Only 17.1% reported adequate time allotted for pumping, with 54.9% reporting no time and 28.0% inadequate time allotted for pumping. Twenty-nine percent (29.3%) reported adequate space for storing breast milk, whereas almost half reported that there is no space for storing breast milk (46.3%), and 24.4% reported that there is space for storing breast milk, but it is inadequate. Dedicated childcare Respondents with children were asked whether there was a nursery or childcare center affiliated with the hospital/clinic. Almost a quarter reported that there was a nursery/childcare center affiliated with the hospital/clinic but not located on the hospital premises (23.2%), and 17.4% reported that there was a nursery/childcare center on the hospital/clinic premises. Almost half (47.7%) reported that there was no nursery/childcare center affiliated with the hospital/clinic.
An inclusive estimate of possible physicians on the listserv includes 83.32% of the contacts, a total of 4509 contacts. Our survey was completed by 349 respondents, with a response rate of 7.7%. The survey was answered by 199 US-based respondents with an MD or DO credential. There was a wide distribution of respondents across 30 states (Figure ). Demographic characteristics are listed in Table . Respondent gender included 130 women (65.3%) and 69 men (34.7%), with no respondents selecting gender nonbinary. The age range was between 29 and 84 years old, with a mean of 43.9 ± 11.3. The ethnicity of respondents is reported in Table . Current practice settings include academic—primarily clinical practice (69.8%, n = 139), academic—primarily research (19.6%, n = 39) and private practice (5.5%, n = 11), industry (0.5%, n = 1), and other (4.5%, n = 9). Respondents were asked their years in practice since they completed clinical training (either gastroenterology fellowship or transplant hepatology fellowship, whichever was completed most recently) (Table ).
Three-quarters (75.2%) of women reported having experienced workplace discrimination compared with one-third (37.3%) of men (Figure ). Regarding differences by race/ethnicity, Black, and Hispanic women more frequently reported types of workplace discrimination compared with White counterparts. Overall, 83.3% of Black women and 62.5% of Hispanic women reported discrimination. Types of discrimination more frequently reported by Black and Hispanic women included unequal pay or benefits (50.0% Black women, 50.0% Hispanic women, and 41.1% White women) and unfair lack of consideration for promotion or management (50.0% Black women, 25.0% Hispanic women, and 17.8% White women). Participants were also asked specifically if they have perceived negative bias from colleagues or supervisors regarding child-rearing or parental leave. Forty-six percent of all respondents (46.5%) had perceived bias about either their own parental leave or child-rearing, or that of others. Of respondents with children, almost half of women reported experiencing bias about their own parental leave or child-rearing (43.4% of women versus 9.8% of men) and experienced bias about the parental leave or child-rearing of others (39.4% of women vs. 18.0% of men) (Figure ). Of respondents without children, 46.7% of women experienced bias about the parental leave or child-rearing of others compared with zero men. We assessed the frequency with which respondents were asked about their pregnancy intentions or child-rearing plans during interviews. One out of 5 (20.0%) women and 4.4% of men reported being asked about their or their partners’ pregnancy intentions or child-rearing plans during interviews for training programs. During interviews for attending positions, 13.8% of women and 5.9% of men reported being asked about their or their partners’ pregnancy intentions or child-rearing plans.
Respondents were asked if they altered their career plans or their training because of child-rearing, pregnancy, or adoption. Significantly more women than men altered their career plans because of child-rearing, pregnancy, or adoption (30.0% of women vs. 15.9% of men, p = 0.030 Table ). If respondents were a trainee during pregnancy, adoption, or birth of a child, they were asked whether they adjusted their training because of pregnancy or child-rearing plans. Men were significantly more likely to report that their training path did not change due to pregnancy or child-rearing (women 35.1% vs. men 57.6%; p = 0.006). Respondents were asked about specific ways in which training was changed due to pregnancy or child-rearing (Figure ). Many women reported “my training was extended (eg, I completed training later than planned)” (women: 13.4%; men 0%), “my research time was reduced (women 21.6%; men 5.1%),” and “my ability to pursue an additional degree was affected” (women 3.1%; men 1.7%). Many respondents reported that this was not applicable since pregnancy/adoption did not occur during training (women 27.8%; men 35.6%). Excluding those for whom this was not applicable (pregnancy/adoption did not occur during training), over half (52.9%) of women reported that their training was changed due to pregnancy or child-rearing plans, including 30.0% reporting that their research time was reduced.
Many women reported their choice to have children negatively impacted promotion or career advancement. Of women who were pregnant and/or had children, 41.8% believed that having children had a negative impact, 55.1% believed that it had a neutral impact, and 3.1% believed that it had a positive impact (Figure ). Of men whose partner was pregnant and/or had children, 9.8% stated they believed that it had a negative impact, 88.5% believed that it was neutral, and 1.6% believed that it had a positive impact. The majority of respondents without children thought that their decision to not have children had a neutral impact on their promotion (96.8% women; 100% men).
When asked if they had in the past delayed, or are currently delaying, having children, 69.5% of women and 35.9% of men reported that they had delayed or were currently delaying having children (Figure ). Two-thirds (65.6%) of men selected that they have not delayed having children compared with less than one-third (31.3%) of women. For current trainees, the most common reasons for delaying having children included “career concerns” (69.6% of women; 71.4% of men) and “concern about lack of parental leave or lack of sufficient parental leave” (39.1% of women; 28.6% of men). Respondents were asked if job-related stressors or responsibilities contributed to an adverse outcome of pregnancy or in getting pregnant. One-third of women (35.4%) reported yes, and 16.9% said that this was not applicable since they or their partner have not been pregnant or tried to become pregnant. Ten percent of men reported yes, and 13.0% reported not applicable.
Child-rearing The majority of respondents (77.9%) currently had children, and additional 2.5% were pregnant or their partner was pregnant, without current children. Men were significantly more likely to have children, and/or they/their partner were currently pregnant (88.4% of men, compared with 76.2% of women; p = 0.038). Of respondents with children, the average number of children was 2.1 ± 0.8, and men had a significantly higher number of children than women (men: mean 2.4 ±0.9 vs. women mean 1.9 ±0.7; p = < .001). Of respondents without children, 56.4% plan to have a child, and 50.0% were actively trying to have a child. Respondents with children were asked about their age, career stage, and practice setting at the birth of each child. Women hepatologists were older than their male counterparts when having children, with a nonsignificant trend for the average age at birth of their first child (mean for women: 33.2 y vs. men: 32.8 y), and statistical significance for their second child (women: 35.9 y vs. men: 34.0; p = 0.013 (full results in Table ). For the first child of women, the highest percentage had their first child during fellowship (43.3%), followed by an attending (30.9%), then residency (24.7%), and then medical school (1.0%). For the first child of men, the highest percentage had their first child as an attending (36.2%), followed by during fellowship (32.8%), then residency (25.9%), and then medical school (5.2%). Parental leave weeks, paid and unpaid Respondents were asked about their parental leave, including paid leave, unpaid leave, and weeks taken from other protected time off. For women’s first child, the average leave included a mean of 7.5 ± 3.5 weeks of paid leave and 3.7 ± 4.5 weeks of unpaid leave. Mean 4.1 ± 2.8 weeks were taken from other protected time (eg, vacation, sick days, or research time). For men’s first child, the average leave included 1.7 ±2.4 weeks of paid leave and 0.8 ±1.8 weeks of unpaid leave. A mean of 1.1 ±2.3 weeks was taken from other protected times. For women’s second child, the average leave included a mean of 8.3 ±3.7 weeks of paid leave and 4.0 ±4.8 weeks of unpaid leave, with 4.4 ±3.5 weeks taken away from other protected time. For men’s second child, average leave included 1.7 ±2.8 weeks of paid leave and 0.5 ±1.0 weeks of unpaid leave, with 0.9 ±1.2 weeks taken from other protected time. The duration of paid leave was significantly longer for women in primarily research academic positions (mean 9.1 wk) than those in primarily clinical academic positions (mean 7.1 wk), p = 0.02. For all women who provided their parental leave length, 79.3% had fewer paid weeks than the American Academy of Pediatrics recommended 12 weeks of leave. When the number of weeks taken away from other protected time (such as research and vacation) was subtracted from the number of weeks of paid parental leave, 90.9% had fewer than 12 weeks of dedicated paid parental leave.
The majority of respondents (77.9%) currently had children, and additional 2.5% were pregnant or their partner was pregnant, without current children. Men were significantly more likely to have children, and/or they/their partner were currently pregnant (88.4% of men, compared with 76.2% of women; p = 0.038). Of respondents with children, the average number of children was 2.1 ± 0.8, and men had a significantly higher number of children than women (men: mean 2.4 ±0.9 vs. women mean 1.9 ±0.7; p = < .001). Of respondents without children, 56.4% plan to have a child, and 50.0% were actively trying to have a child. Respondents with children were asked about their age, career stage, and practice setting at the birth of each child. Women hepatologists were older than their male counterparts when having children, with a nonsignificant trend for the average age at birth of their first child (mean for women: 33.2 y vs. men: 32.8 y), and statistical significance for their second child (women: 35.9 y vs. men: 34.0; p = 0.013 (full results in Table ). For the first child of women, the highest percentage had their first child during fellowship (43.3%), followed by an attending (30.9%), then residency (24.7%), and then medical school (1.0%). For the first child of men, the highest percentage had their first child as an attending (36.2%), followed by during fellowship (32.8%), then residency (25.9%), and then medical school (5.2%).
Respondents were asked about their parental leave, including paid leave, unpaid leave, and weeks taken from other protected time off. For women’s first child, the average leave included a mean of 7.5 ± 3.5 weeks of paid leave and 3.7 ± 4.5 weeks of unpaid leave. Mean 4.1 ± 2.8 weeks were taken from other protected time (eg, vacation, sick days, or research time). For men’s first child, the average leave included 1.7 ±2.4 weeks of paid leave and 0.8 ±1.8 weeks of unpaid leave. A mean of 1.1 ±2.3 weeks was taken from other protected times. For women’s second child, the average leave included a mean of 8.3 ±3.7 weeks of paid leave and 4.0 ±4.8 weeks of unpaid leave, with 4.4 ±3.5 weeks taken away from other protected time. For men’s second child, average leave included 1.7 ±2.8 weeks of paid leave and 0.5 ±1.0 weeks of unpaid leave, with 0.9 ±1.2 weeks taken from other protected time. The duration of paid leave was significantly longer for women in primarily research academic positions (mean 9.1 wk) than those in primarily clinical academic positions (mean 7.1 wk), p = 0.02. For all women who provided their parental leave length, 79.3% had fewer paid weeks than the American Academy of Pediatrics recommended 12 weeks of leave. When the number of weeks taken away from other protected time (such as research and vacation) was subtracted from the number of weeks of paid parental leave, 90.9% had fewer than 12 weeks of dedicated paid parental leave.
Health issues Respondents with children who were pregnant partners were asked about health issues during pregnancy and delivery. For their first child, 15.8% reported health issues during pregnancy, and 18.9% reported health issues during delivery. Two-thirds (67.4%) reported no health issues. For their second child, 22.9% reported health issues during pregnancy, and 7.1% reported health issues during delivery. Over two-thirds (72.9%) reported no health issues. Overnight call Respondents were asked how often they had overnight call responsibilities in their third trimester of pregnancy. For their first child, only one-fifth of women pregnant with their first child did not have any overnight calls in their third trimester of pregnancy (19.6%), while all the others had an increasing number of overnight calls. For subsequent children, the frequency of overnight calls during the third trimester decreased, with a quarter reporting no call for their second (26.5%) and third (26.3%) child. Weekly calls decreased to just over half for their second child (51.5%) and third child (52.6%). A higher percentage of those who worked 6 or more overnight calls per month in their third trimester reported health issues during pregnancy (22.2%, compared with 13.8%) and in delivery (22.2%, compared with 18.5%). Changes to call or work schedule before and after birth Respondents were asked if they changed their call or work schedule because of pregnancy and child-rearing. Over half of women changed their schedule before birth, during pregnancy (55.2%, compared with 18.6% of men). Of those who changed their schedule during pregnancy, they were asked what changes were made. Analysis of these open responses shows that, for women, over half (56.0%) increased the difficulty of their schedule to “front-load,” meaning that they would decrease calls during birth or delivery, or for some in their third trimester. This increased their call and service burden during pregnancy compared with their original schedule. A third (32.0%) reduced their call or endoscopy burden, and for 12%, changes were made but without a clear impact on the difficulty of their schedule. After the birth of their child, one-third of women (33.3%) and one-fifth of men (22.4%) reported changing their schedule. Respondents were also asked about changes to procedural volume and type if they performed procedures during their pregnancy. One-fifth decreased their procedural volume (21.3%), while two-thirds did not make changes to procedural volume (69.7%), and none reported increasing their procedural volume. Fifteen percent (15.7%) made changes to the types of procedures they performed, such as decreased procedures with fluoroscopy. Breastfeeding and pumping Respondents reported whether or not they breastfed and their breastfeeding duration. Of those who breastfed, one-fifth breastfed for <6 months (21.6%), one-third breastfed between 6 months and 11 months (33.0%), 40% between 1 and 2 years (40.9%), and 4.5% breastfed for 2 years or more. Only half of the women who breastfed reported adequate space for pumping breast milk (50.0%), with 20.7% reporting no space and 29.3% having inadequate space. Only 17.1% reported adequate time allotted for pumping, with 54.9% reporting no time and 28.0% inadequate time allotted for pumping. Twenty-nine percent (29.3%) reported adequate space for storing breast milk, whereas almost half reported that there is no space for storing breast milk (46.3%), and 24.4% reported that there is space for storing breast milk, but it is inadequate. Dedicated childcare Respondents with children were asked whether there was a nursery or childcare center affiliated with the hospital/clinic. Almost a quarter reported that there was a nursery/childcare center affiliated with the hospital/clinic but not located on the hospital premises (23.2%), and 17.4% reported that there was a nursery/childcare center on the hospital/clinic premises. Almost half (47.7%) reported that there was no nursery/childcare center affiliated with the hospital/clinic.
Respondents with children who were pregnant partners were asked about health issues during pregnancy and delivery. For their first child, 15.8% reported health issues during pregnancy, and 18.9% reported health issues during delivery. Two-thirds (67.4%) reported no health issues. For their second child, 22.9% reported health issues during pregnancy, and 7.1% reported health issues during delivery. Over two-thirds (72.9%) reported no health issues.
Respondents were asked how often they had overnight call responsibilities in their third trimester of pregnancy. For their first child, only one-fifth of women pregnant with their first child did not have any overnight calls in their third trimester of pregnancy (19.6%), while all the others had an increasing number of overnight calls. For subsequent children, the frequency of overnight calls during the third trimester decreased, with a quarter reporting no call for their second (26.5%) and third (26.3%) child. Weekly calls decreased to just over half for their second child (51.5%) and third child (52.6%). A higher percentage of those who worked 6 or more overnight calls per month in their third trimester reported health issues during pregnancy (22.2%, compared with 13.8%) and in delivery (22.2%, compared with 18.5%).
Respondents were asked if they changed their call or work schedule because of pregnancy and child-rearing. Over half of women changed their schedule before birth, during pregnancy (55.2%, compared with 18.6% of men). Of those who changed their schedule during pregnancy, they were asked what changes were made. Analysis of these open responses shows that, for women, over half (56.0%) increased the difficulty of their schedule to “front-load,” meaning that they would decrease calls during birth or delivery, or for some in their third trimester. This increased their call and service burden during pregnancy compared with their original schedule. A third (32.0%) reduced their call or endoscopy burden, and for 12%, changes were made but without a clear impact on the difficulty of their schedule. After the birth of their child, one-third of women (33.3%) and one-fifth of men (22.4%) reported changing their schedule. Respondents were also asked about changes to procedural volume and type if they performed procedures during their pregnancy. One-fifth decreased their procedural volume (21.3%), while two-thirds did not make changes to procedural volume (69.7%), and none reported increasing their procedural volume. Fifteen percent (15.7%) made changes to the types of procedures they performed, such as decreased procedures with fluoroscopy.
Respondents reported whether or not they breastfed and their breastfeeding duration. Of those who breastfed, one-fifth breastfed for <6 months (21.6%), one-third breastfed between 6 months and 11 months (33.0%), 40% between 1 and 2 years (40.9%), and 4.5% breastfed for 2 years or more. Only half of the women who breastfed reported adequate space for pumping breast milk (50.0%), with 20.7% reporting no space and 29.3% having inadequate space. Only 17.1% reported adequate time allotted for pumping, with 54.9% reporting no time and 28.0% inadequate time allotted for pumping. Twenty-nine percent (29.3%) reported adequate space for storing breast milk, whereas almost half reported that there is no space for storing breast milk (46.3%), and 24.4% reported that there is space for storing breast milk, but it is inadequate.
Respondents with children were asked whether there was a nursery or childcare center affiliated with the hospital/clinic. Almost a quarter reported that there was a nursery/childcare center affiliated with the hospital/clinic but not located on the hospital premises (23.2%), and 17.4% reported that there was a nursery/childcare center on the hospital/clinic premises. Almost half (47.7%) reported that there was no nursery/childcare center affiliated with the hospital/clinic.
Sufficient parental leave and a family-friendly culture in hepatology are critical to promote sex equity and improve the well-being of all physician parents. Broadly, women hepatologists experienced bias around pregnancy and parenthood, and took a short duration of parental leave. Women reported altering their training and career plans to accommodate child-rearing and family planning due to career concerns. In addition, work schedules during pregnancy were often more rigorous to attempt to cover time for parental leave. They reported that their return-to-work environment provided limited time and space for lactation, and few were provided childcare. Two-thirds of respondents with children had their first child before becoming an attending, making fellowship program leave policies and accommodations for pregnancy, postpartum, and breastfeeding physicians critically important. Our findings support the conclusion that the career and family planning decisions of trainees are commonly impacted by inconsistent, and often inadequate, policies for parental leave. , New policies released in 2021 by the Accreditation Council for Graduate Medical Education and the American Board of Medical Specialties to require 6 weeks of parental leave during training offer some potential improvement to this situation; however, it should be noted that this is still half of the leave duration that is recommended by the American Academy of Pediatrics. – In addition, the updated American Board of Medical Specialties policy excludes transplant hepatology fellowships, as they are 1-year fellowships. Our findings reinforce that more women than men reported the need to change their training due to pregnancy and parental leave, including extending time to graduation and decreasing research time, with a potential long-term impact on their careers and the talent pipeline for hepatology physician-scientists. In addition, respondents reported challenging work environments with minimal accommodations for pregnancy and child-rearing. Respondents reported a short average leave duration, with women indicating that a high percentage of their leave came from other protected time—with potential consequences on research time, vacation, and time available for sick leave. Ninety percent of women had fewer than the 12 weeks of dedicated paid parental leave time that is recommended by the American Academy of Pediatrics and is increasingly commonly mandated by state laws. , , Women frequently reported increasing call and service burden during pregnancy to take parental leave. Concerningly, widespread bias against pregnancy, child-rearing, and parental leave was reported. Upon returning to work postpartum, half of women hepatologists reported no or inadequate space allotted for pumping and storing breast milk (50.0%), and 82.9% reported no or inadequate time allotted. Over half of the women stopped breastfeeding before 1 year. This situation is despite the fact that the US Fair Labor Standards Act requires that employers provide time and space to pump breast milk. Women also frequently reported that their work environment and career concerns led to altered family planning. Women reported delaying child-rearing, most commonly due to concerns about the impact on their careers and inadequate parental leave. Predictably, women hepatologists were less likely to have children, had children when older, and had fewer children compared with their counterparts who are men. Studies across other medical disciplines have identified that physicians delay pregnancy more than nonphysician comparators, even when comparators were restricted to the highest income quintile. This delay was pronounced for specialist physicians. Our findings are consistent with literature from other areas of medicine, which have shown widespread bias against pregnancy and parenthood, as well as work environments that are incompatible with child-rearing. , , Cardiology is a similar medical subspecialty that is often procedurally based, and a recent study identified three-fourths of cardiologists reported practices surrounding their maternity leave, which are illegal in many circumstances. Our study has several limitations. First, the response rate of 7.7% is low but is consistent with other studies distributed through large email contact lists without incentives for participation. , In addition, the representativeness of our sample size is limited by a lack of gender diversity, with no respondents reporting that they are nonbinary, as well as an overrepresentation of female and White respondents. Furthermore, several of our findings may be reflective of medical training more broadly and may not be unique to hepatology. In addition, members of the email listserv may have been more likely to respond to a survey on pregnancy, child-rearing, and work environments if they have opinions on these issues. Our respondents are representative of a large age range, which suggests that some of the experiences reported here may be reflective of years ago when these respondents had children. It is possible that experiences have improved over time as more attention has been paid to sex-related issues. Nevertheless, it does provide some initial insight into the perceptions of many in our profession and suggests a need for further exploration of this topic to maximize both individual opportunities and an equitable, diverse, and inclusive workforce. There are several pathways within hepatology and beyond that can improve work environments for hepatologists who are parents. Given our findings regarding issues with parental leave in hepatology training, the creation of clear parental leave policies for hepatology fellows, which allows for equity in career opportunities and preserves research time, should be considered. The hepatology community can provide a statement about how best to implement recent Accreditation Council for Graduate Medical Education regulations that require sponsoring institutions to provide a minimum of 6 weeks of paid parental leave. There is an ongoing discussion regarding competency-based medical education versus time-based medical education that may provide increased flexibility regarding parental leave. , In addition to protections for trainees, department and division leadership should consider pregnancy accommodations to mitigate high rates of pregnancy complications, including reduced overnight calls and a reduced clinical load, which are both associated with adverse pregnancy outcomes. Those who participate in endoscopy should be allowed to adjust their endoscopic volume without financial penalty. Parental leave policies should be transparent and accessible, as well as equitable for diverse family units, including availability for all genders. Furthermore, the creation of a family-friendly return-to-work environment should include flexible scheduling options and assistance with childcare. In addition, we should discuss as a hepatology community what steps can be taken to allow pregnancy, parental leave, and child-rearing without overburdening either parents or colleagues. Sufficient ancillary staffing and improved family leave policies would provide benefits to not only parents but also all hepatologists who need to balance career and family responsibilities. Ultimately, reforms beyond the hepatology community are likely needed to support workforce equity. The hepatology community could join in advocacy efforts with the medical societies of other specialties that have called for legislation in the US supporting paid family leave.
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Value of the clinical pharmacist interventions in the application of the American College of Cardiology (ACC/AHA) 2018 guideline for cholesterol management | 2d071e88-bf5f-4e61-a809-cb71a6121cfd | 10042341 | Internal Medicine[mh] | Coronary heart disease (CHD) is considered one of the main causes of morbidity and mortality worldwide. One of the major risk factors that contributes to the development and progression of CHD is dyslipidemia . According to the World Health Organization (WHO), an estimated 17.9 million patients died each year because of cardiovascular diseases, of which more than 80.0% of the deaths were due to stroke and myocardial infarction . Ischemic heart diseases and stroke are among the top 3 leading causes of years of life lost (YLL) and mortality according to a global burden disease study . Another recent study in UAE showed that the overall prevalence of dyslipidemia among adults was 72.5%, where the total cholesterol and LDL-C levels were high in 42.8% and 38.6% of the participants, respectively . In addition, a study including an expatriate population in the UAE reported a high prevalence of either overweight or obesity (75.3%) as well as known associated risk factors for developing both metabolic syndrome and dyslipidemia . A large number of clinical trials have reported the benefits of lowering cholesterol levels, particularly LDL-C, in reducing the mortality rate among CHD patients. Based on that, the American College of Cardiology (ACC/AHA) published the 2013 blood cholesterol treatment guidelines to reduce atherosclerotic cardiovascular risk in adults. This guideline has been updated several times since then . The latest update of the ACC/AHA management of blood cholesterol guideline (2018) emphasizes on the importance of categorizing patients into the four statins benefit groups and on the importance of statin therapy using evidence-based intensity level (high- or moderate-intensity statins). Furthermore, it highlights the importance of adding PCSK9 inhibitor therapy after receiving the maximum tolerated statin therapy and ezetimibe to achieve LDL-C < 70 mg/dl or non-HDL-C < 100 mg/dl for some patients . The prevalence and treatment rates of dyslipidemia are high in the UAE and worldwide , however, it was found that a significant percentage of patients worldwide were not taking appropriate lipid-lowering agents or were taking statins but were not meeting the primary treatment goal . One of the reasons identified was the low adherence to the guideline recommendations. Clinical pharmacists play important role in individualizing patient treatment and improving adherence to guideline’s recommendations. The present study aims to examine the extent to which the updated ACC/AHA management of blood cholesterol guideline (2018) is implemented in practice and to assess the value of the clinical pharmacists’ interventions in improving physicians’ adherence to the guideline’s recommendations. In UAE, the ACC / AHA guidelines are the most commonly followed and recommended guidelines by the health authorities.
Subjects and settings The study was conducted on adult patients attending an internal medicine clinic at a large hospital in Al Ain City, UAE, from January to April 2019 (n = 647). Patients’ information had been collected through Hospital Information System (HIS). The study pharmacist evaluated the data for all patients attending the internal medicine clinic on daily basis during the study period to identify eligible patients. Patients aged ≥ 21 years who met the criteria of one of the statin benefit groups requiring high- or moderate-intensity statin therapy according to the 2018 ACC/AHA guidelines were included in this study if they had no of the below exclusion criteria (number of included patients = 272, 42%). As per 2018 ACC / AHA guideline recommendations, the following were the statins benefits groups: subjects with a history of ASCVD; a high intensity statin should be considered (Class 1 recommendation). subjects with a primary elevation of LDL cholesterol ≥190 mg/dL; a high intensity statin should be considered (Class 1 recommendation). subjects with diabetes. In adults 40 to 75 years of age with diabetes mellitus, regardless of estimated 10-year ASCVD risk, moderate-intensity statin therapy is indicated (Class 1 recommendation). In adults 40 to 75 years of age with diabetes mellitus who have multiple ASCVD risk factors, it is reasonable to prescribe high intensity statin therapy (Class 2A recommendation) In adults older than 75 years with diabetes mellitus, it may be reasonable to initiate statin therapy after a clinician–patient discussion of potential benefits and risks (Class 2B recommendation, Class 2A if already on statin) For diabetic patients 20–39 years old, statin may be considered in case of presence of multiple diabetes specific risk enhancers such as long disease duration, albuminuria ≥ 30 mcg albumin/mg creatinine, eGFR < 60 ml/min/1.73 m2, neuropathy, and retinopathy (Class 2B recommendation) subjects 40–75 years old without diabetes or ASCVD, with baseline LDL cholesterol levels of 70 to 189 mg/dL. Treatment recommendations are based on the 10-year ASCVD risk as follows: Borderline risk (10-year ASCVD risk 5–7.4%): consider a moderate intensity statin if risk enhancers present (Class 2B recommendation). Intermediate risk (10-year ASCVD risk 7.5–19.9%): consider moderate intensity statin (Class 1 recommendation). High risk (10-year ASCVD risk ≥20%): consider high intensity statin (Class 1 recommendation). In addition, the guideline recommends considering treatment with statins in individuals aged 20 to 39 years old with a family history of premature ASCVD disease and a high LDL of ≥ 160 mg/dL (Class 2B recommendation). The main exclusion criteria were: 1) history of statin-induced rhabdomyolysis or myopathy; 2) history of allergic reaction to statins; 3) current active liver disease; 4) creatine kinase levels >3 times the upper limit of normal; 5) Any contraindications to statins use; 6. Patients for whom a lipid profile was not available or who did not have a sufficient data to classify them into statin benefit groups or enough information for calculating the ASCVD risk score at the time the study was conducted were excluded as well. Ethical consideration This study was approved by the Hospital Research Ethics Committee (Ref. CR /2018/40). All methods were performed in accordance with relevant guidelines and regulations. The study was explained to patients and their consent was obtained before participation. Study design and data collection We utilized in this study an interventional before-after design. Demographic and clinical characteristics of the study sample were extracted from the hospital information system. Data collected did not include any personal or sensitive information such as patient’s identity or medical record number. represents the flowchart of the study design. Data collection before clinical pharmacists’ intervention Eligibility for statin therapy was evaluated based on 2018 ACC / AHA guideline recommendations as stated above. Adherence to guideline recommendations before clinical pharmacist’s intervention was measured by calculating the percentage of patients identified per each statin benefit group, the percentage of patients receiving statin therapy as per guideline recommendation, the type and intensity (moderate or high intensity) of statin therapy used, and the need for additional non-statin therapy. We calculated only adherence to class 1 and class 2A guideline’s recommendations. Clinical pharmacists’ interventions The clinical pharmacists received the medication order for each patient after the patients’ appointment with the physician. The clinical pharmacists evaluated all patients’ data and the appropriateness of their medication order and recommended therapy modifications to meet the 2018 ACC/AHA cholesterol management guideline recommendations. Physicians were automatically notified with the pharmacist’s intervention in the online system and responded accordingly by agreeing, modifying, or rejecting the pharmacist’s recommendation. Physician response and treatment plan changes due to clinical pharmacist interventions were extracted from the Hospital Information System. Data collection after clinical pharmacists’ intervention Adherence to guideline recommendations was measured by calculating the percentage of patients identified per each statin benefit group, the percentage of patients receiving statin therapy as per guideline recommendations, the type and intensity (moderate or high intensity) of statin therapy used, and the need for additional non-statin therapy. We calculated only adherence to class 1 and class 2A recommendations. Rejecting a recommendation that is based on a class 2B guideline recommendation was not considered as nonadherent. These class 2B recommendations are usually considered by the guideline as “may be reasonable” and “weak” where their benefit is ≥ risk. Study outcomes The following outcomes were examined in this study: Adherence to the 2018 ACC /AHA guideline recommendations was measured by determining the following: The number and percentage of statin benefit group patients who were prescribed a statin Appropriateness of statin dose (high intensity vs moderate intensity) The need for additional non-statin therapy. The impact of clinical pharmacist interventions on the application of guideline recommendations was determined by measuring the following: The number and type of recommendations attained by the clinical pharmacist. Physicians’ acceptance of recommendations Comparison of differences in adherence to 2018 ACC /AHA guidelines before and after clinical pharmacist interventions. Statistical analysis All data were entered and analyzed using Statistical Package for the Social Sciences (SPSS) version 22 (IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp.). Descriptive statistics were used to measure the frequencies and percentages. The chi-square test was used to compare adherence to guidelines before and after clinical pharmacist interventions. A p-value of 0.05 was considered statistically significant, using a 95.0% confidence interval for differences.
The study was conducted on adult patients attending an internal medicine clinic at a large hospital in Al Ain City, UAE, from January to April 2019 (n = 647). Patients’ information had been collected through Hospital Information System (HIS). The study pharmacist evaluated the data for all patients attending the internal medicine clinic on daily basis during the study period to identify eligible patients. Patients aged ≥ 21 years who met the criteria of one of the statin benefit groups requiring high- or moderate-intensity statin therapy according to the 2018 ACC/AHA guidelines were included in this study if they had no of the below exclusion criteria (number of included patients = 272, 42%). As per 2018 ACC / AHA guideline recommendations, the following were the statins benefits groups: subjects with a history of ASCVD; a high intensity statin should be considered (Class 1 recommendation). subjects with a primary elevation of LDL cholesterol ≥190 mg/dL; a high intensity statin should be considered (Class 1 recommendation). subjects with diabetes. In adults 40 to 75 years of age with diabetes mellitus, regardless of estimated 10-year ASCVD risk, moderate-intensity statin therapy is indicated (Class 1 recommendation). In adults 40 to 75 years of age with diabetes mellitus who have multiple ASCVD risk factors, it is reasonable to prescribe high intensity statin therapy (Class 2A recommendation) In adults older than 75 years with diabetes mellitus, it may be reasonable to initiate statin therapy after a clinician–patient discussion of potential benefits and risks (Class 2B recommendation, Class 2A if already on statin) For diabetic patients 20–39 years old, statin may be considered in case of presence of multiple diabetes specific risk enhancers such as long disease duration, albuminuria ≥ 30 mcg albumin/mg creatinine, eGFR < 60 ml/min/1.73 m2, neuropathy, and retinopathy (Class 2B recommendation) subjects 40–75 years old without diabetes or ASCVD, with baseline LDL cholesterol levels of 70 to 189 mg/dL. Treatment recommendations are based on the 10-year ASCVD risk as follows: Borderline risk (10-year ASCVD risk 5–7.4%): consider a moderate intensity statin if risk enhancers present (Class 2B recommendation). Intermediate risk (10-year ASCVD risk 7.5–19.9%): consider moderate intensity statin (Class 1 recommendation). High risk (10-year ASCVD risk ≥20%): consider high intensity statin (Class 1 recommendation). In addition, the guideline recommends considering treatment with statins in individuals aged 20 to 39 years old with a family history of premature ASCVD disease and a high LDL of ≥ 160 mg/dL (Class 2B recommendation). The main exclusion criteria were: 1) history of statin-induced rhabdomyolysis or myopathy; 2) history of allergic reaction to statins; 3) current active liver disease; 4) creatine kinase levels >3 times the upper limit of normal; 5) Any contraindications to statins use; 6. Patients for whom a lipid profile was not available or who did not have a sufficient data to classify them into statin benefit groups or enough information for calculating the ASCVD risk score at the time the study was conducted were excluded as well.
This study was approved by the Hospital Research Ethics Committee (Ref. CR /2018/40). All methods were performed in accordance with relevant guidelines and regulations. The study was explained to patients and their consent was obtained before participation.
We utilized in this study an interventional before-after design. Demographic and clinical characteristics of the study sample were extracted from the hospital information system. Data collected did not include any personal or sensitive information such as patient’s identity or medical record number. represents the flowchart of the study design.
Eligibility for statin therapy was evaluated based on 2018 ACC / AHA guideline recommendations as stated above. Adherence to guideline recommendations before clinical pharmacist’s intervention was measured by calculating the percentage of patients identified per each statin benefit group, the percentage of patients receiving statin therapy as per guideline recommendation, the type and intensity (moderate or high intensity) of statin therapy used, and the need for additional non-statin therapy. We calculated only adherence to class 1 and class 2A guideline’s recommendations.
The clinical pharmacists received the medication order for each patient after the patients’ appointment with the physician. The clinical pharmacists evaluated all patients’ data and the appropriateness of their medication order and recommended therapy modifications to meet the 2018 ACC/AHA cholesterol management guideline recommendations. Physicians were automatically notified with the pharmacist’s intervention in the online system and responded accordingly by agreeing, modifying, or rejecting the pharmacist’s recommendation. Physician response and treatment plan changes due to clinical pharmacist interventions were extracted from the Hospital Information System.
Adherence to guideline recommendations was measured by calculating the percentage of patients identified per each statin benefit group, the percentage of patients receiving statin therapy as per guideline recommendations, the type and intensity (moderate or high intensity) of statin therapy used, and the need for additional non-statin therapy. We calculated only adherence to class 1 and class 2A recommendations. Rejecting a recommendation that is based on a class 2B guideline recommendation was not considered as nonadherent. These class 2B recommendations are usually considered by the guideline as “may be reasonable” and “weak” where their benefit is ≥ risk.
The following outcomes were examined in this study: Adherence to the 2018 ACC /AHA guideline recommendations was measured by determining the following: The number and percentage of statin benefit group patients who were prescribed a statin Appropriateness of statin dose (high intensity vs moderate intensity) The need for additional non-statin therapy. The impact of clinical pharmacist interventions on the application of guideline recommendations was determined by measuring the following: The number and type of recommendations attained by the clinical pharmacist. Physicians’ acceptance of recommendations Comparison of differences in adherence to 2018 ACC /AHA guidelines before and after clinical pharmacist interventions.
All data were entered and analyzed using Statistical Package for the Social Sciences (SPSS) version 22 (IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp.). Descriptive statistics were used to measure the frequencies and percentages. The chi-square test was used to compare adherence to guidelines before and after clinical pharmacist interventions. A p-value of 0.05 was considered statistically significant, using a 95.0% confidence interval for differences.
Demographic and clinical characteristics of the study sample The demographic and clinical characteristics of the study sample are shown in . The mean age of the studied patients was 52.6 ±10.5, and 71.3% (n = 194) of them were males. Majority of the patients (95.6%, n = 260) had previous illness or chronic disease. Out of these patients, 178 patients (65.4%) had hypertension, 150 patients (55.1%) had dyslipidemia, and 196 patients (72.1%) had diabetes mellitus. Nevertheless, 20 patients (7.4%) had LDL-C levels less than 70 mg/dl, 236 patients (86.8%) had LDL-C levels between 70–189 mg/dl, and 16 patients (5.9%) had LDL-C levels equal to or more than 190. Additionally, 52 patients (19.1%) had a history of clinical ASCVD. Of these, 38 patients (14.0%) were at very high risk of recurrent CVD. Out of all participants without a history of clinical ASCVD, 50 patients (18.4%) had an estimated 10-year CVD risk less than 7.5%, 110 patients (40.5%) had an estimated 10-year CVD risk greater than or equal to 7.5% but less than 20.0%, and 60 patients (22.1%) had an estimated 10-year CVD risk equal to or greater than 20.0%. The adherence with the 2018 ACC/AHA guideline recommendations for the management of cholesterol in adults before clinical pharmacist interventions Adherence with the 2018 ACC/AHA guideline recommendations for the management of cholesterol in adults is shown in . Based on the inclusion criteria, all the patients who were enrolled (100.0%, n = 272) were identified as statin benefit groups according to the 2018 ACC/AHA guideline recommendations. Of these, only 60.3% (n = 164) were initiated on statin therapy. Out of those who were on statin therapy, 9.8% (n = 16) were on low intensity statin (e.g., simvastatin 10 mg and pitavastatin 1 mg), 52.4% (n = 86) were on moderate intensity statin (e.g., simvastatin 40 mg, rosuvastatin 10 mg, atorvastatin 20 mg, pitavastatin 2 mg and 4 mg) and 37.8% (n = 62) were on high intensity statin (e.g., atorvastatin 40 mg and 80 mg and rosuvastatin 20 mg and 40 mg). Adherence to the recommend level of statins intensity was identified in only 47.6% of patients (n = 78). The addition of non-statin therapies to achieve LDL-C goals was also assessed, and ezetimibe was required for 51.2% (n = 84) of those who were on statin therapy. While it was initiated for only 8.5% (n = 14). PCSK9 inhibitors were required for 3.7% (n = 6) of those who were on statin and ezetimibe therapies. However, such treatment was not initiated in any patient. Other lipid-lowering agents, such as fibric acid derivatives (fenofibrate 145 mg and 300 mg and gemfibrozil 600 mg), were initiated on 14.6% (n = 24) of those who were on statin therapy. The value of the clinical pharmacist’s interventions on applying the 2018 ACC/AHA guideline recommendations The impact of the clinical pharmacist interventions on applying the 2018 ACC/AHA guideline recommendations is shown in . In patients with LDL-C<70 mg/dl, 18 recommendations were made, ranging from adding moderate- or high-intensity statins for those who were not initiated on statins (need additional therapy–class I and IIa recommendations as per 2018 ACC/AHA guideline definition of recommendation class), changing to moderate- or high-intensity statin agents for those who were on lower-intensity statin agents and stopping other lipid-lowering agents that may not help in achieving LDL-C goals (dose adjustment/stop unnecessary medications—class I and IIa recommendations). However, the physicians’ acceptance of the aforementioned recommendations was only 22.2%. In patients with LDL-C between 70–189 mg/dl, 262 recommendations were carried out ranged from adding ezetimibe and stopping other ineffective LDL-C lowering agents for those who were in maximum tolerated dose of statin (need additional therapy/stop the unnecessary medication–class I and IIa recommendations), adding moderate or high intensity statin for those with who were not initiated on statin (need additional therapy–class I and IIa recommendations) and changing to high intensity statin dose or drug for those who were on lower intensity statin agents and stopping other ineffective LDL-C lowering agents (dose adjustment/change drug/stop the unnecessary medications—class I and IIa recommendations). The physicians’ acceptance of these recommendations was 79.4%. In patients with LDL-C ≥190 mg/dl, 30 recommendations were submitted, ranging from adding ezetimibe, PCSK9 inhibitor and stopping gemfibrozil for those with very high LDL-C results and requiring a more than 25.0% reduction in LDL-C levels despite the use of high-intensity statins (requiring additional therapy–class I recommendation), adding high-intensity statins together with ezetimibe for those who were not on statins (requiring additional therapies–class I recommendation), adding PCSK9 inhibitors for those with high LDL-C levels, although they were on high-intensity statins together with ezetimibes (requiring additional therapy–class I recommendation) and changing to high-intensity statins and adding ezetimibe for those on moderate-intensity statins even though the LDL-C level was more than or equal to 190 mg/dl (dose adjustment/requiring additional therapy–class I recommendation). Interestingly, the physicians’ acceptance of these recommendations was 93.2%. summarizes the number of recommendations and type of interventions performed by the clinical pharmacist to achieve the desired outcomes. Adherence with the 2018 ACC/AHA guideline after clinical pharmacist’s interventions Adherence with the 2018 ACC/AHA guideline for the management of cholesterol in adults after clinical pharmacist interventions is shown in . Accordingly, the number of patients who were initiated on statin therapy increased significantly up to 92.6% (n = 252) after the clinical pharmacist interventions were implemented ( X 2 (df = 1, n = 272) = 79.1, p = 0.0001). Consequently, the number of patients who were on low- or moderate-intensity statins decreased to 2.4% (n = 6) and 17.9% (n = 45), respectively. However, the number of patients who were on high-intensity statins potentially increased to 79.8% (n = 201). Based on that, adherence with the recommendations regarding the level of statin intensity used was significantly improved to 94.4% (n = 238) after the clinical pharmacist interventions ( X 2 (df = 1, n = 252) = 72.5, p = 0.0001). The use of ezetimibe as an add-on nonstatin therapy was encouraged and effectively added to the treatment plan to achieve LDL-C goals. The number of patients who were initiated ezetimibe increased significantly to 91.7% (n = 77) after the clinical pharmacist interventions ( X 2 (df = 1, n = 84) = 95, p < 0.0001). Interestingly, for those who were on statin and ezetimibe therapies and required PCSK9 inhibitors to achieve LDL-C goals, adherence with the recommendations was effectively improved to 66.7% (n = 4); ( X 2 (df = 1, n = 6) = 6, p = 0.014). The use of other lipid-lowering agents, such as fibrates, was markedly reduced to 3.2% (n = 8) for those who were on statin therapy after the clinical pharmacist interventions ( X 2 (df = 1, n = 208) = 19.2, p < 0.0001). shows comparison of adherence with the 2018 ACC/AHA guideline recommendations for the management of cholesterol before and after clinical pharmacist interventions regarding the initiation of statins, the proper use of moderate- or high-intensity statins, evidence-based addition of ezetimibe and PCSK9 inhibitors and minimization of other lipid-lowering agent abuse.
The demographic and clinical characteristics of the study sample are shown in . The mean age of the studied patients was 52.6 ±10.5, and 71.3% (n = 194) of them were males. Majority of the patients (95.6%, n = 260) had previous illness or chronic disease. Out of these patients, 178 patients (65.4%) had hypertension, 150 patients (55.1%) had dyslipidemia, and 196 patients (72.1%) had diabetes mellitus. Nevertheless, 20 patients (7.4%) had LDL-C levels less than 70 mg/dl, 236 patients (86.8%) had LDL-C levels between 70–189 mg/dl, and 16 patients (5.9%) had LDL-C levels equal to or more than 190. Additionally, 52 patients (19.1%) had a history of clinical ASCVD. Of these, 38 patients (14.0%) were at very high risk of recurrent CVD. Out of all participants without a history of clinical ASCVD, 50 patients (18.4%) had an estimated 10-year CVD risk less than 7.5%, 110 patients (40.5%) had an estimated 10-year CVD risk greater than or equal to 7.5% but less than 20.0%, and 60 patients (22.1%) had an estimated 10-year CVD risk equal to or greater than 20.0%.
Adherence with the 2018 ACC/AHA guideline recommendations for the management of cholesterol in adults is shown in . Based on the inclusion criteria, all the patients who were enrolled (100.0%, n = 272) were identified as statin benefit groups according to the 2018 ACC/AHA guideline recommendations. Of these, only 60.3% (n = 164) were initiated on statin therapy. Out of those who were on statin therapy, 9.8% (n = 16) were on low intensity statin (e.g., simvastatin 10 mg and pitavastatin 1 mg), 52.4% (n = 86) were on moderate intensity statin (e.g., simvastatin 40 mg, rosuvastatin 10 mg, atorvastatin 20 mg, pitavastatin 2 mg and 4 mg) and 37.8% (n = 62) were on high intensity statin (e.g., atorvastatin 40 mg and 80 mg and rosuvastatin 20 mg and 40 mg). Adherence to the recommend level of statins intensity was identified in only 47.6% of patients (n = 78). The addition of non-statin therapies to achieve LDL-C goals was also assessed, and ezetimibe was required for 51.2% (n = 84) of those who were on statin therapy. While it was initiated for only 8.5% (n = 14). PCSK9 inhibitors were required for 3.7% (n = 6) of those who were on statin and ezetimibe therapies. However, such treatment was not initiated in any patient. Other lipid-lowering agents, such as fibric acid derivatives (fenofibrate 145 mg and 300 mg and gemfibrozil 600 mg), were initiated on 14.6% (n = 24) of those who were on statin therapy.
The impact of the clinical pharmacist interventions on applying the 2018 ACC/AHA guideline recommendations is shown in . In patients with LDL-C<70 mg/dl, 18 recommendations were made, ranging from adding moderate- or high-intensity statins for those who were not initiated on statins (need additional therapy–class I and IIa recommendations as per 2018 ACC/AHA guideline definition of recommendation class), changing to moderate- or high-intensity statin agents for those who were on lower-intensity statin agents and stopping other lipid-lowering agents that may not help in achieving LDL-C goals (dose adjustment/stop unnecessary medications—class I and IIa recommendations). However, the physicians’ acceptance of the aforementioned recommendations was only 22.2%. In patients with LDL-C between 70–189 mg/dl, 262 recommendations were carried out ranged from adding ezetimibe and stopping other ineffective LDL-C lowering agents for those who were in maximum tolerated dose of statin (need additional therapy/stop the unnecessary medication–class I and IIa recommendations), adding moderate or high intensity statin for those with who were not initiated on statin (need additional therapy–class I and IIa recommendations) and changing to high intensity statin dose or drug for those who were on lower intensity statin agents and stopping other ineffective LDL-C lowering agents (dose adjustment/change drug/stop the unnecessary medications—class I and IIa recommendations). The physicians’ acceptance of these recommendations was 79.4%. In patients with LDL-C ≥190 mg/dl, 30 recommendations were submitted, ranging from adding ezetimibe, PCSK9 inhibitor and stopping gemfibrozil for those with very high LDL-C results and requiring a more than 25.0% reduction in LDL-C levels despite the use of high-intensity statins (requiring additional therapy–class I recommendation), adding high-intensity statins together with ezetimibe for those who were not on statins (requiring additional therapies–class I recommendation), adding PCSK9 inhibitors for those with high LDL-C levels, although they were on high-intensity statins together with ezetimibes (requiring additional therapy–class I recommendation) and changing to high-intensity statins and adding ezetimibe for those on moderate-intensity statins even though the LDL-C level was more than or equal to 190 mg/dl (dose adjustment/requiring additional therapy–class I recommendation). Interestingly, the physicians’ acceptance of these recommendations was 93.2%. summarizes the number of recommendations and type of interventions performed by the clinical pharmacist to achieve the desired outcomes.
Adherence with the 2018 ACC/AHA guideline for the management of cholesterol in adults after clinical pharmacist interventions is shown in . Accordingly, the number of patients who were initiated on statin therapy increased significantly up to 92.6% (n = 252) after the clinical pharmacist interventions were implemented ( X 2 (df = 1, n = 272) = 79.1, p = 0.0001). Consequently, the number of patients who were on low- or moderate-intensity statins decreased to 2.4% (n = 6) and 17.9% (n = 45), respectively. However, the number of patients who were on high-intensity statins potentially increased to 79.8% (n = 201). Based on that, adherence with the recommendations regarding the level of statin intensity used was significantly improved to 94.4% (n = 238) after the clinical pharmacist interventions ( X 2 (df = 1, n = 252) = 72.5, p = 0.0001). The use of ezetimibe as an add-on nonstatin therapy was encouraged and effectively added to the treatment plan to achieve LDL-C goals. The number of patients who were initiated ezetimibe increased significantly to 91.7% (n = 77) after the clinical pharmacist interventions ( X 2 (df = 1, n = 84) = 95, p < 0.0001). Interestingly, for those who were on statin and ezetimibe therapies and required PCSK9 inhibitors to achieve LDL-C goals, adherence with the recommendations was effectively improved to 66.7% (n = 4); ( X 2 (df = 1, n = 6) = 6, p = 0.014). The use of other lipid-lowering agents, such as fibrates, was markedly reduced to 3.2% (n = 8) for those who were on statin therapy after the clinical pharmacist interventions ( X 2 (df = 1, n = 208) = 19.2, p < 0.0001). shows comparison of adherence with the 2018 ACC/AHA guideline recommendations for the management of cholesterol before and after clinical pharmacist interventions regarding the initiation of statins, the proper use of moderate- or high-intensity statins, evidence-based addition of ezetimibe and PCSK9 inhibitors and minimization of other lipid-lowering agent abuse.
Based on this study, adherence with the 2018 ACC/AHA guideline recommendation for the management of cholesterol in adult patients before clinical pharmacist interventions was 60.3% for the initiation of statins therapy and 47.6% for adherence to proper intensity statin therapy. Accordingly, the initiation of statins, particularly high-intensity statins, is prescribed to far fewer patients than recommended. Consequently, the use of non-statin therapies such as ezetimibe and PCSK9 inhibitors was nearly diminished, taking into consideration that several studies highlighted the importance of pharmacist intervention on cholesterol risk management and revealed the treatment gap between research evidence and clinical practice . According to our findings, the clinical pharmacist plays a crucial role in the management of cholesterol levels by recommending new therapies, adjusting or increasing drug doses and stopping or changing medications. Furthermore, systematic reviews and meta-analyses of randomized trials conducted by Machado et al. and Santschi et al. emphasized the importance of pharmaceutical care interventions in the management of CVDs . Pharmacist interventions achieved greater reductions in systolic and diastolic blood pressure (BP), total cholesterol (TC), and LDL-C and in the risk of smoking compared with the usual care group . Nevertheless, various clinical trials have illustrated great benefits of statin use, such as pleiotropic effects, which could be beneficial for the treatment and management of several comorbidities . In this study, adherence with the 2018 ACC/AHA guideline to achieve the required LDL-C goals was significantly improved after clinical pharmacist interventions and the implementation of the appropriate recommendations. Consistently, Bozovich et al. 2000 and Tahaineh et al. 2011 showed significant improvement in achieving LDL-C goals when clinical pharmacists managed lipid clinics or through clinical pharmacy services under the supervision of cardiologists . The same was achieved by Tsuyuki RT et al. (2016) . In the current study, physicians’ acceptance of the clinical pharmacist’s recommendation according to the guidelines was variable based on patients’ LDL-C levels. For instance, physicians” acceptance of clinical pharmacist interventions was high among patients with LDL-C ≥70 mg/dl. Subsequently, this resulted in greater improvement of LDL-C levels and improvement in health outcomes. Likewise, recent studies reported that primary healthcare physicians significantly relied on clinical pharmacists in assessing and improving patients’ adherence to their medications as well as in educating and counseling the patients to avoid clinical malpractice and achieve better health outcomes . Several studies presented the major explanations for statin refractoriness reported by healthcare practitioners, and patients were concerned about adverse events . Rosenson, R. S 2016 stated that evaluation of potential adverse events requires validated tools to differentiate between statin-associated adverse events versus nonspecific complaints. Additionally, treatment options for statin-intolerant patients include the use of different statins, often at a lower dose or frequency. To lower LDL cholesterol, lower doses of statins may be combined with ezetimibe or bile acid sequestrants . Newer treatment options for patients with statin-associated muscle symptoms may include proprotein convertase subtilisin kexin 9 (PCSK9) inhibitors . There are many reasons that contribute to non-adherence with the guidelines or rejecting the pharmacists’ recommendations such as the availability of specific drugs and patient’s reluctant for treatment initiation or dose escalation. The results of the current study indicated that many physicians are reluctant to prescribe high intensity statins due the worry about side effects and myopathy. In some cases, physicians stop or change the dose of statins when patients’ report intolerance of such medications or due to the high cost. Another reason for rejecting the pharmacists’ recommendations in this study was low bassline LDL-C level for some patients despite the patient being categorized as a statin benefit group. In clinical trials, statin-associated adverse events showed no differences between participants assigned to statins or placebo . However, it is important to know that these trials select patients with better tolerability and lower risk for myopathy based on their ages, absence of musculoskeletal complaints, normal renal function and less concomitant medications that may alter the pharmacokinetic pathways . One of the solutions to overcome the problem is to switch to the fully human monoclonal antibodies proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors (alirocumab and evolocumab) that caused fewer muscle symptoms based on clinical trials and were no more often than when ezetimibe was used . However, the cost of such treatment is still one of the main barriers. Limitations This study is an interventional before after design. This design is usually used in circumstances where it is not possible to use a control group for ethical or practical issues. Although this design is suitable for the current study, the lack of control group makes this design prone to bias and many confounders. Therefore, the outcome can instead be related to any changes that occurred around the same time as the intervention. Although the clinical pharmacists and physicians who treated the patients in the studied clinics remained the same during the study period, other unknown confounders could have occurred. Another limitation is that it is not an easy task to initiate statin therapy for those are low or intermediate risk for ASCVD. It involves looking for wide range of risk-enhancing factors which could favor the initiation of statin therapy for the low or intermediate risk group, for example the presence of premature CVD in the family. These risk-enhancing factors can be missed during patient assessment or during data extraction. on the other hand, the patient with low or intermediate ASCVD risk is allowed to option for not taking statins for primary ASCVD prevention. Therefore, it is difficult to precisely judge physicians for adherence to guideline for initiating lipid-lowering agents. In addition, the estimate ASCVD risk is more imprecise in some patients when cholesterol levels were used after treatment.
This study is an interventional before after design. This design is usually used in circumstances where it is not possible to use a control group for ethical or practical issues. Although this design is suitable for the current study, the lack of control group makes this design prone to bias and many confounders. Therefore, the outcome can instead be related to any changes that occurred around the same time as the intervention. Although the clinical pharmacists and physicians who treated the patients in the studied clinics remained the same during the study period, other unknown confounders could have occurred. Another limitation is that it is not an easy task to initiate statin therapy for those are low or intermediate risk for ASCVD. It involves looking for wide range of risk-enhancing factors which could favor the initiation of statin therapy for the low or intermediate risk group, for example the presence of premature CVD in the family. These risk-enhancing factors can be missed during patient assessment or during data extraction. on the other hand, the patient with low or intermediate ASCVD risk is allowed to option for not taking statins for primary ASCVD prevention. Therefore, it is difficult to precisely judge physicians for adherence to guideline for initiating lipid-lowering agents. In addition, the estimate ASCVD risk is more imprecise in some patients when cholesterol levels were used after treatment.
The clinical pharmacist has a key role in improving the management of blood cholesterol by recommending therapies, adjusting doses and stopping or changing medications. Furthermore, adherence with the latest updated guideline recommendations to achieve the desired treatment goals was notably enhanced after the clinical pharmacist interventions and the implementation of the appropriate recommendations. This study illustrates how collaboration between physicians and clinical pharmacists can be crucial strategy to improve patients’ treatment and hence, achieve better health outcomes among patients suffering from dyslipidemia.
S1 Data (XLSX) Click here for additional data file.
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FOXO3a deregulation in uterine smooth muscle tumors | 26dbbf24-077f-4d28-9b5b-bd42c37201d0 | 11031728 | Anatomy[mh] | Forkhead family of transcription factors – class O (FOXO) transcription factors are involved in several physiological and pathological processes, including aging, stress resistance, neurological diseases, and cancer development. Within FOXO family, FOXO3a is a crucial protein considered a tumor suppressor by regulating the expression of genes involved in apoptosis, cell cycle arrest, oxidative stress resistance and autophagy. Some researchers have suggested that FOXO3a acts as an adaptable player in dynamic homeostasis both in normal and stressed tissue. In addition, several works have pointed to the relevance of FOXO3a/HER-2 (EGFR) signaling in cancer development and prognosis. The growth factors ligation to their receptors triggers the signaling cascade that leads to FOXO3a phosphorylation, cytoplasmic translocation, and consequent degradation. Recently, microRNAs (miRNAs) have been described as one of the mechanisms involved in FOXO3a regulation. MiRNAs are non-protein-coding RNA molecules that repress the translation and/or promote mRNA degradation. The 3′-UTR (3′-Untranslated region) of FOXO3a mRNA contains multiple target sequences for miRNAs. The regulation of FOXO3a by miR-155 has been documented in various cancer types, including breast and lymphoma. Additionally, FOXO3a expression is modulated by miR-132, miR-212, and miR-223.Lin and colleagues showed that, in human breast cancer, miR-96 repressing FOXO3a mRNA, leads to expression decreasing in FOXO3a targets (p27 and p21) and increasing of cyclin D1. FOXO3a can also be directly regulated by several other miRNAs in a direct and indirect way. Usually, FOXO3a loss of function determines deregulation in cell proliferation and DNA damage accumulation, resulting in tissue disorders and several cancer types development (including breast and prostate cancer, glioblastoma, rhabdomyosarcoma and leukemia). However, despite the relevance of FOXO proteins in several tumors, very little is known about its role, regulation or expression profile in Uterine Smooth Muscle Tumors (USMTs). These neoplasms can present a broad spectrum of clinical complications from pelvic pain to death. Among them, Leiomyomas (LM) are the most common benign tumor in reproductive-age women. Despite their indolent clinical behavior, these tumors can induce several troubles both for patients, due to symptoms, and for the government, due the hysterectomies cost by year. LMS, on the other hand, though rare, is the most common and aggressive USMT. These tumors show high mortality and morbidity rates, with poor response to chemotherapy and radiotherapy. Generally, LMS occurs in menopausal women, and metastasis and relapse are very common. As an intermediary entity, Unusual Leiomyomas (ULM) present features that have similarities with both LM and LMS, encompassing bizarre nuclei leiomyomas, symplastic and pleomorphic leiomyomas, mitotically active, cellular and highly cellular leiomyomas, epithelioid leiomyomas, myxoid leiomyomas, and others. They can represent a diagnosis challenge for pathologist concerning their differentiation from LMS. USMTs characterization by morphologic features and their biologic diversity may be complex mostly due to their wide spectrum of features. The exact origin of those tumors is unknown, and there are still controversies regarding the possibility of LMS arising from a degenerated pre-existing LM or their de novo development. The exploration of new markers might help tumors' differential diagnosis, patients’ prognosis, and treatment response prediction, beyond to contribute with potential new targets for specific therapy. Additionally, advances in the knowledge of these neoplasms' biology and behavior will benefit their better clinical management. Here, the authors found FOXO3a with differential gene expression profiles among USMT samples (LM, ULM and LMS), using an array-based gene expression screening analysis of 112 genes well described in the literature associated with several types of cancer. Based on the fact that FOXO3a is described in the literature as a tumor suppressor, the authors decided to assess its expression pattern and role in the USMT. The main focus was to evaluate whether FOXO3a expression profile and regulation could be useful for these tumors diagnosis, prognosis, and treatment prediction.
Sample selection and classification The authors collected and analyzed a total of 55 Leiomyosarcoma (LMS), 103 conventional Leiomyomas (LM), 16 Unusual Leiomyomas (ULM), and 20 Myometrium (MM) samples from frozen and Formalin-Fixed Paraffin-Embedded (FFPE) tissues. These samples were obtained through surgeries conducted between 2000 and 2015. The follow-up period for LMS patients was over thirty months, and relevant clinicopathological data were gathered for each tissue type. The FFPE tissues were sourced from Instituto Brasileiro de Controle do Cancer, Hospital Santa Marcelina, A C Camargo Cancer Center, and Disciplina de Ginecologia do Hospital das Clinicas da Faculdade de Medicina de Sao Paulo. The MM samples were collected from patients who underwent hysterectomies without cancer, inflammatory, or infectious diseases. The category “Unusual Leiomyoma” (ULM) encompassed tumors that did not fit the criteria for conventional leiomyomas. This included cellular or highly cellular, atypical, metastatic, and mitotically active leiomyomas, as well as STUMPs, forming an intermediate group for comparative analysis. Medical records of participants were examined, gathering information such as age, primary complaints, associated secondary diseases, surgical procedures, treatments, tumor recurrence, and metastasis. Tumor staging followed the FIGO-2009 guidelines, while histological grading was based on nuclear polymorphism and mitotic index. The study received ethical approval from the Research Ethics Committee of Faculdade de Medicina da Universidade de São Paulo-FMUSP and the Research Ethics Committee of Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo ‒ CAPpesq (Nos. 143/11 and 0845/11) and was conducted in accordance with the Helsinki Declaration. RNA extraction and qRT-PCR for gene and miRNAS expression analysis Total RNA was isolated from FFPE samples (5 MM, 5 LM, 8 ULM, and 37 LMS) following established protocols. Gene expression analysis focused on 112 genes spanning diverse biological pathways, with exclusive consideration of genes linked to FOXO3a regulation. For cDNA synthesis, High-Capacity kits (Applied Biosystems, USA) were utilized, employing 2 µg of total RNA. qRT-PCR reactions, executed in duplicate, utilized 1.2 µL cDNA and 3.8 µL TaqMan Gene Expression Master Mix (Applied Biosystems, USA), conducted on the QuantStudio 12K Flex Open Array Real-Time PCR System (Applied Biosystems, USA). Cycling conditions adhered to manufacturer recommendations. Housekeeping genes included ACTB, B2M, GAPDH, GUSB, HPRT1, and RPLP0. Data analysis employed expression suite software v1.0.3 employing the comparative Cτ (ΔΔCτ) method (Life Technologies, USA), using MM samples as references. For miRNA expression analysis, tissues were dissected to optimize tumor cell yield. Qiagen miRNeasy FFPE Kit facilitated total RNA extraction from tissues. For cDNA synthesis and relative miRNA quantification, Qiagen miScript II RT Kit, miScript SYBR Green PCR Kit, and miScript miRNA PCR Arrays were employed. Specific miRNA sequences were identified using the MIHS 102Z cancer-related development miRNA PCR Array (Qiagen, Hilden, Germany). Reactions and analyses followed established protocols. Immunohistochemistry (IHC) and protein expression quantification All cases were reviewed and selected based on the evaluations of two independent pathologists (IWC and FAS). Discordant cases were evaluated by another observer and retrieved for discussion and consensus. The TMA blocks, hematoxylin and eosin, and immunohistochemical analysis were performed as previously described. All IHC reactions for FOXO3a (1:100, pressure cooker, pH6.0, rabbit polyclonal antibody, Novus Biological Inc, USA), FOXO3a-Phospho Ser-253 (1:100, pressure cooker, pH6.0, rabbit polyclonal antibody, Arigobio, USA), EGF (1:50, pH6.0, mouse monoclonal antibody, pressure cooker + enzymatic digestion, DakoCytomation, USA), VEGF (1:100, pressure cooker, ph6.0, rabbit polyclonal antibody, Abcam) and HER-2 (1:2,000, pressure cooker, pH6.0, rabbit polyclonal antibody, A0485, DakoCytomation, USA) detection were standardized on conventional slides before the analysis was performed on the TMA. Negative controls were obtained by omitting the primary antibody or including nonreactive IgG. All IHC reactions were performed in duplicate. For visual evaluation, each spot was scored for staining intensity and the positive cell quantitation (frequency). To determine the protein immunostaining score, the authors used a design proposed elsewhere for nuclear and cytoplasmic protein staining. HER-2 protein evaluation was performed using the internationally recognized scoring system from the ASCO/CAP guideline. Fluorescent and colorimetric in situ hybridization (FISH and CISH) for HER-2 gene assessment Vysis LSI Dual Color HER-2/CEN17 (Abbott Laboratories, Abbott Park, IL, USA) was used for FISH analysis. All the pretreatment phase was performed in a semi-automated machine VP2000 Processor™ (Abbott). Reactions were performed as described previously. FISH slides were analyzed by observing the presence of green signals (for HER-2 gene) and red signals (chromosome 17). The same proportion of both green and red signals indicate no copy number alterations; proportion ≥2.5 (2;10) could be considered gene amplification. Slides were evaluated by pathologists using fluorescent microscopy. Automated SISH was performed on Ventana Benchmark XT (Ventana Medical Systems, Tucson, AZ, USA) using whole sample tissues´. Ultraview Inform HER-2 DNA probe and Inform Chromosome 17 centromere (cen17) probe were visualized on the same slide. Assay conditions were modified to obtain optimal results. The protocol (deparaffinization, pretreatment, hybridization, stringency wash, signal detection and counterstaining) was fully automated. HER-2 probe was denatured at 95°C for 20 min and hybridized at 52°C for 6h. The chromosome 17 centromere probe was denatured at 95°C for 20 min and hybridized at 44°C for 6h. Stringency washes were performed at 72°C for 8 min. The silver signal for HER2 was revealed by sequential silver reactions. The signal of the centromere was visualized with the RedISH Naphtol reaction. The tissues were counterstained with Hematoxylin II and Bluing Reagent. Western blot assays for antibody specificity assessment Breast cancer (MCF7, ATCC) cells were used for antibody specificity analysis by western blot. Cell lines were grown in a specific medium indicated by ATCC, supplemented with 10% fetal bovine serum and 0.1% penicillin-streptomycin. After the removal of the supernatant, the cells were washed and scraped into Phosphate-Buffered Saline (PBS 1X). The total protein extract from all samples was obtained with RIPA buffer (50 mM Tris–HCl Ph 8.0, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS). Protein concentration was determined using a Brad-ford assay and 20‒30 μg of protein were separated using 10% SDS-polyacrylamide gels. After protein transference to nitrocellulose or PVDF membranes (Thermo Fisher Scientific, Waltham, MA, USA), monoclonal antibodies against FOXO3a total e ‒phospho (1:1000), in PBS-Tween (0,001%) containing 5% non-fat milk, was added to the membrane at 4°C overnight. Actin-b was included as a positive control of the protein detection in all the experiments. Statistical analysis Fisher's exact test was used to evaluate associations between protein expression and clinicopathological parameters. Overall and disease-free survival rates were calculated using the Kaplan-Meier method based on a follow-up of 5 years for all ULM and LMS patients included in this study. The odds ratio was calculated using the log-rank test. Hazard Ratio (HR) and their 95% (95% IC) interval of confidence were calculated using the regression model of Cox. All calculations were performed using GraphPad Prism 5.0 statistical software (San Diego, CA, USA) and SPSS v.25 for Windows (SPSS Inc. Chicago. IL, USA). Statistical significance was accepted for p-values ≤0.05.
The authors collected and analyzed a total of 55 Leiomyosarcoma (LMS), 103 conventional Leiomyomas (LM), 16 Unusual Leiomyomas (ULM), and 20 Myometrium (MM) samples from frozen and Formalin-Fixed Paraffin-Embedded (FFPE) tissues. These samples were obtained through surgeries conducted between 2000 and 2015. The follow-up period for LMS patients was over thirty months, and relevant clinicopathological data were gathered for each tissue type. The FFPE tissues were sourced from Instituto Brasileiro de Controle do Cancer, Hospital Santa Marcelina, A C Camargo Cancer Center, and Disciplina de Ginecologia do Hospital das Clinicas da Faculdade de Medicina de Sao Paulo. The MM samples were collected from patients who underwent hysterectomies without cancer, inflammatory, or infectious diseases. The category “Unusual Leiomyoma” (ULM) encompassed tumors that did not fit the criteria for conventional leiomyomas. This included cellular or highly cellular, atypical, metastatic, and mitotically active leiomyomas, as well as STUMPs, forming an intermediate group for comparative analysis. Medical records of participants were examined, gathering information such as age, primary complaints, associated secondary diseases, surgical procedures, treatments, tumor recurrence, and metastasis. Tumor staging followed the FIGO-2009 guidelines, while histological grading was based on nuclear polymorphism and mitotic index. The study received ethical approval from the Research Ethics Committee of Faculdade de Medicina da Universidade de São Paulo-FMUSP and the Research Ethics Committee of Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo ‒ CAPpesq (Nos. 143/11 and 0845/11) and was conducted in accordance with the Helsinki Declaration.
Total RNA was isolated from FFPE samples (5 MM, 5 LM, 8 ULM, and 37 LMS) following established protocols. Gene expression analysis focused on 112 genes spanning diverse biological pathways, with exclusive consideration of genes linked to FOXO3a regulation. For cDNA synthesis, High-Capacity kits (Applied Biosystems, USA) were utilized, employing 2 µg of total RNA. qRT-PCR reactions, executed in duplicate, utilized 1.2 µL cDNA and 3.8 µL TaqMan Gene Expression Master Mix (Applied Biosystems, USA), conducted on the QuantStudio 12K Flex Open Array Real-Time PCR System (Applied Biosystems, USA). Cycling conditions adhered to manufacturer recommendations. Housekeeping genes included ACTB, B2M, GAPDH, GUSB, HPRT1, and RPLP0. Data analysis employed expression suite software v1.0.3 employing the comparative Cτ (ΔΔCτ) method (Life Technologies, USA), using MM samples as references. For miRNA expression analysis, tissues were dissected to optimize tumor cell yield. Qiagen miRNeasy FFPE Kit facilitated total RNA extraction from tissues. For cDNA synthesis and relative miRNA quantification, Qiagen miScript II RT Kit, miScript SYBR Green PCR Kit, and miScript miRNA PCR Arrays were employed. Specific miRNA sequences were identified using the MIHS 102Z cancer-related development miRNA PCR Array (Qiagen, Hilden, Germany). Reactions and analyses followed established protocols.
All cases were reviewed and selected based on the evaluations of two independent pathologists (IWC and FAS). Discordant cases were evaluated by another observer and retrieved for discussion and consensus. The TMA blocks, hematoxylin and eosin, and immunohistochemical analysis were performed as previously described. All IHC reactions for FOXO3a (1:100, pressure cooker, pH6.0, rabbit polyclonal antibody, Novus Biological Inc, USA), FOXO3a-Phospho Ser-253 (1:100, pressure cooker, pH6.0, rabbit polyclonal antibody, Arigobio, USA), EGF (1:50, pH6.0, mouse monoclonal antibody, pressure cooker + enzymatic digestion, DakoCytomation, USA), VEGF (1:100, pressure cooker, ph6.0, rabbit polyclonal antibody, Abcam) and HER-2 (1:2,000, pressure cooker, pH6.0, rabbit polyclonal antibody, A0485, DakoCytomation, USA) detection were standardized on conventional slides before the analysis was performed on the TMA. Negative controls were obtained by omitting the primary antibody or including nonreactive IgG. All IHC reactions were performed in duplicate. For visual evaluation, each spot was scored for staining intensity and the positive cell quantitation (frequency). To determine the protein immunostaining score, the authors used a design proposed elsewhere for nuclear and cytoplasmic protein staining. HER-2 protein evaluation was performed using the internationally recognized scoring system from the ASCO/CAP guideline.
Vysis LSI Dual Color HER-2/CEN17 (Abbott Laboratories, Abbott Park, IL, USA) was used for FISH analysis. All the pretreatment phase was performed in a semi-automated machine VP2000 Processor™ (Abbott). Reactions were performed as described previously. FISH slides were analyzed by observing the presence of green signals (for HER-2 gene) and red signals (chromosome 17). The same proportion of both green and red signals indicate no copy number alterations; proportion ≥2.5 (2;10) could be considered gene amplification. Slides were evaluated by pathologists using fluorescent microscopy. Automated SISH was performed on Ventana Benchmark XT (Ventana Medical Systems, Tucson, AZ, USA) using whole sample tissues´. Ultraview Inform HER-2 DNA probe and Inform Chromosome 17 centromere (cen17) probe were visualized on the same slide. Assay conditions were modified to obtain optimal results. The protocol (deparaffinization, pretreatment, hybridization, stringency wash, signal detection and counterstaining) was fully automated. HER-2 probe was denatured at 95°C for 20 min and hybridized at 52°C for 6h. The chromosome 17 centromere probe was denatured at 95°C for 20 min and hybridized at 44°C for 6h. Stringency washes were performed at 72°C for 8 min. The silver signal for HER2 was revealed by sequential silver reactions. The signal of the centromere was visualized with the RedISH Naphtol reaction. The tissues were counterstained with Hematoxylin II and Bluing Reagent.
Breast cancer (MCF7, ATCC) cells were used for antibody specificity analysis by western blot. Cell lines were grown in a specific medium indicated by ATCC, supplemented with 10% fetal bovine serum and 0.1% penicillin-streptomycin. After the removal of the supernatant, the cells were washed and scraped into Phosphate-Buffered Saline (PBS 1X). The total protein extract from all samples was obtained with RIPA buffer (50 mM Tris–HCl Ph 8.0, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS). Protein concentration was determined using a Brad-ford assay and 20‒30 μg of protein were separated using 10% SDS-polyacrylamide gels. After protein transference to nitrocellulose or PVDF membranes (Thermo Fisher Scientific, Waltham, MA, USA), monoclonal antibodies against FOXO3a total e ‒phospho (1:1000), in PBS-Tween (0,001%) containing 5% non-fat milk, was added to the membrane at 4°C overnight. Actin-b was included as a positive control of the protein detection in all the experiments.
Fisher's exact test was used to evaluate associations between protein expression and clinicopathological parameters. Overall and disease-free survival rates were calculated using the Kaplan-Meier method based on a follow-up of 5 years for all ULM and LMS patients included in this study. The odds ratio was calculated using the log-rank test. Hazard Ratio (HR) and their 95% (95% IC) interval of confidence were calculated using the regression model of Cox. All calculations were performed using GraphPad Prism 5.0 statistical software (San Diego, CA, USA) and SPSS v.25 for Windows (SPSS Inc. Chicago. IL, USA). Statistical significance was accepted for p-values ≤0.05.
The average age of Leiomyoma (LM), Unusual Leiomyoma (ULM), and Leiomyosarcoma (LMS) patients was 44 ± 7.0, 43 ± 9.0, and 55.4 ± 15.2 years old, respectively. Among LM patients, 59% were Caucasian, while 44% of ULM patients were Caucasian. In the LMS group, 59% were Caucasian, 13% were non-Caucasian, and 5% were Asian. Menopausal status was reported as 0%, 6%, and 46% in LM, ULM, and LMS cases, respectively. Recurrence was observed in 18% of ULM patients, whereas LMS had a recurrent/relapsed rate of 81.8%. Among LMS patients, 76.4% presented a high-grade lesion, with the primary symptom being vaginal bleeding (43.6%). It is noteworthy that 25.5% of LMS patients did not use contraceptives, 27.3% underwent replacement therapy, and 25.5% were multiparous. Forty percent of these women did not perform treatment, 29.1% were submitted to chemotherapy, and 20% performed radiotherapy. All additional clinical and pathological data from LMS and LM patients are presented in and Supplementary Table 1, respectively. Samples underwent dual pathology review, with representative Hematoxylin-Eosin photomicrographs in Figure S1. An initial gene expression screening encompassing 112 literature-linked genes from pivotal cellular signaling pathways related to diverse cancer types was conducted (Supplementary Table 2). qRT-PCR highlighted FOXO3a and 11 pathway-related genes exhibiting substantial differential expression in USMT samples ( A). FOXO3a expression was notably elevated, approximately 30-fold (RQ) in LMS samples and 18-fold in ULM, compared to LM and MM samples. GSK3α, GSK3β, CCND1, and CTNNB1 also displayed elevated expression in ULM (RQ = 2.89, 3.23, 7.17, and 2.01, respectively) and LMS (RQ = 5.11, 4.42, 2.08, and 2.72, respectively). ULM samples exhibited increased expression of CCND2, MAPK1 (ERK1), MAPK8 (JNK1), and PTEN ( A). FOXO3a overexpression was corroborated at protein levels via Immunohistochemical (IHC) analysis across patients' samples on Tissue Microarray (TMA) slides. Both nuclear and phosphorylated (Ser253) cytoplasmic forms of FOXO3a were assessed ( B‒D). For nuclear FOXO3a expression (wild-type protein), over 80% of LMS samples exhibited positive protein expression, while ULM showed 36.4% strong/weak expression and 27% moderate staining. LM samples had 25% strong and 31% moderate expression. Comparatively, ULM and LMS had higher protein expression scores, with statistical disparities between LMS and both LM and MM ( B). Similarly, phosphorylated (Ser253) FOXO3a (cytoplasmic) was elevated in ULM and LMS, contrasting with MM and LM samples ( C). ULM demonstrated the highest protein levels. D shows the staining pattern observed for nuclear cytoplasmic forms of the FOXO3a protein. Forty-eight (out of 56) samples of LMS were evaluated for nuclear FOXO3a and 47 were assessed for its phosphorylated form. The protein levels were considered negative when the Hscore values were < 3 and positive for Hscore >3. No significant correlation was observed between patients clinical and pathological features and nuclear protein expression (p > 0.05), but metastasis occurrence (p = 0.035) was associated with cytoplasmic FOXO3a expression . A marginal significance was found for relapse (p = 0.078) and metastasis site (p = 0.061) with phosphorylated protein expression in LMS samples . Overall Survival (OS) and Disease-Free Survival (DFS) were analyzed considering the time between the diagnosis and decease, or the last information (relapse, recurrence, and metastasis). Follow-up time was established as 60 months and live patients (for OS) or misses of view (both to OS and DFS) were included in the censored group. A presents the OS curve observed for all the LMS patients. FOXO3a strong protein expression (weakly, moderate and strong staining), was associated with higher OS time ( B). The authors also evaluated positive or negative categories of protein the expression, considering its cell location separately (nuclear or cytoplasmic) and, although a more precocious curve of death was obtained for patients with negative nuclear FOXO3a expression, no significant differences were found ( C and D). The Hazard Ratio (HR) values were assessed using the regression model of Cox to analyze the prognosis value of FOXO3a expression . The global group survival probability is presented according to the features. Adjuvant therapy (p = 0.015), disease staging (p = 0.021), and relapse (p = 0.008) showed significant association with overall survival in LMS patients. Metastasis occurrence and age showed marginal values of significance concerning overall survival (p = 0.074 and 0.071, respectively), and five years survival was 15.5% . Although no statistical significance was observed, a higher percentage of deaths occurred in patients with negative FOXO3a nuclear expression. Subsequent analyses encompassed the assessment of HER-2 and EGFR membrane receptor expression to investigate the potential involvement of the EGF pathway in FOXO3a deregulation . However, no positive staining was observed for both receptors in the samples. Given the frequent association of negative HER-2 expression with gene alterations, FISH (on TMA slides) and CISH (on whole LMS tissues) were conducted to evaluate the gene status. A illustrates the reaction profiles for HER-2 detection using IHC, FISH, and CISH. Neither FISH nor CISH reactions showed chromosomal alterations in the HER-2 gene. Additionally, the authors examined EGF and VEGF as ligands in the pathway potentially responsible for FOXO3a phosphorylation and subsequent inactivation. EGF exhibited both cytoplasmic and nuclear expression, while VEGF was exclusively observed in the cytoplasmic compartment ( B and C). Immunohistochemistry revealed lower levels of these proteins; however, considering only positive samples, higher cytoplasmic EGF expression was observed in ULM compared to LMS and LM ( C). Nuclear EGF expression was lower in LMS samples ( B and C). VEGF expression was similar in ULM and LMS samples, with notably lower values (below the cutoff = 3) and negative expression in LM samples ( C). Due to the limited number of positive samples, statistical analysis could not be conducted. Another significant regulatory mechanism considered in gene expression is miRNAs. These molecules are known to control HER-2, growth factors, and FOXO3a expression. Evaluating their profiles could aid in understanding the gene and protein expression results for USMT samples. The authors assessed 84 miRNAs implicated in the development of several types of cancer and potentially involved in those three genes regulation . The authors used MM samples as a reference for miRNA expression in normal uterine tissue due to its mesenchymal nature and similar location and biological changes to benign (LM and ULM) and malignant mesenchymal tumors (LMS). Initial miRNA expression analysis focused on comparing tumor samples to normal tissue ( A). Between MM and LM samples, 21 miRNAs showed differential expression (14 upregulated and 7 downregulated in LM). For MM vs. ULM, 31 miRNAs were upregulated and 9 downregulated in tumors. The MM vs. LMS comparison revealed 50 miRNAs with distinct expression (21 upregulated and 29 downregulated in LMS). Specifically considering miRNA regulators of HER-2, VEGF, EGF, and FOXO3a from literature and the arrays, 15 sequences displayed differential expression, linked with FOXO3a/VEGF/HER-2 deregulation. The clustergram ( B) displays expression values across samples for each tissue type, utilizing a color scale. Tumors, particularly LMS, displayed notably different profiles from normal tissue (reference group ‒ MM). Among FOXO3a regulators, six miRNAs were identified (miR-96-5p, miR-222-3p, miR-132-3p, let7c-5p, miR-155-5p, and miR-25-3p). For HER-2, absent in 100% of samples without deletion/loss of the encoding gene, four regulatory miRNAs (miR-125b-5p, miR-21-5p, miR-125a-5p, and miR-205-5p) showed differential expression. Concerning VEGF regulatory miRNAs, five exhibited distinct regulation in the present study's samples (miR-134-5p, miR-373-3p, miR-29b-3p, miR-150-5p, and miR-126-3p). No differentially expressed miRNA involved in EGF regulation was found in the array-based analysis. The expression of the six miRNAs identified as FOXO3a regulators (miR-96-5p, miR-222-3p, miR-132-3p, let7c-5p, miR-155-5p, and miR-25-3p) was validated using a more sensitive and specific qRT-PCR detection method (Taqman® probes and primers, Thermo Fisher Scientific). C displays miRNA-96-5p and miR-155-5p as the most expressed in LMS samples, followed by miR-25-3p and miR-132-3p, with let-7c-5p having the lowest expression. miR-155-5p appears to be a significant miRNA regulator of FOXO3a, as the authors found four binding sites described for this miRNA in the gene sequence ( D). Moreover, an in-silico assessment of FOXO3a gene interactions with its associated miRNAs and genes elucidated pertinent signaling pathways linked to FOXO3a expression. miRTARBase exclusively incorporated validated outcomes for FOXO3a and regulatory miRNAs, substantiated via gene reporter assays, western blots, and qRT-PCR. Each miRNA exhibited potential to modulate numerous genes, some of which significantly influence FOXO3a regulation or might be impacted by its expression . The robust green connections directly tied to FOXO3a signify miRNAs wielding substantial influence (miR-96, 155, and 222) on gene regulation. While in silico analysis didn't unveil a direct robust correlation between let7c-5p and FOXO3a, a negative correlation surfaced in their expression across IHQ (-0.002887213) and qRT-PCR (-0.00752953) assays in LMS samples (data not shown). Furthermore, supplementary network analysis spotlighted multiple genes ensconced within pivotal biological pathways entwined with tumor development, cell migration, invasion, metastasis, and patient prognosis. comprehensively illustrates all genes co-expressed with FOXO3a in gynecological tumors as substantiated by literature. The biological functions of these genes ( A) and their delineated biological process pathways (blue lines) pertinent to gynecological tumors ( B) are also delineated.
As a heterogeneous group of tumors, USMT ranges from benign to aggressive malignant tumors (LM and LMS, respectively). , , Here, the authors included LM, LMS, and Unconventional Leiomyoma (ULM) in the present analyses, focusing on their morphological and clinical features. The goal was to compare these tumors' gene expression profiles and to identify potential new markers for their differential diagnosis, prognostic, and treatment prediction. Initially, the clinical and pathological data of the patients were evaluated. The average age of LMS women was 55.4 years old, corroborating the literature[12] as well as observed for LM and LMU. The treatment of choice for LMS patients was hysterectomy (98%), which is considered the gold standard treatment for all uterine sarcomas. Occurrence of metastasis was observed in 59% of the cases, the lungs being the main affected site. The high tendency of recurrence and distant metastasis has already been well documented for this kind of tumor. Overall Survival (OS) at two years is generally less than 50%, with hematogenous metastasis, mainly to the lungs. The present results showed lower than 30% of OS after 30 months of initial diagnosis, and DFS of 0% at this same time. These data corroborate the higher rates of recurrence and aggressiveness of LMS described in the literature. As expected, OS was lower in patients with relapse and metastasis occurrence as well as lung metastatic disease. The mean follow-up of the patients was 36 months. The molecular study of the events involved in the development of different types of cancer has led to new strategies used in their diagnosis and treatment. The origin of the USMT is still not well understood alike there are still not effective and specific therapies for these tumors. Molecularly, uterine Leiomyoma (LM) presents important genetic dysfunctions such as alterations in RAD51, BRCA1, MED12 and HMGA2, genes related to DNA repair and cell growth. This tumor presents biological and morphological characteristics like uterine Leiomyosarcomas (LMS), making it difficult to establish a differential diagnosis. LMS, in turn, shows molecular alterations in genes responsible for several functions such as p51, p16, and BCL-2, responsible for regulating the cell cycle, growth and apoptosis, in addition to the downregulation of tumor suppressors’ genes such as RB1, DCC, NM23, WT1, D14S267, P16 and PTCH. The studied group has performed several molecular analyses in USMT patients and samples. The present study was started after qRT-PCR data showed FOXO3a with significant differential levels of expression among USMT samples. Initially, an array-based method showed FOXO3a with an increasing expression profile in LM, ULM and LMS, compared to normal Myometrium (MM). Gene expression data was validated by IHC analyses both to wild-type protein as well as to the phosphorylated one. The loss of FOXO3a expression has been associated with poor prognosis in several types of cancer. In ovarian cancer, the loss of FOXO3a function may limit the sensitivity of cancerous cells to chemotherapy. Some chemotherapeutic drugs, currently used in the treatment of breast cancer and in acute myeloid leukemia can activate FOXO3a by reducing AKT activity. According to Yang and Hung, the antitumor activity of FOXO3a can sensitize resistant tumor cells to radiotherapy through combined treatment of radiation with chemotherapy. A comparison of FOXO3a expression between MM and tumors pointed out that most samples of MM showed weak or no protein expression. These results suggest that, for mesenchymal tissues, an increment in FOXO3a expression might indicate the malignant potential of these tumors. The fact that a predicted tumor suppressor marker exhibits a higher expression in ULM and LMS caught the authors’ attention. In this sense, the authors found research showing that, in addition to its function as a tumor suppressor, nuclear FOXO3 can also promote tumor cell survival. In Chronic Myeloid Leukemia (CML), the inhibition or blockade of TGFβ-FOXO3a led to a significant reduction in the leukemia-initiating cell population. The authors showed that a combination of TGF-β inhibition, FOXO3a deficiency, and Imatinib treatment induces efficient depletion of CML in vivo . Another work showed a new mechanism contributing to multidrug resistance involving FOXO3a as a sensor for cytotoxic stress induced by anticancer therapies. It was observed that the sustained activation of FOXO3a promotes cell resistance and survival via activation of ABCB1 expression. In fibroblasts, similar to breast cancer cells, FOXO3a inhibited HIF1-induced apoptosis via CITED2, resulting in reduced expression of NAP1 and RTP801 (pro-apoptotic). Thus, FOXO3a plays an important role in the survival response of normal and cancer cells in response to hypoxic stress. In glioblastomas, it was observed that upregulation of FOXO3a is associated with tumor progression and worse prognosis for the patients. The authors proposed that FOXO3a may represent a new biomarker for prognosis or a potential therapeutic target in glioblastoma. Based on all this information, the authors attempted to understand the role and regulation of FOXO3a expression in the USMT. When the PI3K pathway is activated in response to growth factors, inhibition of FOXO3a activity occurs, preventing its translocation to the cell nucleus. Generally, FOXO3a loss of function occurs after its phosphorylation and consequent degradation. Several studies have shown the relevance of the HER-2/FOXO3a signaling pathway since these markers are associated with growth, proliferation, and cell survival. According to previous literature, overexpression of HER-2 due to gene amplification occurs in breast cancer, ovarian tumors, lung, colon, stomach, esophagus, endometrium, and cervix. In this series, no positive HER2 expression was found by immunohistochemistry. FISH (TMA samples) and SISH (whole tumor) analysis were performed to assess if this protein lack was a consequence of gene deletion, but no alteration was observed. These results were not surprising because Layfield and colleagues had studied HER-2 protein expression in the LMS and found only 20% of positive cases (4 out of 20 samples). Amant et al. demonstrated the absence of expression in uterine LMS, AS and SEE. The authors were not able to detect EGFR1 expression in those samples too. In parallel, tumor samples were evaluated for two growth factors protein expression (EGF and VEGF – as ligand and signaling initiators). Among the main growth factors involved in the development of cancer which represent important therapeutic targets, are the Epidermal Growth Factor (EGF) and the Vascular Endothelial Growth Factor (VEGF). EGF acts on several cell types, including epithelial and non-epithelial cells. Here, cytoplasmic and nuclear EGF expression was observed, with a predominance of protein in the cytoplasm of malignant tumors. ULM sample showed a higher amount of the cytoplasmic protein expression followed by LMS, but no statistical significance was observed. Concerning nuclear expression of the EGF, apparently, the cell nucleus would be a second site of action of EGF and its receptor, and that location would be linked to the regulation of cell proliferation. Nuclear expression was found in LM samples, followed by ULM. The biological actions of EGF are mediated through its binding to its receptor and once activated, the receptors trigger the recruitment and phosphorylation of various intracellular substrates, leading to mitogenic signaling and other cellular activities. Moreover, VEGF pathway is well described as playing a role in tumoral angiogenesis and several therapeutic or neutralizing antibodies for the protein or its receptor have been documented. The present samples showed lower expression of VEGF with score values below the cut-off with detected protein only in ULM and LMS samples. Although a relevant role of IGF in the FOXO3a inactivation had been described, the authors did not perform this analysis, but a preliminary study from the group found that IGFR and ISR1 genes are upregulated in the LMS cell line. To assess the prognostic role of FOXO3a expression, the clinical and pathological data of the LMS patients were evaluated in function of the wild type and phosphorylated form of the protein expression scores. Only metastasis occurrence showed significant association with phosphorylated protein expression. Relapse occurrence and distant metastasis were more frequent in those patients too, but without statistical significance (p>0.05). FOXO3a expression was associated with higher DFS in LMS patients, with no significant differences in OS. Yu and collaborators observed that patients with gastric cancer, showing a lack of FOXO3a expression, presented significantly lower OS than those patients with higher protein amounts. However, patients with increased FOXO3a expression, in the normal tissue cell nucleus adjacent to the tumor, had significantly lower OS than other patients. No significant differences were observed comparing the OS of patients with FOXO3a wild type or phosphorylated form. The authors hypothesize that the absence of statistical significance in the prognosis analyses was due to both the higher number of LMS positive samples, and because the overall and DFS are always lower in these patients too. Regarding miRNA expression findings, it was observed that many of them presented high values of fold regulation, considering the overexpression or down expression values of ±2. Since all the miRNAs included in the plates had been previously described as being involved in carcinogenesis, their expression was expected to be lower in normal and in benign tissue. Among the six miRNAs (miR-96-5p, miR-222-3p, miR-132-3p, let7c-5p, miR-155-5p, and miR-25-3p) found with differential expression in the LMS samples, and that were described in the literature as FOXO3a regulators, miR-96-5p was the highest expressed one, followed by miR-155-5p. MiR-96-5p was found overexpressed both in tumors and serum from patients with ovarian cancer, which is a relevant hormone-dependent gynecologic cancer. In breastcancer cells and tissues, miR-96 was described as upregulated compared with the normal ones. This upregulation resulted in modulation of the cells' entry into the G1/S phase, as a consequence of the Cyclin-Dependent Kinase (CDK) inhibitors, p27 and p21 downregulation, and cyclin D1 upregulation. The authors demonstrated that miR-96 downregulates FOXO3a expression by targeting directly its 3′-untranslated region. In colorectal cancer, miR-96 seems to contribute to cell growth, and target directly TP53INP1, FOXO1 and FOXO3a53. These results indicate its potential to be used in miRNA-based therapies for patients. Concerning miR-155, Li and colleagues showed that its deficiency decreases vascular calcification due to increased Akt phosphorylation and FOXO3a degradation. Other study confirmed that miR-155 drives the angiogenesis in gastric cancer, enhancing the generation of new vessels in vitro through FOXO3a protein inhibition. The authors pointed to miR-155 as a potential biomarker for the detection of migration and angiogenesis in gastric cancer cells, suggesting that it could acts as a novel target for anti-angiogenesis therapy. Overall, the present results, together with currently available data, show FOXO transcription factors as molecules that may present flexible action. They can have a suppressor or oncogenic role according to the timing of the cells and tissues. Additionally, FOXOs suppression in cancer cells is thought a consequence of multiple onco-kinase activation by a phosphorylation-ubiquitylation-mediated cascade. Therefore, several evidence show that inhibition of FOXO proteins would naturally occur due to a multifactorial post-translational process, as the authors hypothesize that occurs in USMT patients . To the best of our knowledge, this study is the first evidence of the FOXO3a expression in USMT. The results suggest the FOXO3a impairment is associated with these tumors' malignancy risk. These findings will contribute significantly to the biological knowledge of the USMT and, in the future, FOXO3a might become a potential prognostic marker to these patients. Beyond that, these molecules may represent potential therapeutic targets for individualized treatments for LMS patients. It is known that LMS precise diagnosis is only possible after surgery, so, the majority of the studies include a small number of samples. Here, the authors believe that this sample set has a size enough to make the present data robust. On the other side, the inclusion of some older specimens may limit the evaluation of some clinical data; but that does not invalidate the contribution of these findings to the knowledge of tumor biology.
T.G.A performed all patients’ data and samples collection and performed the growth factors analysis. A.R.R performed the IHQ reactions and analysis for FOXO3a nuclear and cytoplasmic expression, and statistical analysis. L.G.A. performed miRNA analysis and manuscript review. G.A.R.M. and E.C.B contributed with intellectual support and manuscript review. K.C.C. idea conception, data analysis and manuscript preparation. All authors have read and agreed to the published version of the manuscript.
This work was supported by the FAPESP grant – 2012/23652-0.
The authors declare no conflict of interest and funding disclosures.
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Population Pharmacokinetics of Ponatinib in Healthy Adult Volunteers and Patients With Hematologic Malignancies and Model‐Informed Dose Selection for Pediatric Development | 30729a70-441f-4f2e-bdc5-54b2c3c2441e | 9300170 | Pediatrics[mh] | Data Collection The protocols of all 7 studies included in this population PK analysis were approved by the appropriate local institutional review boards (IRBs) or independent ethics committees. Studies AP24534‐11‐102, AP24534‐11‐103, AP24534‐12‐107, and AP24534‐12‐108 were approved by Institutional Review Board Services Ontario. , , , The Japanese phase 1/2 study (AP24534‐11‐106, NCT01667133) was approved by IRBs or independent ethics committees of the 9 participating centers in Japan. The phase 1 study (AP24534‐07‐101, NCT00660920) was approved by the IRB at each of the 5 study centers. The phase 3 EPIC (Evaluation of Ponatinib Versus Imatinib in Chronic Myeloid Leukemia) study (AP24534‐12‐301, NCT01650805) was approved by the IRBs or independent ethics committees of the 106 study sites enrolling patients. All participants provided written informed consent. Ponatinib plasma concentration–time data were collected from adult healthy volunteers and patients with hematologic malignancies who had participated in 1 of 7 clinical trials. , , , , , , Participant eligibility criteria for each study are described in the original publications. Table provides a summary of the studies included in the population PK analysis. For the food‐effect study in healthy volunteers, only data collected under fasted conditions were included in the population PK analysis. For the drug‐drug interaction studies in healthy volunteers, , , ponatinib data collected in the presence of the coadministered drug (ie, ketoconazole, rifampin, or lansoprazole) were excluded from the population PK analysis. All study procedures were performed in accordance with the International Council for Harmonisation Good Clinical Practice guidelines and appropriate regulatory requirements. Plasma concentrations of ponatinib were measured using 2 validated liquid chromatography–tandem mass spectrometry assays. , , , Population PK Modeling The population PK analysis was performed using NONMEM (version 7.3; ICON Development Solutions, Hanover, Maryland ) for nonlinear mixed‐effects models, running under Perl‐speaks‐NONMEM (version 4.6) on a grid of CentOS 7.1 Linux servers and the Fortran compiler (version 12.0.4; Intel, Santa Clara, California). Analysis of results and simulations was performed using R (version 3.4.3; R Foundation for Statistical Computing, Vienna, Austria ). For development of the base population PK model, fixed‐effect model parameters (θ), variances of the interindividual variability (ω 2 ), and residual error (σ 2 ) were estimated. Interindividual variability was implemented by exponential random‐effect models, corresponding to log‐normally distributed individual parameters, and was defined as: (1) θ i = θ TV , i · exp ( η i ) where θ i and θ TV are individual and typical values of the parameter (eg, apparent oral clearance [CL/F]). η i is an individual‐level random variable sampled from a normal distribution with a mean of 0 and variance of ω 2 , and it represents the i th individual's deviation from the typical value. Initially, random effects were assumed to be independent; however, random‐effect models defined by a nondiagonal variance‐covariance matrix (Ω) were preferred if they resulted in meaningful improvements in model fit. Models describing untransformed data, as well as data that were log‐transformed on both sides, were evaluated during model development. In models applying the log‐transformed on both sides approach, the residual unexplained variability was described by an additive (on the log‐scale) error model that was parameterized as: (2) log ( Y ik ) = log ( C ik ) + ε ik where Y ik was the k th observed concentration in the i th individual, C ik was the corresponding individual model‐predicted concentration, and ε ik was the residual error sampled from a normal distribution with a mean of 0 and variance of σ 2 . Alternative residual error models with >1 ε were considered with a covariance matrix Σ to define the variances and covariances of the ε's. Initially, the ε's were assumed to be uncorrelated. Nondiagonal Σ was estimated to evaluate if the data supported estimation of correlations between ε's. Appropriate transformations of parameters were considered to appropriately constrain parameter values. For example, log transformation of CL/F was considered to constrain the estimate to positive values. Similarly, logit transformations were considered for parameters describing the fraction of a dose to constrain the estimate to between 0 and 1. Shrinkage of interindividual random effects ( η ) was evaluated for diagnostic purposes. The shrinkage for a structural parameter s h θ ( η shrinkage) was calculated as : (3) s h θ = 1 − S D η E B E , θ ω θ where S D ( η E B E , θ ) is the standard deviation of the individual η for θ , and ω θ is the model estimate of the SD associated with θ. Covariate Model Development Continuous covariates (age, body weight, albumin, alanine aminotransferase [ALT], total bilirubin, and creatinine clearance [CrCL]) and categorical covariates (race, patient or healthy volunteer status, and sex) were tested in the development of the covariate model (Table ). Continuous covariates were included in the model as power functions, while binary covariates were implemented as factors: (4) θ T V , i = θ T V , P o p · x C o n t , i m e d i a n ( x C o n t , i ) θ 1 · 1 + x C a t , i · θ 2 In this equation, the parameter θ TV,i for the i th subject is defined as a function of the population typical value, θ TV,Pop , and the individual contributions from continuous ( x Cont,i ) and binary ( x Cat,i with values 0 and 1) covariates. θ 1 and θ 2 represent the respective covariate coefficients. A stepwise covariate modeling strategy (single addition, forward inclusion, and backward elimination) was performed. Model selection was based on the likelihood ratio test. During the forward inclusion step, statistical significance of a covariate effect was evaluated using the chi‐square test for P < .01. Covariates that were statistically significant were retained in the model. In the backward elimination phase, statistical significance of covariate effects was evaluated using the chi‐square test for P < .001. Significant covariates were retained, and covariates whose removal did not lead to a significant worsening of the objective function value (OFV) were iteratively dropped until no such nonsignificant covariates ( P > .001) remained in the model. Finally, covariate effects that were imprecisely estimated (% relative standard error [%RSE] >50%; that is, the 95% confidence interval included 0) were considered for exclusion from the covariate model. Model Evaluation and Qualification Nested models were compared using the likelihood ratio test. Structural and residual error model discrimination were based on standard model diagnostics, such as a decrease in the OFV, precision and accuracy of parameter estimation (%RSE), condition number, successful model convergence and covariance step, and examination of goodness‐of‐fit plots and prediction‐corrected visual predictive checks (VPCs). In the VPCs, percentiles (median, 5th, and 95th percentiles) of observed data were superimposed on those of the individual model‐predicted ponatinib concentration‐time profiles, based on 250 simulated replicates of the analysis data set. Model robustness and parameter estimates were assessed by bootstrap based on 1000 resampled data sets with replacement up to the total number of patients in the original data set. Simulations The final population PK model was used to perform simulations for patients treated with daily ponatinib doses of 15, 30, and 45 mg. Individual plasma concentration–time profiles of ponatinib were simulated for the typical patient and 1000 virtual patients to describe ponatinib plasma concentrations with each once‐daily dosing regimen, relative to reference concentrations of 10.7 ng/mL (20 nM) and 21.3 ng/mL (40 nM), which have been previously demonstrated to suppress most BCR‐ABL1 mutants and T315I BCR‐ABL1 mutants, respectively, in cell‐based mutagenesis assays. For the typical patient, random effects were set to zero, and covariate values were set to the median value in the analysis data set. For virtual patients, random effects were sampled from the random effects variance–covariate matrix and covariates were sampled from distributions designed to reflect values reported in the data set. The 5th and 95th percentiles of the concentration‐time profiles were derived from the profiles of the 1000 virtual patients. The AUC, C max , trough concentration, and average concentration (C average ) were derived for each simulated patient and summarized. Model‐Informed Dose Selection for Pediatric Development A primary objective of the pediatric program for ponatinib is to evaluate its safety and efficacy in combination with multiagent chemotherapy for the treatment of pediatric patients ≥1 year of age with Ph+ ALL. A 30‐mg dose is being evaluated in combination with chemotherapy in adult patients with Ph+ ALL (ClinicalTrials.gov Identifier: NCT03589326). Accordingly, a model‐informed approach was used to establish pediatric posology to approximately match adult exposures at 30 mg for the design of a pediatric study (ClinicalTrials.gov Identifier: NCT04501614). For the purpose of predicting pediatric doses that would match adult exposures at ponatinib 30 mg once daily, the developed model was adapted by removing the previously estimated adult covariate effects and including allometric scaling coefficients of 0.75 and 1 for clearance and volume parameters, respectively. The adapted model, through simulation, was used to predict the target exposure (AUC) in adult patients and to simulate pediatric exposures after administration of fixed doses of ponatinib. Virtual pediatric patients were simulated on the basis of body size vs age distributions from the National Health and Nutrition Examination Survey data set provided by the Centers for Disease Control and Prevention. A pediatric population consisting of 250,000 virtual pediatric patients was simulated on the basis of a stepwise uniform pediatric age distribution designed to mimic the age distribution published for an imatinib study in pediatric Ph+ ALL and stratified by sex (50:50 male to female). The pediatric simulations assumed similar bioavailability between the age‐appropriate formulation(s) and the currently available tablet formulation.
The protocols of all 7 studies included in this population PK analysis were approved by the appropriate local institutional review boards (IRBs) or independent ethics committees. Studies AP24534‐11‐102, AP24534‐11‐103, AP24534‐12‐107, and AP24534‐12‐108 were approved by Institutional Review Board Services Ontario. , , , The Japanese phase 1/2 study (AP24534‐11‐106, NCT01667133) was approved by IRBs or independent ethics committees of the 9 participating centers in Japan. The phase 1 study (AP24534‐07‐101, NCT00660920) was approved by the IRB at each of the 5 study centers. The phase 3 EPIC (Evaluation of Ponatinib Versus Imatinib in Chronic Myeloid Leukemia) study (AP24534‐12‐301, NCT01650805) was approved by the IRBs or independent ethics committees of the 106 study sites enrolling patients. All participants provided written informed consent. Ponatinib plasma concentration–time data were collected from adult healthy volunteers and patients with hematologic malignancies who had participated in 1 of 7 clinical trials. , , , , , , Participant eligibility criteria for each study are described in the original publications. Table provides a summary of the studies included in the population PK analysis. For the food‐effect study in healthy volunteers, only data collected under fasted conditions were included in the population PK analysis. For the drug‐drug interaction studies in healthy volunteers, , , ponatinib data collected in the presence of the coadministered drug (ie, ketoconazole, rifampin, or lansoprazole) were excluded from the population PK analysis. All study procedures were performed in accordance with the International Council for Harmonisation Good Clinical Practice guidelines and appropriate regulatory requirements. Plasma concentrations of ponatinib were measured using 2 validated liquid chromatography–tandem mass spectrometry assays. , , ,
The population PK analysis was performed using NONMEM (version 7.3; ICON Development Solutions, Hanover, Maryland ) for nonlinear mixed‐effects models, running under Perl‐speaks‐NONMEM (version 4.6) on a grid of CentOS 7.1 Linux servers and the Fortran compiler (version 12.0.4; Intel, Santa Clara, California). Analysis of results and simulations was performed using R (version 3.4.3; R Foundation for Statistical Computing, Vienna, Austria ). For development of the base population PK model, fixed‐effect model parameters (θ), variances of the interindividual variability (ω 2 ), and residual error (σ 2 ) were estimated. Interindividual variability was implemented by exponential random‐effect models, corresponding to log‐normally distributed individual parameters, and was defined as: (1) θ i = θ TV , i · exp ( η i ) where θ i and θ TV are individual and typical values of the parameter (eg, apparent oral clearance [CL/F]). η i is an individual‐level random variable sampled from a normal distribution with a mean of 0 and variance of ω 2 , and it represents the i th individual's deviation from the typical value. Initially, random effects were assumed to be independent; however, random‐effect models defined by a nondiagonal variance‐covariance matrix (Ω) were preferred if they resulted in meaningful improvements in model fit. Models describing untransformed data, as well as data that were log‐transformed on both sides, were evaluated during model development. In models applying the log‐transformed on both sides approach, the residual unexplained variability was described by an additive (on the log‐scale) error model that was parameterized as: (2) log ( Y ik ) = log ( C ik ) + ε ik where Y ik was the k th observed concentration in the i th individual, C ik was the corresponding individual model‐predicted concentration, and ε ik was the residual error sampled from a normal distribution with a mean of 0 and variance of σ 2 . Alternative residual error models with >1 ε were considered with a covariance matrix Σ to define the variances and covariances of the ε's. Initially, the ε's were assumed to be uncorrelated. Nondiagonal Σ was estimated to evaluate if the data supported estimation of correlations between ε's. Appropriate transformations of parameters were considered to appropriately constrain parameter values. For example, log transformation of CL/F was considered to constrain the estimate to positive values. Similarly, logit transformations were considered for parameters describing the fraction of a dose to constrain the estimate to between 0 and 1. Shrinkage of interindividual random effects ( η ) was evaluated for diagnostic purposes. The shrinkage for a structural parameter s h θ ( η shrinkage) was calculated as : (3) s h θ = 1 − S D η E B E , θ ω θ where S D ( η E B E , θ ) is the standard deviation of the individual η for θ , and ω θ is the model estimate of the SD associated with θ.
Continuous covariates (age, body weight, albumin, alanine aminotransferase [ALT], total bilirubin, and creatinine clearance [CrCL]) and categorical covariates (race, patient or healthy volunteer status, and sex) were tested in the development of the covariate model (Table ). Continuous covariates were included in the model as power functions, while binary covariates were implemented as factors: (4) θ T V , i = θ T V , P o p · x C o n t , i m e d i a n ( x C o n t , i ) θ 1 · 1 + x C a t , i · θ 2 In this equation, the parameter θ TV,i for the i th subject is defined as a function of the population typical value, θ TV,Pop , and the individual contributions from continuous ( x Cont,i ) and binary ( x Cat,i with values 0 and 1) covariates. θ 1 and θ 2 represent the respective covariate coefficients. A stepwise covariate modeling strategy (single addition, forward inclusion, and backward elimination) was performed. Model selection was based on the likelihood ratio test. During the forward inclusion step, statistical significance of a covariate effect was evaluated using the chi‐square test for P < .01. Covariates that were statistically significant were retained in the model. In the backward elimination phase, statistical significance of covariate effects was evaluated using the chi‐square test for P < .001. Significant covariates were retained, and covariates whose removal did not lead to a significant worsening of the objective function value (OFV) were iteratively dropped until no such nonsignificant covariates ( P > .001) remained in the model. Finally, covariate effects that were imprecisely estimated (% relative standard error [%RSE] >50%; that is, the 95% confidence interval included 0) were considered for exclusion from the covariate model.
Nested models were compared using the likelihood ratio test. Structural and residual error model discrimination were based on standard model diagnostics, such as a decrease in the OFV, precision and accuracy of parameter estimation (%RSE), condition number, successful model convergence and covariance step, and examination of goodness‐of‐fit plots and prediction‐corrected visual predictive checks (VPCs). In the VPCs, percentiles (median, 5th, and 95th percentiles) of observed data were superimposed on those of the individual model‐predicted ponatinib concentration‐time profiles, based on 250 simulated replicates of the analysis data set. Model robustness and parameter estimates were assessed by bootstrap based on 1000 resampled data sets with replacement up to the total number of patients in the original data set.
The final population PK model was used to perform simulations for patients treated with daily ponatinib doses of 15, 30, and 45 mg. Individual plasma concentration–time profiles of ponatinib were simulated for the typical patient and 1000 virtual patients to describe ponatinib plasma concentrations with each once‐daily dosing regimen, relative to reference concentrations of 10.7 ng/mL (20 nM) and 21.3 ng/mL (40 nM), which have been previously demonstrated to suppress most BCR‐ABL1 mutants and T315I BCR‐ABL1 mutants, respectively, in cell‐based mutagenesis assays. For the typical patient, random effects were set to zero, and covariate values were set to the median value in the analysis data set. For virtual patients, random effects were sampled from the random effects variance–covariate matrix and covariates were sampled from distributions designed to reflect values reported in the data set. The 5th and 95th percentiles of the concentration‐time profiles were derived from the profiles of the 1000 virtual patients. The AUC, C max , trough concentration, and average concentration (C average ) were derived for each simulated patient and summarized.
A primary objective of the pediatric program for ponatinib is to evaluate its safety and efficacy in combination with multiagent chemotherapy for the treatment of pediatric patients ≥1 year of age with Ph+ ALL. A 30‐mg dose is being evaluated in combination with chemotherapy in adult patients with Ph+ ALL (ClinicalTrials.gov Identifier: NCT03589326). Accordingly, a model‐informed approach was used to establish pediatric posology to approximately match adult exposures at 30 mg for the design of a pediatric study (ClinicalTrials.gov Identifier: NCT04501614). For the purpose of predicting pediatric doses that would match adult exposures at ponatinib 30 mg once daily, the developed model was adapted by removing the previously estimated adult covariate effects and including allometric scaling coefficients of 0.75 and 1 for clearance and volume parameters, respectively. The adapted model, through simulation, was used to predict the target exposure (AUC) in adult patients and to simulate pediatric exposures after administration of fixed doses of ponatinib. Virtual pediatric patients were simulated on the basis of body size vs age distributions from the National Health and Nutrition Examination Survey data set provided by the Centers for Disease Control and Prevention. A pediatric population consisting of 250,000 virtual pediatric patients was simulated on the basis of a stepwise uniform pediatric age distribution designed to mimic the age distribution published for an imatinib study in pediatric Ph+ ALL and stratified by sex (50:50 male to female). The pediatric simulations assumed similar bioavailability between the age‐appropriate formulation(s) and the currently available tablet formulation.
Data Summary The population PK analysis included data from 260 participants (86 healthy volunteers and 174 patients with hematologic malignancies; Table ). The analysis population was predominantly male (68.8%) and White (71.5%) with a median age of 49 years (range, 19‐85 years; Table ). A total of 2637 PK samples were available, of which 121 (4.6%) were below the limit of quantification. Given the low number of samples below the limit of quantification, they were excluded from the analysis. Population PK Model The observed ponatinib PK data were described by a 2‐compartment model with first‐order elimination from the central compartment (Figure ). Of note, a 3‐compartment model did not result in a meaningful improvement in goodness‐of‐fit and was associated with imprecise estimates of the apparent volume of the second peripheral compartment (RSE >100%), thereby supporting the selection of a 2‐compartment model. For healthy subjects, absorption of ponatinib into the central compartment was best described by two parallel processes where a fraction of the dose (F1) was absorbed via 2 sequential transit compartments and the remaining fraction (F2) was described by first‐order absorption with a lag time. However, for patients, first‐order absorption with a lag time was not required to describe the PK of ponatinib, which is likely explained by the richer serial PK sampling schedules during the absorption phase in healthy subject studies compared with the patient studies. Thus, the value of F2 was set to 0 for patients. The first‐order rate constant describing the second absorption route (K a2 ) for the F2 route was associated with considerable parameter uncertainty (RSE >100%) in preliminary model evaluation. Therefore, K a2 was fixed to a value of 4.41 based on its estimate in initial runs during base model development. For the F1 route, an absorption model with the estimated number of transit compartments based on the Stirling approximation was initially evaluated. The number of transit compartments estimated by this initial model was 0.5, suggesting that the model could be simplified by including a number of explicitly defined transit compartments. Models containing 1 and 2 transit compartments were therefore evaluated. Despite being closer to the estimated number of transit compartments, an alternative model with 1 transit compartment resulted in a worse description of the data than the model with 2 transit compartments. Consequently, a transit model consisting of 2 explicitly defined transit compartments was included to describe absorption via the F1 route in the base population PK model. The base model included interindividual variability on the rate constant of absorption through the F1 route (K tr , identical to the first‐order absorption rate constant via the F1 route [K a1 ]), CL/F, and the apparent central volume of distribution (V3/F). Additionally, a correlation between the random effects on CL/F and V3/F was introduced in the base model, which reduced the OFV by 42.48 points. The residual error model included distinct terms to characterize the unexplained variability in patients and healthy subjects reflecting the richer serial PK sampling schedule in the healthy volunteer studies. Multivariate stepwise covariate modeling identified age and body weight as the 2 most statistically significant covariates on V3/F. In a third forward addition step, the effect of age on CL/F was included ( P = .007); however, this parameter‐covariate relationship was removed during backward elimination. Accordingly, the final model only included age and body weight as covariates on V3/F. The PK parameter values estimated for the final population PK model are presented in Table . Final model parameters were estimated with good precision with RSE <31% with the exception of F2, which had an estimated RSE of 94%. The F2 parameter represented a fraction and was implemented as a logit‐transformed parameter. Accordingly, a value of F2 = 0 for the transformed parameter corresponded to 50% absorption through each route of absorption. In addition, for patients, the entire absorbed dose entered the central compartment via the F1 route; therefore, the higher RSE on the F2 parameter was not considered to impact the characterization of ponatinib PK in patients. Shrinkage of random effects on CL/F, V3/F, and K a1 was <20%. Residual error was best described as log additive with distinct terms describing the unexplained variability for patients separately from healthy volunteers. The residual variability expressed as the coefficient of variation was ≈15% for healthy volunteers and 39% for patients. The condition number, a measure of collinearity between parameter estimates, was acceptable at 29.32. Ponatinib CL/F was estimated at 34.28 L/h with an interindividual variability of 48.0%, indicating that 90% of the population would be expected to have a ponatinib CL/F between 15.55 and 75.54 L/h. The V3/F was estimated at 838.6 L with interindividual variability of 42.3%, indicating that 90% of the population with the same age and body weight would have a V3/F between 418 and 1682 L. Goodness‐of‐fit plots demonstrated close agreement between the observed and individual predicted ponatinib concentrations (Figure ). Although some bias was observed at the population level for the lowest and highest concentrations, the majority of data points fell along the line of unity. Conditional weighted residuals over time plots supported that the residual error model was appropriately specified and independent of time (Figure and ). In the bootstrap analysis of the final covariate model, all of the 1000 bootstrap replicates (100%) achieved successful convergence. Parameter estimates based on the analysis data set were in good agreement with the 95% confidence interval of parameter values based on the bootstrap analysis (Table ). A prediction‐corrected VPC of the final model confirmed that the model was appropriately specified (Figure ). Stratification of the VPC by dose, study, and population (ie, patient vs healthy volunteers) indicated the absence of readily apparent sources of heterogeneity in ponatinib PK by these factors. Based on the final model, the individual predicted steady‐state AUC of ponatinib for a 45‐mg dose, calculated as AUC i = 45 mg/(CL/F i ), was evaluated vs relevant covariates using linear regression analyses. Figure shows the correlations between individual predicted exposure and the continuous covariates of age (Figure ), body weight (Figure ), albumin (Figure ), total bilirubin (Figure ), CrCL (Figure ), and ALT values (Figure ). Across the entire analysis population, the 5th and 95th percentiles of individual predicted exposures were −51.8% and +113% relative to the median AUC, respectively. The AUC at the 5th and 95th percentiles of continuous covariates relative to the AUC at the median covariate value was at most 14.5% for any covariate, which was well below the variability in individual predicted AUC across the entire analysis population. Similarly, for categorical covariates of sex (Figure ), population (ie, healthy volunteer or patient; Figure ) and race (Figure 3I), the magnitude of relative difference in predicted AUC for each category was at most 15.1% compared to the most common category, which was below the total variability in individual predicted AUC across the entire analysis population. Additionally, these differences are substantially lower than the reported overall variability for ponatinib PK (coefficient of variation of 73% for AUC). Figure illustrates the magnitude of covariate effects relative to the overall population of ponatinib exposures. Taken together, these analyses confirmed the absence of clinically meaningful effects of the covariates of interest on the systemic exposure (AUC) of ponatinib and were consistent with these covariates not having clinically meaningful effects on CL/F. Figure 3 (A‐F). Individual predicted ponatinib steady‐state exposures (45 mg once daily) vs continuous covariates: age (A), body weight (B), serum albumin (C), bilirubin (D), CrCL (E), and ALT (F). Small black circles represent individual ponatinib exposures; black line (gray‐shaded area) represents a linear regression (95%CI) of individual exposures vs covariate; numbers [ranges] at the top of the plots are changes in percent [95%CI] in ponatinib exposure predicted by the linear regression at the 5th or 95th percentile of individual covariate values (large black circles) relative to the predicted AUC at the median of individual covariate values (red circle and horizontal line). (G‐I) Individual predicted exposures vs categorical covariates: sex (G), disease status (H), and race (I). Boxplots represent distributions of individual ponatinib exposures vs covariates; numbers [ranges] at the top of the plots are changes in percent [95%CI] in ponatinib mean exposure at categorical covariate values (large black circles) relative to the predicted AUC in the most common covariate category (red circle and horizontal line); numbers below each box represent the sample size within each category. ALT, alanine aminotransferase; AUC, area under the plasma concentration–time curve; CI, confidence interval; CrCL, creatinine clearance; HV, healthy volunteers; Pts, patients. Model‐Based Simulations Simulated ponatinib concentration‐time profiles for the typical patient and the 5th to 95th percentile ranges across 1000 virtual patients following once‐daily administration of 15, 30, or 45 mg ponatinib over the first week of treatment and on day 28 are shown in Figure . Steady‐state ponatinib PK parameters for a typical patient and the associated 90% prediction interval for the simulated population are summarized in Table . Based on the model simulations, the AUC and C average at steady state following treatment with 45 mg of ponatinib once daily in the typical patient (90% prediction interval) were 1.31 µg·h/mL (0.598‐2.94) and 54.7 ng/mL (24.9‐123), respectively. For 30 mg once daily and 15 mg once daily, the corresponding values for AUC were 0.875 µg·h/mL (0.398‐1.96) and 0.438 µg·h/mL (0.199‐0.981), respectively, and for C average were 36.5 ng/mL (16.6‐81.7) and 18.2 ng/mL (8.3‐40.9), respectively. Over the 15‐ to 45‐mg dose range, there was an increase in the percentage of simulated patients achieving C average values associated with inhibition of BCR‐ABL1 (>10.7 ng/mL) and T315I mutants (>21.3 ng/mL) in cell‐based assays. Allometric Scaling of the Population PK Model for Pediatric Dose Selection The developed population PK model was subsequently adapted using allometric scaling to inform pediatric dose selection. Simulations were performed to identify pediatric doses that would result in systemic exposures comparable to those observed at an adult reference dose of 30 mg. Results of the pediatric simulations (Figure ) indicated that ponatinib doses of 5 mg, 10 mg, 20 mg, or 30 mg for patients weighing ≥5 and <15 kg, ≥15 and <30 kg, ≥30 and <45 kg, and ≥45 kg are anticipated to result in systemic exposures that approximately match adult exposures following a 30‐mg dose.
The population PK analysis included data from 260 participants (86 healthy volunteers and 174 patients with hematologic malignancies; Table ). The analysis population was predominantly male (68.8%) and White (71.5%) with a median age of 49 years (range, 19‐85 years; Table ). A total of 2637 PK samples were available, of which 121 (4.6%) were below the limit of quantification. Given the low number of samples below the limit of quantification, they were excluded from the analysis.
The observed ponatinib PK data were described by a 2‐compartment model with first‐order elimination from the central compartment (Figure ). Of note, a 3‐compartment model did not result in a meaningful improvement in goodness‐of‐fit and was associated with imprecise estimates of the apparent volume of the second peripheral compartment (RSE >100%), thereby supporting the selection of a 2‐compartment model. For healthy subjects, absorption of ponatinib into the central compartment was best described by two parallel processes where a fraction of the dose (F1) was absorbed via 2 sequential transit compartments and the remaining fraction (F2) was described by first‐order absorption with a lag time. However, for patients, first‐order absorption with a lag time was not required to describe the PK of ponatinib, which is likely explained by the richer serial PK sampling schedules during the absorption phase in healthy subject studies compared with the patient studies. Thus, the value of F2 was set to 0 for patients. The first‐order rate constant describing the second absorption route (K a2 ) for the F2 route was associated with considerable parameter uncertainty (RSE >100%) in preliminary model evaluation. Therefore, K a2 was fixed to a value of 4.41 based on its estimate in initial runs during base model development. For the F1 route, an absorption model with the estimated number of transit compartments based on the Stirling approximation was initially evaluated. The number of transit compartments estimated by this initial model was 0.5, suggesting that the model could be simplified by including a number of explicitly defined transit compartments. Models containing 1 and 2 transit compartments were therefore evaluated. Despite being closer to the estimated number of transit compartments, an alternative model with 1 transit compartment resulted in a worse description of the data than the model with 2 transit compartments. Consequently, a transit model consisting of 2 explicitly defined transit compartments was included to describe absorption via the F1 route in the base population PK model. The base model included interindividual variability on the rate constant of absorption through the F1 route (K tr , identical to the first‐order absorption rate constant via the F1 route [K a1 ]), CL/F, and the apparent central volume of distribution (V3/F). Additionally, a correlation between the random effects on CL/F and V3/F was introduced in the base model, which reduced the OFV by 42.48 points. The residual error model included distinct terms to characterize the unexplained variability in patients and healthy subjects reflecting the richer serial PK sampling schedule in the healthy volunteer studies. Multivariate stepwise covariate modeling identified age and body weight as the 2 most statistically significant covariates on V3/F. In a third forward addition step, the effect of age on CL/F was included ( P = .007); however, this parameter‐covariate relationship was removed during backward elimination. Accordingly, the final model only included age and body weight as covariates on V3/F. The PK parameter values estimated for the final population PK model are presented in Table . Final model parameters were estimated with good precision with RSE <31% with the exception of F2, which had an estimated RSE of 94%. The F2 parameter represented a fraction and was implemented as a logit‐transformed parameter. Accordingly, a value of F2 = 0 for the transformed parameter corresponded to 50% absorption through each route of absorption. In addition, for patients, the entire absorbed dose entered the central compartment via the F1 route; therefore, the higher RSE on the F2 parameter was not considered to impact the characterization of ponatinib PK in patients. Shrinkage of random effects on CL/F, V3/F, and K a1 was <20%. Residual error was best described as log additive with distinct terms describing the unexplained variability for patients separately from healthy volunteers. The residual variability expressed as the coefficient of variation was ≈15% for healthy volunteers and 39% for patients. The condition number, a measure of collinearity between parameter estimates, was acceptable at 29.32. Ponatinib CL/F was estimated at 34.28 L/h with an interindividual variability of 48.0%, indicating that 90% of the population would be expected to have a ponatinib CL/F between 15.55 and 75.54 L/h. The V3/F was estimated at 838.6 L with interindividual variability of 42.3%, indicating that 90% of the population with the same age and body weight would have a V3/F between 418 and 1682 L. Goodness‐of‐fit plots demonstrated close agreement between the observed and individual predicted ponatinib concentrations (Figure ). Although some bias was observed at the population level for the lowest and highest concentrations, the majority of data points fell along the line of unity. Conditional weighted residuals over time plots supported that the residual error model was appropriately specified and independent of time (Figure and ). In the bootstrap analysis of the final covariate model, all of the 1000 bootstrap replicates (100%) achieved successful convergence. Parameter estimates based on the analysis data set were in good agreement with the 95% confidence interval of parameter values based on the bootstrap analysis (Table ). A prediction‐corrected VPC of the final model confirmed that the model was appropriately specified (Figure ). Stratification of the VPC by dose, study, and population (ie, patient vs healthy volunteers) indicated the absence of readily apparent sources of heterogeneity in ponatinib PK by these factors. Based on the final model, the individual predicted steady‐state AUC of ponatinib for a 45‐mg dose, calculated as AUC i = 45 mg/(CL/F i ), was evaluated vs relevant covariates using linear regression analyses. Figure shows the correlations between individual predicted exposure and the continuous covariates of age (Figure ), body weight (Figure ), albumin (Figure ), total bilirubin (Figure ), CrCL (Figure ), and ALT values (Figure ). Across the entire analysis population, the 5th and 95th percentiles of individual predicted exposures were −51.8% and +113% relative to the median AUC, respectively. The AUC at the 5th and 95th percentiles of continuous covariates relative to the AUC at the median covariate value was at most 14.5% for any covariate, which was well below the variability in individual predicted AUC across the entire analysis population. Similarly, for categorical covariates of sex (Figure ), population (ie, healthy volunteer or patient; Figure ) and race (Figure 3I), the magnitude of relative difference in predicted AUC for each category was at most 15.1% compared to the most common category, which was below the total variability in individual predicted AUC across the entire analysis population. Additionally, these differences are substantially lower than the reported overall variability for ponatinib PK (coefficient of variation of 73% for AUC). Figure illustrates the magnitude of covariate effects relative to the overall population of ponatinib exposures. Taken together, these analyses confirmed the absence of clinically meaningful effects of the covariates of interest on the systemic exposure (AUC) of ponatinib and were consistent with these covariates not having clinically meaningful effects on CL/F. Figure 3 (A‐F). Individual predicted ponatinib steady‐state exposures (45 mg once daily) vs continuous covariates: age (A), body weight (B), serum albumin (C), bilirubin (D), CrCL (E), and ALT (F). Small black circles represent individual ponatinib exposures; black line (gray‐shaded area) represents a linear regression (95%CI) of individual exposures vs covariate; numbers [ranges] at the top of the plots are changes in percent [95%CI] in ponatinib exposure predicted by the linear regression at the 5th or 95th percentile of individual covariate values (large black circles) relative to the predicted AUC at the median of individual covariate values (red circle and horizontal line). (G‐I) Individual predicted exposures vs categorical covariates: sex (G), disease status (H), and race (I). Boxplots represent distributions of individual ponatinib exposures vs covariates; numbers [ranges] at the top of the plots are changes in percent [95%CI] in ponatinib mean exposure at categorical covariate values (large black circles) relative to the predicted AUC in the most common covariate category (red circle and horizontal line); numbers below each box represent the sample size within each category. ALT, alanine aminotransferase; AUC, area under the plasma concentration–time curve; CI, confidence interval; CrCL, creatinine clearance; HV, healthy volunteers; Pts, patients.
Simulated ponatinib concentration‐time profiles for the typical patient and the 5th to 95th percentile ranges across 1000 virtual patients following once‐daily administration of 15, 30, or 45 mg ponatinib over the first week of treatment and on day 28 are shown in Figure . Steady‐state ponatinib PK parameters for a typical patient and the associated 90% prediction interval for the simulated population are summarized in Table . Based on the model simulations, the AUC and C average at steady state following treatment with 45 mg of ponatinib once daily in the typical patient (90% prediction interval) were 1.31 µg·h/mL (0.598‐2.94) and 54.7 ng/mL (24.9‐123), respectively. For 30 mg once daily and 15 mg once daily, the corresponding values for AUC were 0.875 µg·h/mL (0.398‐1.96) and 0.438 µg·h/mL (0.199‐0.981), respectively, and for C average were 36.5 ng/mL (16.6‐81.7) and 18.2 ng/mL (8.3‐40.9), respectively. Over the 15‐ to 45‐mg dose range, there was an increase in the percentage of simulated patients achieving C average values associated with inhibition of BCR‐ABL1 (>10.7 ng/mL) and T315I mutants (>21.3 ng/mL) in cell‐based assays.
The developed population PK model was subsequently adapted using allometric scaling to inform pediatric dose selection. Simulations were performed to identify pediatric doses that would result in systemic exposures comparable to those observed at an adult reference dose of 30 mg. Results of the pediatric simulations (Figure ) indicated that ponatinib doses of 5 mg, 10 mg, 20 mg, or 30 mg for patients weighing ≥5 and <15 kg, ≥15 and <30 kg, ≥30 and <45 kg, and ≥45 kg are anticipated to result in systemic exposures that approximately match adult exposures following a 30‐mg dose.
This population PK analysis of the oral TKI ponatinib provides a comprehensive model‐based integration of data from 260 participants (174 patients and 86 healthy volunteers) enrolled across 7 clinical trials, including 5 phase 1 studies, , , , , 1 phase 1/2 study, and 1 phase 3 study. The PK of ponatinib was adequately described by a 2‐compartment model with linear first‐order elimination from the central compartment. The absorption component of the model consisted of 2 routes of absorption where the first route of absorption was described by 2 discrete transit compartments, and the second route was described by a delayed first‐order absorption process. While the absorption in patients could be described solely by the first absorption route, absorption in healthy volunteers necessitated a split of the absorbed dose between the 2 routes. The need for the complex absorption profile in the healthy volunteer group appeared to be driven in part by differences in the study designs and PK sampling schemes employed across the clinical program. Data obtained from the studies in patients with hematologic malignancies , , was based on a heterogeneous mix of patients with varying degrees of comorbidities and concomitant medications, and PK samples were obtained predominantly following repeated doses. In contrast, PK samples in the healthy volunteer trials were obtained following single doses of ponatinib under a strict serial sampling schedule. The final population PK model included individual random effects on CL/F, V3/F, and K a1 . The correlation between random effects for CL/F and V3/F was estimated in the model to improve fit and allow the model to reproduce the observed correlation in simulations. Multivariate stepwise covariate modeling did not identify significant effects of any covariates on CL/F. Age and body weight were the only covariates that had statistically significant effects on V3/F. The effects of these covariates on V3/F did not influence overall systemic exposure (AUC), were small relative to the overall variability of ponatinib V3/F in the patient population, and were therefore not considered to be of clinical significance. To further confirm the selected covariate model and the lack of an impact on total systemic exposure of ponatinib (AUC), relationships between individual model‐predicted ponatinib AUC and covariates were explored. For continuous and categorical covariates, the model‐predicted exposure at the 5th and 95th percentiles of the covariate fell within –13.9% and 15.1% of the exposure at the median covariate value, respectively. Based on these findings, it was concluded that patient‐specific factors, including albumin (23‐52.5 g/L), sex, age (19‐85 years), body weight (40.7‐152 kg), total bilirubin (0.1‐3.16 mg/dL), ALT (6‐188 U/L), creatinine clearance (27.8‐296 mL/min), and race (including Asian race), did not contribute to clinically important differences in ponatinib exposure. Of note, a common global dose without adjustment for any baseline covariates was used during the clinical development of ponatinib. The lack of an effect of mild and moderate renal impairment (ie, creatinine clearance ≥30 mL/min) is consistent with metabolism being the primary route of clearance for ponatinib as there was negligible urinary excretion of ponatinib in the radiolabeled mass balance study. The final model was then used to simulate ponatinib plasma concentrations at varying doses in a patient population. In cell‐based assays, a ponatinib concentration of 20 nM (10.7 ng/mL) was sufficient to suppress most BCR‐ABL1 mutant clones and a concentration of 40 nM (21.3 ng/mL) completely suppressed T315I mutant clones. In the simulations using the final population PK model, ponatinib doses of 15 to 45 mg once daily were predicted to result in steady‐state C average values that approximated or exceeded these concentrations associated with in vitro pharmacological activity of ponatinib. The comparison of total plasma concentrations to in vitro potency estimates without corrections for plasma protein binding is supported by data demonstrating that the presence of physiologically relevant concentrations of albumin had no meaningful impact on the cellular potency of ponatinib. Ponatinib was initially approved in 2012. However, subsequent to its approval, a dose‐optimization study (NCT02467270; OPTIC) was initiated due to long‐term safety data indicating a risk for arterial occlusive events. The OPTIC (Optimizing Ponatinib Treatment in Chronic Myeloid Leukemia) study was designed to evaluate starting doses of ponatinib 45 mg, 30 mg, and 15 mg once daily with a mandatory dose reduction to 15 mg once daily upon achievement of ≤1% BCR‐ABL1/ABL1 IS for patients receiving 45 mg or 30 mg of ponatinib. The results of the current population PK analysis indicate that exposures achieved with doses of 15 to 45 mg are within the pharmacologically active range for BCR‐ABL1 inhibition, thereby supporting the selection of these doses for evaluation of dose‐response for efficacy and safety in OPTIC. Because no pediatric clinical PK data are currently available for ponatinib, an allometric scaling approach was used to project pediatric PK using the developed adult population PK model. The use of allometry was supported by knowledge of clearance mechanisms for ponatinib and their corresponding ontogeny. Specifically, ponatinib is metabolized predominantly by CYP3A with additional contributions by esterases and/or amidases. These clearance mechanisms are expected to approach adult levels within the first year of life. , , , The results of these simulations using the allometrically adapted model supported the selection of weight‐binned posology for pediatric development (ClinicalTrials.gov Identifier: NCT04501614).
Ponatinib PK was described by a 2‐compartment model with linear first‐order elimination. Covariates of interest, including sex, age, race, body weight, total bilirubin, ALT, albumin, and CrCL did not have clinically meaningful effects on the PK of ponatinib, suggesting that no dose adjustment is required based on these covariates. Doses of 15 to 45 mg resulted in exposures within the pharmacologically active range for BCR‐ABL1 inhibition. Simulations from the final model were used to inform dose selection for pediatric development.
M.H. is an employee of Takeda Pharmaceutical Company Limited. P.D. is an employee of Certara and consultant to Takeda Pharmaceutical Company Limited. N.N. is a previous employee of ARIAD Pharmaceuticals, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. S.S. is a previous employee of Takeda Pharmaceutical Company Limited. N.G. is an employee of Takeda Pharmaceutical Company Limited. K.V. is a previous employee of Takeda Pharmaceutical Company Limited.
Supplemental Information, Additional supplemental information can be found by clicking the Supplements link in the PDF toolbar or the Supplemental Information section at the end of the web‐based version of this article. Click here for additional data file.
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4D-Flow MRI and Vector Ultrasound in the In-Vitro Evaluation of Surgical Aortic Heart Valves – a Pilot Study | ada58d19-0b94-4de0-b6b6-ffea57484649 | 11885334 | Surgical Procedures, Operative[mh] | Degenerative diseases of the aortic valve are one of the leading causes of cardiac morbidity and mortality . From a very crude initial concept, the field of surgical aortic valves saved or enhanced the quality of life for millions of patients over the last decades. Due to the high demand for functional and lasting replacement options, the aortic valve device market turned into an ever-evolving field, trying to improve upon the existing bileaflet mechanical heart valves and xenogeneic bioprosthetic valves . Additionally to these two established models, different options were developed over the years, ranging from trileaflet mechanical valves to tissue engineered approaches . One common aim for iterations of established valve systems and even radical innovations is to enhance the hemodynamic performance. Many factors, such as pressure gradients, velocities, flow patterns and thrombogenicity are inherently responsible for adequate blood flow and lasting functionality of the aortic valve and the overall cardiovascular system. The visualization and quantification of blood flow characteristics distal to the aortic valve have been at the center of cardiovascular research for decades . In-vivo evaluation of patients has been performed using radiological modalities ranging from ultrasound (US) to magnetic resonance imaging (MRI) . In basic research, different technologies were developed over time, with particle image velocimetry (PIV) being one of the most applied techniques to visualize fluid characteristics in mock circulation setups . In the past, these mock circulation setups mostly relied on acrylic vessels or silicone cast phantoms . The emergence of additive manufacturing opened new ways of creating accurate anatomical phantoms for integration in mock flow loops . Besides the printing accuracy, an increasing range of printable materials allows for individualized design of the model’s properties, to more closely match the behavior of the human aorta. While these models offer great accuracy, current materials and printing techniques often result in printed vessel walls that are opaque, leading to limited usability in PIV measurements. This technical limitation makes exploring alternative imaging modalities necessary. Technological advances in the field of radiological imaging, offer new capturing techniques, such as 4D-Flow MRI, a type of three-dimensional, time resolved phase-contrast MRI . This technology allows the visualization of disturbed flow patterns and quantification of flow parameters, such as velocity, pressure drops and WSS. In clinical research, 4D- Flow MRI has been widely used in the analysis of congenital heart defects , ventricular flow and portal veins. Besides 4D-Flow MRI, the computing power of modern sonographic imaging devices led to the introduction of vector flow doppler imaging, that allows the visualization of dynamic flow patterns, as well as the calculation of wall shear stress (WSS) and energy loss. These imaging modalities give clinical radiology a broader toolbox to accurately examine patients. Furthermore, they can be used in translational and basic research for fast, non-invasive measurements. Therefore, the goal of this research project was the initial investigation of 4D-Flow MRI and Vector Ultrasound as novel imaging techniques in the in-vitro analysis of hemodynamics in anatomical models. Specifically, by looking at the hemodynamic performance of state-of-the-art surgical heart valves in a 3D-printed aortic arch.
Model Creation The main part of the flow loop setup is represented by a 3D-printed flexible thoracic aorta including the ascending aorta, the aortic arch and the descending aorta. The model creation workflow followed a previously published work . Briefly, an anonymized contrast-enhanced CT dataset of a patient who had an indication for surgical aortic valve replacement with a 25 mm prosthesis, was segmented to extract the ascending aorta, aortic arch, aortic root and supra-aortic vessels. Different datasets were measured retrospectively to select a patient sized for a 25 mm aortic valve. Exclusion criteria were any of the following in the region of interest: poor image quality (i.e. device-related artefacts), pathologic diameter change, calcifications outside the aortic root and non-standard configuration of supra-aortic vessels. After segmentation of the blood volume, the digital model was hollowed by adding a constant wall thickness of 2.5 mm external to the blood volume . All vessel ends were modified in a circular uniform diameter for easy attachment to standardized connectors (Fig. A). The proximal end of the left ventricular outflow tract was prolonged to allow for adequate sealing, as well as placement of the heart valve prostheses according to manufacturer’s specifications. Afterwards, the digital model was transferred into the slicing software Modeling Studio (Keyence Corp., Osaka, JP), subsequently uploaded onto a 3D-printer (Agilista 3200W, Keyence Corp.) and printed using a flexible, printing material (AR-G1L, Shore 35A, elongation at break: 160%, Keyence Corp.). After the printing process, the aortic phantom was taken from the build plate and soaked in boiling water to remove the water-soluble support material. Subsequently, the model was placed in a heating cabinet to dry for 24 h at 50 °C. Heart Valve Prostheses To perform standardized comparative tests of different heart valve prostheses, a uniform prosthesis size of 25 mm (manufacturer’s specification) was selected for all valves tested in this study. Included are five different valves for surgical implantation, with two mechanical prosthetic valves (Masters Series 25, Abbott Laboratories, Chicago, USA; On-Xane-25, CryoLife Inc., Kennesaw, USA) and three different bioprosthetic heart valves (Epic 25 mm, Abbott Laboratories; Magna Ease 25 mm, Edwards Lifesciences Inc., Irvine, USA; Perimount 25 mm, Edwards Lifesciences Inc.). Individual valve mounts were designed to follow the individual curvature of the valve’s suture rings (Fig. B). Subsequently, valves were fixed to the mount using surgical sutures (Prolene 5–0, Ethicon Inc., Raritan, USA) and tested for paravalvular leakages. Each mount has a defined height, to allow for supra or intra-annular placement of the valves, according to manufacturer’s recommendations (Fig. C). The orientation of the mechanical valve leaflets was adjusted to match manufacturer’s recommendations. Bioprosthetic valves were stored in their original container with storage solution up until testing. Mock Circulation To allow for testing of the valves in an MRI setting, an entire MRI-compatible mock circulation setup was designed and constructed (Fig. ). The setup was divided into two parts, the external drive unit and the internal fluid circulation unit. The external drive unit consisted of a dedicated computer, linear motor (PS01- 48 × 240 HP, NTI AG, Spreitenbach, CH) with corresponding driver (Series C1100, NTI AG). The linear motor was connected to a piston, which in turn is connected air-tight via a pneumatic hose to the fluid circulation unit. The connecting point also represents the heart of the mock circulation with a self-developed pump chamber, representing the left ventricle. To transfer the pneumatic force created by the piston to the test fluid, a rubber roll membrane with a defined volume of 80 ml was placed between the pneumatic and fluid chambers. The fluid chamber has a total volume of 100 ml resulting in a theoretical peak ejection fraction of 80%. An ejection fraction above physiological levels was chosen to adjust for the rigid nature of the artificial ventricle The chamber was connected to the valve mount via a straight rigid tube to allow for any flow disturbances to subside before passing through the valve prostheses. The 3D-printed aortic arch was then fixed to the valve mount which was placed in a plastic container. The container has five openings, for the proximal fluid entrance, the distal descending aorta and the supra-aortic vessels. After implantation of the valves in the aortic arch, the model was embedded in a hydrogel of 1% agar (Agarose, Sigma-Aldrich Corp., St. Louis, USA) to simulate the surrounding tissue and thereby reduce movement artefacts during MRI acquisition. Distal to the descending aorta and the supra-aortic vessels, a combination of compliance and resistance elements were placed to allow the approximation of the Windkessel-effect and peripheral vascular resistance. The compliance elements consist of an airtight cylinder filled partially with water and air, with a pneumatic valve at the top to adjust the height of the water column. The resistance element is realized through a ball valve that is placed distally to the compliance element. Therefore, realistic pressure conditions of 120/80 mmHg and a cardiac output of 4.6 l/min were achieved. Pressure was measured at the left ventricle, compliance chamber and descending aorta prior to MRI experiments. For all experiments, heart rate was set at 55 bpm, while systolic and diastolic pressure were adjusted to reach 120/80 mmHg. An ECG trigger signal was created and connected to the MRI according to manufacturer’s specifications. The trigger signal allowed the prospective synchronization of the ventricle movement with the acquisition time window. To simulate the viscous behavior of blood, a blood mimicking fluid (calculated viscosity 4.6cP) consisting of 40% glycerin (Rotipuran® ≥ 99.5%, Carl Roth GmbH, Karlsruhe, GER) and 60% distilled water was used . Radiological Imaging Acquisition of the 4D-Flow MRI imaging was performed on a 1.5 T scanner (MAGNETOM Aera, Siemens Healthineers AG, Erlangen, GER) with an 18-channel body coil (Biomatrix Body 18, Siemens Healthineers AG) placed on top of the agar filled plastic box. The acquisition protocol consisted of a non-contrast-enhanced MR-angiography and the 4D-flow sequence. For 4D-flow an isotropic dataset with 25 phases and a slice thickness of 1.0 mm (TE 2.300, TR 38.800, FA 7°, matrix size: 298 × 298 px) was acquired. Velocity encoding was set at 150 cm/s for all measurements . Evaluation and visualization of 4D-Flow MRI results was conducted using a dedicated radiological analysis software (cvi42, CCI Inc., Calgary, CA) . Within the software, the blood volume was separated from surrounding motion artefacts. Four measurement planes were placed perpendicular to the vessel’s centerline, specifically proximal to the valve as a reference plane, 10 mm distal to the top of the valve, at the center of the ascending curvature and at the distal end of the aortic arch (Fig. ). At each plane, velocity, tangential WSS and pressure drop with respect to the reference plane were measured. Calculation of WSS followed the publication by Stalder et al.. It describes an interpolation of local velocity vectors along the contour of the underlying measuring plane. The effective orifice area (EOA) was calculated using the continuity equation (Eq. ) with the velocity time integral in the left ventricular outflow tract (LVOT) and aortic valve (AV) derived from the underlying MRI dataset. 1 [12pt]{minimal}
$$EOA= _{LVOT}^{2}* *{VTI}_{LVOT}}{{VTI}_{AV}}$$ E O A = d LVOT 2 ∗ π 4 ∗ VTI LVOT VTI AV Equation : Continuity equation to determine the EOA; d = diameter; VTI = velocity time integral. Sonographic imaging was performed using a dedicated sonography device (Resona 9, Mindray Medical Int. Ltd., Shenzhen, CN) and the v-flow protocol, developed for carotid artery imaging. For image acquisition a linear array transducer (L14-3WU, Mindray Medical Int. Ltd.) was placed on to the agar block in correspondence to the above-mentioned planes, placing the center of the transducer on the according plane. The acquisition window was increased to the biggest possible size (20 × 30 mm) while all other parameters were set to the most precise setting available (acquisition time: 2 s; acquisition quality: 7). Since the acquisition window was developed for application at the carotid bifurcation, measurements had to be split into two parts at the inner and outer curvature of the aorta to cover the entire cross-section, due to the smaller ROI of the acquisition window. Flow velocity, total WSS at five spots along the aortic wall as well as the oscillatory shear index (OSI) were calculated from the measurements. The OSI was calculated as an expression for the magnitude and change in direction of local WSS described by the following formula: 2 [12pt]{minimal}
$$OSI= *(1.0- )$$ O S I = 1 2 ∗ ( 1.0 - AWSSV AWSS ) where AWSSV = magnitude of the time-averaged WSS vector, and AWSS = time-averaged WSS magnitude .
The main part of the flow loop setup is represented by a 3D-printed flexible thoracic aorta including the ascending aorta, the aortic arch and the descending aorta. The model creation workflow followed a previously published work . Briefly, an anonymized contrast-enhanced CT dataset of a patient who had an indication for surgical aortic valve replacement with a 25 mm prosthesis, was segmented to extract the ascending aorta, aortic arch, aortic root and supra-aortic vessels. Different datasets were measured retrospectively to select a patient sized for a 25 mm aortic valve. Exclusion criteria were any of the following in the region of interest: poor image quality (i.e. device-related artefacts), pathologic diameter change, calcifications outside the aortic root and non-standard configuration of supra-aortic vessels. After segmentation of the blood volume, the digital model was hollowed by adding a constant wall thickness of 2.5 mm external to the blood volume . All vessel ends were modified in a circular uniform diameter for easy attachment to standardized connectors (Fig. A). The proximal end of the left ventricular outflow tract was prolonged to allow for adequate sealing, as well as placement of the heart valve prostheses according to manufacturer’s specifications. Afterwards, the digital model was transferred into the slicing software Modeling Studio (Keyence Corp., Osaka, JP), subsequently uploaded onto a 3D-printer (Agilista 3200W, Keyence Corp.) and printed using a flexible, printing material (AR-G1L, Shore 35A, elongation at break: 160%, Keyence Corp.). After the printing process, the aortic phantom was taken from the build plate and soaked in boiling water to remove the water-soluble support material. Subsequently, the model was placed in a heating cabinet to dry for 24 h at 50 °C.
To perform standardized comparative tests of different heart valve prostheses, a uniform prosthesis size of 25 mm (manufacturer’s specification) was selected for all valves tested in this study. Included are five different valves for surgical implantation, with two mechanical prosthetic valves (Masters Series 25, Abbott Laboratories, Chicago, USA; On-Xane-25, CryoLife Inc., Kennesaw, USA) and three different bioprosthetic heart valves (Epic 25 mm, Abbott Laboratories; Magna Ease 25 mm, Edwards Lifesciences Inc., Irvine, USA; Perimount 25 mm, Edwards Lifesciences Inc.). Individual valve mounts were designed to follow the individual curvature of the valve’s suture rings (Fig. B). Subsequently, valves were fixed to the mount using surgical sutures (Prolene 5–0, Ethicon Inc., Raritan, USA) and tested for paravalvular leakages. Each mount has a defined height, to allow for supra or intra-annular placement of the valves, according to manufacturer’s recommendations (Fig. C). The orientation of the mechanical valve leaflets was adjusted to match manufacturer’s recommendations. Bioprosthetic valves were stored in their original container with storage solution up until testing.
To allow for testing of the valves in an MRI setting, an entire MRI-compatible mock circulation setup was designed and constructed (Fig. ). The setup was divided into two parts, the external drive unit and the internal fluid circulation unit. The external drive unit consisted of a dedicated computer, linear motor (PS01- 48 × 240 HP, NTI AG, Spreitenbach, CH) with corresponding driver (Series C1100, NTI AG). The linear motor was connected to a piston, which in turn is connected air-tight via a pneumatic hose to the fluid circulation unit. The connecting point also represents the heart of the mock circulation with a self-developed pump chamber, representing the left ventricle. To transfer the pneumatic force created by the piston to the test fluid, a rubber roll membrane with a defined volume of 80 ml was placed between the pneumatic and fluid chambers. The fluid chamber has a total volume of 100 ml resulting in a theoretical peak ejection fraction of 80%. An ejection fraction above physiological levels was chosen to adjust for the rigid nature of the artificial ventricle The chamber was connected to the valve mount via a straight rigid tube to allow for any flow disturbances to subside before passing through the valve prostheses. The 3D-printed aortic arch was then fixed to the valve mount which was placed in a plastic container. The container has five openings, for the proximal fluid entrance, the distal descending aorta and the supra-aortic vessels. After implantation of the valves in the aortic arch, the model was embedded in a hydrogel of 1% agar (Agarose, Sigma-Aldrich Corp., St. Louis, USA) to simulate the surrounding tissue and thereby reduce movement artefacts during MRI acquisition. Distal to the descending aorta and the supra-aortic vessels, a combination of compliance and resistance elements were placed to allow the approximation of the Windkessel-effect and peripheral vascular resistance. The compliance elements consist of an airtight cylinder filled partially with water and air, with a pneumatic valve at the top to adjust the height of the water column. The resistance element is realized through a ball valve that is placed distally to the compliance element. Therefore, realistic pressure conditions of 120/80 mmHg and a cardiac output of 4.6 l/min were achieved. Pressure was measured at the left ventricle, compliance chamber and descending aorta prior to MRI experiments. For all experiments, heart rate was set at 55 bpm, while systolic and diastolic pressure were adjusted to reach 120/80 mmHg. An ECG trigger signal was created and connected to the MRI according to manufacturer’s specifications. The trigger signal allowed the prospective synchronization of the ventricle movement with the acquisition time window. To simulate the viscous behavior of blood, a blood mimicking fluid (calculated viscosity 4.6cP) consisting of 40% glycerin (Rotipuran® ≥ 99.5%, Carl Roth GmbH, Karlsruhe, GER) and 60% distilled water was used .
Acquisition of the 4D-Flow MRI imaging was performed on a 1.5 T scanner (MAGNETOM Aera, Siemens Healthineers AG, Erlangen, GER) with an 18-channel body coil (Biomatrix Body 18, Siemens Healthineers AG) placed on top of the agar filled plastic box. The acquisition protocol consisted of a non-contrast-enhanced MR-angiography and the 4D-flow sequence. For 4D-flow an isotropic dataset with 25 phases and a slice thickness of 1.0 mm (TE 2.300, TR 38.800, FA 7°, matrix size: 298 × 298 px) was acquired. Velocity encoding was set at 150 cm/s for all measurements . Evaluation and visualization of 4D-Flow MRI results was conducted using a dedicated radiological analysis software (cvi42, CCI Inc., Calgary, CA) . Within the software, the blood volume was separated from surrounding motion artefacts. Four measurement planes were placed perpendicular to the vessel’s centerline, specifically proximal to the valve as a reference plane, 10 mm distal to the top of the valve, at the center of the ascending curvature and at the distal end of the aortic arch (Fig. ). At each plane, velocity, tangential WSS and pressure drop with respect to the reference plane were measured. Calculation of WSS followed the publication by Stalder et al.. It describes an interpolation of local velocity vectors along the contour of the underlying measuring plane. The effective orifice area (EOA) was calculated using the continuity equation (Eq. ) with the velocity time integral in the left ventricular outflow tract (LVOT) and aortic valve (AV) derived from the underlying MRI dataset. 1 [12pt]{minimal}
$$EOA= _{LVOT}^{2}* *{VTI}_{LVOT}}{{VTI}_{AV}}$$ E O A = d LVOT 2 ∗ π 4 ∗ VTI LVOT VTI AV Equation : Continuity equation to determine the EOA; d = diameter; VTI = velocity time integral. Sonographic imaging was performed using a dedicated sonography device (Resona 9, Mindray Medical Int. Ltd., Shenzhen, CN) and the v-flow protocol, developed for carotid artery imaging. For image acquisition a linear array transducer (L14-3WU, Mindray Medical Int. Ltd.) was placed on to the agar block in correspondence to the above-mentioned planes, placing the center of the transducer on the according plane. The acquisition window was increased to the biggest possible size (20 × 30 mm) while all other parameters were set to the most precise setting available (acquisition time: 2 s; acquisition quality: 7). Since the acquisition window was developed for application at the carotid bifurcation, measurements had to be split into two parts at the inner and outer curvature of the aorta to cover the entire cross-section, due to the smaller ROI of the acquisition window. Flow velocity, total WSS at five spots along the aortic wall as well as the oscillatory shear index (OSI) were calculated from the measurements. The OSI was calculated as an expression for the magnitude and change in direction of local WSS described by the following formula: 2 [12pt]{minimal}
$$OSI= *(1.0- )$$ O S I = 1 2 ∗ ( 1.0 - AWSSV AWSS ) where AWSSV = magnitude of the time-averaged WSS vector, and AWSS = time-averaged WSS magnitude .
MRI Image Analysis Visualization of flow patterns and pathlines was achieved in the aortic arch, the brachiocephalic trunk and the left subclavian artery (Fig. ). Visualization in the left common carotid artery proved difficult due to the smaller diameter of the vessel and was not achieved for all datasets. For the Masters mechanical valve, pathline visualization revealed a central jet during peak systole that closely followed the outer curvature of the ascending aorta. This led to a decentralized flow pattern with lower velocities along the inner curvature. During peak systole, recirculation zones with the formation of sinus vortices at both sides of the proximal aortic root were visible. WSS analysis revealed high local load on the outer curvature of the ascending aorta during peak systole, closely following the high velocity. Other parts of the aortic arch showed no increase in WSS during the systolic phase. The On-Xane mechanical valve showed a slightly less centralized jet during peak systole. This led to a more even distribution of flow velocity across the aortic diameter, while still showing a tendency towards higher flow velocities along the outer curvature. This even distribution could also be visualized in the WSS analysis, where a moderate load and distribution across the ascending aorta could be observed (Fig. ). The examination of the porcine bioprosthetic valve Epic showed a high velocity central jet hitting the outer curvature of the ascending aorta and partially reflecting onto the top of the inner curve. The central jet also showed a symmetric distribution with a tendency of tilting towards the outer curvature, resulting in an asymmetric distribution of systolic flow. WSS analysis revealed a high load on the outer curvature with an added high stress put on the anterior ascending aorta, close to the trunk. The Perimount bioprosthetic valve showed a central jet with high symmetric velocity, reflecting from the outer curvature of the ascending aorta. Visualization of WSS was consistent with the other bioprosthetic valves, where a high WSS occurred on the anterior wall of the ascending aorta. Lastly, the strong central jet could also be observed in the latest generation of bovine bioprosthetic valves, the Magna Ease. Here, the jet also showed a central symmetric velocity distribution distal to the valve followed by a tendency to adhere to the outer curvature, leading to asymmetric flow distribution. Due to the sharp angulation of the jet, wall shear stress was increased on the outer curvature close to the aortic root (Fig. ). Similarly, wall shear stress was also increased on the anterior side of the ascending curvature. MRI Quantitative Analysis Cross-sectional visualization of flow velocities and WSS for all valves can be seen in Fig. . Measured velocity values in the three ROI planes are shown in Fig. A. While all biological heart valves show a constant decrease in peak velocity between the planes, both mechanical heart valves cause an increase in peak velocity, reaching the highest value in the ascending aorta (Plane 2). In this study, the On-Xane mechanical valve reached the highest overall peak velocity of 265,6 cm/s in the ascending aorta while the Epic bioprosthetic valve exhibits the slowest velocity in the ascending aorta of 140.5 cm/s (Fig. A). Analysis of the tangential WSS presented the highest WSS closer to the aortic bulbus (Fig. , measuring plane 1) with a steady drop towards the descending aorta. The overall highest WSS could be observed for the Magna Ease biological valve at the aortic root, reaching 0.37 Pa (Fig. C). Peak pressure gradient measurement of mechanical valves between the proximal inlet and the aortic root revealed a gradient of 5.86 mmHg for the On-Xane valve and 8.50 mmHg for the Masters valve. The biological valves reached a peak pressure gradient of 7.67 mmHg for the Epic, 11.24 mmHg for the Perimount and 11.91 mmHg for the Magna Ease (Fig. E). Additionally, EOA was measured inside the respective valve, with On-X (2.8 cm 2 ) and Masters (2.1 cm 2 ) having the largest EOA, followed by the biological heart valves, Epic (2.0 cm 2 ), Perimount (1.4 cm 2 ) and Magna Ease (1.3 cm 2 ). Especially, the Perimount and Magna Ease valve showed artifacts around the valve mount, which led to some difficulties when setting the plane for velocity assessment in the LVOT. Sonographic Image Analysis Vector flow analysis of the surgical valves revealed overall strong signal during the systolic phase, while diastolic phase led to many visible artefacts (Video File in Supplement). In the aortic bulbus, the mechanical valves revealed a central jet, showcasing the disturbance created by the two semicircular leaflets (Fig. ). Both Masters and On-Xane mechanical valves displayed large recirculation areas and the distinct formation of vortices close to the coronary arteries. In the ascending aorta, as well as the descending aorta, flow patterns exhibited uniform flow with no distinct recirculation areas. The Epic bioprosthetic valve showed a broader central jet during peak systole with a distinct recirculation area above the aortic annular plane. For the Perimount valve, a broader central jet could be observed during peak systole, leading to a smaller low-flow area at the aortic wall. This also significantly reduced the occurrence of turbulences and recirculation. A similar behavior could be observed in the aortic root proximal to the Magna Ease valve, with a large recirculating turbulence next to the central jet (Fig. ). Similarly to the mechanical valves, the flow pattern in the ascending and descending aorta revealed a uniform flow with small recirculation areas for all biological valves. Sonographic Quantitative Analysis Analysis of peak flow velocity during systole revealed a similar behavior to the MRI analysis with mechanical valves showing a lower flow velocity in the aortic bulb, an increase in the ascending aorta, followed by a decrease in the descending aorta (Fig. B). Biological valves created the highest peak flow velocity in the aortic root with a steady decrease along the aortic arch. The highest overall velocity in the sonographic imaging was measured for the On-Xane valve at 263.6 cm/s. Biological valves displayed slightly lower peak velocities with the Perimount valve reaching the highest value of 237.9 cm/s directly in the aortic root. WSS measurements along the aortic wall also exposed big differences between mechanical and biological valves. The Masters valve (5.07 Pa) and the On-Xane valve (12.83 Pa) exhibited much higher total WSS in the aortic root compared to the biological valves (Epic: 2.55 Pa; Perimount: 2.46 Pa; Magna Ease: 1.53 Pa, Fig. D). In the ascending aorta, the WSS dropped for the mechanical valves and increased for the Epic and Perimount valve, with all valves reaching similar wall shear stress values in the descending aorta. The OSI as a measure for the change in direction and magnitude of WSS, is visualized in Fig. F. Mechanical valves reveal a higher initial OSI in the aortic root, with a drop in the ascending aorta. Biological valves showed a lower rate of change compared to the mechanical valves, with a slight drop of the OSI in the ascending aortic arch.
Visualization of flow patterns and pathlines was achieved in the aortic arch, the brachiocephalic trunk and the left subclavian artery (Fig. ). Visualization in the left common carotid artery proved difficult due to the smaller diameter of the vessel and was not achieved for all datasets. For the Masters mechanical valve, pathline visualization revealed a central jet during peak systole that closely followed the outer curvature of the ascending aorta. This led to a decentralized flow pattern with lower velocities along the inner curvature. During peak systole, recirculation zones with the formation of sinus vortices at both sides of the proximal aortic root were visible. WSS analysis revealed high local load on the outer curvature of the ascending aorta during peak systole, closely following the high velocity. Other parts of the aortic arch showed no increase in WSS during the systolic phase. The On-Xane mechanical valve showed a slightly less centralized jet during peak systole. This led to a more even distribution of flow velocity across the aortic diameter, while still showing a tendency towards higher flow velocities along the outer curvature. This even distribution could also be visualized in the WSS analysis, where a moderate load and distribution across the ascending aorta could be observed (Fig. ). The examination of the porcine bioprosthetic valve Epic showed a high velocity central jet hitting the outer curvature of the ascending aorta and partially reflecting onto the top of the inner curve. The central jet also showed a symmetric distribution with a tendency of tilting towards the outer curvature, resulting in an asymmetric distribution of systolic flow. WSS analysis revealed a high load on the outer curvature with an added high stress put on the anterior ascending aorta, close to the trunk. The Perimount bioprosthetic valve showed a central jet with high symmetric velocity, reflecting from the outer curvature of the ascending aorta. Visualization of WSS was consistent with the other bioprosthetic valves, where a high WSS occurred on the anterior wall of the ascending aorta. Lastly, the strong central jet could also be observed in the latest generation of bovine bioprosthetic valves, the Magna Ease. Here, the jet also showed a central symmetric velocity distribution distal to the valve followed by a tendency to adhere to the outer curvature, leading to asymmetric flow distribution. Due to the sharp angulation of the jet, wall shear stress was increased on the outer curvature close to the aortic root (Fig. ). Similarly, wall shear stress was also increased on the anterior side of the ascending curvature.
Cross-sectional visualization of flow velocities and WSS for all valves can be seen in Fig. . Measured velocity values in the three ROI planes are shown in Fig. A. While all biological heart valves show a constant decrease in peak velocity between the planes, both mechanical heart valves cause an increase in peak velocity, reaching the highest value in the ascending aorta (Plane 2). In this study, the On-Xane mechanical valve reached the highest overall peak velocity of 265,6 cm/s in the ascending aorta while the Epic bioprosthetic valve exhibits the slowest velocity in the ascending aorta of 140.5 cm/s (Fig. A). Analysis of the tangential WSS presented the highest WSS closer to the aortic bulbus (Fig. , measuring plane 1) with a steady drop towards the descending aorta. The overall highest WSS could be observed for the Magna Ease biological valve at the aortic root, reaching 0.37 Pa (Fig. C). Peak pressure gradient measurement of mechanical valves between the proximal inlet and the aortic root revealed a gradient of 5.86 mmHg for the On-Xane valve and 8.50 mmHg for the Masters valve. The biological valves reached a peak pressure gradient of 7.67 mmHg for the Epic, 11.24 mmHg for the Perimount and 11.91 mmHg for the Magna Ease (Fig. E). Additionally, EOA was measured inside the respective valve, with On-X (2.8 cm 2 ) and Masters (2.1 cm 2 ) having the largest EOA, followed by the biological heart valves, Epic (2.0 cm 2 ), Perimount (1.4 cm 2 ) and Magna Ease (1.3 cm 2 ). Especially, the Perimount and Magna Ease valve showed artifacts around the valve mount, which led to some difficulties when setting the plane for velocity assessment in the LVOT.
Vector flow analysis of the surgical valves revealed overall strong signal during the systolic phase, while diastolic phase led to many visible artefacts (Video File in Supplement). In the aortic bulbus, the mechanical valves revealed a central jet, showcasing the disturbance created by the two semicircular leaflets (Fig. ). Both Masters and On-Xane mechanical valves displayed large recirculation areas and the distinct formation of vortices close to the coronary arteries. In the ascending aorta, as well as the descending aorta, flow patterns exhibited uniform flow with no distinct recirculation areas. The Epic bioprosthetic valve showed a broader central jet during peak systole with a distinct recirculation area above the aortic annular plane. For the Perimount valve, a broader central jet could be observed during peak systole, leading to a smaller low-flow area at the aortic wall. This also significantly reduced the occurrence of turbulences and recirculation. A similar behavior could be observed in the aortic root proximal to the Magna Ease valve, with a large recirculating turbulence next to the central jet (Fig. ). Similarly to the mechanical valves, the flow pattern in the ascending and descending aorta revealed a uniform flow with small recirculation areas for all biological valves.
Analysis of peak flow velocity during systole revealed a similar behavior to the MRI analysis with mechanical valves showing a lower flow velocity in the aortic bulb, an increase in the ascending aorta, followed by a decrease in the descending aorta (Fig. B). Biological valves created the highest peak flow velocity in the aortic root with a steady decrease along the aortic arch. The highest overall velocity in the sonographic imaging was measured for the On-Xane valve at 263.6 cm/s. Biological valves displayed slightly lower peak velocities with the Perimount valve reaching the highest value of 237.9 cm/s directly in the aortic root. WSS measurements along the aortic wall also exposed big differences between mechanical and biological valves. The Masters valve (5.07 Pa) and the On-Xane valve (12.83 Pa) exhibited much higher total WSS in the aortic root compared to the biological valves (Epic: 2.55 Pa; Perimount: 2.46 Pa; Magna Ease: 1.53 Pa, Fig. D). In the ascending aorta, the WSS dropped for the mechanical valves and increased for the Epic and Perimount valve, with all valves reaching similar wall shear stress values in the descending aorta. The OSI as a measure for the change in direction and magnitude of WSS, is visualized in Fig. F. Mechanical valves reveal a higher initial OSI in the aortic root, with a drop in the ascending aorta. Biological valves showed a lower rate of change compared to the mechanical valves, with a slight drop of the OSI in the ascending aortic arch.
The introduction of additive manufacturing in the medical field enabled for the creation of highly accurate anatomical models based on underlying radiological data. This study focused on the application of the 3D-printing technology to create a flexible aortic arch for testing of the hemodynamics caused by the implantation of different surgical aortic valves. So far, the hemodynamic evaluation of such valves has been limited to PIV measurements using pulse duplicators. The advancements in computing power seen in the last decades accelerated the use of computational fluid dynamics, as well as 4D-Flow MRI to further investigate hemodynamics in the aorta . 4D-Flow MRI has proven to be a vital tool in clinical assessment with broad opportunities for further validation in an in-vitro setting . It allows for a holistic examination of the cardiovascular region of interest, opening new possibilities in the diagnosis and prevention of i.e., aortic aneurysms. The larger region of interest is especially beneficial when comparing the technology to PIV, where the camera only allows for a limited field of view. The measurement of WSS in the entire aortic arch is a clear benefit of the 4D-Flow MRI with numerous applications in both basic research and clinical routine. The WSS values measured in our 3D model show great comparability to the WSS values measured in patients by Bürk et al., who looked at the WSS in healthy and dilated aortas . While additional comparative studies are required, this shows a good initial approximation of the WSS values created by the flow loop to patient-based data. This slight discrepancy in WSS between our model and the values measured in patients can be explained by the mechanical properties of the 3D-printed aortic arch. Current 3D-printed flexible models lack the possibility to add fiber-orientation and therefore are not able to mimic the exact native aorta’s non-linear elastic behavior. Another explanation for this mismatch could be the material-geometry coupling of aortic replicas described by Comunale et al., which confirms, that not only material properties, but also geometry have an impact on the hemodynamic parameters . Besides the quantification of WSS, the localization of higher WSS areas is important to predict the risk of aortic aneurysm formation . The increase in both WSS and OSI has been associated with an upregulation of inflammatory markers . Especially, the localization of increased WSS on the anterior wall of the ascending aortic arch for all biological valves is a key finding of our study. This has been previously described by Farag et al., for patients undergoing transcatheter aortic valve replacement with a Sapien 3 transcatheter valve, where a large percentage of patients displayed an increase in WSS on the anterior wall compared to a control group . The increased WSS on the outer curvature of the ascending aortic arch observed is in accordance to previously described findings by in-vitro PIV studies . Another parameter measured via 4D-Flow MRI was the pressure drop across the artificial heart valves. The pressure gradient helps in the evaluation of the overall performance of native and artificial valves and is a standard parameter in the sonographic assessment of patients. For the mechanical valves, Hatoum et al. measured the pressure gradients for both the On-Xane as well as the SJM Masters valve reaching 4.15 and 4.75 mmHg in their in-vitro setting, respectively . Lee et al. analyzed the performance of Magna Ease bioprosthetic valves in patients who underwent surgical aortic valve replacement, where the mean pressure gradient for the 25 mm valve reached 12.2 mmHg . Compared to these studies, the pressure gradient for the mechanical valves was a bit lower in our study. While the pressure drop is a valuable metric in determining the performance of an artificial heart valve, comparison between in-vitro and in-vivo studies can prove challenging. A multitude of variables can have an impact on the measured pressure drop, ranging from the exact position of the measurement, the aortic diameter, measurement technique, prosthesis size and additionally, fluid viscosity in case of in-vitro studies. Pressure drops are therefore most comparable within the same experimental setup and a comparison to the aforementioned studies can only be seen as informative. The EOA of surgical valves is another factor having an influence on the transvalvular pressure and flow velocity. Different surgical valves with the same size (e.g., 25 mm) can have highly varying EOA. Pibarot et al. have determined the EOA of different surgical valve models and sizes for comparison, with the 25 mm Edwards Perimount having an EOA of 1.8 ± 0.4 cm 2 while the 25 mm On-X has a EOA of 2.4 ± 0.8 cm 2 . This corresponds to a difference in EOA of 33%, highlighting the importance of individualized prosthesis selection for every patient. The effect of the increased EOA can also be observed in our study, since the mechanical valves show a lower transvalvular pressure gradient compared to the biological valves. The usage of vector sonography is a rather young technique with great potential to improve treatment of cardiovascular patients. The current clinical use-case of quantifying the WSS in carotid arteries is a first step of improving one of the most commonly used radiological modalities . Its application in a benchtop setting offers great opportunities to analyze anatomical structures, which are not easily accessible in a clinical setting. Compared to the 4D-Flow MRI, vector ultrasound allows a much closer analysis of small cardiovascular structures and flow phenomena, like vortices at the aortic valve. In this study, motion artefacts were presented, especially during the diastolic phase, which might be caused by the reflective nature of the 3D-printed material. During the systolic phase, no artifacts were visible, allowing for a precise analysis of the flow conditions in the ROI. The observed vortices for both the mechanical and bioprosthetic valves match closely to the previously described hemodynamics caused by the different designs . The mechanical valves show three distinct forward jets with small recirculation zones distal to the valvular plane, while the bioprosthetic valves display one larger central forward jet with counter-rotating recirculation areas surrounding the central jet. The design improvements from the Perimount to the Magna Ease valve could be partially confirmed in the quantitative analysis. The Magna Ease, which is designed to have a smaller sewing ring and therefore larger EOA has lower WSS in the aortic root, whereas the Perimount valve shows a slightly higher velocity at the aortic arch. The biggest difference in the parameters derived from MRI and ultrasound is the WSS, especially in the aortic root. Vector ultrasound presents consistently higher WSS values, reaching a tenfold higher value for the On-X mechanical valve. These WSS values are much closer to values derived from CFD analyses of the aortic arch . The difference could also be explained by the different measurement techniques employed by MRI and vector ultrasound. MRI using an interpolation of velocity vectors along a circumferential contour, while vector ultrasound uses singular points in the longitudinal axis of the aortic wall.
While this study presents in-vitro results that are comparable to clinical data, there are still a few limitations to the setting. Firstly, the flexible material used for the anatomical aortic arch does not offer the same mechanical properties as a native human aorta. The fixed wall thickness and linear elastic behavior of the material are clear limitations. Furthermore, as described in the discussion, the geometry of the arch has an additional impact on the hemodynamic parameters. To minimize the effects of these three aspects, we decided to use the same arch design for all valves to properly compare them, nevertheless, this is an aspect that has to be taken into account when evaluating the collected data. Additionally, the presented model is lacking coronary perfusion. Due to the mechanical properties of the printing material, inclusion of coronary vessels would have led to an unnatural enlargement of the aortic root, which was previously described by other research groups as well. Secondly, although vector ultrasound presents a promising technique to analyze hemodynamic effects in the cardiovascular system, the technique is still rather new and requires further improvements to become a staple in the clinical field. Especially the limited depth of the ROI window represents a limitation when analyzing the aorta, since there is no possibility to examine the entire cross-section at once. Finally, this pilot-study lacks the comparison to measurements in a real-life patient, which is a clear limitation.
Combining novel radiological imaging modalities with 3D-printed anatomical models offer great possibilities to further improve the in-vitro analysis of the hemodynamic effects of medical implants. This will be a valuable addition to a more patient-oriented medicine that can prevent patient-prosthesis mismatch and reduce overall complication rate through the usage of patient-specific anatomies in the mock circulatory loop. This study presents a first pilot study, which will lead to further research projects, focusing on the analysis of other cardiovascular implants, as well as the impact of specific anatomical configurations on the hemodynamic.
Below is the link to the electronic supplementary material. Supplementary file1 4D-MRI Visualization of Flow Pathlines in a 3D printed aortic arch with a Magna Ease valve implanted (MP4 1459 KB) Supplementary file2 Vector Ultrasound Visualization of the Aortic Bulbus right after a Magna Ease biological heart valve (MP4 12599 KB) Supplementary file3 (MP4 863 KB) Supplementary file4 (MP4 12619 KB) Supplementary file5 (JPG 904 KB) Supplementary file6 (PNG 90 KB)
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Diagnostic accuracy of a minimal immunohistochemical panel in at/rt molecular subtyping, correlated to dna-methylation profiling | fc285084-8a12-4aa0-a950-6f5b27017f8a | 10440909 | Anatomy[mh] | Below is the link to the electronic supplementary material. Supplementary Material 1: Fig. S1. t-distributed stochastic neighbor embedding (t-SNE) analysis of the DNA methylation profiles of the 51 investigated tumors alongside selected reference samples of the DKFZ classifier (v12.5). Reference DNA methylation classes: AT/RT, MYC (Atypical teratoid/rhabdoid tumor, MYC-subtype); AT/RT, SHH (Atypical teratoid/rhabdoid tumor, SHH-subtype), AT/RT, TYR (Atypical teratoid/rhabdoid tumor, TYR-subtype), CNS NB, FOXR2 (CNS neuroblastoma, FOXR2-activated), CNS tumor, BCOR ITD (CNS tumor with BCOR internal tandem duplication); CTRL, HEMI (Control tissue, cerebral hemisphere); ETMR, C19MC (Embryonal tumor with multilayered rosettes, C19MC-altered); ETMR, DICER1 (Embryonal tumor with multilayered rosettes, DICER1-altered); MB, non-WNT/ non-SHH (Medulloblastoma, non-WNT, non-SHH); MB, SHH (Medulloblastoma, SHH-activated); MB, WNT (Medulloblastoma, WNT-activated). Cohort cases are designated by their number Supplementary Material 2: Fig. S2. Additional immunohistochemical results.A: Comparison of results for molecular subtyping using nineteen different immunohistochemical panels (x: panels; y: number of cases). NEC: Not Elsewhere Classified. *designate the panels with the highest accuracy for subtyping. B: Discrepant cases with immunohistochemical findings (magnification x400). Black scale bars represent 50 μm Supplementary Material 3: Detailed data of the cohort and synthesis
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Leveraging swin transformer with ensemble of deep learning model for cervical cancer screening using colposcopy images | 2a05627f-bb99-461e-8fa2-50467d7aaf95 | 11885420 | Surgical Procedures, Operative[mh] | In emerging countries, CC is the most common cancer among adults and teenage women globally. It initiates in the cervix, and it is mainly affected by sexually-attained infection with HPV. CC is a significant health-worsening tumorous infection that is common among females in the world . As per the International Agency for Study on Cancer, because of CC, the mortality rate of India is in second place and third place globally. An increasing rate of CC is still unknown, and there is no effective method to evade it, even if women don’t experience any particular symptoms during the initial phases . So, the initial recognition of CC or precancerous phase can decrease the mortality rates owing to CC. A CN diagnosis is a histologic analysis attained from biopsies of the suspicious lesions without or with colposcopy; treatment is suggested. Screening for CN could be achieved by cytological check-ups, HPV screening, or colposcopy images . Colposcopy is a standard treatment to prevent CC. Early classification and detection of this cancer can substantially improve the patient’s medical care. Many studies were conducted using many methods for gathering details from images in digital colposcopy. This research aims to give health physicians utensils in colposcopy examinations regardless of their capability level . Earlier research has improved diagnosis by utilizing computer-aided methods for a task range, containing evaluation and enhancement of image quality, picture identification, regional segmentation, unstable areas and patterns identification, cancer risk classification, and type of transition zone (TZ) type classification. In the medical field, using artificial intelligence (AI) can enhance care and cost quality . Though ML can handle a massive quantity of data in a relatively short period and is effectively used in several medical conditions, the efficient usage of ML in real medical practice remains challenging. Many researchers have displayed the possibility of AI medical applications enhancing the quality of diagnostics in CN. DL is a sector of AI and ML that is very effective in many areas, such as government, education, business, and health care . By attaining human corresponding performance, DL has effectively changed other ML methods for applications such as computer vision processing and recognition. DL contains many layers of computational data processing methods that permit learning by giving input data through various abstraction levels. In recent times, DL has been utilized effectively to resolve real problems in extensive applications . DL approaches are an outstanding basis for improving medical image analysis in different clinical and research areas, such as diagnosing and detecting various cancers. Generally, DL techniques like VGG-19, ResNet-50, SAE, DenseNet-121, CNN, ResNet-18, ResNet-152, Xception, DenseNet-169, and Inception v3 are utilized to identify CC over the images of colposcopy . CC remains a major cause of mortality among women, specifically in developing countries, where access to early detection and efficient treatment is often limited. Despite advances in healthcare, the need for noticeable symptoms in the early stages makes diagnosing and treating the disease difficult . Early detection of CC or its precursors significantly mitigates the risk of progression, thus enhancing survival rates. With the growing global burden, there is an urgent requirement for reliable, accessible screening methods to detect CC at its earliest and most treatable stages. Utilizing advanced technologies, namely DL models, can significantly improve the accuracy and efficiency of screening systems, giving a timely solution for improved healthcare outcomes . This study presents a Leveraging Swin Transformer with an Ensemble of Deep Learning Model for Cervical Cancer Screening (LSTEDL-CCS) technique for colposcopy images. The presented LSTEDL-CCS technique aims to detect and classify CC on colposcopy images. Initially, the wiener filtering (WF) model is used for image pre-processing. Next, the swin transformer (ST) network is utilized for feature extraction. For the cancer detection process, the ensemble learning method is performed by employing three models, namely autoencoder (AE), bidirectional gated recurrent unit (BiGRU), and deep belief network (DBN). Finally, the hyperparameter tuning of the DL techniques is performed using the Pelican Optimization Algorithm (POA). A comprehensive experimental analysis is conducted, and the results are evaluated under diverse metrics. The major contribution of the LSTEDL-CCS model is listed below. The LSTEDL-CCS technique utilizes a WF-based pre-processing method to improve the quality of input colposcopy images. This enhancement enables more effectual feature extraction, facilitating better model performance. By using WF, the methodology addresses noise and distortion, resulting in more accurate results in CC detection. An ST network is utilized for advanced feature extraction, effectively capturing local and global colposcopy images’ dependencies. This approach enables the model to understand complex patterns and significant variances better for accurate cancer detection. By employing the merits of the ST, the LSTEDL-CCS model improves the overall performance of the detection system. The LSTEDL-CCS approach utilizes three DL methods: AE, BiGRU, and DBN to improve cancer detection accuracy. Each model brings a unique approach, complementing the others to improve classification performance. These diverse models work together, confirming a robust and reliable detection system for CC. The POA model is used for hyperparameter tuning to optimize model performance. By finetuning the parameters, POA improves the detection accuracy of the DL methods. This optimization ensures the models attain improved results in CC detection, improving overall system efficiency. The LSTEDL-CCS technique integrates the ST with an ensemble of DL models, improving feature extraction and classification accuracy for CC detection. By integrating AE, BiGRU, and DBN, the method captures a range of intrinsic patterns in colposcopy images. Furthermore, POA-based hyperparameter tuning optimizes model performance, improving detection accuracy. This unique incorporation of advanced architectures and optimization techniques sets the approach apart in cancer detection systems. The article is structured as follows: Sect. 2 presents the literature review, Sect. 3 outlines the proposed method, Sect. 4 details the results evaluation, and Sect. 5 concludes the study.
Mukku and Thomas presented a segmentation network utilizing AI. A computational method is used to train and develop a DL method, which is particularly personalized for cervix regions and acetowhite lesion segmentation in cervical imageries. The segmentation technique based on effective net structure and atrous spatial pyramid pooling was intended to delineate and detect the objective areas precisely. In , the authors propose a model to improve DL-based techniques for effectual CC detection by integrating cytology and colposcopy screening. It uses DeepCyto + for cytology and DeepColpo for colposcopy images. The methods have been trained on many datasets, including the self-collected CC dataset. The ensemble method incorporates DeepCyto + and DeepColpo by utilizing ML methods. Jiménez Gaona et al. proposed and previously authorized a method that depends on the U-net and SVM models to identify cervical lesions on colposcopy imageries. Dual image sets are utilized: the Intel and Mobile ODT CC Screening private, a public dataset in a regular colposcopy, and afterwards, the lugol and acetic acid applications. The related medical data has been gathered, particularly cytology on the PAP smear and the screening of HPV analysis before colposcopy. The cervix lesions or areas of interest are classified and segmented using the U-net and SVM methods. Rakesh et al. offer dual CNN structures based on DL for CC identification over colposcopy image analysis. The methods utilized in this study are CYENET and VGG19 (TL). VGG19 as a TL method was used in the CNN structure for research. The Colposcopy Ensemble model was presented as a new method for the CC automatic classification from colposcopy images. In , a DL-based model is proposed to identify cervical transformation areas from colposcopy images automatically. Cervical regions are initially identified from unique colposcopy images and then served in the multiscale feature fusion classification model. Yu et al. developed a cervical lesion segmentation (CLS) model. Initially, the enhanced Faster (R-CNN) has been utilized to get the cervical region without interfering with other instruments or tissues. After that, a deep CNN was presented that utilized EfficientNet-B3 to mine the features of the cervical area and used the restructured ASPP model based on the lesion region size and the feature map after sub-sampling to seizure multiscale features. Then, the segmentation outcome has been mapped to the unique image. Saranya and Sujatha evaluate and propose a DL method based on Mask R-CNN and Adam optimizer for automatic segmentation and detection of cervical lesions in colposcopy images. The presented method uses Mask R-CNN, a deep CNN equal to object instance and detection segmentation. Pretrained on the COCO dataset, the method is improved on a considered colposcopy image dataset for CLS and detection. Adam optimization, an effective gradient descent method, is utilized to increase the training method of the model. Kalbhor et al. developed a method for CC prediction depending on the images of pap smears. Pretrained DNN methods are utilized for feature extraction, and various ML methods have been trained on extracted features. In the presented approach, four pre-trained methods are finetuned for feature extraction, which is succeeded by the various ML methods. Ali and Mohammed review and assess the latest research on omics-related AI methods, highlight the threats in omics data analysis, and demonstrate the potential of AI in addressing these challenges. Lakhan et al. propose a secure Blockchain Internet of Medical Things (BIoMT) architecture for lung cancer data fusion in fog-cloud networks, utilizing the Blockchain Data Fusion Secure (BDFS) approach. Mohammed and Ali improve cancer subclassification accuracy by incorporating multiple omics data using the Quantum Cat Swarm Optimization (QCSO) model for feature selection, integrated with K-means clustering and Support Vector Machine (SVM) for classification. Pacal and Kılıcarslan utilize advanced DL techniques, comprising CNN and Vision Transformer (ViT), data augmentation and ensemble learning, to improve the accuracy of CC diagnosis. Mohammed et al. explore the usage of an ST and Convolutional Neural Network (CNN) hybrid model, incorporated with the transfer learning (TL) method, for classifying precancerous colposcopy images to improve early CC diagnosis. Darwish, Altabel, and Abiyev developed an automatic cervix-type identification system by utilizing a ViT improved with shifted patch tokenization (SPT) to distinguish between three cervical precancerous kinds. Alohali et al. present Swin-GA-RF, a novel approach integrating ST, genetic algorithm (GA)-based feature selection, and random forest (RF)-based classification to improve cervical cell classification in Pap smear images, improved with data augmentation techniques. Fan et al. present a Conjugated Attention Mechanism and Visual Transformer (CAM-VT) approach for improved accuracy. Chatterjee and Siddiqui propose a lesion-specific multi-branch architecture by integrating attention mechanisms, deep feature extraction, and ensemble learning for colposcopy image classification, utilizing EfficientNetB0 and MobileNetV2 with classifiers such as Logistic Regression (LR), XGBoost, and CatBoost, optimized through hyperparameter tuning and cross-validation. Hemalatha, Vetriselvi, and Dhandapani propose an automated system for classifying unsegmented cervical cell images using CNN and ViT models, with a novel cervix feature fusion (CFF) and fuzzy feature selection (FFS) methods for improved classification of cell abnormalities. Mathivanan et al. developed a hybrid methodology incorporating pre-trained deep neural networks (DNNs) and ML models for improved CC detection. Hamdi et al. develop automated WSI image analysis models using the Active Contour Algorithm (ACA) for segmentation and hybrid DL models such as ResNet50, VGG19, GoogLeNet, RF, and SVM for classification. Hemajothi et al. developed an AI-driven system using Vision Transformer models for early and accurate CC detection, ensuring ethical compliance, clinical validation, and improved patient outcomes. Jin et al. propose an E-UNet + + architecture with an EfficientNet encoder for effectual multiscale feature encoding and fine-grained detail detection. Nirmala et al. propose an automatic CC classification system by utilizing DL models, comprising pre-processing, segmentation with ADRAN, and classification with AVTE and CNN. Hyperparameters are optimized by employing the Adaptive Cat Swarm Optimization (ACSO) approach. Permana and Setiawan review DL and ML models for CC detection using colposcopy images. Abinaya and Sivakumar present a CC classification system by utilizing 3D CNN for feature extraction, a Vision Transformer (ViT) for complex feature learning, and a Kernel Extreme Learning Machine (KELM) technique for final classification. Tang et al. propose a high-precision CC screening method using ConvNeXt, self-supervised data augmentation, and ensemble learning for feature extraction and inter-class discrimination. Mehedi et al. efficiently detect CC types using the novel lightweight DL model CCanNet, which incorporates squeeze blocks, residual blocks and skip layer connections. Harika et al. propose a CC classification method using CNN with ResNet50 architecture applied to the SIPAKMED pap-smear dataset, enhancing feature extraction and classification. Despite the advancements in CC detection using AI-based techniques, various limitations and research gaps still exist. The lack of high-quality labelled datasets, particularly for rare cancers, remains a major threat. Multimodal image fusion and incorporating diverse datasets for enhanced diagnosis accuracy still need to be explored. While diverse models have been proposed, they often need help in generalization and overfitting, specifically when applied to diverse real-world data. Furthermore, the explainability of DL techniques in medical applications needs additional attention, as black-box models deter trust and clinical acceptance. Most studies also concentrate on specific image types or datasets, and there is a requirement for more comprehensive models that can handle various imaging modalities together. Moreover, ensuring ethical compliance, privacy, and data security in AI models remains a critical research gap, particularly in cloud-based solutions.
The manuscript introduces a LSTEDL-CCS technique for colposcopy images. The presented LSTEDL-CCS method mainly emphasizes classifying and identifying CC on colposcopy images. The LSTEDL-CCS approach performs WF-based image pre-processing, ST network-based feature extraction, AE, BiGRU, DBN-based cancer detection, and POA-based hyperparameter tuning. Figure signifies the entire procedure of the LSTEDL-CCS technique. Image pre-processing The LSTEDL-CCS model performs pre-processing of the images using the WF model . This method is chosen due to its efficiency in noise reduction while preserving significant image details. The WF method is particularly suited for medical image processing as it adapts to local image discrepancies, ensuring that noise is minimized without blurring crucial features. Compared to other denoising techniques, such as Gaussian filters, the WF provides an optimal trade-off between smoothing and edge preservation, making it ideal for maintaining the fine details required in CC detection. Furthermore, it is computationally effectual and capable of handling noisy datasets, which is common in medical imaging due to discrepancies in image quality and lighting conditions. By mitigating noise and enhancing the clarity of features, the WF improves the accuracy of subsequent feature extraction and classification stages. This makes it a reliable choice over more complex or slower methods. Figure specifies the WF structure. The WF is a method employed in image processing to reduce noise and improve image quality. When functional to colposcopy images for CC recognition, WF aids in increasing the detail and clarity of the images by minimalizing the effect of noise. This increases the visibility of significant features like lesions and abnormal tissue structures, vital for precise diagnosis. By offering more detailed and cleaner images, WF supports superior recognition and evaluation of CC, eventually assisting in more effectual medical evaluations and cure planning. Feature extraction process The feature extraction method of the LSTEDL-CCS approach is performed by an ST network , . This model is selected due to its ability to capture local and global dependencies in images. Unlike conventional CNNs, the ST model utilizes shifted window attention mechanisms, enabling it to handle large-scale image data while maintaining computational efficiency effectually. This methodology outperforms in extracting hierarchical features at multiple scales, specifically beneficial for medical imaging, where fine-grained and multi-level data is critical for accurate diagnosis. Furthermore, the ST model adapts well to high-resolution images, making it ideal for intrinsic CC detection tasks. Its flexibility in handling variable input sizes and robust performance in various image recognition tasks make it a more robust and versatile choice related to older techniques, such as CNNs or simpler transformers. The technique’s capability to generalize across diverse datasets improves its efficiency in medical imaging applications. Figure represents the structure of the ST network. The Transformer method is a usual Encoder-Decoder model that utilizes a Multi-Layer Perceptron (MLP) technique for positional channel and embedding mixings. It uses the mechanisms of Multi‐Head Self‐Attention (MSA) and Self‐Attention (SA) models for positional relationship modelling. It is primarily presented for natural language processing (NLP); the Transformer structure was given to the computer vision field over innovative works, such as VIT. The self‐attention mechanism computes the significance of all inputs to the method. In the VIT self‐attention layer, normalized dot product attention is utilized to calculate the associations among every input location. The self‐attention layer initially applies three independent linear transformations, producing the query matrix [12pt]{minimal}
$$\:Q$$ , key matrix [12pt]{minimal}
$$\:K$$ , and value matrix [12pt]{minimal}
$$\:V$$ . The computation was formulated below: 1 [12pt]{minimal}
$$\:Q=X{W}_{q},\:K=X{W}_{k},\:V=X{W}_{v}$$ [12pt]{minimal}
$$\:{W}_{q},{W}_{k},{\:and\:W}_{v}$$ are the parameter matrices, and [12pt]{minimal}
$$\:X$$ is the input matrix. The product of [12pt]{minimal}
$$\:K$$ and [12pt]{minimal}
$$\:Q$$ and the Softmax function is utilized to compute the attention weight of every location, and the weighted quantity of all locations is utilized as the self-attention layer output, computed as: 2 [12pt]{minimal}
$$\:{F}_{A}(Q,\:K,\:V)=\:(^{T}}{_{k}}})V$$ whereas [12pt]{minimal}
$$\:{F}_{A}$$ denotes the attention layer, [12pt]{minimal}
$$\:\:$$ represents the activation function of Softmax, and [12pt]{minimal}
$$\:{d}_{k}$$ is the size of [12pt]{minimal}
$$\:K$$ . The attention weight matrix is separated by [12pt]{minimal}
$$\:{d}_{k}$$ to remove excessive change from impacting the backpropagation (BP) and secure the optimization method. VIT is extensively used in various computer vision tasks, as illustrated by the Dual-Branch Geometric Attention model for accurate LCNet and 3D dental method segmentation that improves numerical efficacy over a partial-channel transformation strategy, lowering latency and hardware needs. The ST is a worldwide feature extraction submodule for handling imagery. SW-MSA and W‐MSA subblocks are used consecutively in dual consecutive ST blocks. The mathematical calculation is represented below: 3 [12pt]{minimal}
$$\:{}^{l}={W}_{MSA}(LN({z}^{l-1}))+{z}^{l-1}$$ 4 [12pt]{minimal}
$$\:{z}^{l}=MLP(LN({}^{l}))+{}^{l}$$ 5 [12pt]{minimal}
$$\:{}^{(l+1)}={W}_{MSA}(LN({z}^{l}))+{z}^{l}$$ 6 [12pt]{minimal}
$$\:{z}^{(l+1)}=MLP(LN({}^{(l+1)}))+{}^{(l+1)}$$ [12pt]{minimal}
$$\:{}^{l},{z}^{l}$$ represent the output features of the [12pt]{minimal}
$$\:W$$ - [12pt]{minimal}
$$\:MSA\:and\:MLP$$ sub-blocks of the first block and [12pt]{minimal}
$$\:{}^{l+1}$$ , [12pt]{minimal}
$$\:{z}^{l+1}$$ denotes the output features of the [12pt]{minimal}
$$\:SW-MSA\:and\:MLP$$ sub-blocks of the second block, correspondingly. The W-MSA sub-block divides an input feature map into several nonoverlapping and calculates self-attention. This approach substantially decreases the network’s numerical difficulty. However, owing to the portioning of windows, the usage of [12pt]{minimal}
$$\:W$$ ‐MSA may cause data loss. To tackle this problem, the ST submodule uses a SW‐MSA sub-block. It combines an offset matrix [12pt]{minimal}
$$\:B\:{R}^{{M}^{2}\:{M}^{2}}$$ while computing self‐attention as represented below: 7 [12pt]{minimal}
$$\:Attention(Q,\:K,\:V)=SoftMax(^{T}}{}+B)V$$ whereas [12pt]{minimal}
$$\:Q,K,V\:{R}^{{M}^{2}\:d}$$ represent the query, key, and value matrices; correspondingly, [12pt]{minimal}
$$\:d$$ represents the size, and [12pt]{minimal}
$$\:{M}^{2}$$ represents the patch count. The matrix [12pt]{minimal}
$$\:B$$ is attained from the offset matrix [12pt]{minimal}
$$\: R^{{( {2M - 1} ) ( {2M - 1} )}} .$$ The SW-MSA subblock enables data propagation. By integrating the SW‐MSA and W‐MSA subblocks, the ST submodule can effectively manage large images and efficiently seize worldwide features. Ensemble learning classifiers The LSTEDL-CCS approach performs the cancer detection process by utilizing AE, BiGRU, and DBN models for the classification process. This ensemble model is chosen due to their complementary strengths in feature extraction and sequence modelling. The AE effectually mitigates dimensionality and learns a compact representation of complex data, which assists in removing noise and improving the accuracy of subsequent models. BiGRU, a variant of the GRU, outperforms in capturing long-range dependencies in sequential data, making it ideal for analyzing temporal or structured patterns in medical imaging data. The DBN, known for its DL capabilities, improves the feature extraction process by stacking layers of unsupervised networks, which assists in learning intrinsic hierarchical features. This integration of models allows for a robust, multifaceted approach to cancer detection, outperforming conventional techniques that may depend on simpler feature extraction or shallow learning. Integrating AE, BiGRU, and DBN gives a robust, scalable solution with superior generalization capabilities, making it appropriate for complex medical datasets. AE model The AE becomes a DL approach that reconstructs the inputs for an output layer2 . The AE’s symmetric structure enables the attainment of a less-dimension illustration of the input data inside the main hidden layer (HL). Its principal intention was to transfer the input data that usually occurs in higher- to lower‐dimensional spaces. This decoder designates the element between the middle and the output layers that can recreate the primary information. The intermediary layer was generally termed the bottleneck layer. The node counts in these layers have been directly proportional to the input vector dimensions utilized for encoding. The encoding and decoding processes are represented in Eqs. and as below: 8 [12pt]{minimal}
$$\:{x}_{i}=f(WX+bias)$$ 9 [12pt]{minimal}
$$\:=\:({W}^{{\:}}X+bia{s}^{{\:}})$$ The input vector, represented as [12pt]{minimal}
$$\:X$$ , can be decoded and encoded with the vectors [12pt]{minimal}
$$\:{x}_{i}$$ and [12pt]{minimal}
$$\:{}_{i}.f$$ and [12pt]{minimal}
$$\:{f}^{{\:}}$$ remain activation functions in decoding and encoding elements correspondingly, and that is chosen for the sigmoid functions. [12pt]{minimal}
$$\:W$$ and [12pt]{minimal}
$$\:{W}^{{\:}}$$ correspondingly represent the matrix weight of the HL’s input and output layers. Biased vectors are typically characterized as [12pt]{minimal}
$$bias^{}$$ and [12pt]{minimal}
$$\:bias$$ . The DAE aim is to minimize the rebuilding [12pt]{minimal}
$$\:loss$$ among the input and output values of [12pt]{minimal}
$$\:{x}_{i}$$ & [12pt]{minimal}
$$\:{}_{i}$$ that are mathematically signified as Eq. : 10 [12pt]{minimal}
$$loss( {W,bias,W^{},bias^{}} ) = _{{i = 1}}^{t} {\| {x_{i} - _{i} } \|^{2} }$$ It describes the hyperparameters, which are good in the training method for a deep AE. After training, the latent depiction can be gained from the intermediary layer of the AE. Figure depicts the structure of the AE method. BiGRU technique Recurrent neural networks (RNNs) can memorize prior inputs, prepare them suitable for processing time-sequence data, and are primarily effectual at removing sequential features from curves . However, standard RNNs are delayed by problems associated with the exploding or vanishing of gradients, limiting their capacity to maintain long‐term memory. The GRU was introduced to overcome the dependency problems of RNNs. These networks increase additional reset and update gates in every recurrent unit to control the input, which lets the network preserve state data across long periods. The structure of the GRU element operates based on the succeeding equations: 11 [12pt]{minimal}
$$\:{z}_{t}=\:({W}_{i}{x}_{t}+{b}_{iz}+{W}_{h}z{h}_{t-1}+{b}_{hz})$$ 12 [12pt]{minimal}
$$\:{r}_{t}=\:({W}_{ir}{x}_{t}+{b}_{ir}+{W}_{hr}{h}_{t-1}+{b}_{hr})$$ 13 [12pt]{minimal}
$$\:{}_{}=({W}_{in}{x}_{t}+{b}_{in}+{r}_{t}\:({W}_{hn}{h}_{(t-1)}+{b}_{hn}))$$ 14 [12pt]{minimal}
$$\:{h}_{t}=(1-{z}_{t})\:{h}_{(t-1)}+{z}_{t}\:{}_{}$$ Now, [12pt]{minimal}
$$\:{h}_{t-1}$$ signifies HL, [12pt]{minimal}
$$\:{x}_{t}$$ means present input, and [12pt]{minimal}
$$\:\:$$ represents sigmoid activation function; [12pt]{minimal}
$$\:{r}_{t}$$ and [12pt]{minimal}
$$\:{z}_{t}\:$$ signify the gates of reset and update; [12pt]{minimal}
$$\:{}_{t}$$ and [12pt]{minimal}
$$\:{h}_{t}$$ specify the candidate and final HL; [12pt]{minimal}
$$\:W$$ exists weight matrix, [12pt]{minimal}
$$\:\:$$ indicates Hadamard products, and [12pt]{minimal}
$$\:b$$ stands for the biased parameter. Figure demonstrates the architecture of the BiGRU model. GRUs can design the BiGRU, processing time-sequence data in contrasting orientations over two‐layer GRU networks. Every orientation has been formed to handle both future and historical data. These bidirectional architectures allow the BiGRU to take data inside the information accurately, thus improving the rebuilding model’s performance. DBN architecture Among the classes of DBN and DNN is a dynamic graphic method . This deep-layer network has generated many RBM networks, constructed on each other. Every two sequential HLs that compose a DBN architecture create an RBM. Usually, the preceding RBM output assists as the next RBM’s input layer. A deep hierarchical group of training information creates a DBN graphic model. The succeeding equation can be applied to explain the combined probability distribution of visible vectors [12pt]{minimal}
$$\:v$$ and [12pt]{minimal}
$$\:l$$ HL [12pt]{minimal}
$$\:({h}_{k}(k=,\:,\:l),\:{h}_{0}=v)$$ 15 [12pt]{minimal}
$$\:P({h}_{1},\:{h}_{2},\:,\:{h}_{l}|v)=P({h}_{1}|{h}_{l-1})P({h}_{l-1}|{h}_{l-2})\:P({h}_{1}|v)={\:}_{k=1}^{l}P({h}_{k}|{h}_{k-1})$$ Based on these definitions, the probability that an inference should be prepared from the HL [12pt]{minimal}
$$\:{h}_{k}$$ to visible layer [12pt]{minimal}
$$\:v$$ can be stated as: 16 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({b}_{j}^{k}+{\:}_{j=1}^{m}{w}_{ij}^{k}{h}_{j}^{k-1})$$ Whereas [12pt]{minimal}
$$\:{b}^{k}$$ is specified as [12pt]{minimal}
$$\:{k}^{th}$$ layer bias. Similar to bottom-up inference, the top‐down inference has been indicated in the subsequent symmetric method: 17 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({a}_{j}^{k-1}+{\:}_{j=1}^{m}{w}_{ij}^{k-1}{h}_{j}^{k})$$ where [12pt]{minimal}
$$\:{a}^{k}$$ are named as [12pt]{minimal}
$$\:(k-1{)}^{th}$$ layer bias. BP and pre-training are the two segments of a DBN’s training process. DBN training has been effectively achieved over finetuning and pre‐training. Figure portrays the structure of the DBN model. Hyperparameter tuning process Eventually, the hyperparameter tuning process of the LSTEDL-CCS model is accomplished by utilizing the POA model . This method is chosen because it can handle intrinsic, high-dimensional optimization problems commonly faced in DL models. POA is a bio-inspired optimization technique that replicates the foraging behaviour of pelicans, enabling it to search large solution spaces while averting local minima efficiently. Unlike conventional gradient-based methods, POA does not require gradient information, making it more appropriate for models with non-differentiable loss functions. Its robustness in dealing with multimodal and noisy search spaces makes it ideal for tuning hyperparameters in models like LSTEDL-CCS, which may exhibit complex, nonlinear relationships between parameters. Furthermore, the flexibility and strong convergence properties of the POA model improve its capability to deliver optimal solutions in a relatively short time, making it preferable over other optimization techniques, namely GAs or particle swarm optimization (PSO). Figure illustrates the workflow of the POA model. For data analysis, the POA is employed to increase accuracy and efficacy. The approach is nominated to enhance the BP neural networks method because of the global search ability, versatile finetuning mechanism, and efficacy in trading with multifaceted nonlinear issues that permit it to perceptively direct the weight upgrade and efficiently evade local optimizer by presenting major benefits in enhancing training efficacy and ultimate precision. The POA is a heuristic technique that pretends to be pelicans’ natural strategies and behaviours during hunting and attack. This exclusive hunting technique entails dual phases, such as approaching the prey and surface fight. Prey approach stage In this phase, the pelicans recognize their victim’s position and then travel near the objective region. By exhibiting this pelican hunt plan, the search space is effectively examined, and POA’s search abilities are utilized to discover dissimilar areas in the search space. The mentioned models and the numerical calculation of pelicans’ poignant near-prey location are expressed in Eq. . 18 [12pt]{minimal}
$$\:{x}_{i,j}^{{P}_{1}}=\{_{i,j}+rand\:\:({p}_{j}-I.{x}_{i,j}),&\:{F}_{p}<{F}_{i},\\\:{x}_{i,j}+rand\:({x}_{i,j}-{p}_{j}),&\:else,.$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel state of [12pt]{minimal}
$$\:an\:ith$$ pelican in [12pt]{minimal}
$$\:a\:jth$$ dimension defined by the randomly generated parameter [12pt]{minimal}
$$\:I$$ , where it is fixed to 1 or 2. [12pt]{minimal}
$$\:{p}_{j}$$ signifies the location of prey in [12pt]{minimal}
$$\:the\:jth$$ dimension. [12pt]{minimal}
$$\:{F}_{p}$$ means the value of the objective function. [12pt]{minimal}
$$\:I\:$$ is selected at random for every member of Pelican and iteration. If [12pt]{minimal}
$$\:I$$ is equivalent to 2, then it stimulates the members of the Pelican to create a greater shift that leads them to discover novel zones that were not visited previously. The POA method defines the novel pelican position when the objective function is enhanced. This upgrade is effective because it certifies that the technique does not drop into a non-optimal area. The complete upgrading method has been demonstrated in Eq. . Here, [12pt]{minimal}
$$\:{X}_{i}^{P1}$$ denotes the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P1}$$ depends upon the value of the objective function of the primary phase. 19 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{1}},{F}_{i}^{{P}_{1}}<{F}_{i;}.\\\:{X}_{i},\:else,.$$ Surface flight stage In this phase, if the pelicans arrive at the surface, they extend their wings to carry the prey from the sea and finally gather it in their throat. This exclusive hunting approach permits the pelicans to capture the fish in their attack region. The developed POA is warranted to unite an enhanced solution for the hunt region. Its mathematical formulation is expressed below: 20 [12pt]{minimal}
$$\:{x}_{i,{j}^{2}}^{P}={x}_{i,j}+R\:(1-)\:(2\:rand-1)\:{x}_{i,j}$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican in [12pt]{minimal}
$$\:the\:jth$$ dimension; [12pt]{minimal}
$$\:R\:(1-t/T)$$ indicates the neighbourhood radius; [12pt]{minimal}
$$\:R$$ denotes a constant value fixed to 0.2. Here, [12pt]{minimal}
$$\:t$$ refers to a present iteration count, and [12pt]{minimal}
$$\:T$$ means maximum iteration count. This calculation signifies the assortment of areas where a local search was achieved near every pelican member in the prospect of convergence. Simultaneously, in this present iteration phase, the technique can be efficiently upgraded and receive or discard the novel population position as per an exact condition, as displayed in Eq. . In this equation, [12pt]{minimal}
$$\:{X}_{i}^{P2}$$ denotes a novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P2}$$ is dependent upon the value of an objective function. 21 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{2}},{F}_{i}^{{P}_{2}}<{F}_{i};\\\:{X}_{i},\:else,.$$ Conversely, the POA has some major drawbacks. Initially, it employs an entirely randomly generated model to produce the preliminary population, frequently resulting in a lack of essential population range, uneven distribution of the early population, and restricted spatial position for the optimizer, affecting the convergence rate. Next, the POA method includes selecting the position with the value of finest fitness in every iteration, effortlessly dropping into the local optimum area and decreasing the optimization accuracy. Moreover, the POA global search capability is comparatively standard in the initial phase, and the local development capability is weak, increasing the danger of the technique dropping into the local optimum. The POA originates an FF to reach an enhanced classification solution. It defines an optimistic number to indicate the improved efficiency of the candidate solution. In this work, the minimizer of the classifier rate of error is regarded as FF and set in Eq. . 22 [12pt]{minimal}
$$\:fitness({x}_{i})=ClassifierErrorRate({x}_{i})=\:100$$
The LSTEDL-CCS model performs pre-processing of the images using the WF model . This method is chosen due to its efficiency in noise reduction while preserving significant image details. The WF method is particularly suited for medical image processing as it adapts to local image discrepancies, ensuring that noise is minimized without blurring crucial features. Compared to other denoising techniques, such as Gaussian filters, the WF provides an optimal trade-off between smoothing and edge preservation, making it ideal for maintaining the fine details required in CC detection. Furthermore, it is computationally effectual and capable of handling noisy datasets, which is common in medical imaging due to discrepancies in image quality and lighting conditions. By mitigating noise and enhancing the clarity of features, the WF improves the accuracy of subsequent feature extraction and classification stages. This makes it a reliable choice over more complex or slower methods. Figure specifies the WF structure. The WF is a method employed in image processing to reduce noise and improve image quality. When functional to colposcopy images for CC recognition, WF aids in increasing the detail and clarity of the images by minimalizing the effect of noise. This increases the visibility of significant features like lesions and abnormal tissue structures, vital for precise diagnosis. By offering more detailed and cleaner images, WF supports superior recognition and evaluation of CC, eventually assisting in more effectual medical evaluations and cure planning.
The feature extraction method of the LSTEDL-CCS approach is performed by an ST network , . This model is selected due to its ability to capture local and global dependencies in images. Unlike conventional CNNs, the ST model utilizes shifted window attention mechanisms, enabling it to handle large-scale image data while maintaining computational efficiency effectually. This methodology outperforms in extracting hierarchical features at multiple scales, specifically beneficial for medical imaging, where fine-grained and multi-level data is critical for accurate diagnosis. Furthermore, the ST model adapts well to high-resolution images, making it ideal for intrinsic CC detection tasks. Its flexibility in handling variable input sizes and robust performance in various image recognition tasks make it a more robust and versatile choice related to older techniques, such as CNNs or simpler transformers. The technique’s capability to generalize across diverse datasets improves its efficiency in medical imaging applications. Figure represents the structure of the ST network. The Transformer method is a usual Encoder-Decoder model that utilizes a Multi-Layer Perceptron (MLP) technique for positional channel and embedding mixings. It uses the mechanisms of Multi‐Head Self‐Attention (MSA) and Self‐Attention (SA) models for positional relationship modelling. It is primarily presented for natural language processing (NLP); the Transformer structure was given to the computer vision field over innovative works, such as VIT. The self‐attention mechanism computes the significance of all inputs to the method. In the VIT self‐attention layer, normalized dot product attention is utilized to calculate the associations among every input location. The self‐attention layer initially applies three independent linear transformations, producing the query matrix [12pt]{minimal}
$$\:Q$$ , key matrix [12pt]{minimal}
$$\:K$$ , and value matrix [12pt]{minimal}
$$\:V$$ . The computation was formulated below: 1 [12pt]{minimal}
$$\:Q=X{W}_{q},\:K=X{W}_{k},\:V=X{W}_{v}$$ [12pt]{minimal}
$$\:{W}_{q},{W}_{k},{\:and\:W}_{v}$$ are the parameter matrices, and [12pt]{minimal}
$$\:X$$ is the input matrix. The product of [12pt]{minimal}
$$\:K$$ and [12pt]{minimal}
$$\:Q$$ and the Softmax function is utilized to compute the attention weight of every location, and the weighted quantity of all locations is utilized as the self-attention layer output, computed as: 2 [12pt]{minimal}
$$\:{F}_{A}(Q,\:K,\:V)=\:(^{T}}{_{k}}})V$$ whereas [12pt]{minimal}
$$\:{F}_{A}$$ denotes the attention layer, [12pt]{minimal}
$$\:\:$$ represents the activation function of Softmax, and [12pt]{minimal}
$$\:{d}_{k}$$ is the size of [12pt]{minimal}
$$\:K$$ . The attention weight matrix is separated by [12pt]{minimal}
$$\:{d}_{k}$$ to remove excessive change from impacting the backpropagation (BP) and secure the optimization method. VIT is extensively used in various computer vision tasks, as illustrated by the Dual-Branch Geometric Attention model for accurate LCNet and 3D dental method segmentation that improves numerical efficacy over a partial-channel transformation strategy, lowering latency and hardware needs. The ST is a worldwide feature extraction submodule for handling imagery. SW-MSA and W‐MSA subblocks are used consecutively in dual consecutive ST blocks. The mathematical calculation is represented below: 3 [12pt]{minimal}
$$\:{}^{l}={W}_{MSA}(LN({z}^{l-1}))+{z}^{l-1}$$ 4 [12pt]{minimal}
$$\:{z}^{l}=MLP(LN({}^{l}))+{}^{l}$$ 5 [12pt]{minimal}
$$\:{}^{(l+1)}={W}_{MSA}(LN({z}^{l}))+{z}^{l}$$ 6 [12pt]{minimal}
$$\:{z}^{(l+1)}=MLP(LN({}^{(l+1)}))+{}^{(l+1)}$$ [12pt]{minimal}
$$\:{}^{l},{z}^{l}$$ represent the output features of the [12pt]{minimal}
$$\:W$$ - [12pt]{minimal}
$$\:MSA\:and\:MLP$$ sub-blocks of the first block and [12pt]{minimal}
$$\:{}^{l+1}$$ , [12pt]{minimal}
$$\:{z}^{l+1}$$ denotes the output features of the [12pt]{minimal}
$$\:SW-MSA\:and\:MLP$$ sub-blocks of the second block, correspondingly. The W-MSA sub-block divides an input feature map into several nonoverlapping and calculates self-attention. This approach substantially decreases the network’s numerical difficulty. However, owing to the portioning of windows, the usage of [12pt]{minimal}
$$\:W$$ ‐MSA may cause data loss. To tackle this problem, the ST submodule uses a SW‐MSA sub-block. It combines an offset matrix [12pt]{minimal}
$$\:B\:{R}^{{M}^{2}\:{M}^{2}}$$ while computing self‐attention as represented below: 7 [12pt]{minimal}
$$\:Attention(Q,\:K,\:V)=SoftMax(^{T}}{}+B)V$$ whereas [12pt]{minimal}
$$\:Q,K,V\:{R}^{{M}^{2}\:d}$$ represent the query, key, and value matrices; correspondingly, [12pt]{minimal}
$$\:d$$ represents the size, and [12pt]{minimal}
$$\:{M}^{2}$$ represents the patch count. The matrix [12pt]{minimal}
$$\:B$$ is attained from the offset matrix [12pt]{minimal}
$$\: R^{{( {2M - 1} ) ( {2M - 1} )}} .$$ The SW-MSA subblock enables data propagation. By integrating the SW‐MSA and W‐MSA subblocks, the ST submodule can effectively manage large images and efficiently seize worldwide features.
The LSTEDL-CCS approach performs the cancer detection process by utilizing AE, BiGRU, and DBN models for the classification process. This ensemble model is chosen due to their complementary strengths in feature extraction and sequence modelling. The AE effectually mitigates dimensionality and learns a compact representation of complex data, which assists in removing noise and improving the accuracy of subsequent models. BiGRU, a variant of the GRU, outperforms in capturing long-range dependencies in sequential data, making it ideal for analyzing temporal or structured patterns in medical imaging data. The DBN, known for its DL capabilities, improves the feature extraction process by stacking layers of unsupervised networks, which assists in learning intrinsic hierarchical features. This integration of models allows for a robust, multifaceted approach to cancer detection, outperforming conventional techniques that may depend on simpler feature extraction or shallow learning. Integrating AE, BiGRU, and DBN gives a robust, scalable solution with superior generalization capabilities, making it appropriate for complex medical datasets. AE model The AE becomes a DL approach that reconstructs the inputs for an output layer2 . The AE’s symmetric structure enables the attainment of a less-dimension illustration of the input data inside the main hidden layer (HL). Its principal intention was to transfer the input data that usually occurs in higher- to lower‐dimensional spaces. This decoder designates the element between the middle and the output layers that can recreate the primary information. The intermediary layer was generally termed the bottleneck layer. The node counts in these layers have been directly proportional to the input vector dimensions utilized for encoding. The encoding and decoding processes are represented in Eqs. and as below: 8 [12pt]{minimal}
$$\:{x}_{i}=f(WX+bias)$$ 9 [12pt]{minimal}
$$\:=\:({W}^{{\:}}X+bia{s}^{{\:}})$$ The input vector, represented as [12pt]{minimal}
$$\:X$$ , can be decoded and encoded with the vectors [12pt]{minimal}
$$\:{x}_{i}$$ and [12pt]{minimal}
$$\:{}_{i}.f$$ and [12pt]{minimal}
$$\:{f}^{{\:}}$$ remain activation functions in decoding and encoding elements correspondingly, and that is chosen for the sigmoid functions. [12pt]{minimal}
$$\:W$$ and [12pt]{minimal}
$$\:{W}^{{\:}}$$ correspondingly represent the matrix weight of the HL’s input and output layers. Biased vectors are typically characterized as [12pt]{minimal}
$$bias^{}$$ and [12pt]{minimal}
$$\:bias$$ . The DAE aim is to minimize the rebuilding [12pt]{minimal}
$$\:loss$$ among the input and output values of [12pt]{minimal}
$$\:{x}_{i}$$ & [12pt]{minimal}
$$\:{}_{i}$$ that are mathematically signified as Eq. : 10 [12pt]{minimal}
$$loss( {W,bias,W^{},bias^{}} ) = _{{i = 1}}^{t} {\| {x_{i} - _{i} } \|^{2} }$$ It describes the hyperparameters, which are good in the training method for a deep AE. After training, the latent depiction can be gained from the intermediary layer of the AE. Figure depicts the structure of the AE method. BiGRU technique Recurrent neural networks (RNNs) can memorize prior inputs, prepare them suitable for processing time-sequence data, and are primarily effectual at removing sequential features from curves . However, standard RNNs are delayed by problems associated with the exploding or vanishing of gradients, limiting their capacity to maintain long‐term memory. The GRU was introduced to overcome the dependency problems of RNNs. These networks increase additional reset and update gates in every recurrent unit to control the input, which lets the network preserve state data across long periods. The structure of the GRU element operates based on the succeeding equations: 11 [12pt]{minimal}
$$\:{z}_{t}=\:({W}_{i}{x}_{t}+{b}_{iz}+{W}_{h}z{h}_{t-1}+{b}_{hz})$$ 12 [12pt]{minimal}
$$\:{r}_{t}=\:({W}_{ir}{x}_{t}+{b}_{ir}+{W}_{hr}{h}_{t-1}+{b}_{hr})$$ 13 [12pt]{minimal}
$$\:{}_{}=({W}_{in}{x}_{t}+{b}_{in}+{r}_{t}\:({W}_{hn}{h}_{(t-1)}+{b}_{hn}))$$ 14 [12pt]{minimal}
$$\:{h}_{t}=(1-{z}_{t})\:{h}_{(t-1)}+{z}_{t}\:{}_{}$$ Now, [12pt]{minimal}
$$\:{h}_{t-1}$$ signifies HL, [12pt]{minimal}
$$\:{x}_{t}$$ means present input, and [12pt]{minimal}
$$\:\:$$ represents sigmoid activation function; [12pt]{minimal}
$$\:{r}_{t}$$ and [12pt]{minimal}
$$\:{z}_{t}\:$$ signify the gates of reset and update; [12pt]{minimal}
$$\:{}_{t}$$ and [12pt]{minimal}
$$\:{h}_{t}$$ specify the candidate and final HL; [12pt]{minimal}
$$\:W$$ exists weight matrix, [12pt]{minimal}
$$\:\:$$ indicates Hadamard products, and [12pt]{minimal}
$$\:b$$ stands for the biased parameter. Figure demonstrates the architecture of the BiGRU model. GRUs can design the BiGRU, processing time-sequence data in contrasting orientations over two‐layer GRU networks. Every orientation has been formed to handle both future and historical data. These bidirectional architectures allow the BiGRU to take data inside the information accurately, thus improving the rebuilding model’s performance. DBN architecture Among the classes of DBN and DNN is a dynamic graphic method . This deep-layer network has generated many RBM networks, constructed on each other. Every two sequential HLs that compose a DBN architecture create an RBM. Usually, the preceding RBM output assists as the next RBM’s input layer. A deep hierarchical group of training information creates a DBN graphic model. The succeeding equation can be applied to explain the combined probability distribution of visible vectors [12pt]{minimal}
$$\:v$$ and [12pt]{minimal}
$$\:l$$ HL [12pt]{minimal}
$$\:({h}_{k}(k=,\:,\:l),\:{h}_{0}=v)$$ 15 [12pt]{minimal}
$$\:P({h}_{1},\:{h}_{2},\:,\:{h}_{l}|v)=P({h}_{1}|{h}_{l-1})P({h}_{l-1}|{h}_{l-2})\:P({h}_{1}|v)={\:}_{k=1}^{l}P({h}_{k}|{h}_{k-1})$$ Based on these definitions, the probability that an inference should be prepared from the HL [12pt]{minimal}
$$\:{h}_{k}$$ to visible layer [12pt]{minimal}
$$\:v$$ can be stated as: 16 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({b}_{j}^{k}+{\:}_{j=1}^{m}{w}_{ij}^{k}{h}_{j}^{k-1})$$ Whereas [12pt]{minimal}
$$\:{b}^{k}$$ is specified as [12pt]{minimal}
$$\:{k}^{th}$$ layer bias. Similar to bottom-up inference, the top‐down inference has been indicated in the subsequent symmetric method: 17 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({a}_{j}^{k-1}+{\:}_{j=1}^{m}{w}_{ij}^{k-1}{h}_{j}^{k})$$ where [12pt]{minimal}
$$\:{a}^{k}$$ are named as [12pt]{minimal}
$$\:(k-1{)}^{th}$$ layer bias. BP and pre-training are the two segments of a DBN’s training process. DBN training has been effectively achieved over finetuning and pre‐training. Figure portrays the structure of the DBN model.
The AE becomes a DL approach that reconstructs the inputs for an output layer2 . The AE’s symmetric structure enables the attainment of a less-dimension illustration of the input data inside the main hidden layer (HL). Its principal intention was to transfer the input data that usually occurs in higher- to lower‐dimensional spaces. This decoder designates the element between the middle and the output layers that can recreate the primary information. The intermediary layer was generally termed the bottleneck layer. The node counts in these layers have been directly proportional to the input vector dimensions utilized for encoding. The encoding and decoding processes are represented in Eqs. and as below: 8 [12pt]{minimal}
$$\:{x}_{i}=f(WX+bias)$$ 9 [12pt]{minimal}
$$\:=\:({W}^{{\:}}X+bia{s}^{{\:}})$$ The input vector, represented as [12pt]{minimal}
$$\:X$$ , can be decoded and encoded with the vectors [12pt]{minimal}
$$\:{x}_{i}$$ and [12pt]{minimal}
$$\:{}_{i}.f$$ and [12pt]{minimal}
$$\:{f}^{{\:}}$$ remain activation functions in decoding and encoding elements correspondingly, and that is chosen for the sigmoid functions. [12pt]{minimal}
$$\:W$$ and [12pt]{minimal}
$$\:{W}^{{\:}}$$ correspondingly represent the matrix weight of the HL’s input and output layers. Biased vectors are typically characterized as [12pt]{minimal}
$$bias^{}$$ and [12pt]{minimal}
$$\:bias$$ . The DAE aim is to minimize the rebuilding [12pt]{minimal}
$$\:loss$$ among the input and output values of [12pt]{minimal}
$$\:{x}_{i}$$ & [12pt]{minimal}
$$\:{}_{i}$$ that are mathematically signified as Eq. : 10 [12pt]{minimal}
$$loss( {W,bias,W^{},bias^{}} ) = _{{i = 1}}^{t} {\| {x_{i} - _{i} } \|^{2} }$$ It describes the hyperparameters, which are good in the training method for a deep AE. After training, the latent depiction can be gained from the intermediary layer of the AE. Figure depicts the structure of the AE method.
Recurrent neural networks (RNNs) can memorize prior inputs, prepare them suitable for processing time-sequence data, and are primarily effectual at removing sequential features from curves . However, standard RNNs are delayed by problems associated with the exploding or vanishing of gradients, limiting their capacity to maintain long‐term memory. The GRU was introduced to overcome the dependency problems of RNNs. These networks increase additional reset and update gates in every recurrent unit to control the input, which lets the network preserve state data across long periods. The structure of the GRU element operates based on the succeeding equations: 11 [12pt]{minimal}
$$\:{z}_{t}=\:({W}_{i}{x}_{t}+{b}_{iz}+{W}_{h}z{h}_{t-1}+{b}_{hz})$$ 12 [12pt]{minimal}
$$\:{r}_{t}=\:({W}_{ir}{x}_{t}+{b}_{ir}+{W}_{hr}{h}_{t-1}+{b}_{hr})$$ 13 [12pt]{minimal}
$$\:{}_{}=({W}_{in}{x}_{t}+{b}_{in}+{r}_{t}\:({W}_{hn}{h}_{(t-1)}+{b}_{hn}))$$ 14 [12pt]{minimal}
$$\:{h}_{t}=(1-{z}_{t})\:{h}_{(t-1)}+{z}_{t}\:{}_{}$$ Now, [12pt]{minimal}
$$\:{h}_{t-1}$$ signifies HL, [12pt]{minimal}
$$\:{x}_{t}$$ means present input, and [12pt]{minimal}
$$\:\:$$ represents sigmoid activation function; [12pt]{minimal}
$$\:{r}_{t}$$ and [12pt]{minimal}
$$\:{z}_{t}\:$$ signify the gates of reset and update; [12pt]{minimal}
$$\:{}_{t}$$ and [12pt]{minimal}
$$\:{h}_{t}$$ specify the candidate and final HL; [12pt]{minimal}
$$\:W$$ exists weight matrix, [12pt]{minimal}
$$\:\:$$ indicates Hadamard products, and [12pt]{minimal}
$$\:b$$ stands for the biased parameter. Figure demonstrates the architecture of the BiGRU model. GRUs can design the BiGRU, processing time-sequence data in contrasting orientations over two‐layer GRU networks. Every orientation has been formed to handle both future and historical data. These bidirectional architectures allow the BiGRU to take data inside the information accurately, thus improving the rebuilding model’s performance.
Among the classes of DBN and DNN is a dynamic graphic method . This deep-layer network has generated many RBM networks, constructed on each other. Every two sequential HLs that compose a DBN architecture create an RBM. Usually, the preceding RBM output assists as the next RBM’s input layer. A deep hierarchical group of training information creates a DBN graphic model. The succeeding equation can be applied to explain the combined probability distribution of visible vectors [12pt]{minimal}
$$\:v$$ and [12pt]{minimal}
$$\:l$$ HL [12pt]{minimal}
$$\:({h}_{k}(k=,\:,\:l),\:{h}_{0}=v)$$ 15 [12pt]{minimal}
$$\:P({h}_{1},\:{h}_{2},\:,\:{h}_{l}|v)=P({h}_{1}|{h}_{l-1})P({h}_{l-1}|{h}_{l-2})\:P({h}_{1}|v)={\:}_{k=1}^{l}P({h}_{k}|{h}_{k-1})$$ Based on these definitions, the probability that an inference should be prepared from the HL [12pt]{minimal}
$$\:{h}_{k}$$ to visible layer [12pt]{minimal}
$$\:v$$ can be stated as: 16 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({b}_{j}^{k}+{\:}_{j=1}^{m}{w}_{ij}^{k}{h}_{j}^{k-1})$$ Whereas [12pt]{minimal}
$$\:{b}^{k}$$ is specified as [12pt]{minimal}
$$\:{k}^{th}$$ layer bias. Similar to bottom-up inference, the top‐down inference has been indicated in the subsequent symmetric method: 17 [12pt]{minimal}
$$\:P({h}_{k}|{h}_{k-1})=\:({a}_{j}^{k-1}+{\:}_{j=1}^{m}{w}_{ij}^{k-1}{h}_{j}^{k})$$ where [12pt]{minimal}
$$\:{a}^{k}$$ are named as [12pt]{minimal}
$$\:(k-1{)}^{th}$$ layer bias. BP and pre-training are the two segments of a DBN’s training process. DBN training has been effectively achieved over finetuning and pre‐training. Figure portrays the structure of the DBN model.
Eventually, the hyperparameter tuning process of the LSTEDL-CCS model is accomplished by utilizing the POA model . This method is chosen because it can handle intrinsic, high-dimensional optimization problems commonly faced in DL models. POA is a bio-inspired optimization technique that replicates the foraging behaviour of pelicans, enabling it to search large solution spaces while averting local minima efficiently. Unlike conventional gradient-based methods, POA does not require gradient information, making it more appropriate for models with non-differentiable loss functions. Its robustness in dealing with multimodal and noisy search spaces makes it ideal for tuning hyperparameters in models like LSTEDL-CCS, which may exhibit complex, nonlinear relationships between parameters. Furthermore, the flexibility and strong convergence properties of the POA model improve its capability to deliver optimal solutions in a relatively short time, making it preferable over other optimization techniques, namely GAs or particle swarm optimization (PSO). Figure illustrates the workflow of the POA model. For data analysis, the POA is employed to increase accuracy and efficacy. The approach is nominated to enhance the BP neural networks method because of the global search ability, versatile finetuning mechanism, and efficacy in trading with multifaceted nonlinear issues that permit it to perceptively direct the weight upgrade and efficiently evade local optimizer by presenting major benefits in enhancing training efficacy and ultimate precision. The POA is a heuristic technique that pretends to be pelicans’ natural strategies and behaviours during hunting and attack. This exclusive hunting technique entails dual phases, such as approaching the prey and surface fight. Prey approach stage In this phase, the pelicans recognize their victim’s position and then travel near the objective region. By exhibiting this pelican hunt plan, the search space is effectively examined, and POA’s search abilities are utilized to discover dissimilar areas in the search space. The mentioned models and the numerical calculation of pelicans’ poignant near-prey location are expressed in Eq. . 18 [12pt]{minimal}
$$\:{x}_{i,j}^{{P}_{1}}=\{_{i,j}+rand\:\:({p}_{j}-I.{x}_{i,j}),&\:{F}_{p}<{F}_{i},\\\:{x}_{i,j}+rand\:({x}_{i,j}-{p}_{j}),&\:else,.$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel state of [12pt]{minimal}
$$\:an\:ith$$ pelican in [12pt]{minimal}
$$\:a\:jth$$ dimension defined by the randomly generated parameter [12pt]{minimal}
$$\:I$$ , where it is fixed to 1 or 2. [12pt]{minimal}
$$\:{p}_{j}$$ signifies the location of prey in [12pt]{minimal}
$$\:the\:jth$$ dimension. [12pt]{minimal}
$$\:{F}_{p}$$ means the value of the objective function. [12pt]{minimal}
$$\:I\:$$ is selected at random for every member of Pelican and iteration. If [12pt]{minimal}
$$\:I$$ is equivalent to 2, then it stimulates the members of the Pelican to create a greater shift that leads them to discover novel zones that were not visited previously. The POA method defines the novel pelican position when the objective function is enhanced. This upgrade is effective because it certifies that the technique does not drop into a non-optimal area. The complete upgrading method has been demonstrated in Eq. . Here, [12pt]{minimal}
$$\:{X}_{i}^{P1}$$ denotes the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P1}$$ depends upon the value of the objective function of the primary phase. 19 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{1}},{F}_{i}^{{P}_{1}}<{F}_{i;}.\\\:{X}_{i},\:else,.$$ Surface flight stage In this phase, if the pelicans arrive at the surface, they extend their wings to carry the prey from the sea and finally gather it in their throat. This exclusive hunting approach permits the pelicans to capture the fish in their attack region. The developed POA is warranted to unite an enhanced solution for the hunt region. Its mathematical formulation is expressed below: 20 [12pt]{minimal}
$$\:{x}_{i,{j}^{2}}^{P}={x}_{i,j}+R\:(1-)\:(2\:rand-1)\:{x}_{i,j}$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican in [12pt]{minimal}
$$\:the\:jth$$ dimension; [12pt]{minimal}
$$\:R\:(1-t/T)$$ indicates the neighbourhood radius; [12pt]{minimal}
$$\:R$$ denotes a constant value fixed to 0.2. Here, [12pt]{minimal}
$$\:t$$ refers to a present iteration count, and [12pt]{minimal}
$$\:T$$ means maximum iteration count. This calculation signifies the assortment of areas where a local search was achieved near every pelican member in the prospect of convergence. Simultaneously, in this present iteration phase, the technique can be efficiently upgraded and receive or discard the novel population position as per an exact condition, as displayed in Eq. . In this equation, [12pt]{minimal}
$$\:{X}_{i}^{P2}$$ denotes a novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P2}$$ is dependent upon the value of an objective function. 21 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{2}},{F}_{i}^{{P}_{2}}<{F}_{i};\\\:{X}_{i},\:else,.$$ Conversely, the POA has some major drawbacks. Initially, it employs an entirely randomly generated model to produce the preliminary population, frequently resulting in a lack of essential population range, uneven distribution of the early population, and restricted spatial position for the optimizer, affecting the convergence rate. Next, the POA method includes selecting the position with the value of finest fitness in every iteration, effortlessly dropping into the local optimum area and decreasing the optimization accuracy. Moreover, the POA global search capability is comparatively standard in the initial phase, and the local development capability is weak, increasing the danger of the technique dropping into the local optimum. The POA originates an FF to reach an enhanced classification solution. It defines an optimistic number to indicate the improved efficiency of the candidate solution. In this work, the minimizer of the classifier rate of error is regarded as FF and set in Eq. . 22 [12pt]{minimal}
$$\:fitness({x}_{i})=ClassifierErrorRate({x}_{i})=\:100$$
In this phase, the pelicans recognize their victim’s position and then travel near the objective region. By exhibiting this pelican hunt plan, the search space is effectively examined, and POA’s search abilities are utilized to discover dissimilar areas in the search space. The mentioned models and the numerical calculation of pelicans’ poignant near-prey location are expressed in Eq. . 18 [12pt]{minimal}
$$\:{x}_{i,j}^{{P}_{1}}=\{_{i,j}+rand\:\:({p}_{j}-I.{x}_{i,j}),&\:{F}_{p}<{F}_{i},\\\:{x}_{i,j}+rand\:({x}_{i,j}-{p}_{j}),&\:else,.$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel state of [12pt]{minimal}
$$\:an\:ith$$ pelican in [12pt]{minimal}
$$\:a\:jth$$ dimension defined by the randomly generated parameter [12pt]{minimal}
$$\:I$$ , where it is fixed to 1 or 2. [12pt]{minimal}
$$\:{p}_{j}$$ signifies the location of prey in [12pt]{minimal}
$$\:the\:jth$$ dimension. [12pt]{minimal}
$$\:{F}_{p}$$ means the value of the objective function. [12pt]{minimal}
$$\:I\:$$ is selected at random for every member of Pelican and iteration. If [12pt]{minimal}
$$\:I$$ is equivalent to 2, then it stimulates the members of the Pelican to create a greater shift that leads them to discover novel zones that were not visited previously. The POA method defines the novel pelican position when the objective function is enhanced. This upgrade is effective because it certifies that the technique does not drop into a non-optimal area. The complete upgrading method has been demonstrated in Eq. . Here, [12pt]{minimal}
$$\:{X}_{i}^{P1}$$ denotes the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P1}$$ depends upon the value of the objective function of the primary phase. 19 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{1}},{F}_{i}^{{P}_{1}}<{F}_{i;}.\\\:{X}_{i},\:else,.$$
In this phase, if the pelicans arrive at the surface, they extend their wings to carry the prey from the sea and finally gather it in their throat. This exclusive hunting approach permits the pelicans to capture the fish in their attack region. The developed POA is warranted to unite an enhanced solution for the hunt region. Its mathematical formulation is expressed below: 20 [12pt]{minimal}
$$\:{x}_{i,{j}^{2}}^{P}={x}_{i,j}+R\:(1-)\:(2\:rand-1)\:{x}_{i,j}$$ Here, [12pt]{minimal}
$$\:{X}_{i,j}^{P1}$$ signifies the novel location of the [12pt]{minimal}
$$\:ith$$ Pelican in [12pt]{minimal}
$$\:the\:jth$$ dimension; [12pt]{minimal}
$$\:R\:(1-t/T)$$ indicates the neighbourhood radius; [12pt]{minimal}
$$\:R$$ denotes a constant value fixed to 0.2. Here, [12pt]{minimal}
$$\:t$$ refers to a present iteration count, and [12pt]{minimal}
$$\:T$$ means maximum iteration count. This calculation signifies the assortment of areas where a local search was achieved near every pelican member in the prospect of convergence. Simultaneously, in this present iteration phase, the technique can be efficiently upgraded and receive or discard the novel population position as per an exact condition, as displayed in Eq. . In this equation, [12pt]{minimal}
$$\:{X}_{i}^{P2}$$ denotes a novel location of the [12pt]{minimal}
$$\:ith$$ Pelican, and [12pt]{minimal}
$$\:{F}_{i}^{P2}$$ is dependent upon the value of an objective function. 21 [12pt]{minimal}
$$\:{X}_{i}=\{_{i}^{{P}_{2}},{F}_{i}^{{P}_{2}}<{F}_{i};\\\:{X}_{i},\:else,.$$ Conversely, the POA has some major drawbacks. Initially, it employs an entirely randomly generated model to produce the preliminary population, frequently resulting in a lack of essential population range, uneven distribution of the early population, and restricted spatial position for the optimizer, affecting the convergence rate. Next, the POA method includes selecting the position with the value of finest fitness in every iteration, effortlessly dropping into the local optimum area and decreasing the optimization accuracy. Moreover, the POA global search capability is comparatively standard in the initial phase, and the local development capability is weak, increasing the danger of the technique dropping into the local optimum. The POA originates an FF to reach an enhanced classification solution. It defines an optimistic number to indicate the improved efficiency of the candidate solution. In this work, the minimizer of the classifier rate of error is regarded as FF and set in Eq. . 22 [12pt]{minimal}
$$\:fitness({x}_{i})=ClassifierErrorRate({x}_{i})=\:100$$
In this section, the experimental validation outcomes of the LSTEDL-CCS model are examined using the Kaggle Coloscopy Image Dataset , which comprises 600 samples with three class labels definite in Table . Figure denotes the sample images. The suggested technique is simulated using the Python 3.6.5 tool on PC i5-8600k, 250GB SSD, GeForce 1050Ti 4GB, 16GB RAM, and 1 TB HDD. The parameter settings are provided: learning rate: 0.01, activation: ReLU, epoch count: 50, dropout: 0.5, and batch size: 5. Figure institutes the classifier results of the LSTEDL-CCS method under the test dataset. Figure a and b represents the confusion matrices presented by the LSTEDL-CCS technique on 80:20 TRAP/TESP. The result implies that the LSTEDL-CCS method is familiar and classifies all class labels precisely. Also, Fig. c authorizes the PR study of the LSTEDL-CCS approach. The result stated that the LSTEDL-CCS method has enlarged the highest efficiency of PR under every class. Lastly, Fig. d shows the ROC study of the LSTEDL-CCS technique. The outcome signified that the LSTEDL-CCS method has resulted in proficient outcomes with the greatest ROC values below dissimilar classes. Table shows the classifier results of the LSTEDL-CCS model with 80%TRAP and 20%TESP. The outcomes indicated that the LSTEDL-CCS method correctly recognized different phases. With 80%TRAP, the LSTEDL-CCS approach provides an average [12pt]{minimal}
$$\:acc{u}_{y}$$ of 98.47%, [12pt]{minimal}
$$\:pre{c}_{n}$$ of 97.70%, [12pt]{minimal}
$$\:sen{s}_{y}$$ of 97.73%, [12pt]{minimal}
$$\:spe{c}_{y}$$ of 98.86%, and [12pt]{minimal}
$$\:AU{C}_{score}$$ of 98.29%. Besides, with 20%TESP, the LSTEDL-CCS technique offers an average [12pt]{minimal}
$$\:acc{u}_{y}$$ of 99.44%, [12pt]{minimal}
$$\:pre{c}_{n}$$ of 99.22%, [12pt]{minimal}
$$\:sen{s}_{y}$$ of 99.05%, [12pt]{minimal}
$$\:spe{c}_{y}$$ of 99.57%, and [12pt]{minimal}
$$\:AU{C}_{score}$$ of 99.31%. Figure depicts the training and validation accuracy outcomes of the LSTEDL-CCS method under 80%TRAP and 20%TESP. The precision values are computed throughout 0–25 epoch counts. This figure emphasized that the training and validation accuracy values show a growing trend that informed the capacity of the LSTEDL-CCS method with better performance over numerous iterations. Moreover, the training and validation accuracy stay nearer over the epoch counts that point out the least minimum overfitting and display improved performance of the LSTEDL-CCS technique, ensuring constant prediction on hidden samples. Figure represents the training and validation loss graph of the LSTEDL-CCS approach under 80%TRAP and 20%TESP. The loss values are computed for 0–25 epoch counts. The training and validation accuracy values demonstrate a lowering trend, reporting the ability of the LSTEDL-CCS technique to balance a trade-off between generalization and data fitting. The consistent decrease in loss values also assures the superior performance of the LSTEDL-CCS method and tunes the prediction outcomes in time. Figure establishes the classifier results of the LSTEDL-CCS method under the test dataset. Figure a and b represents the confusion matrices presented by the LSTEDL-CCS model on 70:30 of TRAP/TESP. This result defines that the LSTEDL-CCS technique is familiar and classifies all classes precisely. Furthermore, Fig. c authenticates the PR analysis of the LSTEDL-CCS method. This result indicates that the LSTEDL-CCS technique has improved the maximal proficiency of PR under each class label. Lastly, Fig. d shows the ROC study of the LSTEDL-CCS technique. The outcome indicated that the LSTEDL-CCS technique has resulted in efficient results with greater ROC values under diverse class labels. Table shows the classifier outcomes of the LSTEDL-CCS approach with 70%TRAP and 30%TESP. These results indicate that the LSTEDL-CCS process accurately recognized different phases. With 70%TRAP, the LSTEDL-CCS method provides an average [12pt]{minimal}
$$\:acc{u}_{y}$$ of 97.78%, [12pt]{minimal}
$$\:pre{c}_{n}$$ of 96.69%, [12pt]{minimal}
$$\:sen{s}_{y}$$ of 96.70%, [12pt]{minimal}
$$\:spe{c}_{y}$$ of 98.33%, and [12pt]{minimal}
$$\:AU{C}_{score}$$ of 97.52%. Therefore, with 30%TESP, the LSTEDL-CCS technique presents an average [12pt]{minimal}
$$\:acc{u}_{y}$$ of 98.52%, [12pt]{minimal}
$$\:pre{c}_{n}$$ of 97.70%, [12pt]{minimal}
$$\:sen{s}_{y}$$ of 97.88%, [12pt]{minimal}
$$\:spe{c}_{y}$$ of 98.94%, and [12pt]{minimal}
$$\:AU{C}_{score}$$ of 98.41%. Figure reports the training and validation accuracy outcomes of the LSTEDL-CCS approach under 70%TRAP and 30%TESP. The precision values are computed throughout 0–25 epoch counts. This figure underlines that the training and validation accuracy values display an increasing trend, reporting the capability of the LSTEDL-CCS technique with better performance over numerous iterations. In addition, the training accuracy and validation accuracy stay adjacent over the epoch counts, illustrating low minimum overfitting and improving the LSTEDL-CCS method’s performance, assuring continuous prediction on hidden samples. Figure shows the training and validation loss graph of the LSTEDL-CCS method under 70%TRAP and 30%TESP. The loss values are computed for 0–25 epoch counts. This implies that the training and validation accuracy values showed a reducing trend, informing the ability of the LSTEDL-CCS method to balance a trade-off between generalization and data fitting. The constant lowering in loss values also promises better performance of the LSTEDL-CCS technique and tuning of the prediction outcomes in time. To illustrate the superior performance of the LSTEDL-CCS model, a short comparative analysis is performed in Table ; Fig. . The results showed that the U-Net, ML, and Faster R-CNN models presented the least outcomes. Meanwhile, the TernausNet-DLV2, InceptionV3, and EfficienNet-B3 approaches have tried to gain slightly nearer outcomes. Nevertheless, the LSTEDL-CCS methodologies reported guaranteeing performance with [12pt]{minimal}
$$\:acc{u}_{y}$$ of 99.44%, [12pt]{minimal}
$$\:pre{c}_{n}$$ of 99.22%, [12pt]{minimal}
$$\:sen{s}_{y}\:$$ of 99.05%, and [12pt]{minimal}
$$\:spe{c}_{y}$$ of 99.57%. Figure shows a computation time (CT) to establish the superior performance of the LSTEDL-CCS approach. The results report that the ML and EfficienNet-B3 models displayed greater processing time. Meanwhile, the U-Net, Faster R-CNN, TernausNet-DLV2, and InceptionV3 methodologies have tried to achieve somewhat lesser classification results. On the other hand, the LSTEDL-CCS technique portrays reduced performance with a time of 2.51 s.
The manuscript introduced a LSTEDL-CCS technique for colposcopy images. Initially, image pre-processing was performed using the WF model. Next, the ST network was used to extract features from images. The ensemble learning method was performed for cancer detection by utilizing three models: AE, BiGRU, and DBN. Finally, the hyperparameter tuning of the DL techniques was accomplished by using the POA. A comprehensive experimental analysis was conducted, and the results were evaluated under diverse metrics. The performance validation of the LSTEDL-CCS methodology portrayed a superior accuracy value of 99.44% over existing models. The limitations of the LSTEDL-CCS methodology include reliance on a relatively small dataset, which may affect the model’s generalization capability to diverse and larger real-world datasets. Furthermore, the presented approach may face difficulty distinguishing between early-stage lesions and normal discrepancies in colposcopy images due to the inherent difficulty of detecting subtle variances. Additionally, the study needs an extensive evaluation across diverse populations, potentially limiting its clinical applicability. Future work may focus on utilizing massive, more varied datasets to improve model robustness, integrating multimodal data (e.g., histopathology, HPV tests) for improved diagnostic accuracy, and exploring unsupervised learning techniques to handle unannotated data. Further optimization of the model for real-time clinical use and validation in clinical settings is also crucial.
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Patient-, Provider-, and Facility-Level Contributors to the Use of Cardiology Telehealth Care in the Veterans Health Administration: Retrospective Cohort Study | 136cece6-20dd-4bde-9ce8-3c7934a7d3a5 | 11549580 | Internal Medicine[mh] | The coronavirus (COVID-19) pandemic has been a catalyst for the expansion of telehealth (medical care delivered by phone or video), in the Veterans Health Administration (VHA) system and in health care settings worldwide . While in-person care has largely been restored as the pandemic has subsided, telehealth continues to play a crucial role in improving access to medical care. However, as telehealth shifts from a requirement to an option , this role is evolving; beyond replacing an in-person encounter, telehealth can be used to address staffing gaps at a given location. For example, VHA has implemented a hub-and-spoke model across primary, mental health, and specialty care to compensate for staffing shortages, wherein clinicians at the “hub” site see patients at a “spoke” sites via telehealth . For optimal and equitable use, such novel applications of telehealth depend on a thorough understanding of the drivers of telehealth use. Unsurprisingly, these drivers may differ by medical specialty and clinical conditions. Acknowledging this, professional societies have called for more research into determinants of telehealth provision for cardiovascular disease specifically . Use of cardiology telehealth care varies depending on patients’ sociodemographic characteristics, such as age, rurality, socioeconomic status, and number of comorbid conditions . At the clinician level, significant variability exists regarding comfort level with and support for telehealth adoption among cardiologists . Additionally, facility-level characteristics have also been shown to influence telehealth adoption . Given that all 3 levels are likely influencing telehealth use, understanding the relative contribution of each is useful for informing decisions about where to direct policy change for the highest impact . While other studies have examined this question across a range of specialties , none has specifically focused on cardiology telehealth care. In this study, we estimate the variability in cardiology telehealth care use attributable to patients, clinicians, and health care facilities. Understanding the relative contribution of factors at these levels can inform policy initiatives and interventions to promote the optimal and equitable use of telehealth in specialty settings. Data This retrospective cohort study focused on active users of VHA cardiology care. Veterans aged 18 and older were included in the cohort if they had at least 1 outpatient cardiology visit for a cardiology diagnosis (the full list of diagnoses is provided in Table S1 in ) in the approximately 15-month period leading up the COVID-19 pandemic’s onset (calendar year 2019 and the beginning of 2020; January 1, 2019, to March 10, 2020) and had at least 2 outpatient cardiology visits in the first 2 years of the pandemic (March 11, 2020, to March 10, 2022). The first day of the pandemic was considered to be March 11, 2020, consistent with World Health Organization directives . We sourced all data from VHA’s Corporate Data Warehouse, a repository for veteran’s electronic health care records (172VA10P2: VHA Corporate Data Warehouse - VA 79 FR 4377). In addition to veterans’ dates of birth and, when applicable, dates of death, the dataset included all cardiology outpatient encounters in VHA, as defined by VHA-specific “stop codes,” where the visits were associated with an independent licensed practitioner with a unique National Provider Identifier (NPI). These 3-digit codes, available through VHA’s Managerial Cost Accounting system, characterize all VHA outpatient encounters and associated clinical work units (Table S2 in ). Stop codes were also used to define whether the visit was conducted in person or via phone or video, with telehealth visits defined as those taking place by phone or video. Visits for cardiac rehabilitation were not included. We captured veteran sociodemographic and clinical characteristics in a manner consistent with existing VHA telehealth literature . Age at the beginning of the pandemic was categorized into 4 groups, roughly corresponding to quartiles for the study population: <50, 50-64, 65-74, and ≥75 years. Race was categorized as American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, unknown, or White, and ethnicity was categorized as Hispanic or Latino, not Hispanic or Latino, or unknown, both based on the most frequently recorded race or ethnicity identification in the electronic health record. Separate categories were created for missing race or ethnicity classification. Rurality, defined as highly rural (population density of fewer than 7 people per square mile), rural, or urban, was based on US Census Bureau criteria and derived from VHA’s Planning Systems Support Group (PSSG) Geocoded Enrollee Files in the Corporate Data Warehouse. Drive time to secondary care, which includes cardiology care, was also sourced from PSSG files and was categorized as short (≤30 min), medium (31-60 min), or long (>60 min). We included VHA enrollment priority category as a measure of social and medical risk; this system groups veterans based on military service–connected disability, recent military service, income, and other factors . As in prior work , the 8 enrollment priority categories were condensed into 4: high disability (>50% service-connected disability or VHA catastrophically disabled), low/moderate disability (10%-40% service-connected disability or military exposure), low income (annual income below area-adjusted mean), or without special VHA enrollment priority. Noncardiology care was captured as primary care visits in the year prior to the study period and categorized into tertiles thereof (0-4, 5-8, or ≥9). Use of mental health care and emergency department or urgent care visits in the year prior to the analysis period were included as binary variables. Veteran chronic conditions were calculated out of a predefined group of 47 possible International Classification of Disease, Tenth Revision ( ICD-10 ) diagnosis groups, constructed in prior studies in VHA’s population (Table S3 in ). Housing instability was based on a combination of outpatient stop codes denoting use of Veterans Affairs housing services and diagnosis codes (Table S2 in ). Calendar year (2020, 2021, and 2022) was also included. While in practice patients may see multiple clinicians (including, eg, a nurse practitioner and a physician, or a trainee and an attending physician), sometimes across different facilities, for the purposes of this analysis, we assigned patients a primary cardiology clinician and both patients and clinicians a primary facility. If patients had cardiology encounters with multiple independent licensed practitioners, we defined their main cardiology provider as the provider they had seen most often, or in the case of ties, most recently. In this cohort, 25.1% (56,176/223,809) of patients saw a single cardiology provider; 27.9% (62,443/223,809/N) saw 2, and 47% (105,190/223,809) saw 3 or more cardiology providers. Likewise, for patients seen at multiple VHA medical centers (ie, facilities) for cardiology care, the patient’s home site was the site at which the majority of their cardiology encounters took place. In total, 92.6% (207,247/223,809) of patients received care from a single VHA medical center, and 99.6% (222,914/223,809) received care from 2 or fewer. Statistical Analysis In addition to descriptive statistics for patient characteristics, we constructed multilevel logistic regression models of our primary outcome, a patient’s odds of receiving cardiology telehealth care (ie, care delivered by phone or video). These models included random effects for the patient, the patient’s main cardiology provider, and the patient’s home VHA facility for specialty cardiology care. Models were adjusted for the patient sociodemographic and clinical characteristics delineated above and calendar year as fixed effects. Statistical analyses were conducted in Stata 17 (StataCorp, LLC). Ethical Considerations This analysis was carried out as part of the Virtual Access Quality Enhancement Research Initiative, which is designated as nonresearch quality improvement by VHA program office partners in the VHA Office of Rural Health. The institutional review board at the Stanford Research Compliance Office determined this evaluation does not meet the requirement of research or clinical investigation per Federal Regulations 45CFR 46.104 (Subsection 4) and VA 38CFR 16.104 (Subsection 4) . To protect the privacy and confidentiality of human subjects, study data were anonymous. This retrospective cohort study focused on active users of VHA cardiology care. Veterans aged 18 and older were included in the cohort if they had at least 1 outpatient cardiology visit for a cardiology diagnosis (the full list of diagnoses is provided in Table S1 in ) in the approximately 15-month period leading up the COVID-19 pandemic’s onset (calendar year 2019 and the beginning of 2020; January 1, 2019, to March 10, 2020) and had at least 2 outpatient cardiology visits in the first 2 years of the pandemic (March 11, 2020, to March 10, 2022). The first day of the pandemic was considered to be March 11, 2020, consistent with World Health Organization directives . We sourced all data from VHA’s Corporate Data Warehouse, a repository for veteran’s electronic health care records (172VA10P2: VHA Corporate Data Warehouse - VA 79 FR 4377). In addition to veterans’ dates of birth and, when applicable, dates of death, the dataset included all cardiology outpatient encounters in VHA, as defined by VHA-specific “stop codes,” where the visits were associated with an independent licensed practitioner with a unique National Provider Identifier (NPI). These 3-digit codes, available through VHA’s Managerial Cost Accounting system, characterize all VHA outpatient encounters and associated clinical work units (Table S2 in ). Stop codes were also used to define whether the visit was conducted in person or via phone or video, with telehealth visits defined as those taking place by phone or video. Visits for cardiac rehabilitation were not included. We captured veteran sociodemographic and clinical characteristics in a manner consistent with existing VHA telehealth literature . Age at the beginning of the pandemic was categorized into 4 groups, roughly corresponding to quartiles for the study population: <50, 50-64, 65-74, and ≥75 years. Race was categorized as American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, unknown, or White, and ethnicity was categorized as Hispanic or Latino, not Hispanic or Latino, or unknown, both based on the most frequently recorded race or ethnicity identification in the electronic health record. Separate categories were created for missing race or ethnicity classification. Rurality, defined as highly rural (population density of fewer than 7 people per square mile), rural, or urban, was based on US Census Bureau criteria and derived from VHA’s Planning Systems Support Group (PSSG) Geocoded Enrollee Files in the Corporate Data Warehouse. Drive time to secondary care, which includes cardiology care, was also sourced from PSSG files and was categorized as short (≤30 min), medium (31-60 min), or long (>60 min). We included VHA enrollment priority category as a measure of social and medical risk; this system groups veterans based on military service–connected disability, recent military service, income, and other factors . As in prior work , the 8 enrollment priority categories were condensed into 4: high disability (>50% service-connected disability or VHA catastrophically disabled), low/moderate disability (10%-40% service-connected disability or military exposure), low income (annual income below area-adjusted mean), or without special VHA enrollment priority. Noncardiology care was captured as primary care visits in the year prior to the study period and categorized into tertiles thereof (0-4, 5-8, or ≥9). Use of mental health care and emergency department or urgent care visits in the year prior to the analysis period were included as binary variables. Veteran chronic conditions were calculated out of a predefined group of 47 possible International Classification of Disease, Tenth Revision ( ICD-10 ) diagnosis groups, constructed in prior studies in VHA’s population (Table S3 in ). Housing instability was based on a combination of outpatient stop codes denoting use of Veterans Affairs housing services and diagnosis codes (Table S2 in ). Calendar year (2020, 2021, and 2022) was also included. While in practice patients may see multiple clinicians (including, eg, a nurse practitioner and a physician, or a trainee and an attending physician), sometimes across different facilities, for the purposes of this analysis, we assigned patients a primary cardiology clinician and both patients and clinicians a primary facility. If patients had cardiology encounters with multiple independent licensed practitioners, we defined their main cardiology provider as the provider they had seen most often, or in the case of ties, most recently. In this cohort, 25.1% (56,176/223,809) of patients saw a single cardiology provider; 27.9% (62,443/223,809/N) saw 2, and 47% (105,190/223,809) saw 3 or more cardiology providers. Likewise, for patients seen at multiple VHA medical centers (ie, facilities) for cardiology care, the patient’s home site was the site at which the majority of their cardiology encounters took place. In total, 92.6% (207,247/223,809) of patients received care from a single VHA medical center, and 99.6% (222,914/223,809) received care from 2 or fewer. In addition to descriptive statistics for patient characteristics, we constructed multilevel logistic regression models of our primary outcome, a patient’s odds of receiving cardiology telehealth care (ie, care delivered by phone or video). These models included random effects for the patient, the patient’s main cardiology provider, and the patient’s home VHA facility for specialty cardiology care. Models were adjusted for the patient sociodemographic and clinical characteristics delineated above and calendar year as fixed effects. Statistical analyses were conducted in Stata 17 (StataCorp, LLC). This analysis was carried out as part of the Virtual Access Quality Enhancement Research Initiative, which is designated as nonresearch quality improvement by VHA program office partners in the VHA Office of Rural Health. The institutional review board at the Stanford Research Compliance Office determined this evaluation does not meet the requirement of research or clinical investigation per Federal Regulations 45CFR 46.104 (Subsection 4) and VA 38CFR 16.104 (Subsection 4) . To protect the privacy and confidentiality of human subjects, study data were anonymous. Our analytic cohort comprised 989,271 encounters for 223,809 veteran patients, among 2235 clinicians and 138 facilities (VHA medical centers). illustrates the structure of a basic 3-level multilevel statistical model and the numbers included at each level. depicts examples of how varying numbers of patients and clinicians may be grouped under a given facility (in this case, a Veterans Affairs medical center). Numbers in parentheses denote the level numbers in the model. Overall, among the 989,271 encounters, 4.2% (n=41,480) of encounters were video based and 34.3% (n=338,834) were phone based. Of these, 385,707 (39%) were virtual (telehealth) over the 2-year period, although this dropped from 52.5% (278,053/529,401) of encounters being conducted virtually in the first year of the pandemic to 23.4% (107,654/459,870) in the second year. Of these veterans, 161,424 had at least 1 telehealth (video or phone) visit . The majority of these individuals (n=137,004, 84.9%) used only the phone option for telehealth, as there were only 24,420 video care users. The average age for veterans in the overall cohort and the subset of telehealth users was the same: 70.2 years . Users of video care were a bit younger, with an average age of 68.7 years. Women comprised 3.4% (7616/223,809 and 5528/161,424, respectively) of the overall and telehealth groups. Most sociodemographic and clinical characteristics were similar between the general cohort and the subset of telehealth users, including proportions of each racial or ethnic group, rurality, drive time to care, enrollment priority, use of prior care, and numbers of chronic conditions. Veterans and providers varied considerably in their encounters per person (Figure S1 in ). For patients, the mean number of encounters was 4 (SD 3), and for providers, the mean number of encounters among this patient cohort was 443 (SD 648). The mean patients per facility was 1749 (SD 1139) and the mean cardiology providers per facility was 17 (SD 14). In adjusted multilevel models with random intercepts for the patient, patient’s main clinician, and patient’s home site, most differences by patient characteristics were small in magnitude if present ( ; Table S4 in ). However, there were several groups of veterans with higher adjusted odds of using cardiology telehealth care: most notably, women (adjusted odds ratio [AOR] 1.08, 95% CI 1.05-1.1); Hispanic or Latino veterans (AOR 1.46, 95% CI 1.43-1.49); and those with medium or long drive time (AOR 1.11, 95% CI 1.10-1.12 and AOR 1.09, 95% CI 1.07-1.10, respectively). Adjusted odds of using cardiology telehealth care differed minimally by age (for age 65-74 years compared to the reference category of age 18-49 years, AOR 0.97, 95% CI 0.94-0.99; adjusted odds for the other age categories were not statistically different from 1). Adjusted odds of using telehealth were slightly lower for rural and highly rural veterans compared to those living in urban settings (AOR 0.92, 95% CI 0.91-0.93 and AOR 0.93, 95% CI 0.91-0.96, respectively). Among veterans of different race and ethnicity groups, adjusted odds were lower for those of American Indian or Alaska Native or Black or African American race compared to White veterans (AOR 0.93, 95% CI 0.89-0.98 and AOR 0.97, 95% CI 0.96-0.98, respectively) and higher for those of unknown (to VHA) race (AOR 1.08, 95% CI 1.05-1.10). As above, we did see a larger-magnitude increase for veterans identifying as Hispanic or Latino, and to a lesser extent, unknown ethnicity (AOR 1.12, 95% CI 1.09-1.15). Compared to those enrolled in VHA without special considerations, patients with low income had a slightly lower AOR for using cardiology telehealth care (AOR 0.96, 95% CI 0.94-0.97), as did those with low or moderate levels of disability (AOR 0.94, 95% CI 0.93-0.96); there was no difference from the reference group for those with high levels of disability. We also saw no differences in AOR for telehealth use among patients with a history of housing instability compared to those without such a history. Having a higher number of chronic health conditions was associated with slightly lower odds of using cardiology telehealth care compared to our reference of having 0-3 chronic conditions (4-7 conditions, AOR 0.95, 95% CI 0.94-0.97; 8-11 conditions, AOR 0.93, 95% CI 0.91-0.94; 12 or more conditions, AOR 0.93, 95% CI 0.91-0.95). Examining relative proportions of variation in a patient’s likelihood of cardiology telehealth care use (ie, the intraclass correlation coefficient), 40.5% (95% CI 35.8%-45.3%) of variation was found at the patient level, 30.8% (95% CI 25.8%-36.2%) at the clinician level, and 7.0% (95% CI 6.3%-7.7%) at the facility level. In total, 21.7% of variation remained unexplained. Principal Findings This analysis examines predictors of cardiology telehealth use among active users of cardiology care in this nation-wide integrated health care system. We found that patient-level characteristics explained the largest share of the attributable variability in VHA cardiology telehealth use. Clinician-level characteristics explained a more modest share, while facility-level factors contributed little to the variability seen. Our findings may reflect a high level of standardization in telehealth-related policies (eg, around reimbursement) across VHA facilities. These results suggest that policy solutions intended to improve access and equity in use of cardiology telehealth care should focus on the patient and clinician levels. Such policy levers could include device or technical support for both patients and clinicians to increase the uptake of telehealth. For example, VHA has implemented a Digital Divide consult and tablet distribution program to offer video-enabled devices to veterans with access barriers. Other strategies might include additional support staff to “room” a patient virtually and enter vital signs or chief complaint information; travel reimbursement for in-person appointments; and differential reimbursement for different visit modalities for clinicians, among many others. It should be noted that the desirability of increasing equity of telehealth use depends on the extent to which similar outcomes result from in-person and telehealth care. If the 2 modes are unequal in quality for a given use case, greater use of telehealth in a given subpopulation could represent worse access to quality care. Ongoing research comparing quality of telehealth and in-person care will help to unravel this issue. The highest-yield drivers may be different in other environments. For example, Tzeng et al found that facility-level factors accounted for more than clinician-level factors in total variance in outpatient virtual clinic use across multiple specialties in Taiwan. Rodriguez et al found contributions to variance in the opposite order from our study (38% attributable to practices, 26% to clinicians, and 9% to patients) in video use (rather than telehealth use more generally) in primary and specialty care practices in the Mass General Brigham system. This variability underscores that drivers of telehealth use are likely to depend heavily on context: the level of the facility (department, practice, or medical center), whether the analysis focuses only on video or on all telehealth, and which specialties are included. An important caveat when considering patient- versus clinician-level characteristics or policies is that it is challenging to completely disentangle factors at the level of patient versus clinician, as some subset of “patient” contribution may actually be clinician response to a given patient-level characteristic (eg, preferentially seeing older patients in person rather than via telehealth). To the extent that identified clinician-level variability reflects true clinician-level variation in practice, this raises the question of what the optimal breakdown of modalities ought to be for a given clinician, and how much variability in that breakdown across individuals is reasonable. Given that clinicians have differing preferences for telehealth use , are all clinicians obliged to offer some telehealth? Or is it acceptable—for quality and patient satisfaction—for some “virtualists” to offer mostly or exclusively telehealth and others, primarily in-person care? These questions require further attention in the postpandemic period. The reimbursement landscape for telehealth modalities will continue to evolve and affect the type of care offered. Reimbursing clinical time differentially depending on how care is delivered influences clinicians’ preferences around telehealth—even in integrated health care systems , where the clinician’s income is not directly impacted. If the Centers of Medicare and Medicaid (CMS) and health insurers choose to reimburse differently for video, telephone, and in-person visits, the drivers of telehealth use will undoubtedly change. With regard to the association between telehealth use and other patient-level characteristics, consistent with other studies of VHA cardiology , Hispanic or Latino veterans had higher adjusted odds of cardiology telehealth use compared to not Hispanic or Latino individuals, and rural-dwelling veterans had lower odds of telehealth use compared to urban-dwellers. Earlier in the pandemic, we found that men were more likely than women to use cardiology telehealth care, an effect reversed in this study (potentially because of evolving patterns of use over time). Previously, we also found no association between telehealth use and long drive time, whereas in this study, those with a longer drive time were more likely to use telehealth. As in prior work examining disparities in cardiology telehealth care in VHA and across other health care systems, there were small or no differences by race ; whether or not differences in telehealth use appear by age has varied across systems . Limitations Our study has limitations common to observational data and work in VHA’s system. First, generalizability beyond VHA—a national, integrated health care system with long-standing, well-established processes in place to standardize practices across facilities—or to populations with less engaged users of care may be limited. Second, because we constructed our facility-level variable at the VHA medical center level, we cannot assess whether more granular facility levels (eg, individual clinics) could explain additional variation in telehealth use. Third, while all patients included had at least 1 cardiology diagnosis, we lack the specific diagnoses that were being addressed at these encounters. Fourth, we have analyzed telehealth visits with phone and video visits combined; in this population, video visits were rare enough that 3-level multilevel models were not feasible, and thus we cannot specifically report on the differential contributions to variability in video care use or whether those differ from the pattern among all telehealth visits. Fifth, our results represent a pooled estimate across the study period of 2020-2022, while use patterns may have varied across the pandemic . Sixth, we do not include facility-level or provider-level characteristics due to computational limitations and data availability. Finally, we attributed patients to a single clinician and site to allow our statistical models to run; as a majority of veterans did see more than 1 cardiology provider during the study period, this required a significant simplification of our complex real-world data. Conclusions In sum, within VHA, a nationally integrated health care system, there are marked differences in the degree to which patient, clinician, and facility factors influence use of cardiology telehealth care. Given that most variability occurs at the patient and clinician levels, it suggests that these levels might be optimal targets for interventions intended to alter the mix of telehealth versus in-person care use. This analysis examines predictors of cardiology telehealth use among active users of cardiology care in this nation-wide integrated health care system. We found that patient-level characteristics explained the largest share of the attributable variability in VHA cardiology telehealth use. Clinician-level characteristics explained a more modest share, while facility-level factors contributed little to the variability seen. Our findings may reflect a high level of standardization in telehealth-related policies (eg, around reimbursement) across VHA facilities. These results suggest that policy solutions intended to improve access and equity in use of cardiology telehealth care should focus on the patient and clinician levels. Such policy levers could include device or technical support for both patients and clinicians to increase the uptake of telehealth. For example, VHA has implemented a Digital Divide consult and tablet distribution program to offer video-enabled devices to veterans with access barriers. Other strategies might include additional support staff to “room” a patient virtually and enter vital signs or chief complaint information; travel reimbursement for in-person appointments; and differential reimbursement for different visit modalities for clinicians, among many others. It should be noted that the desirability of increasing equity of telehealth use depends on the extent to which similar outcomes result from in-person and telehealth care. If the 2 modes are unequal in quality for a given use case, greater use of telehealth in a given subpopulation could represent worse access to quality care. Ongoing research comparing quality of telehealth and in-person care will help to unravel this issue. The highest-yield drivers may be different in other environments. For example, Tzeng et al found that facility-level factors accounted for more than clinician-level factors in total variance in outpatient virtual clinic use across multiple specialties in Taiwan. Rodriguez et al found contributions to variance in the opposite order from our study (38% attributable to practices, 26% to clinicians, and 9% to patients) in video use (rather than telehealth use more generally) in primary and specialty care practices in the Mass General Brigham system. This variability underscores that drivers of telehealth use are likely to depend heavily on context: the level of the facility (department, practice, or medical center), whether the analysis focuses only on video or on all telehealth, and which specialties are included. An important caveat when considering patient- versus clinician-level characteristics or policies is that it is challenging to completely disentangle factors at the level of patient versus clinician, as some subset of “patient” contribution may actually be clinician response to a given patient-level characteristic (eg, preferentially seeing older patients in person rather than via telehealth). To the extent that identified clinician-level variability reflects true clinician-level variation in practice, this raises the question of what the optimal breakdown of modalities ought to be for a given clinician, and how much variability in that breakdown across individuals is reasonable. Given that clinicians have differing preferences for telehealth use , are all clinicians obliged to offer some telehealth? Or is it acceptable—for quality and patient satisfaction—for some “virtualists” to offer mostly or exclusively telehealth and others, primarily in-person care? These questions require further attention in the postpandemic period. The reimbursement landscape for telehealth modalities will continue to evolve and affect the type of care offered. Reimbursing clinical time differentially depending on how care is delivered influences clinicians’ preferences around telehealth—even in integrated health care systems , where the clinician’s income is not directly impacted. If the Centers of Medicare and Medicaid (CMS) and health insurers choose to reimburse differently for video, telephone, and in-person visits, the drivers of telehealth use will undoubtedly change. With regard to the association between telehealth use and other patient-level characteristics, consistent with other studies of VHA cardiology , Hispanic or Latino veterans had higher adjusted odds of cardiology telehealth use compared to not Hispanic or Latino individuals, and rural-dwelling veterans had lower odds of telehealth use compared to urban-dwellers. Earlier in the pandemic, we found that men were more likely than women to use cardiology telehealth care, an effect reversed in this study (potentially because of evolving patterns of use over time). Previously, we also found no association between telehealth use and long drive time, whereas in this study, those with a longer drive time were more likely to use telehealth. As in prior work examining disparities in cardiology telehealth care in VHA and across other health care systems, there were small or no differences by race ; whether or not differences in telehealth use appear by age has varied across systems . Our study has limitations common to observational data and work in VHA’s system. First, generalizability beyond VHA—a national, integrated health care system with long-standing, well-established processes in place to standardize practices across facilities—or to populations with less engaged users of care may be limited. Second, because we constructed our facility-level variable at the VHA medical center level, we cannot assess whether more granular facility levels (eg, individual clinics) could explain additional variation in telehealth use. Third, while all patients included had at least 1 cardiology diagnosis, we lack the specific diagnoses that were being addressed at these encounters. Fourth, we have analyzed telehealth visits with phone and video visits combined; in this population, video visits were rare enough that 3-level multilevel models were not feasible, and thus we cannot specifically report on the differential contributions to variability in video care use or whether those differ from the pattern among all telehealth visits. Fifth, our results represent a pooled estimate across the study period of 2020-2022, while use patterns may have varied across the pandemic . Sixth, we do not include facility-level or provider-level characteristics due to computational limitations and data availability. Finally, we attributed patients to a single clinician and site to allow our statistical models to run; as a majority of veterans did see more than 1 cardiology provider during the study period, this required a significant simplification of our complex real-world data. In sum, within VHA, a nationally integrated health care system, there are marked differences in the degree to which patient, clinician, and facility factors influence use of cardiology telehealth care. Given that most variability occurs at the patient and clinician levels, it suggests that these levels might be optimal targets for interventions intended to alter the mix of telehealth versus in-person care use. |
The role of rhizosphere phages in soil health | 0206fff0-9a8a-40e3-844f-98949bfcb066 | 11065364 | Microbiology[mh] | The One Health concept underscores the interconnectedness of human, animal, plant, and environmental health, emphasizing their interdependence (Banerjee and van der Heijden ). Originally, the One Health concept centered on the transmission of zoonotic pathogens, vectors of pathogens, and movement and persistence of antibiotic resistance genes (ARGs) across environments (Destoumieux-Garzón et al. ). Recently, soils have been proposed to be a critical compartment linking human, animal, and plant health via the sharing of microorganisms (Banerjee and van der Heijden ). Further, soil microbiomes have been estimated to provide over 40 functions linked with plant growth, nutrient uptake and cycling, provision of essential ecosystem services, and suppression of pathogens, highlighting their importance in One Health framework (Lehmann et al. , Banerjee and van der Heijden ). Especially, plant rhizosphere is considered to play an important role in maintaining high microbial diversity, which has been positively associated with soil health, crop yields, and ecosystem functioning (Fierer , Saleem et al. , Wagg et al. , Banerjee and van der Heijden ). The benefits of soil biodiversity can be mediated via mutualistic interactions between plants and microorganisms, resulting in improved plant growth (Trivedi et al. , Li et al. ). Additionally, high microbial diversity can be beneficial in preventing pathogen invasions and dominance, reducing economic losses on agricultural production (Strange and Scott , Delgado-Baquerizo et al. , Zheng et al. ). Such pathogen suppression can be driven by several different groups of microorganisms, including bacteria, fungi, protists, and bacteria-specific viruses—phages (Buee et al. , Wei et al. , Wang et al. , Xiong et al. ). Of these microbes, phages are the most understudied group even though they are estimated to be the most abundant entities on Earth (estimate 10 31 ) (Breitbart and Rohwer , Srinivasiah et al. ), constituting a significant portion of virus-like particles (VLPs) in the environment (Breitbart and Rohwer ). Previous research has demonstrated that phages play crucial roles in influencing microbial abundances, diversity, and functioning of ecosystems across aquatic, human, and terrestrial environments (Wilhelm and Suttle , Brum et al. , Argov et al. ). However, the role of phages in soil, rhizosphere and plant health remains relatively understudied. In this perspective, we review the significance of phages for soil health and microbial diversity within the One Health framework by focusing on both their ecological and evolutionary roles in rhizosphere microbiomes. The diversity of phages in the plant rhizosphere While the significance of phages for microbial ecology and evolution has been extensively studied especially in marine ecosystems (Diaz-Munoz and Koskella , Breitbart et al. ), the knowledge of phage diversity and their roles in soil and plant rhizosphere microbiomes is still relatively limited. In contrast to aquatic environments, soils exhibit higher heterogeneity due to variations in soil particle size, nutrient composition, soil biota, and plant community diversity and composition (Sharma et al. , ). Soils exhibit higher heterogeneity compared to aquatic environments, consisting of solid, liquid, and gaseous phases, which can considerably vary across space and time (Moldrup et al. ). Specifically, soil particle and aggregate sizes, and pore spaces affect hydraulic connectivity (Tecon and Or , Roux and Emerson ), which influences the movement of phages and bacteria within the soil matrix along with water (Mckay et al. , Marsh and Wellington , Philippot et al. ). Well-aggregated soils typically possess larger pores and better water infiltration compared to poorly structured ones, potentially facilitating greater dispersal and distribution of phages. Similarly, soils with larger particles (e.g. sandy soils) might allow easier phage movement owing to greater pore space and better water flow. In support of this, previous studies have shown that viral communities respond rapidly to wetting events, resulting in a significant increase in viral richness (Santos-Medellin et al. ). Additionally, the adsorption of viruses to soil particles, such as colloidal surfaces, has been found to enhance viral persistence and support higher viral abundances (Lipson and Stotzky , Zhuang and Jin ). It has also been shown that viral communities undergo shifts along thawing permafrost peatland soils, with correlations observed with host community composition, pH, soil moisture content, and soil depth (Emerson et al. ). As a result, the abundance and diversity of bacteria and phages varies spatially between and within terrestrial habitats and soil types (Williamson et al. , Geisen et al. ), resulting in relatively higher phage diversity in soils compared to aquatic environments (Guemes et al. ). The estimated number of distinct viral genotypes (richness) identified in soils varies between 1000 and 1 000 000 depending on the soil type (Ashelford et al. , Williamson et al. , Reavy et al. , Williamson et al. ). In contrast, viral richness estimates vary from 532 to 129 000 for marine, and between 400 and 40 000 viral types for freshwater systems (Green et al. ). Moreover, phage abundances have been estimated to be relatively more homogeneous in seawater (between 10 5 and 10 7 particles per millilitre) compared to soils (between 10 3 and 10 9 particles per gram of soil) (Graham et al. ). While these diversity and abundance estimates are highly variable, likely due to variation in abiotic and biotic factors between and within both habitats, they suggest that terrestrial environments harbour higher taxonomic viral diversity. Phages also exhibit extensive morphological diversity, including tailed, nontailed, and filamentous forms (Nobrega et al. ), show high variability in nucleic acids composition (dsDNA, ssDNA, dsRNA, and ssRNA) (Dion et al. ) and have adopted various life cycles, ranging from lytic to lysogenic and chronic (Simmonds et al. , Ofir and Sorek ). Especially, temperate phages capable of either lysing the host cell or integrating and replicating as part of the host genome are prevalent in soils (Argov et al. , Howard-Varona et al. , Sharma et al. ). When integrated into the host genome during lysogeny, temperate phages can facilitate their host survival, thus sustaining phage and bacterial population densities in soils (Williamson et al. , Weinbauer et al. , Chibani-Chennoufi et al. ). Soil phage diversity also varies spatially within a given location. One important factor shaping local phage community diversity is the presence of plants. For example, it has been shown that viral-to-bacterial ratios differ between the rhizosphere and bulk soils and that lower bacterial abundances in the bulk soil are thought to be the contributing factor explaining relatively lower phage diversity (Swanson et al. ). Similarly, Bi et al. identified significant differences in phage community composition between rhizosphere and bulk soils, which were mainly attributed to the absence of plant root exudates and plant litter in the bulk soil that acts as nutrient sources for bacteria (Haichar et al. , Zhalnina et al. ), promoting also higher phage abundances and diversity. Moreover, rhizosphere phage communities vary between different plant species, due to differences in plant root exudate composition (Zhalnina et al. ), which can determine the composition and abundances of plant-associated bacterial microbiomes (Wang et al. ). In addition to spatial variation, the diversity and activity of phages can show dynamic temporal changes, driven by seasonal fluctuations in temperature (Coclet et al. ), soil moisture (Santos-Medellin et al. ), plant growth and development (Yang et al. ), and anthropogenic factors such as crop management (Muscatt et al. ). These external factors can also influence the intrinsic dynamics between phages and their host, e.g. by triggering population fluctuations and ecological succession in microbial communities, which can feed back to ecosystem functioning (Liao et al. , Santos-Medellin et al. ). The emergence of novel methodologies for purifying, extracting, and quantifying phage assemblages from soils (Williamson et al. ), coupled with advancements in metagenomic sequencing, has paved the way for a more in-depth exploration of the true soil phage diversity (Paez-Espino et al. , Koonin and Yutin , Roux and Emerson , Mabrouk et al. ), while metatranscriptomic approaches have opened the door to study phage activity and RNA phage diversity (Callanan et al. , Neri et al. ). With these methods, we are continuously discovering novel phage diversity that does not exist in the current databases (Roux and Emerson ), increasing our understanding on the significance and various roles phages play for soil and rhizosphere microbiome diversity and functioning in terrestrial ecosystems. Ecological impacts of rhizosphere phages in soil ecosystems The viral shunt: the role of phages in soil nutrient cycle Phages play a crucial role in impacting the mortality of bacteria by lysing and releasing host cell contents into the environment, with significant consequences for the global cycling of nutrients, energy flow, and food web dynamics—a phenomenon known as the “viral shunt” in aquatic systems (Brum and Sullivan , Breitbart et al. ) (Fig. ). For instance, marine phages are estimated to lyse approximately one-third of ocean microorganisms per day, liberating carbon at a globally significant scale (Suttle , , Guidi et al. ). In contrast, there are still significant knowledge gaps regarding how soil phages contribute to food webs, decomposition of organic matter, carbon and nutrient cycling, greenhouse gas emissions, and agricultural productivity. Virulent phages can control host population abundances, thereby influencing rates of microbially mediated processes linked with the cycling of carbon, nitrogen, sulfur, and phosphorus in soils (Williamson et al. , Kimura et al. , Allen et al. , Helsley et al. ). For instance, phages that infect nitrogen-fixing rhizobia bacteria, have been shown to reduce nodulation by phage-sensitive rhizobia, thus influencing nitrogen fixation in legume–rhizobium symbiosis (Evans et al. , Sharma et al. ). Recently, temporal changes in phage communities were linked with nutrient cycling during composting, where phages specific to mesophilic and thermophilic bacteria tracked their host densities, triggering bacteria-phage community succession via top-down control (Liao et al. ). Crucially, nutrient turnover correlated positively with virus–host ratio, indicative of a positive relationship between ecosystem functioning, viral abundances, and viral activity (Liao et al. ). Moreover, viruses specific to mesophilic bacteria encoded and expressed several auxiliary metabolic genes (AMGs) linked to carbon cycling, impacting nutrient turnover alongside bacteria (Liao et al. ). Both temperate phages and virulent phages can encode AMGs, which can affect the host cell metabolism in ways that promote viral replication and host survival (Howard-Varona et al. , Puxty and Millard ). Phages are hence likely to influence nutrient cycling by metabolically reprogramming their host bacteria through the expression of virus-carried AMGs (Breitbart ) linked with carbon metabolism and degradation of soil organic matter (Trubl et al. , Wu et al. ). It remains yet unclear how phage-mediated nutrient cycling in the soil cascades through microbial food webs, affecting the plant growth and fertility of soils. Both lab- and field-scale experiments, are hence required to directly test how viruses might shape the soil microbiome composition and plant growth by turning over bacterial biomass via lysis and by encoding AMGs associated with nutrient cycling. Virulent phages: suppression of soil-borne bacterial pathogens via top-down density control Virulent phages obligately infect and lyse their host cells, exerting significant effects on host cell densities and triggering competitive dynamics within microbial communities (Morella et al. ) (Fig. ). As a result, virulent phages have been extensively explored for their potential as biological control agents, demonstrating successful applications in the control of plant and zoonotic pathogens in soils (Jones et al. , Buttimer et al. ). Phages are also more likely to survive in the soil as long as their host bacteria are present compared to biocontrol bacteria that might have poor survival in the rhizosphere due to lack of vacant niche space and competition with native microbiota (Jones et al. , Brodeur , Meyer , Buttimer et al. , Kaminsky et al. , AL-Ishaq et al. ). The earliest evidence of phage therapy applied to plant disease dates back to 1924 when the filtrate from rotten cabbage was used to inhibit the growth of Xanthomonas campestris (Mallmann and Hemstreet ). Since then, phage therapies have been used in the treatment of various phytopathogens, including Pseudomonas syringae (Frampton et al. , Rombouts et al. ), Ralstonia solanacearum (Fujiwara et al. , Wang et al. ), Xanthomonas spp. (Balogh et al. ), Erwinia amylovora (Schnabel and Jones , Kim et al. ), as well as zoonotic pathogens present in soils, including Salmonella anatum (Gessel et al. ) and Rhodococcus equi (Salifu et al. ). Most of these studies predominantly examined the direct effects of virulent phages on the population densities of target pathogens through cell lysis. As a result, there is a growing interest in utilizing phage-derived proteins, such as endolysins, for pathogen biocontrol (O’Flaherty et al. ). Researchers have identified several techniques to enhance the efficacy of phage biocontrol, including optimizing the timing, frequency, and dosage of application (Iriarte et al. , Cui et al. , Li et al. ), employing phages as multiphage cocktails (Alvarez et al. , Wang et al. , Rabiey et al. , Thapa Magar et al. ) or rationally combining phages with antibiotics (Torres-Barcelo and Hochberg , Torres-Barcelo et al. ) or probiotics (Wang et al. ). Several products have been developed and already made commercially available, including AgriPhage ™ and Erwiphage ™ (Grace et al. ). However, most of these products target pathogens in the phyllosphere and no products targeting soil-borne pathogens are yet commercially available to our knowledge. Beyond the ecological impacts of phage therapy in controlling pathogen densities, phages may also have indirect benefits for soil microbiome diversity by preventing pathogens from monopolizing the niche space, and potentially stabilizing interactions in rhizosphere microbiomes (Federici et al. ) (Fig. ). One previous study demonstrated that R. solanacearum -specific phage cocktail buffered the resident rhizosphere microbiota against changes induced by the pathogen invasion (Wang et al. ). In addition to affecting the bacterial community composition, the application of the phage cocktail also changed the potential functioning of the bacterial community by altering the proportion of taxa that exhibited facilitative or antagonistic pairwise interactions with the pathogen (Wang et al. ). These experimental findings are in line with other studies where healthy plants were associated with higher abundances of R. solanacearum -specific phages and a higher proportion of bacterial taxa exhibiting antagonism towards the pathogen (Wei et al. , Yang et al. ). Interestingly, phages specific to bacterial taxa that showed antagonism towards R. solanacearum , had an indirect positive effect on plant disease by controlling the densities of antagonistic bacteria both in the lab and the greenhouse experiments (Yang et al. ). While phage effets might not always be so drastic on the surrounding microbiota (Magar et al. ), these findings suggest that phage efficacy could be context-dependent, shaping and being shaped by the resident microbiota present in the rhizosphere. Such complex ecological feedback and dynamics triggered by virulent phages are now only starting to be discovered and will have implications for microbial soil ecology beyond pathogen density control. Evolutionary impacts of rhizosphere phages in soil ecosystems Temperate phages: horizontal transfer of AMGs in soils Temperate phages are widely acknowledged for their role in mediating horizontal gene transfer between bacteria via transduction and phages could hence drive bacterial evolution by promoting recombination and provision of new genes (Lwoff , Brussow et al. , Bobay et al. , De Paepe et al. , Martin-Galiano and Garcia ). Earlier microcosm work has demonstrated high efficiency of phage transduction in soils (Zeph et al. ). Even though the rate of phage transduction in natural soils is still less well-understood, several examples exist on phage-mediated HGT and associated benefits for host bacteria in soils. For instance, phages in atrazine-contaminated soils were found to be able to acquire the trzN gene, encoding a chlorohydrolase required for atrazine catabolism (Ghosh et al. ). Additionally, Ross and Topp conducted transduction experiments using phages isolated from the soil to infect Escherichia coli K-12 and discovered that sublethal antibiotic concentrations could promote phage-mediated HGT of ARGs in agricultural soil microbiomes. These phage-encoded ARGs include multidrug resistance, polymyxin, and β-lactamase resistance genes (Lekunberri et al. , Moon et al. ), that can help bacteria resist antimicrobials originating from anthropogenic or environmental sources when produced by plants, bacteria, or fungi. Phages carrying ARGs have been shown to be infective in propagation experiments, indicating their role as vehicles of ARG transmission between bacteria (Larranaga et al. ). While ARGs can be mobilized by phages (Torres-Barceló ), it is still, however, unclear how common this phenomenon is in soil microbiomes (Enault et al. ). Integration of temperate phages into bacterial genomes as prophages could also change bacterial gene expression, leading to loss of functioning of certain genes (Chen et al. , Hsu et al. , Zhou et al. ). For example, Davies et al. found that when transposable phage ɸ4 integrated randomly into the bacterial chromosome, it resulted in insertional inactivation of type IV pilus and Quorum Sensing-associated genes, which was adaptive. Lysogenic phages could further become ‘grounded’ if mutations in one or more phage genes result in the failure of prophage excision from the host genome, also referred to as ‘cryptic’ or defective prophages (Ramisetty and Sudhakari ). These defective prophages can further promote genome evolution through propensity for genetic variations including inversions, deletions, and insertions via horizontal gene transfer (Monteiro et al. , Ramisetty and Sudhakari ). Moreover, temperate phages can enhance bacterial adaptability by increasing the mutation supply rate and thus help generating new genetic raw material for selection (Canchaya et al. , Zhang et al. ). In addition to facilitating horizontal gene transfer, temperate phages are also capable of altering host metabolism through the expression of AMGs (Yu et al. , Sun et al. ) (Fig. ). AMGs originate from bacterial cells but are carried by phages to enhance their own and their host’s fitness and can also contribute to the breadth of the phage host range (Sharon et al. ). In cyanophages, AMGs have been associated with functions such as photosynthesis, nucleic acid synthesis, metabolism, and stress tolerance (Thompson et al. , Kelly et al. , Enav et al. ). Soil environments are also important reservoirs for viruses that encode AMGs (Sun et al. ). Phages can also provide their host bacteria beneficial traits through lysogenic conversion where they integrate into bacterial chromosome as prophages. These traits can, e.g. include virulence traits (Fortier and Sekulovic , Matos et al. , Taylor et al. ) or AMGs and different soil environments may enrich specific AMGs with diverse ecological functions. For example, phage AMGs have been associated with the breakdown of harmful pollutants, including atrazine degradation gene trzN in atrazine-contaminated soil (Ghosh et al. ), the arsenic resistance gene arsC in lysogenic soil viruses (Tang et al. ), and the virus-encoded L-2-haloacid dehalogenase gene (L-DEX) in organochlorine-contaminated soil (Zheng et al. ). Moreover, the presence of phage AMGs in vermicompost has been linked to both metabolism and pesticide biodegradation (Chao et al. ), while chromium-induced stress can enrich AMGs that contribute to microbial heavy metal detoxification and survival in stressful soil environments (Huang et al. ). Beyond helping host bacteria to survive in contaminated environments, phage AMGs can also be involved in the carbon and nitrogen cycling in agricultural soils (Roux and Emerson ), and participate in carbon and sulfur transformation in agricultural slurry (Cook et al. ). Some AMGs have also been associated with energy acquisition via oxidative respiration, degradation of organic matter, and plant-beneficial functions in the rhizosphere (Braga et al. , Wu et al. ). Selection could, hence act on both host bacteria and prophages, enriching their frequencies if prophage improve host bacterial fitness relative to prophage-free cells. Also, some plant-beneficial AMGs have been detected in phage genomes that possibly contributed to plant–microbe interactions (Braga et al. ). For example, succinoglycan and acetolactate biosynthesis play important roles in nodule formation and plant-growth promotion and have been found to be encoded by phages (Ryu et al. , Mendis et al. ). Phage-encoded AMGs can also carry pathogenicity factors, such as effector proteins, that could help pathogenic bacteria to evade plant immunity (Greenrod et al. ). For example, it was recently shown that hopAR1 effector protein is encoded by a prophage that can transmit these virulence factors between different P. syringae bacterial genotypes (Hulin et al. ). From the evolutionary perspective, selection could, thus act on both host bacteria and prophages, enriching their frequencies if prophages improve host bacterial fitness relative to prophage-free cells. A further investigation into the roles of phage AMGs in soil environments is needed to better understand their associated functions and evolutionary advantages for bacterial hosts and surrounding microbiota and plants. Phage–bacteria coevolution in the rhizosphere Rapid phage–bacteria coevolution plays a pivotal role in shaping the dynamics of microbial communities and ecosystem functioning in rhizosphere microbiomes (Koskella and Taylor , Fields and Friman ). To resist phage infection and lysis, soil bacteria have developed a plethora of resistance and defence mechanisms, while phages have evolved numerous ways to overcome them, resulting in a long-term, coevolutionary arms race (Bernheim and Sorek ) (Fig. ). To initiate the infections, phages first need to adsorb to bacterial surfaces to inject their genetic material inside the bacterial cells. To escape this, bacteria have evolved numerous ways to prevent phage adsorption, including losing the phage receptor, reducing the expression of the receptor, modification of the receptor through mutations, or producing proteins that block phage adsorption by masking the receptor (Rostol and Marraffini ). Once the phage has adsorbed to the surface of the bacteria, bacteria can further alter the permeability of the surface, preventing the injection of phage DNA (Labrie et al. ). If phages are successful in infecting their DNA or RNA within bacterial cells, bacteria can activate a second line of defences to recognize and degrade the phage nucleic acids. In summary, these defence strategies can be divided into two steps: first detecting the infection of incoming phage with sensors, and second, the initiation of interference on phage reproduction cycle (Georjon and Bernheim ). These mechanisms include, e.g. restriction-modification (R-M) (Vasu and Nagaraja ) and the CRISPR–Cas systems (Barrangou et al. ) that recognize and destroy incoming phage nucleic acids. If phages can avoid the recognition by these systems and program the host to start synthesizing phage proteins, other bacterial defence systems, such as ToxIN, DarTG, and CBASS (Georjon and Bernheim ), can detect the viral proteins and trigger abortive cell death, which will eliminate infecting phages, promoting the survival of surrounding uninfected bacterial cells (Gao et al. ). For example, phage infections can activate toxin functions, leading to interference with bacterial DNA replication and protein translation, and prevention of phage reproduction. Alternatively, phage infection can trigger the production of cyclic oligonucleotide-based antiphage signaling system (CBASS), which activates effector protein that destroys the host cell and block phage propagation (Georjon and Bernheim ). However, this hierarchical activation is only as one potential explanation for the presence of multiple different types of defence systems, and alternatively or additionally, complementary and synergistic effect between defence systems, might enable bacteria to adopt flexible defence strategies against phages (Zhuang and Jin ). Interestingly, antiphage defence systems can also be carried by prophages, which include repressor-mediated immunity, exclusion-like systems, and restriction mechanisms, that can offer protection against a broad range of related and unrelated viruses (Kita et al. , Dedrick et al. , Patel and Maxwell ). Owen et al. identified BstA protein—a family of prophage-encoded phage-defence proteins—in various Gram-negative bacteria, which enable prophages to defend host cells against exogenous phage attacks without sacrificing their ability to replicate lytically. Additionally, Patel et al. discovered that a prophage can encode Tab protein, which mediates the antiphage defence by blocking virion assembly of invading phages. Furthermore, prophages have been shown to serve as primary reservoirs and distributors of defence systems in E. coli , which can be located in specific genomic regions, i.e. defence system islands (Rousset et al. , Vassallo et al. ). Through coevolution, phages have evolved multiple counter adaptations to avoid bacterial defence systems or infect bacterial cells with mutated or alternative receptors. For example, phage λ that primarily uses the LamB as its receptor, has been shown to rapidly coevolve to bind more efficiently to this receptor and even evolve to recognize alternative E. coli receptor (OmpF) in response to E. coli resistance evolution (Meyer et al. ). Such phage coevolutionary changes are often achieved via changes in phage tail fibers and other host-recognition proteins (Nobrega et al. , Altamirano and Barr , Borin et al. ). When phage nucleic acids enter the host bacteria, phages can employ various antidefence system strategies, including antirestriction modification and anti-CRISPR proteins. For instance, in coliphage P1 (Myoviridae), the proteins DarA and DarB are coinjected into the host cell with the phage genome. Both proteins bind to phage DNA, masking type I R–M recognition sites, preventing the degradation of phage DNA (Atanasiu et al. ). Moreover, phages have evolved anti-CRISPR proteins (Acrs) that inhibit the cleavage of Cas proteins. For example, AcrIIC4 is a broad-spectrum Acr that binds between the two recognition domains of Cas9, REC1 and REC2, restricting the movement of the REC2 domain and thereby maintaining the integrity of its genome (Sun et al. ). Previous studies have demonstrated that phage–bacteria coevolution follows fluctuating selection in the soil microcosms, where phages and bacteria adapt to their contemporary counterparts in time (Gomez and Buckling ). While a laboratory study showed that the rate of evolution increases with soil-inhabiting Pseudomonas fluorescens SBW25 in the presence of a phage (Pal et al. ), a follow-up microcosm study contradicted this finding, where the presence of virulent phages and a natural soil virome negatively affected the evolution of SBW25 (Gomez and Buckling ). While not specifically examining the coevolution between bacteria and phages, another study revealed that phages can rapidly select for resistant bacteria in the tomato rhizosphere, which leads to trade-off with bacterial growth and competitive ability (Wang et al. ). With the advancement of bioinformatic approaches, numerous novel defence systems and antidefence systems are continuously discovered (Gao et al. , Nussenzweig and Marraffini , Millman et al. ), and it is now becoming important to try to understand their significance, synergies and relative importance for phage–bacteria coevolution in natural environments, including rhizosphere. For example, as receptor and defence system-based resistances are not mutually exclusive (Alseth et al. , Wang et al. ), it is important to quantify their costs and benefits in ecologically realistic contexts to assess their importance for phage–bacteria coevolution in terrestrial ecosystems. Understanding the underlying variation and rate of phage resistance evolution in agricultural environments is especially important for the long-term success of phage biocontrol applications. The consequences of phage resistance evolution for bacterial fitness Research thus far has demonstrated that bacteria can rapidly evolve resistance to phages in the soil (Gomez and Buckling ) and the rhizosphere (Wang et al. ). However, evolving resistance to phages often comes with costs due to loss or reduced functioning of associated receptor genes, which could change how bacteria interact with other microbes (Fig. ). For example, evolution of broad phage resistance of phytopathogenic R. solanacearum was shown to lead to relatively higher costs of resistance in terms of reduced pathogen growth and competitiveness with nonresistant, ancestral R. solanacearum genotype (Wang et al. ). Costs of resistance could also affect how bacteria interact with plants or behave in their environment because receptor mutations often occur in surface proteins that may also use to attach on plant surfaces or move and navigate in the rhizosphere or soil matrix (Addy et al. , Ahmad et al. , Narulita et al. ). For example, phage resistance mutations in genes encoding type IV pilus and type II secretion systems important for bacterial movement and secretion of exoenzymes, respectively, have been linked to both phage resistance and loss of virulence in R. solanacearum (Narulita et al. , Xavier et al. , Wang et al. ). Moreover, mutations in the quorum-sensing (QS) signalling receptor gene, phcS , have been shown to lead to phage resistance and loss of virulence in R. solanacearum even though the underlying molecular mechanisms remain unclear (Wang et al. ). Finally, also the upregulation of CBASS and type I restriction-modification phage defence systems in response to phage exposure were found to correlate with reduced expression of motility and virulence-associated genes, including pilus biosynthesis and type II and III secretion systems, in R. solanacearum (Wang et al. ). Together these findings suggest that both phage resistance mutations and upregulation of phage defence systems could result in trade-offs with pathogen virulence and fitness. The evolution of phage resistance could also make bacteria more susceptible to other stresses. For example, phage-resistance mutations have been found to sensitize bacterial pathogens to antimicrobial compounds (Torres-Barcelo and Hochberg ), and in the clinical context, phage–antibiotic combinations have been found to have superior efficacy to mono-treatments because phage resistant bacteria became more sensitive to antibiotics due to mutations in genes that increase antibiotic efficacy (Chan et al. , Altamirano et al. ). While the evolution of generalist resistance to both antibiotics and phages is also possible (Moulton‐Brown and Friman , Burmeister and Turner ), similar sensitization of R. solanacearum to antibiotics produced by Bacillus amyloliquefaciens soil bacterium has been reported because of phage resistance evolution (Wang et al. ). If such trade-offs are more common among soil bacteria, phages could also indirectly affect antibiotics-mediated competition between different microbes in soil microbiomes. Finally, the magnitude of the cost of phage resistance is known to vary depending on the environmental conditions, such as nutrient availability, spatial structure, and the strength of resource competition (Brockhurst et al. , Lopez-Pascua et al. , Gomez and Buckling , Gomez et al. , Alseth et al. , Chevallereau et al. ). As a result, the evolution of phage resistance could be constrained by its associated costs in complex rhizosphere microbiomes compared to more benign lab environments. More realistic experiments using soil and plant systems are, hence required to better understand the fitness costs of phage–bacteria coevolution for both partners in plant rhizosphere microbiomes. Challenges and avenues for future research While research on phage genetics and molecular biology has been advancing in leaps and bounds along with the discovery of myriad of new defence systems (Georjon and Bernheim ), research on phage ecology and evolution in terrestrial environments is trailing back. While tracking interactions between focal species pairs, such as plant pathogenic bacteria and their specific phages (Gomez and Buckling , Wang et al. ), has helped to understand pairwise coevolution in soils and the rhizosphere, this view is simplistic as most bacteria in the soils are likely to have their own specific phages, and hence potential to coevolve and interact with them. While metagenomic sequencing and separation of phage and bacteria fractions before sequencing will has helped to unravel the true phage diversity in terrestrial systems (Roux and Emerson ), it is still challenging to infer interactions based on sequence data (Wu et al. ). This will undoubtedly change when we discover more about the genetics and molecular biology underlying phage–bacteria interactions, the advancement of bioinformatics and computational techniques (Gaborieau et al. ) and the use of more realistic model ecosystems, such as rhizoboxes (Wei et al. ). The structure of soils also creates limits for understanding phage–bacteria interactions at different spatial scales. For example, it is difficult to determine phage–bacteria population and metapopulation borders. How far can phages migrate passively or by hitchhiking with their host bacteria? How long are phages able to persist in environments in the absence of their hosts? All these questions remain yet to be answered. Going forward, it is also important to employ omics techniques to understand the role of temperate phages for the horizontal transfer of AMGs and how temperate phages interact with other mobile genetic elements such as plasmids, conjugative elements, and phage satellites (Rocha and Bikard ). For example, what is the relative contribution of phages to the accessory genome of bacteria in terrestrial ecosystems? What are the key roles of phages for their host metabolism and how is phage diversity linked with microbial and terrestrial ecosystem diversity? More work on how to potentially harness phage ecology and evolution for the benefit of phage applications and ecosystem functioning in terrestrial ecosystems is also needed. As phages are often specific to their target bacteria, they could potentially be used to precision-edit bacterial communities by removing specific bacterial taxa or functions (Wang et al. ). For example, in addition to targeting plant pathogenic bacteria, one could use phages to target bacteria that interact with the pathogen in the rhizosphere microbiomes (Li et al. , Yang et al. ) or target bacteria that carry ARGs that are located in conjugative plasmids, requiring pilus expression for their transmission, which makes them also susceptible to phage infections (Jalasvuori et al. ). Alternatively, it might be possible just to target specific key taxa known for ARG carriage or just reduce overall bacterial abundances using nonspecific phage communities as has been done with the treatment of sewage systems (Yu et al. ). In contrast to removing bacterial taxa or functions, temperate phages could also be used to introduce new beneficial functions in the soil microbiomes. For example, if plant growth-promoting AMGs are common among temperate phages, such phages might be used to deliver plant-beneficial functions into rhizosphere microbiomes to potentially improve plant health and crop yields. Such beneficial functions could be identified, e.g. from so-called suppressive soils that can constrain plant pathogen infections and promote plant growth (Garbeva et al. , Peralta et al. ). Instead of identifying specific phage species, employing phage communities as part of rhizosphere soil transplants could be used as an initial screen to identify beneficial microbial communities. For example, soil transplant from healthy tomato plants was shown to constrain R. solanacearum pathogen invasion in the next tomato generation and this effect was likely driven by both pathogen-suppressing bacteria and R. solanacearum -specific phages present in the transplanted soil (Wei et al. , Yang et al. ). Finally, ecological theory and experiments suggest that biodiversity correlates positively with ecosystem functioning and this pattern has been also shown to hold in terrestrial ecosystems (Pennekamp et al. , Jochum et al. ). Phage diversity could, hence be important by promoting bacterial community stability and providing a more diverse suite of AMGs and accessory genome functions for the bacterial and plant community. To address all these questions, more research on phage ecology and evolution in terrestrial ecosystems is required where phages are recognized as a vital component of soil microbiomes with clear links with human and plant compartments within the One Health framework.
While the significance of phages for microbial ecology and evolution has been extensively studied especially in marine ecosystems (Diaz-Munoz and Koskella , Breitbart et al. ), the knowledge of phage diversity and their roles in soil and plant rhizosphere microbiomes is still relatively limited. In contrast to aquatic environments, soils exhibit higher heterogeneity due to variations in soil particle size, nutrient composition, soil biota, and plant community diversity and composition (Sharma et al. , ). Soils exhibit higher heterogeneity compared to aquatic environments, consisting of solid, liquid, and gaseous phases, which can considerably vary across space and time (Moldrup et al. ). Specifically, soil particle and aggregate sizes, and pore spaces affect hydraulic connectivity (Tecon and Or , Roux and Emerson ), which influences the movement of phages and bacteria within the soil matrix along with water (Mckay et al. , Marsh and Wellington , Philippot et al. ). Well-aggregated soils typically possess larger pores and better water infiltration compared to poorly structured ones, potentially facilitating greater dispersal and distribution of phages. Similarly, soils with larger particles (e.g. sandy soils) might allow easier phage movement owing to greater pore space and better water flow. In support of this, previous studies have shown that viral communities respond rapidly to wetting events, resulting in a significant increase in viral richness (Santos-Medellin et al. ). Additionally, the adsorption of viruses to soil particles, such as colloidal surfaces, has been found to enhance viral persistence and support higher viral abundances (Lipson and Stotzky , Zhuang and Jin ). It has also been shown that viral communities undergo shifts along thawing permafrost peatland soils, with correlations observed with host community composition, pH, soil moisture content, and soil depth (Emerson et al. ). As a result, the abundance and diversity of bacteria and phages varies spatially between and within terrestrial habitats and soil types (Williamson et al. , Geisen et al. ), resulting in relatively higher phage diversity in soils compared to aquatic environments (Guemes et al. ). The estimated number of distinct viral genotypes (richness) identified in soils varies between 1000 and 1 000 000 depending on the soil type (Ashelford et al. , Williamson et al. , Reavy et al. , Williamson et al. ). In contrast, viral richness estimates vary from 532 to 129 000 for marine, and between 400 and 40 000 viral types for freshwater systems (Green et al. ). Moreover, phage abundances have been estimated to be relatively more homogeneous in seawater (between 10 5 and 10 7 particles per millilitre) compared to soils (between 10 3 and 10 9 particles per gram of soil) (Graham et al. ). While these diversity and abundance estimates are highly variable, likely due to variation in abiotic and biotic factors between and within both habitats, they suggest that terrestrial environments harbour higher taxonomic viral diversity. Phages also exhibit extensive morphological diversity, including tailed, nontailed, and filamentous forms (Nobrega et al. ), show high variability in nucleic acids composition (dsDNA, ssDNA, dsRNA, and ssRNA) (Dion et al. ) and have adopted various life cycles, ranging from lytic to lysogenic and chronic (Simmonds et al. , Ofir and Sorek ). Especially, temperate phages capable of either lysing the host cell or integrating and replicating as part of the host genome are prevalent in soils (Argov et al. , Howard-Varona et al. , Sharma et al. ). When integrated into the host genome during lysogeny, temperate phages can facilitate their host survival, thus sustaining phage and bacterial population densities in soils (Williamson et al. , Weinbauer et al. , Chibani-Chennoufi et al. ). Soil phage diversity also varies spatially within a given location. One important factor shaping local phage community diversity is the presence of plants. For example, it has been shown that viral-to-bacterial ratios differ between the rhizosphere and bulk soils and that lower bacterial abundances in the bulk soil are thought to be the contributing factor explaining relatively lower phage diversity (Swanson et al. ). Similarly, Bi et al. identified significant differences in phage community composition between rhizosphere and bulk soils, which were mainly attributed to the absence of plant root exudates and plant litter in the bulk soil that acts as nutrient sources for bacteria (Haichar et al. , Zhalnina et al. ), promoting also higher phage abundances and diversity. Moreover, rhizosphere phage communities vary between different plant species, due to differences in plant root exudate composition (Zhalnina et al. ), which can determine the composition and abundances of plant-associated bacterial microbiomes (Wang et al. ). In addition to spatial variation, the diversity and activity of phages can show dynamic temporal changes, driven by seasonal fluctuations in temperature (Coclet et al. ), soil moisture (Santos-Medellin et al. ), plant growth and development (Yang et al. ), and anthropogenic factors such as crop management (Muscatt et al. ). These external factors can also influence the intrinsic dynamics between phages and their host, e.g. by triggering population fluctuations and ecological succession in microbial communities, which can feed back to ecosystem functioning (Liao et al. , Santos-Medellin et al. ). The emergence of novel methodologies for purifying, extracting, and quantifying phage assemblages from soils (Williamson et al. ), coupled with advancements in metagenomic sequencing, has paved the way for a more in-depth exploration of the true soil phage diversity (Paez-Espino et al. , Koonin and Yutin , Roux and Emerson , Mabrouk et al. ), while metatranscriptomic approaches have opened the door to study phage activity and RNA phage diversity (Callanan et al. , Neri et al. ). With these methods, we are continuously discovering novel phage diversity that does not exist in the current databases (Roux and Emerson ), increasing our understanding on the significance and various roles phages play for soil and rhizosphere microbiome diversity and functioning in terrestrial ecosystems.
The viral shunt: the role of phages in soil nutrient cycle Phages play a crucial role in impacting the mortality of bacteria by lysing and releasing host cell contents into the environment, with significant consequences for the global cycling of nutrients, energy flow, and food web dynamics—a phenomenon known as the “viral shunt” in aquatic systems (Brum and Sullivan , Breitbart et al. ) (Fig. ). For instance, marine phages are estimated to lyse approximately one-third of ocean microorganisms per day, liberating carbon at a globally significant scale (Suttle , , Guidi et al. ). In contrast, there are still significant knowledge gaps regarding how soil phages contribute to food webs, decomposition of organic matter, carbon and nutrient cycling, greenhouse gas emissions, and agricultural productivity. Virulent phages can control host population abundances, thereby influencing rates of microbially mediated processes linked with the cycling of carbon, nitrogen, sulfur, and phosphorus in soils (Williamson et al. , Kimura et al. , Allen et al. , Helsley et al. ). For instance, phages that infect nitrogen-fixing rhizobia bacteria, have been shown to reduce nodulation by phage-sensitive rhizobia, thus influencing nitrogen fixation in legume–rhizobium symbiosis (Evans et al. , Sharma et al. ). Recently, temporal changes in phage communities were linked with nutrient cycling during composting, where phages specific to mesophilic and thermophilic bacteria tracked their host densities, triggering bacteria-phage community succession via top-down control (Liao et al. ). Crucially, nutrient turnover correlated positively with virus–host ratio, indicative of a positive relationship between ecosystem functioning, viral abundances, and viral activity (Liao et al. ). Moreover, viruses specific to mesophilic bacteria encoded and expressed several auxiliary metabolic genes (AMGs) linked to carbon cycling, impacting nutrient turnover alongside bacteria (Liao et al. ). Both temperate phages and virulent phages can encode AMGs, which can affect the host cell metabolism in ways that promote viral replication and host survival (Howard-Varona et al. , Puxty and Millard ). Phages are hence likely to influence nutrient cycling by metabolically reprogramming their host bacteria through the expression of virus-carried AMGs (Breitbart ) linked with carbon metabolism and degradation of soil organic matter (Trubl et al. , Wu et al. ). It remains yet unclear how phage-mediated nutrient cycling in the soil cascades through microbial food webs, affecting the plant growth and fertility of soils. Both lab- and field-scale experiments, are hence required to directly test how viruses might shape the soil microbiome composition and plant growth by turning over bacterial biomass via lysis and by encoding AMGs associated with nutrient cycling. Virulent phages: suppression of soil-borne bacterial pathogens via top-down density control Virulent phages obligately infect and lyse their host cells, exerting significant effects on host cell densities and triggering competitive dynamics within microbial communities (Morella et al. ) (Fig. ). As a result, virulent phages have been extensively explored for their potential as biological control agents, demonstrating successful applications in the control of plant and zoonotic pathogens in soils (Jones et al. , Buttimer et al. ). Phages are also more likely to survive in the soil as long as their host bacteria are present compared to biocontrol bacteria that might have poor survival in the rhizosphere due to lack of vacant niche space and competition with native microbiota (Jones et al. , Brodeur , Meyer , Buttimer et al. , Kaminsky et al. , AL-Ishaq et al. ). The earliest evidence of phage therapy applied to plant disease dates back to 1924 when the filtrate from rotten cabbage was used to inhibit the growth of Xanthomonas campestris (Mallmann and Hemstreet ). Since then, phage therapies have been used in the treatment of various phytopathogens, including Pseudomonas syringae (Frampton et al. , Rombouts et al. ), Ralstonia solanacearum (Fujiwara et al. , Wang et al. ), Xanthomonas spp. (Balogh et al. ), Erwinia amylovora (Schnabel and Jones , Kim et al. ), as well as zoonotic pathogens present in soils, including Salmonella anatum (Gessel et al. ) and Rhodococcus equi (Salifu et al. ). Most of these studies predominantly examined the direct effects of virulent phages on the population densities of target pathogens through cell lysis. As a result, there is a growing interest in utilizing phage-derived proteins, such as endolysins, for pathogen biocontrol (O’Flaherty et al. ). Researchers have identified several techniques to enhance the efficacy of phage biocontrol, including optimizing the timing, frequency, and dosage of application (Iriarte et al. , Cui et al. , Li et al. ), employing phages as multiphage cocktails (Alvarez et al. , Wang et al. , Rabiey et al. , Thapa Magar et al. ) or rationally combining phages with antibiotics (Torres-Barcelo and Hochberg , Torres-Barcelo et al. ) or probiotics (Wang et al. ). Several products have been developed and already made commercially available, including AgriPhage ™ and Erwiphage ™ (Grace et al. ). However, most of these products target pathogens in the phyllosphere and no products targeting soil-borne pathogens are yet commercially available to our knowledge. Beyond the ecological impacts of phage therapy in controlling pathogen densities, phages may also have indirect benefits for soil microbiome diversity by preventing pathogens from monopolizing the niche space, and potentially stabilizing interactions in rhizosphere microbiomes (Federici et al. ) (Fig. ). One previous study demonstrated that R. solanacearum -specific phage cocktail buffered the resident rhizosphere microbiota against changes induced by the pathogen invasion (Wang et al. ). In addition to affecting the bacterial community composition, the application of the phage cocktail also changed the potential functioning of the bacterial community by altering the proportion of taxa that exhibited facilitative or antagonistic pairwise interactions with the pathogen (Wang et al. ). These experimental findings are in line with other studies where healthy plants were associated with higher abundances of R. solanacearum -specific phages and a higher proportion of bacterial taxa exhibiting antagonism towards the pathogen (Wei et al. , Yang et al. ). Interestingly, phages specific to bacterial taxa that showed antagonism towards R. solanacearum , had an indirect positive effect on plant disease by controlling the densities of antagonistic bacteria both in the lab and the greenhouse experiments (Yang et al. ). While phage effets might not always be so drastic on the surrounding microbiota (Magar et al. ), these findings suggest that phage efficacy could be context-dependent, shaping and being shaped by the resident microbiota present in the rhizosphere. Such complex ecological feedback and dynamics triggered by virulent phages are now only starting to be discovered and will have implications for microbial soil ecology beyond pathogen density control.
Phages play a crucial role in impacting the mortality of bacteria by lysing and releasing host cell contents into the environment, with significant consequences for the global cycling of nutrients, energy flow, and food web dynamics—a phenomenon known as the “viral shunt” in aquatic systems (Brum and Sullivan , Breitbart et al. ) (Fig. ). For instance, marine phages are estimated to lyse approximately one-third of ocean microorganisms per day, liberating carbon at a globally significant scale (Suttle , , Guidi et al. ). In contrast, there are still significant knowledge gaps regarding how soil phages contribute to food webs, decomposition of organic matter, carbon and nutrient cycling, greenhouse gas emissions, and agricultural productivity. Virulent phages can control host population abundances, thereby influencing rates of microbially mediated processes linked with the cycling of carbon, nitrogen, sulfur, and phosphorus in soils (Williamson et al. , Kimura et al. , Allen et al. , Helsley et al. ). For instance, phages that infect nitrogen-fixing rhizobia bacteria, have been shown to reduce nodulation by phage-sensitive rhizobia, thus influencing nitrogen fixation in legume–rhizobium symbiosis (Evans et al. , Sharma et al. ). Recently, temporal changes in phage communities were linked with nutrient cycling during composting, where phages specific to mesophilic and thermophilic bacteria tracked their host densities, triggering bacteria-phage community succession via top-down control (Liao et al. ). Crucially, nutrient turnover correlated positively with virus–host ratio, indicative of a positive relationship between ecosystem functioning, viral abundances, and viral activity (Liao et al. ). Moreover, viruses specific to mesophilic bacteria encoded and expressed several auxiliary metabolic genes (AMGs) linked to carbon cycling, impacting nutrient turnover alongside bacteria (Liao et al. ). Both temperate phages and virulent phages can encode AMGs, which can affect the host cell metabolism in ways that promote viral replication and host survival (Howard-Varona et al. , Puxty and Millard ). Phages are hence likely to influence nutrient cycling by metabolically reprogramming their host bacteria through the expression of virus-carried AMGs (Breitbart ) linked with carbon metabolism and degradation of soil organic matter (Trubl et al. , Wu et al. ). It remains yet unclear how phage-mediated nutrient cycling in the soil cascades through microbial food webs, affecting the plant growth and fertility of soils. Both lab- and field-scale experiments, are hence required to directly test how viruses might shape the soil microbiome composition and plant growth by turning over bacterial biomass via lysis and by encoding AMGs associated with nutrient cycling.
Virulent phages obligately infect and lyse their host cells, exerting significant effects on host cell densities and triggering competitive dynamics within microbial communities (Morella et al. ) (Fig. ). As a result, virulent phages have been extensively explored for their potential as biological control agents, demonstrating successful applications in the control of plant and zoonotic pathogens in soils (Jones et al. , Buttimer et al. ). Phages are also more likely to survive in the soil as long as their host bacteria are present compared to biocontrol bacteria that might have poor survival in the rhizosphere due to lack of vacant niche space and competition with native microbiota (Jones et al. , Brodeur , Meyer , Buttimer et al. , Kaminsky et al. , AL-Ishaq et al. ). The earliest evidence of phage therapy applied to plant disease dates back to 1924 when the filtrate from rotten cabbage was used to inhibit the growth of Xanthomonas campestris (Mallmann and Hemstreet ). Since then, phage therapies have been used in the treatment of various phytopathogens, including Pseudomonas syringae (Frampton et al. , Rombouts et al. ), Ralstonia solanacearum (Fujiwara et al. , Wang et al. ), Xanthomonas spp. (Balogh et al. ), Erwinia amylovora (Schnabel and Jones , Kim et al. ), as well as zoonotic pathogens present in soils, including Salmonella anatum (Gessel et al. ) and Rhodococcus equi (Salifu et al. ). Most of these studies predominantly examined the direct effects of virulent phages on the population densities of target pathogens through cell lysis. As a result, there is a growing interest in utilizing phage-derived proteins, such as endolysins, for pathogen biocontrol (O’Flaherty et al. ). Researchers have identified several techniques to enhance the efficacy of phage biocontrol, including optimizing the timing, frequency, and dosage of application (Iriarte et al. , Cui et al. , Li et al. ), employing phages as multiphage cocktails (Alvarez et al. , Wang et al. , Rabiey et al. , Thapa Magar et al. ) or rationally combining phages with antibiotics (Torres-Barcelo and Hochberg , Torres-Barcelo et al. ) or probiotics (Wang et al. ). Several products have been developed and already made commercially available, including AgriPhage ™ and Erwiphage ™ (Grace et al. ). However, most of these products target pathogens in the phyllosphere and no products targeting soil-borne pathogens are yet commercially available to our knowledge. Beyond the ecological impacts of phage therapy in controlling pathogen densities, phages may also have indirect benefits for soil microbiome diversity by preventing pathogens from monopolizing the niche space, and potentially stabilizing interactions in rhizosphere microbiomes (Federici et al. ) (Fig. ). One previous study demonstrated that R. solanacearum -specific phage cocktail buffered the resident rhizosphere microbiota against changes induced by the pathogen invasion (Wang et al. ). In addition to affecting the bacterial community composition, the application of the phage cocktail also changed the potential functioning of the bacterial community by altering the proportion of taxa that exhibited facilitative or antagonistic pairwise interactions with the pathogen (Wang et al. ). These experimental findings are in line with other studies where healthy plants were associated with higher abundances of R. solanacearum -specific phages and a higher proportion of bacterial taxa exhibiting antagonism towards the pathogen (Wei et al. , Yang et al. ). Interestingly, phages specific to bacterial taxa that showed antagonism towards R. solanacearum , had an indirect positive effect on plant disease by controlling the densities of antagonistic bacteria both in the lab and the greenhouse experiments (Yang et al. ). While phage effets might not always be so drastic on the surrounding microbiota (Magar et al. ), these findings suggest that phage efficacy could be context-dependent, shaping and being shaped by the resident microbiota present in the rhizosphere. Such complex ecological feedback and dynamics triggered by virulent phages are now only starting to be discovered and will have implications for microbial soil ecology beyond pathogen density control.
Temperate phages: horizontal transfer of AMGs in soils Temperate phages are widely acknowledged for their role in mediating horizontal gene transfer between bacteria via transduction and phages could hence drive bacterial evolution by promoting recombination and provision of new genes (Lwoff , Brussow et al. , Bobay et al. , De Paepe et al. , Martin-Galiano and Garcia ). Earlier microcosm work has demonstrated high efficiency of phage transduction in soils (Zeph et al. ). Even though the rate of phage transduction in natural soils is still less well-understood, several examples exist on phage-mediated HGT and associated benefits for host bacteria in soils. For instance, phages in atrazine-contaminated soils were found to be able to acquire the trzN gene, encoding a chlorohydrolase required for atrazine catabolism (Ghosh et al. ). Additionally, Ross and Topp conducted transduction experiments using phages isolated from the soil to infect Escherichia coli K-12 and discovered that sublethal antibiotic concentrations could promote phage-mediated HGT of ARGs in agricultural soil microbiomes. These phage-encoded ARGs include multidrug resistance, polymyxin, and β-lactamase resistance genes (Lekunberri et al. , Moon et al. ), that can help bacteria resist antimicrobials originating from anthropogenic or environmental sources when produced by plants, bacteria, or fungi. Phages carrying ARGs have been shown to be infective in propagation experiments, indicating their role as vehicles of ARG transmission between bacteria (Larranaga et al. ). While ARGs can be mobilized by phages (Torres-Barceló ), it is still, however, unclear how common this phenomenon is in soil microbiomes (Enault et al. ). Integration of temperate phages into bacterial genomes as prophages could also change bacterial gene expression, leading to loss of functioning of certain genes (Chen et al. , Hsu et al. , Zhou et al. ). For example, Davies et al. found that when transposable phage ɸ4 integrated randomly into the bacterial chromosome, it resulted in insertional inactivation of type IV pilus and Quorum Sensing-associated genes, which was adaptive. Lysogenic phages could further become ‘grounded’ if mutations in one or more phage genes result in the failure of prophage excision from the host genome, also referred to as ‘cryptic’ or defective prophages (Ramisetty and Sudhakari ). These defective prophages can further promote genome evolution through propensity for genetic variations including inversions, deletions, and insertions via horizontal gene transfer (Monteiro et al. , Ramisetty and Sudhakari ). Moreover, temperate phages can enhance bacterial adaptability by increasing the mutation supply rate and thus help generating new genetic raw material for selection (Canchaya et al. , Zhang et al. ). In addition to facilitating horizontal gene transfer, temperate phages are also capable of altering host metabolism through the expression of AMGs (Yu et al. , Sun et al. ) (Fig. ). AMGs originate from bacterial cells but are carried by phages to enhance their own and their host’s fitness and can also contribute to the breadth of the phage host range (Sharon et al. ). In cyanophages, AMGs have been associated with functions such as photosynthesis, nucleic acid synthesis, metabolism, and stress tolerance (Thompson et al. , Kelly et al. , Enav et al. ). Soil environments are also important reservoirs for viruses that encode AMGs (Sun et al. ). Phages can also provide their host bacteria beneficial traits through lysogenic conversion where they integrate into bacterial chromosome as prophages. These traits can, e.g. include virulence traits (Fortier and Sekulovic , Matos et al. , Taylor et al. ) or AMGs and different soil environments may enrich specific AMGs with diverse ecological functions. For example, phage AMGs have been associated with the breakdown of harmful pollutants, including atrazine degradation gene trzN in atrazine-contaminated soil (Ghosh et al. ), the arsenic resistance gene arsC in lysogenic soil viruses (Tang et al. ), and the virus-encoded L-2-haloacid dehalogenase gene (L-DEX) in organochlorine-contaminated soil (Zheng et al. ). Moreover, the presence of phage AMGs in vermicompost has been linked to both metabolism and pesticide biodegradation (Chao et al. ), while chromium-induced stress can enrich AMGs that contribute to microbial heavy metal detoxification and survival in stressful soil environments (Huang et al. ). Beyond helping host bacteria to survive in contaminated environments, phage AMGs can also be involved in the carbon and nitrogen cycling in agricultural soils (Roux and Emerson ), and participate in carbon and sulfur transformation in agricultural slurry (Cook et al. ). Some AMGs have also been associated with energy acquisition via oxidative respiration, degradation of organic matter, and plant-beneficial functions in the rhizosphere (Braga et al. , Wu et al. ). Selection could, hence act on both host bacteria and prophages, enriching their frequencies if prophage improve host bacterial fitness relative to prophage-free cells. Also, some plant-beneficial AMGs have been detected in phage genomes that possibly contributed to plant–microbe interactions (Braga et al. ). For example, succinoglycan and acetolactate biosynthesis play important roles in nodule formation and plant-growth promotion and have been found to be encoded by phages (Ryu et al. , Mendis et al. ). Phage-encoded AMGs can also carry pathogenicity factors, such as effector proteins, that could help pathogenic bacteria to evade plant immunity (Greenrod et al. ). For example, it was recently shown that hopAR1 effector protein is encoded by a prophage that can transmit these virulence factors between different P. syringae bacterial genotypes (Hulin et al. ). From the evolutionary perspective, selection could, thus act on both host bacteria and prophages, enriching their frequencies if prophages improve host bacterial fitness relative to prophage-free cells. A further investigation into the roles of phage AMGs in soil environments is needed to better understand their associated functions and evolutionary advantages for bacterial hosts and surrounding microbiota and plants. Phage–bacteria coevolution in the rhizosphere Rapid phage–bacteria coevolution plays a pivotal role in shaping the dynamics of microbial communities and ecosystem functioning in rhizosphere microbiomes (Koskella and Taylor , Fields and Friman ). To resist phage infection and lysis, soil bacteria have developed a plethora of resistance and defence mechanisms, while phages have evolved numerous ways to overcome them, resulting in a long-term, coevolutionary arms race (Bernheim and Sorek ) (Fig. ). To initiate the infections, phages first need to adsorb to bacterial surfaces to inject their genetic material inside the bacterial cells. To escape this, bacteria have evolved numerous ways to prevent phage adsorption, including losing the phage receptor, reducing the expression of the receptor, modification of the receptor through mutations, or producing proteins that block phage adsorption by masking the receptor (Rostol and Marraffini ). Once the phage has adsorbed to the surface of the bacteria, bacteria can further alter the permeability of the surface, preventing the injection of phage DNA (Labrie et al. ). If phages are successful in infecting their DNA or RNA within bacterial cells, bacteria can activate a second line of defences to recognize and degrade the phage nucleic acids. In summary, these defence strategies can be divided into two steps: first detecting the infection of incoming phage with sensors, and second, the initiation of interference on phage reproduction cycle (Georjon and Bernheim ). These mechanisms include, e.g. restriction-modification (R-M) (Vasu and Nagaraja ) and the CRISPR–Cas systems (Barrangou et al. ) that recognize and destroy incoming phage nucleic acids. If phages can avoid the recognition by these systems and program the host to start synthesizing phage proteins, other bacterial defence systems, such as ToxIN, DarTG, and CBASS (Georjon and Bernheim ), can detect the viral proteins and trigger abortive cell death, which will eliminate infecting phages, promoting the survival of surrounding uninfected bacterial cells (Gao et al. ). For example, phage infections can activate toxin functions, leading to interference with bacterial DNA replication and protein translation, and prevention of phage reproduction. Alternatively, phage infection can trigger the production of cyclic oligonucleotide-based antiphage signaling system (CBASS), which activates effector protein that destroys the host cell and block phage propagation (Georjon and Bernheim ). However, this hierarchical activation is only as one potential explanation for the presence of multiple different types of defence systems, and alternatively or additionally, complementary and synergistic effect between defence systems, might enable bacteria to adopt flexible defence strategies against phages (Zhuang and Jin ). Interestingly, antiphage defence systems can also be carried by prophages, which include repressor-mediated immunity, exclusion-like systems, and restriction mechanisms, that can offer protection against a broad range of related and unrelated viruses (Kita et al. , Dedrick et al. , Patel and Maxwell ). Owen et al. identified BstA protein—a family of prophage-encoded phage-defence proteins—in various Gram-negative bacteria, which enable prophages to defend host cells against exogenous phage attacks without sacrificing their ability to replicate lytically. Additionally, Patel et al. discovered that a prophage can encode Tab protein, which mediates the antiphage defence by blocking virion assembly of invading phages. Furthermore, prophages have been shown to serve as primary reservoirs and distributors of defence systems in E. coli , which can be located in specific genomic regions, i.e. defence system islands (Rousset et al. , Vassallo et al. ). Through coevolution, phages have evolved multiple counter adaptations to avoid bacterial defence systems or infect bacterial cells with mutated or alternative receptors. For example, phage λ that primarily uses the LamB as its receptor, has been shown to rapidly coevolve to bind more efficiently to this receptor and even evolve to recognize alternative E. coli receptor (OmpF) in response to E. coli resistance evolution (Meyer et al. ). Such phage coevolutionary changes are often achieved via changes in phage tail fibers and other host-recognition proteins (Nobrega et al. , Altamirano and Barr , Borin et al. ). When phage nucleic acids enter the host bacteria, phages can employ various antidefence system strategies, including antirestriction modification and anti-CRISPR proteins. For instance, in coliphage P1 (Myoviridae), the proteins DarA and DarB are coinjected into the host cell with the phage genome. Both proteins bind to phage DNA, masking type I R–M recognition sites, preventing the degradation of phage DNA (Atanasiu et al. ). Moreover, phages have evolved anti-CRISPR proteins (Acrs) that inhibit the cleavage of Cas proteins. For example, AcrIIC4 is a broad-spectrum Acr that binds between the two recognition domains of Cas9, REC1 and REC2, restricting the movement of the REC2 domain and thereby maintaining the integrity of its genome (Sun et al. ). Previous studies have demonstrated that phage–bacteria coevolution follows fluctuating selection in the soil microcosms, where phages and bacteria adapt to their contemporary counterparts in time (Gomez and Buckling ). While a laboratory study showed that the rate of evolution increases with soil-inhabiting Pseudomonas fluorescens SBW25 in the presence of a phage (Pal et al. ), a follow-up microcosm study contradicted this finding, where the presence of virulent phages and a natural soil virome negatively affected the evolution of SBW25 (Gomez and Buckling ). While not specifically examining the coevolution between bacteria and phages, another study revealed that phages can rapidly select for resistant bacteria in the tomato rhizosphere, which leads to trade-off with bacterial growth and competitive ability (Wang et al. ). With the advancement of bioinformatic approaches, numerous novel defence systems and antidefence systems are continuously discovered (Gao et al. , Nussenzweig and Marraffini , Millman et al. ), and it is now becoming important to try to understand their significance, synergies and relative importance for phage–bacteria coevolution in natural environments, including rhizosphere. For example, as receptor and defence system-based resistances are not mutually exclusive (Alseth et al. , Wang et al. ), it is important to quantify their costs and benefits in ecologically realistic contexts to assess their importance for phage–bacteria coevolution in terrestrial ecosystems. Understanding the underlying variation and rate of phage resistance evolution in agricultural environments is especially important for the long-term success of phage biocontrol applications. The consequences of phage resistance evolution for bacterial fitness Research thus far has demonstrated that bacteria can rapidly evolve resistance to phages in the soil (Gomez and Buckling ) and the rhizosphere (Wang et al. ). However, evolving resistance to phages often comes with costs due to loss or reduced functioning of associated receptor genes, which could change how bacteria interact with other microbes (Fig. ). For example, evolution of broad phage resistance of phytopathogenic R. solanacearum was shown to lead to relatively higher costs of resistance in terms of reduced pathogen growth and competitiveness with nonresistant, ancestral R. solanacearum genotype (Wang et al. ). Costs of resistance could also affect how bacteria interact with plants or behave in their environment because receptor mutations often occur in surface proteins that may also use to attach on plant surfaces or move and navigate in the rhizosphere or soil matrix (Addy et al. , Ahmad et al. , Narulita et al. ). For example, phage resistance mutations in genes encoding type IV pilus and type II secretion systems important for bacterial movement and secretion of exoenzymes, respectively, have been linked to both phage resistance and loss of virulence in R. solanacearum (Narulita et al. , Xavier et al. , Wang et al. ). Moreover, mutations in the quorum-sensing (QS) signalling receptor gene, phcS , have been shown to lead to phage resistance and loss of virulence in R. solanacearum even though the underlying molecular mechanisms remain unclear (Wang et al. ). Finally, also the upregulation of CBASS and type I restriction-modification phage defence systems in response to phage exposure were found to correlate with reduced expression of motility and virulence-associated genes, including pilus biosynthesis and type II and III secretion systems, in R. solanacearum (Wang et al. ). Together these findings suggest that both phage resistance mutations and upregulation of phage defence systems could result in trade-offs with pathogen virulence and fitness. The evolution of phage resistance could also make bacteria more susceptible to other stresses. For example, phage-resistance mutations have been found to sensitize bacterial pathogens to antimicrobial compounds (Torres-Barcelo and Hochberg ), and in the clinical context, phage–antibiotic combinations have been found to have superior efficacy to mono-treatments because phage resistant bacteria became more sensitive to antibiotics due to mutations in genes that increase antibiotic efficacy (Chan et al. , Altamirano et al. ). While the evolution of generalist resistance to both antibiotics and phages is also possible (Moulton‐Brown and Friman , Burmeister and Turner ), similar sensitization of R. solanacearum to antibiotics produced by Bacillus amyloliquefaciens soil bacterium has been reported because of phage resistance evolution (Wang et al. ). If such trade-offs are more common among soil bacteria, phages could also indirectly affect antibiotics-mediated competition between different microbes in soil microbiomes. Finally, the magnitude of the cost of phage resistance is known to vary depending on the environmental conditions, such as nutrient availability, spatial structure, and the strength of resource competition (Brockhurst et al. , Lopez-Pascua et al. , Gomez and Buckling , Gomez et al. , Alseth et al. , Chevallereau et al. ). As a result, the evolution of phage resistance could be constrained by its associated costs in complex rhizosphere microbiomes compared to more benign lab environments. More realistic experiments using soil and plant systems are, hence required to better understand the fitness costs of phage–bacteria coevolution for both partners in plant rhizosphere microbiomes.
Temperate phages are widely acknowledged for their role in mediating horizontal gene transfer between bacteria via transduction and phages could hence drive bacterial evolution by promoting recombination and provision of new genes (Lwoff , Brussow et al. , Bobay et al. , De Paepe et al. , Martin-Galiano and Garcia ). Earlier microcosm work has demonstrated high efficiency of phage transduction in soils (Zeph et al. ). Even though the rate of phage transduction in natural soils is still less well-understood, several examples exist on phage-mediated HGT and associated benefits for host bacteria in soils. For instance, phages in atrazine-contaminated soils were found to be able to acquire the trzN gene, encoding a chlorohydrolase required for atrazine catabolism (Ghosh et al. ). Additionally, Ross and Topp conducted transduction experiments using phages isolated from the soil to infect Escherichia coli K-12 and discovered that sublethal antibiotic concentrations could promote phage-mediated HGT of ARGs in agricultural soil microbiomes. These phage-encoded ARGs include multidrug resistance, polymyxin, and β-lactamase resistance genes (Lekunberri et al. , Moon et al. ), that can help bacteria resist antimicrobials originating from anthropogenic or environmental sources when produced by plants, bacteria, or fungi. Phages carrying ARGs have been shown to be infective in propagation experiments, indicating their role as vehicles of ARG transmission between bacteria (Larranaga et al. ). While ARGs can be mobilized by phages (Torres-Barceló ), it is still, however, unclear how common this phenomenon is in soil microbiomes (Enault et al. ). Integration of temperate phages into bacterial genomes as prophages could also change bacterial gene expression, leading to loss of functioning of certain genes (Chen et al. , Hsu et al. , Zhou et al. ). For example, Davies et al. found that when transposable phage ɸ4 integrated randomly into the bacterial chromosome, it resulted in insertional inactivation of type IV pilus and Quorum Sensing-associated genes, which was adaptive. Lysogenic phages could further become ‘grounded’ if mutations in one or more phage genes result in the failure of prophage excision from the host genome, also referred to as ‘cryptic’ or defective prophages (Ramisetty and Sudhakari ). These defective prophages can further promote genome evolution through propensity for genetic variations including inversions, deletions, and insertions via horizontal gene transfer (Monteiro et al. , Ramisetty and Sudhakari ). Moreover, temperate phages can enhance bacterial adaptability by increasing the mutation supply rate and thus help generating new genetic raw material for selection (Canchaya et al. , Zhang et al. ). In addition to facilitating horizontal gene transfer, temperate phages are also capable of altering host metabolism through the expression of AMGs (Yu et al. , Sun et al. ) (Fig. ). AMGs originate from bacterial cells but are carried by phages to enhance their own and their host’s fitness and can also contribute to the breadth of the phage host range (Sharon et al. ). In cyanophages, AMGs have been associated with functions such as photosynthesis, nucleic acid synthesis, metabolism, and stress tolerance (Thompson et al. , Kelly et al. , Enav et al. ). Soil environments are also important reservoirs for viruses that encode AMGs (Sun et al. ). Phages can also provide their host bacteria beneficial traits through lysogenic conversion where they integrate into bacterial chromosome as prophages. These traits can, e.g. include virulence traits (Fortier and Sekulovic , Matos et al. , Taylor et al. ) or AMGs and different soil environments may enrich specific AMGs with diverse ecological functions. For example, phage AMGs have been associated with the breakdown of harmful pollutants, including atrazine degradation gene trzN in atrazine-contaminated soil (Ghosh et al. ), the arsenic resistance gene arsC in lysogenic soil viruses (Tang et al. ), and the virus-encoded L-2-haloacid dehalogenase gene (L-DEX) in organochlorine-contaminated soil (Zheng et al. ). Moreover, the presence of phage AMGs in vermicompost has been linked to both metabolism and pesticide biodegradation (Chao et al. ), while chromium-induced stress can enrich AMGs that contribute to microbial heavy metal detoxification and survival in stressful soil environments (Huang et al. ). Beyond helping host bacteria to survive in contaminated environments, phage AMGs can also be involved in the carbon and nitrogen cycling in agricultural soils (Roux and Emerson ), and participate in carbon and sulfur transformation in agricultural slurry (Cook et al. ). Some AMGs have also been associated with energy acquisition via oxidative respiration, degradation of organic matter, and plant-beneficial functions in the rhizosphere (Braga et al. , Wu et al. ). Selection could, hence act on both host bacteria and prophages, enriching their frequencies if prophage improve host bacterial fitness relative to prophage-free cells. Also, some plant-beneficial AMGs have been detected in phage genomes that possibly contributed to plant–microbe interactions (Braga et al. ). For example, succinoglycan and acetolactate biosynthesis play important roles in nodule formation and plant-growth promotion and have been found to be encoded by phages (Ryu et al. , Mendis et al. ). Phage-encoded AMGs can also carry pathogenicity factors, such as effector proteins, that could help pathogenic bacteria to evade plant immunity (Greenrod et al. ). For example, it was recently shown that hopAR1 effector protein is encoded by a prophage that can transmit these virulence factors between different P. syringae bacterial genotypes (Hulin et al. ). From the evolutionary perspective, selection could, thus act on both host bacteria and prophages, enriching their frequencies if prophages improve host bacterial fitness relative to prophage-free cells. A further investigation into the roles of phage AMGs in soil environments is needed to better understand their associated functions and evolutionary advantages for bacterial hosts and surrounding microbiota and plants.
Rapid phage–bacteria coevolution plays a pivotal role in shaping the dynamics of microbial communities and ecosystem functioning in rhizosphere microbiomes (Koskella and Taylor , Fields and Friman ). To resist phage infection and lysis, soil bacteria have developed a plethora of resistance and defence mechanisms, while phages have evolved numerous ways to overcome them, resulting in a long-term, coevolutionary arms race (Bernheim and Sorek ) (Fig. ). To initiate the infections, phages first need to adsorb to bacterial surfaces to inject their genetic material inside the bacterial cells. To escape this, bacteria have evolved numerous ways to prevent phage adsorption, including losing the phage receptor, reducing the expression of the receptor, modification of the receptor through mutations, or producing proteins that block phage adsorption by masking the receptor (Rostol and Marraffini ). Once the phage has adsorbed to the surface of the bacteria, bacteria can further alter the permeability of the surface, preventing the injection of phage DNA (Labrie et al. ). If phages are successful in infecting their DNA or RNA within bacterial cells, bacteria can activate a second line of defences to recognize and degrade the phage nucleic acids. In summary, these defence strategies can be divided into two steps: first detecting the infection of incoming phage with sensors, and second, the initiation of interference on phage reproduction cycle (Georjon and Bernheim ). These mechanisms include, e.g. restriction-modification (R-M) (Vasu and Nagaraja ) and the CRISPR–Cas systems (Barrangou et al. ) that recognize and destroy incoming phage nucleic acids. If phages can avoid the recognition by these systems and program the host to start synthesizing phage proteins, other bacterial defence systems, such as ToxIN, DarTG, and CBASS (Georjon and Bernheim ), can detect the viral proteins and trigger abortive cell death, which will eliminate infecting phages, promoting the survival of surrounding uninfected bacterial cells (Gao et al. ). For example, phage infections can activate toxin functions, leading to interference with bacterial DNA replication and protein translation, and prevention of phage reproduction. Alternatively, phage infection can trigger the production of cyclic oligonucleotide-based antiphage signaling system (CBASS), which activates effector protein that destroys the host cell and block phage propagation (Georjon and Bernheim ). However, this hierarchical activation is only as one potential explanation for the presence of multiple different types of defence systems, and alternatively or additionally, complementary and synergistic effect between defence systems, might enable bacteria to adopt flexible defence strategies against phages (Zhuang and Jin ). Interestingly, antiphage defence systems can also be carried by prophages, which include repressor-mediated immunity, exclusion-like systems, and restriction mechanisms, that can offer protection against a broad range of related and unrelated viruses (Kita et al. , Dedrick et al. , Patel and Maxwell ). Owen et al. identified BstA protein—a family of prophage-encoded phage-defence proteins—in various Gram-negative bacteria, which enable prophages to defend host cells against exogenous phage attacks without sacrificing their ability to replicate lytically. Additionally, Patel et al. discovered that a prophage can encode Tab protein, which mediates the antiphage defence by blocking virion assembly of invading phages. Furthermore, prophages have been shown to serve as primary reservoirs and distributors of defence systems in E. coli , which can be located in specific genomic regions, i.e. defence system islands (Rousset et al. , Vassallo et al. ). Through coevolution, phages have evolved multiple counter adaptations to avoid bacterial defence systems or infect bacterial cells with mutated or alternative receptors. For example, phage λ that primarily uses the LamB as its receptor, has been shown to rapidly coevolve to bind more efficiently to this receptor and even evolve to recognize alternative E. coli receptor (OmpF) in response to E. coli resistance evolution (Meyer et al. ). Such phage coevolutionary changes are often achieved via changes in phage tail fibers and other host-recognition proteins (Nobrega et al. , Altamirano and Barr , Borin et al. ). When phage nucleic acids enter the host bacteria, phages can employ various antidefence system strategies, including antirestriction modification and anti-CRISPR proteins. For instance, in coliphage P1 (Myoviridae), the proteins DarA and DarB are coinjected into the host cell with the phage genome. Both proteins bind to phage DNA, masking type I R–M recognition sites, preventing the degradation of phage DNA (Atanasiu et al. ). Moreover, phages have evolved anti-CRISPR proteins (Acrs) that inhibit the cleavage of Cas proteins. For example, AcrIIC4 is a broad-spectrum Acr that binds between the two recognition domains of Cas9, REC1 and REC2, restricting the movement of the REC2 domain and thereby maintaining the integrity of its genome (Sun et al. ). Previous studies have demonstrated that phage–bacteria coevolution follows fluctuating selection in the soil microcosms, where phages and bacteria adapt to their contemporary counterparts in time (Gomez and Buckling ). While a laboratory study showed that the rate of evolution increases with soil-inhabiting Pseudomonas fluorescens SBW25 in the presence of a phage (Pal et al. ), a follow-up microcosm study contradicted this finding, where the presence of virulent phages and a natural soil virome negatively affected the evolution of SBW25 (Gomez and Buckling ). While not specifically examining the coevolution between bacteria and phages, another study revealed that phages can rapidly select for resistant bacteria in the tomato rhizosphere, which leads to trade-off with bacterial growth and competitive ability (Wang et al. ). With the advancement of bioinformatic approaches, numerous novel defence systems and antidefence systems are continuously discovered (Gao et al. , Nussenzweig and Marraffini , Millman et al. ), and it is now becoming important to try to understand their significance, synergies and relative importance for phage–bacteria coevolution in natural environments, including rhizosphere. For example, as receptor and defence system-based resistances are not mutually exclusive (Alseth et al. , Wang et al. ), it is important to quantify their costs and benefits in ecologically realistic contexts to assess their importance for phage–bacteria coevolution in terrestrial ecosystems. Understanding the underlying variation and rate of phage resistance evolution in agricultural environments is especially important for the long-term success of phage biocontrol applications.
Research thus far has demonstrated that bacteria can rapidly evolve resistance to phages in the soil (Gomez and Buckling ) and the rhizosphere (Wang et al. ). However, evolving resistance to phages often comes with costs due to loss or reduced functioning of associated receptor genes, which could change how bacteria interact with other microbes (Fig. ). For example, evolution of broad phage resistance of phytopathogenic R. solanacearum was shown to lead to relatively higher costs of resistance in terms of reduced pathogen growth and competitiveness with nonresistant, ancestral R. solanacearum genotype (Wang et al. ). Costs of resistance could also affect how bacteria interact with plants or behave in their environment because receptor mutations often occur in surface proteins that may also use to attach on plant surfaces or move and navigate in the rhizosphere or soil matrix (Addy et al. , Ahmad et al. , Narulita et al. ). For example, phage resistance mutations in genes encoding type IV pilus and type II secretion systems important for bacterial movement and secretion of exoenzymes, respectively, have been linked to both phage resistance and loss of virulence in R. solanacearum (Narulita et al. , Xavier et al. , Wang et al. ). Moreover, mutations in the quorum-sensing (QS) signalling receptor gene, phcS , have been shown to lead to phage resistance and loss of virulence in R. solanacearum even though the underlying molecular mechanisms remain unclear (Wang et al. ). Finally, also the upregulation of CBASS and type I restriction-modification phage defence systems in response to phage exposure were found to correlate with reduced expression of motility and virulence-associated genes, including pilus biosynthesis and type II and III secretion systems, in R. solanacearum (Wang et al. ). Together these findings suggest that both phage resistance mutations and upregulation of phage defence systems could result in trade-offs with pathogen virulence and fitness. The evolution of phage resistance could also make bacteria more susceptible to other stresses. For example, phage-resistance mutations have been found to sensitize bacterial pathogens to antimicrobial compounds (Torres-Barcelo and Hochberg ), and in the clinical context, phage–antibiotic combinations have been found to have superior efficacy to mono-treatments because phage resistant bacteria became more sensitive to antibiotics due to mutations in genes that increase antibiotic efficacy (Chan et al. , Altamirano et al. ). While the evolution of generalist resistance to both antibiotics and phages is also possible (Moulton‐Brown and Friman , Burmeister and Turner ), similar sensitization of R. solanacearum to antibiotics produced by Bacillus amyloliquefaciens soil bacterium has been reported because of phage resistance evolution (Wang et al. ). If such trade-offs are more common among soil bacteria, phages could also indirectly affect antibiotics-mediated competition between different microbes in soil microbiomes. Finally, the magnitude of the cost of phage resistance is known to vary depending on the environmental conditions, such as nutrient availability, spatial structure, and the strength of resource competition (Brockhurst et al. , Lopez-Pascua et al. , Gomez and Buckling , Gomez et al. , Alseth et al. , Chevallereau et al. ). As a result, the evolution of phage resistance could be constrained by its associated costs in complex rhizosphere microbiomes compared to more benign lab environments. More realistic experiments using soil and plant systems are, hence required to better understand the fitness costs of phage–bacteria coevolution for both partners in plant rhizosphere microbiomes.
While research on phage genetics and molecular biology has been advancing in leaps and bounds along with the discovery of myriad of new defence systems (Georjon and Bernheim ), research on phage ecology and evolution in terrestrial environments is trailing back. While tracking interactions between focal species pairs, such as plant pathogenic bacteria and their specific phages (Gomez and Buckling , Wang et al. ), has helped to understand pairwise coevolution in soils and the rhizosphere, this view is simplistic as most bacteria in the soils are likely to have their own specific phages, and hence potential to coevolve and interact with them. While metagenomic sequencing and separation of phage and bacteria fractions before sequencing will has helped to unravel the true phage diversity in terrestrial systems (Roux and Emerson ), it is still challenging to infer interactions based on sequence data (Wu et al. ). This will undoubtedly change when we discover more about the genetics and molecular biology underlying phage–bacteria interactions, the advancement of bioinformatics and computational techniques (Gaborieau et al. ) and the use of more realistic model ecosystems, such as rhizoboxes (Wei et al. ). The structure of soils also creates limits for understanding phage–bacteria interactions at different spatial scales. For example, it is difficult to determine phage–bacteria population and metapopulation borders. How far can phages migrate passively or by hitchhiking with their host bacteria? How long are phages able to persist in environments in the absence of their hosts? All these questions remain yet to be answered. Going forward, it is also important to employ omics techniques to understand the role of temperate phages for the horizontal transfer of AMGs and how temperate phages interact with other mobile genetic elements such as plasmids, conjugative elements, and phage satellites (Rocha and Bikard ). For example, what is the relative contribution of phages to the accessory genome of bacteria in terrestrial ecosystems? What are the key roles of phages for their host metabolism and how is phage diversity linked with microbial and terrestrial ecosystem diversity? More work on how to potentially harness phage ecology and evolution for the benefit of phage applications and ecosystem functioning in terrestrial ecosystems is also needed. As phages are often specific to their target bacteria, they could potentially be used to precision-edit bacterial communities by removing specific bacterial taxa or functions (Wang et al. ). For example, in addition to targeting plant pathogenic bacteria, one could use phages to target bacteria that interact with the pathogen in the rhizosphere microbiomes (Li et al. , Yang et al. ) or target bacteria that carry ARGs that are located in conjugative plasmids, requiring pilus expression for their transmission, which makes them also susceptible to phage infections (Jalasvuori et al. ). Alternatively, it might be possible just to target specific key taxa known for ARG carriage or just reduce overall bacterial abundances using nonspecific phage communities as has been done with the treatment of sewage systems (Yu et al. ). In contrast to removing bacterial taxa or functions, temperate phages could also be used to introduce new beneficial functions in the soil microbiomes. For example, if plant growth-promoting AMGs are common among temperate phages, such phages might be used to deliver plant-beneficial functions into rhizosphere microbiomes to potentially improve plant health and crop yields. Such beneficial functions could be identified, e.g. from so-called suppressive soils that can constrain plant pathogen infections and promote plant growth (Garbeva et al. , Peralta et al. ). Instead of identifying specific phage species, employing phage communities as part of rhizosphere soil transplants could be used as an initial screen to identify beneficial microbial communities. For example, soil transplant from healthy tomato plants was shown to constrain R. solanacearum pathogen invasion in the next tomato generation and this effect was likely driven by both pathogen-suppressing bacteria and R. solanacearum -specific phages present in the transplanted soil (Wei et al. , Yang et al. ). Finally, ecological theory and experiments suggest that biodiversity correlates positively with ecosystem functioning and this pattern has been also shown to hold in terrestrial ecosystems (Pennekamp et al. , Jochum et al. ). Phage diversity could, hence be important by promoting bacterial community stability and providing a more diverse suite of AMGs and accessory genome functions for the bacterial and plant community. To address all these questions, more research on phage ecology and evolution in terrestrial ecosystems is required where phages are recognized as a vital component of soil microbiomes with clear links with human and plant compartments within the One Health framework.
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Enhanced medical diagnosis for dOCTors: a perspective of optical coherence tomography | cc9ca2a0-fe70-4b78-9949-b99ac9b25143 | 8528212 | Ophthalmology[mh] | Introduction Optical coherence tomography (OCT) is one of the most innovative and successfully translated imaging techniques with substantial clinical and economic impacts and acceptance. , OCT is a non-invasive optical analog to ultrasound (US) with significantly higher resolution ( < 1 μ m ) enabling three- and four-dimensional high-speed (>millions of A-scans/s) imaging with tissue penetration of up to 2 mm, closely matching that of conventional histopathology. The year 2021 marks not only the 30th birthday of OCT (assuming its initiation with the Science paper by Huang et al. in 1991) but also the 35th birthday of low-coherence interferometry and optical ranging in biological systems. , In the last three decades, more than 75,000 OCT related papers have been published (about two thirds in ophthalmology) with continuous yearly increases of published articles. Breaking through the 1000 publications/year barrier was initiated in 2005/2006 with the introduction of spectral domain OCT (SD OCT). In 2020, the OCT-related scientific output was more than 7800 papers, resulting in nearly one paper every single hour on every single day of the year. Extrapolating this publishing performance, a saturation of yearly publication output at about 9500 can be expected around 2030. After 30 years, it is interesting and important to benchmark this performance with other medical imaging techniques: multiphoton microscopy (MPM) [including second harmonic generation (SHG) and third harmonic generation (THG)], developed about three decades before OCT, , has about 50,000 publications so far; photoacoustic imaging (PAI), established in the 1970s, , has about 15,000 papers; and confocal microscopy, developed in the 1940s, , has about 145,000. Developed in the 1940s, US imaging has contributed to about 160,000 papers; positron emission tomography (PET), initiated in the 1970s, , has about 175,000; computed tomography (CT), developed in the 1930s, has about 750,000; and magnetic resonance imaging (MRI), developed in the late 1940s, has close to 1,000,000 publications. This dominance in publications of radiology and nuclear medicine imaging technologies is also one of the reasons why medical imaging is, in general, associated with MRI, CT, PET, or US. It is important to note, though, that from a medical imaging market perspective, optical imaging technologies dominate with 66% versus 34% for radiology and nuclear medicine imaging technologies. In addition, in the United States alone, about 450,000 physicians use primarily optical imaging techniques; 60,000 use primarily radiologic imaging; and about 130,000 use both. In the last three decades, OCT has revolutionized ophthalmic diagnosis, therapy monitoring, and guidance. Every second, a human gets a retinal OCT scan; therefore it is the fastest adopted imaging technology in the history of ophthalmology. This is mainly due to the ease of optical accessibility of the human eye, OCT’s exquisite depth sectioning performance at the micrometer level, and a significantly better performance compared with the previous gold standard in this field, ultrasonography. Furthermore, it is also due to the fact that the human retina cannot be biopsied and finally to the continuous clinically relevant improvements of this technology, due to an exquisite ecosystem between industry and academia in terms of resolution, speed, wide-field imaging, and longer wavelength for choroidal imaging. Motion contrast-based angiography, cellular level retinal visualization, visible light OCT for oximetry and unprecedented retinal layer detection, functional and contrast enhanced extensions, and artificial intelligence (AI)-enhanced performance also contributed to this success. Most of these superb technological developments can be directly translated to the original motivation and idea of OCT: to enable optical biopsy, i.e., the in situ imaging of tissue microstructure with a resolution approaching that of histology but without the need for tissue excision and preparation, allowing for quasi-instantaneous diagnostic feedback for physicians, and thereby reducing healthcare costs. There is no doubt that outside ophthalmology, OCT faces significantly bigger challenges with extremely well performing, long-established diagnostic techniques. Hence, OCT has successfully penetrated into different medical fields outside of ophthalmology, but in the last 30 years, it has not been as successful as in ophthalmic diagnosis. Despite the unprecedented success of this imaging technique in ophthalmology so far, there are still numerous remaining challenges in this field to be addressed (e.g., 4D intrasurgical OCT, portable, handheld OCT, and OCT-based digital adaptive optics) but one of the biggest perspectives for OCT is to further push performance frontiers of all involved technologies to converge to the original motivation of OCT, which is to enable in situ optical biopsy, especially for early cancer diagnosis and for a better understanding of oncogenesis. Consequently, this perspective will focus on the following areas that will pave the way for enabling even further enhanced medical diagnosis using OCT in the future. Imaging speed is absolutely essential in medical diagnosis: on the one hand, to minimize the exam time for the patient, but foremost to enable motion artifact free, properly sampled data sets. The speed of today’s systems already supports three- and even four-dimensional imaging as well as wide fields of view and functional extensions of OCT, such as OCT angiography. In the future, different technologies will enable increased OCT imaging speed with one of the fundamental decisions being at which scanning speed single-beam raster scanning will be abandoned and scanning beam parallelization will be used. Further challenges of OCT’s unmatched axial and transverse resolution will also be discussed. Similar to combining different radiology and nuclear medicine imaging technologies in current clinical diagnosis, multimodal optical imaging not only enables the “best of both/all worlds” but also compensates for the deficits of OCT (metabolic, molecular sensitivity, penetration depth, and limited contrast). Multimodal imaging applications combining techniques complementary to OCT will more and more be transferred from significantly improved microscopy setups—acting as fast quasi-histological optical biopsies next to the operating room—to the miniaturized endoscopic level with OCT acting like a global positioning system (GPS) by prescreening the tissue at a wider field of view (FOV) with microscopic resolution. Aside from OCTA, no other functional or contrast enhancing OCT extension has accomplished comparable clinical impact in the last three decades. Some more recently developed ones that might accomplish this challenging task, including quantitative OCTA (especially in neuro-ophthalmology), optical coherence elastography (OCE), dynamic contrast OCT, oximetry using visible light OCT, optophysiology—also referred to optoretinography—and AI-enhanced OCT, will be covered in this perspective. In addition, OCT miniaturization for portable, compact, handheld OCT applications, as well as for home-OCT and self-OCT, will be discussed. Finally, industrial translation of OCT, including medical device regulatory challenges, will be reviewed.
Key-Technological OCT Performance Specifications: Speed and Resolution 2.1 Measurement Speed The acquisition speed of OCT, typically measured in A-scans per second or voxels per second, has been increasing since its inception. This steady increase in speed has supported the continuous expansion of OCT capabilities and applications. Initially, OCT’s predecessors low-coherence interferometry and optical time domain reflectometry had been used to measure distances along the sample beam or along an optical fiber. , Early time domain OCT systems for ophthalmic diagnostics then recorded B-scans with an A-scan rate of several hundred hertz. , The introduction of Fourier domain OCT (FD-OCT), however, had the biggest impact on speed as well as clinical usability. It increased the A-scan rate to tens of thousands of A-scans per second. With such rates, volume capture scans and high definition scans, i.e., an averaged B-scan calculated from up to 100 B-scans, replaced individual B-scans in ophthalmic diagnostics. More recently, technological improvements of line scan cameras, tunable light sources, digitizers, and data transfer interfaces pushed the speed further to hundreds of kHz and even MHz A-scan rates. – Such speeds now permit the observation of dynamic processes with live volumetric OCT scans, called 4D OCT, in which the fourth dimension is time. In theory, both FD-OCT implementations, SD-OCT and swept-source OCT (SS-OCT), have similar sensitivity and should thereby reach similar acquisition speeds. However, in practice, SS-OCT has lower losses in the detection and does not suffer from a depth dependent sensitivity roll-off in the case of long coherence length sources such as vertical-cavity surface-emitting lasers (VCSELs) or akinetic swept sources, introduced by the limited modulation transfer function of the spectrometer. At imaging depths of several millimeters, SS-OCT may therefore exhibit > 10 dB higher sensitivity than its spectrometer-based counterpart. In consequence, the highest speed confocal point scanning OCT systems so far have been SS-OCT systems. The fastest reported SSOCT systems so far use dispersive stretching of ultrashort pulses propagating through a fiber. – These OCT systems are currently limited by missing fast enough data acquisition boards to sample the stretched ultrashort pulses running at up to 100 MHz. The highest voxel rates are reported for SS OCT systems employing a so-called circular ranging technique, which uses a frequency comb spectrum leading after Fourier transform to degenerate depth ranges sampled in parallel. The most convincing performance for in vivo imaging so far has been demonstrated with systems powered by Fourier domain mode locked lasers, although vertically VCSEL-based systems are gradually closing in concerning speed and bandwidth performance. Such high speeds, however, come at the price of decreased sensitivity, at least when imaging light sensitive samples in which the illumination power cannot be arbitrarily increased, such as the human eye. Ophthalmic OCT systems therefore rely on fast safety circuits, which monitor the motion of the scanning beam and the illumination power to quickly shut off the laser in case of a failure. This permits treating the scanned beam as an extended source and thereby higher permissible light exposure than with a stationary beam. However, because it takes time to detect an unintended slowdown of the scanners, the maximum applicable power with confocal point scanning systems will soon be reached. Another factor limiting the speed of point scanning devices is the requirement for fast scanners. To minimize strain of the scanners and maximize scan speed, sinusoidal or spiral scan patterns may be applied; however, this introduces the need for a resampling step in postprocessing. To continue the trend of ever-increasing imaging speed, we see a shift from single-beam confocal point scanning systems toward parallel systems. – These include systems that illuminate the sample with multiple confocal beams in parallel, often referred to as multibeam OCT systems, and systems that illuminate a line or an area on the sample, called line field and full-field OCT (FFOCT) systems, respectively . 2.1.1 Multibeam OCT Using a parallel interferometer and multiple confocal illumination spots, one can multiply the acquisition speed of an OCT system by the number of spots. In fiber-optic implementations, this requires multiple interferometers, detectors, and data acquisition channels, as well as a powerful light source. Although it seems to be a straightforward approach at first glance, the implementation of such systems is not trivial. The coherence gate of the different interferometers ideally should overlap in the sample plane with high precision to image the same depth in all channels. This can be achieved using a variable delay in each interferometer, which however adds significant cost and complexity. In bulk optic interferometers, the multiple beams may share a common interferometer and hence may have inherently matched pathlengths. Implementations based on photonic integrated circuits (PIC) can rely on the high precision of the lithographic manufacturing processes to control pathlength differences. PICs in general are very attractive for multibeam systems because multiplying the interferometer only costs wafer space, which is cheaper than additional fiber interferometers. From a laser safety perspective, for ophthalmic OCT systems, one can argue that each beam is illuminating a different location on the retina. However, in the anterior segment, the beams are stationary and overlapping. Depending on the combined energy in this “hot spot,” damaging the iris or lens may become a concern. Another challenge with multibeam systems is merging the acquired multichannel data in postprecessing. In particular, when montaging not only 2D images, i.e, en face or B-scans, but also the full volumetric data sets. 2.1.2 Line-field OCT Line-field OCT (LFOCT) comes at all flavors of OCT: TD-OCT, spectral domain OCT (SD-OCT) and swept source OCT (SS-OCT) implementations have been demonstrated. , – Its line illumination has a major advantage: because an entire B-scan is captured at once, only one scanner is required to acquire a volume scan. In most cases, this scanner can even have a lower performance than typical galvanometric scanners used in point scanning systems as the scan in the orthogonal direction relative to the B-scan is typically relatively slow. Further, a line illumination maintains confocality in one dimension and never focuses to a spot. This is beneficial for the suppression of multiply scattered photons and permits high illumination powers when imaging the human retina. TD LFOCT particularly allows for keeping the confocal gate aligned with the coherence gate. Using a high-resolution system with tight coherence gating, such confocal LFOCT, has enabled the production of impressive images of human skin that efficiently suppress scattering . In SD-OCT configurations, B-scan rates of several kHz can be achieved by employing standard off-the-shelf 2D cameras. , Such high B-scan rates make LFOCT attractive for functional extensions that require fast repeated scans, such as elastography, OCTA, or Doppler OCT (see Sec. ). However, high acquisition speed in general is beneficial for achieving high phase stability, making LFOCT also a candidate for phase sensitive extensions, such as computational adaptive optics , , dynamic OCT, or functional OCT (see Sec. ). SS-OCT implementations require very fast line scan cameras. The fastest suitable off-the-shelf line scan cameras reach line rates of ∼ 300 kHz . Assuming 1000 spectral sampling points, this results in a B-scan rate of 300 Hz. The number of sampling points can be reduced using an holographic off-axis approach, resulting in full range imaging with up to a 1 kHz B-scan rate . Yet, the lower axial sampling poses limitations on its practical use for clinical imaging. Although the B-scan rate is comparable to state-of-the-art commercial point scanning OCT systems, the low spectral sampling rate may pose problems in the case of fast sample motion. It introduces a phase shift across the spectral interferogram, which results in a point spread function broadening, similar to a dispersion mismatch between reference and sample arm. For example, for retinal line-field imaging, using B-scan rates of several kHz has been recommended to avoid axial blurring. Recently, a high-speed CMOS camera has been applied for fast line field sensing to overcome the motion limitation, but at increased costs for the sensor. , The advantages of LFOCT and its technical feasibility using readily available components make it the most promising candidate for parallel OCT embodiments and put it closest to market translation. 2.1.3 Full-field OCT FFOCT permits very simple system designs. Without the need for scanning devices, a 2D array camera records the backscattered light from the sample as well as from the reference arm. Additional mechanisms however are necessary for extracting the coherently depth gated cross correlation signal between sample and reference light, comprising the OCT signal. TD-FFOCT is equivalent to holography with a broadband source. , The OCT signal retrieval is achieved either by phase-shifting techniques in an in-line configuration or by off-axis using spatial filtering in postprocessing. The in-line approach has the advantage of exploiting the full sampling provided by the 2D array pixels, but comes with the drawback that several phase-shifted image copies are needed for OCT reconstruction. Although the focal plane can be locked to the coherence gate in TD-FFOCT, this advantage is lost in FD-FFOCT. Another advantage of time domain implementation is that it can be cheap, using readily available area cameras. The advantage of the Fourier domain version on the other hand is its speed, but it requires high-speed cameras, capable of several hundred kHz frame rate, which are still very expensive. An important advantage of FFOCT is its intrinsic phase stability across the full en face FOV. This makes it especially interesting for phase sensitive extensions of OCT, in which fluctuations in the phase or complex signal are measured over time across repeated en face images or volume acquisitions. These include dynamic OCT, which provides a cell type specific contrast by detecting small oscillations of subcellular components (see Sec. ), functional OCT, in which changes in the optical length of neural cells in the retina are measured in response to light stimuli (see Sec. ), or computational adaptive optics, in which the phase slope of the wavefront is extracted to measure and correct aberrations (see Sec. ). In particular, TD-FFOCT implementations often use spatially incoherent light sources that provide intrinsically aberration free imaging over the full FOV . They further suppress cross-talk present in systems using spatially coherent sources, which is beneficial for imaging highly scattering samples, such as brain tissue. To overcome the missing confocal gating mechanism in FD-FFOCT and suppress multiply scattered light, it has been demonstrated to be advantageous to deteriorating the spatial coherence. , , This can be achieved using rotating scattering discs, spatial light modulators, or multimode fiber mode scramblers. Although FFOCT systems typically illuminate a large area on the sample and thereby enable a substantial increase in illumination power when imaging light sensitive tissue, special attention must be paid when the sample is the human retina. To illuminate a large area on the retina, a focus forms in the anterior segment. Critical energy densities are reached in this hot spot soon before the maximum permissible exposure for the retina can be reached. This severely limits the benefit of FFOCT’s large degree of parallelism relative to an LFOCT system when imaging the human retina. 2.2 Lateral Resolution in OCT The lateral resolution of OCT systems is given by the numerical aperture (NA) of the imaging optics. In contrast to, for example, confocal microscopy, it is decoupled from its axial resolution (see Sec. ). Most FD-OCT systems are therefore designed with a comparably low NA to create a large depth of focus and thereby enable an instantaneous imaging depth of several millimeters. Diffraction limited resolution can be achieved when the sample itself does not introduce wavefront aberrations. However, especially when imaging the human retina, the imperfect optics of the eye introduces large wavefront errors that prevent diffraction limited resolution when making use of their full NA. It has been shown that the diffraction limited resolution can be recovered by the use of adaptive optics, using deformable mirrors, or computationally by using the interferometric phase that different approaches have reported, ranging from algorithms from diffraction tomography to iterative and non-iterative approaches to extract and manipulate the wavefront shape. This enables the resolution of individual cells in some retinal layers, i.e., photoreceptors and retinal pigment epithelium (RPE) cells. Although other retinal cells, in theory, are large enough to be resolved even by standard OCT systems, such as ganglion cells, they often remain hidden due to limited contrast. However, it has been shown that averaging a large number of acquisitions or applying dynamic contrast methods helps to reveal them even in the living human eye. In confocal systems, hardware-based adaptive optics has the advantage of correcting the wavefront optically before the light is coupled back into a single-mode fiber, thereby maximizing the signal. Deformable mirrors, especially ones with a large number of elements, are costly, which so far has prevented their use in commercial OCT systems and makes computational approaches more attractive. To overcome the prohibitive cost of hardware-based adaptive optics OCT on the one hand and the limited collection efficiency of confocal computational adaptive optics OCT systems on the other hand, more basic deformable mirrors may be used to correct low-order aberrations optically and higher orders numerically. The detection of an aberrated wavefront is not a concern in FFOCT, as long as the detector has sufficient resolution to resolve the wavefront’s phase slope. Because computational wavefront correction algorithms can propagate the focal plane to any depth, they can realize a depth invariant lateral resolution, whereas high NA hardware-based adaptive optics OCT systems are limited to a depth of focus of only a few micrometers. Cellular and subcellular resolution is the field of optical coherence microscopy (OCM). TD OCT is a natural candidate for OCM since the tight confocal gate can be dynamically aligned with the coherence gate during depth scanning. For FD OCT configurations with a fixed reference arm, other means are needed to extend the FOV beyond the tight confocal gate. Again, computational methods have shown their merit for OCM by extending the focus depth. , These include hardware-based methods used depth fusion approaches, Bessel beams, structured illumination, or employed metalenses. 2.3 Axial Resolution in OCT The axial resolution of OCT is given by the center wavelength and spectral bandwidth of the illumination. The most prominent wavelength band of OCT systems lies at 840 nm. This is a result of OCT’s success in ophthalmology. The near-infrared light permits good penetration through the water-like filled eye to the retina, while not blinding the patient and still maintaining good detection efficiency with silicon cameras. Most OCT in this wavelength band are SD-OCT systems using super-luminescence diodes or Titanium:sapphire lasers. With full-width half-maximum bandwidths of up to 180 nm, an axial resolution down to 1 μ m in tissue can be achieved. However, commercial ophthalmic SD-OCT systems typically employ sources with a much narrower spectrum, realizing an axial resolution of ∼ 5 μ m in tissue. If an axial resolution below 1 μ m in tissue is desired, super-continuum sources with spectral bandwidths of several hundred nanometers that stretch far into the visible spectrum can be used (see Sec. ). Most SS-OCT systems operate at longer center wavelengths, 1060 nm for imaging the posterior segment of the human eye, and 1310 and 1550 nm for imaging more strongly scattering samples, such as skin or brain tissue. The achievable resolution at 1060 nm is typically set by the water absorption window, which limits the useful bandwidth to ∼ 100 nm , resulting in a typical axial resolution of ∼ 7 μ m in tissue. At 1310 and 1550 nm swept-sources with a broader tuning range are available; however, the achievable axial resolution is similar due to the higher central wavelength.
Measurement Speed The acquisition speed of OCT, typically measured in A-scans per second or voxels per second, has been increasing since its inception. This steady increase in speed has supported the continuous expansion of OCT capabilities and applications. Initially, OCT’s predecessors low-coherence interferometry and optical time domain reflectometry had been used to measure distances along the sample beam or along an optical fiber. , Early time domain OCT systems for ophthalmic diagnostics then recorded B-scans with an A-scan rate of several hundred hertz. , The introduction of Fourier domain OCT (FD-OCT), however, had the biggest impact on speed as well as clinical usability. It increased the A-scan rate to tens of thousands of A-scans per second. With such rates, volume capture scans and high definition scans, i.e., an averaged B-scan calculated from up to 100 B-scans, replaced individual B-scans in ophthalmic diagnostics. More recently, technological improvements of line scan cameras, tunable light sources, digitizers, and data transfer interfaces pushed the speed further to hundreds of kHz and even MHz A-scan rates. – Such speeds now permit the observation of dynamic processes with live volumetric OCT scans, called 4D OCT, in which the fourth dimension is time. In theory, both FD-OCT implementations, SD-OCT and swept-source OCT (SS-OCT), have similar sensitivity and should thereby reach similar acquisition speeds. However, in practice, SS-OCT has lower losses in the detection and does not suffer from a depth dependent sensitivity roll-off in the case of long coherence length sources such as vertical-cavity surface-emitting lasers (VCSELs) or akinetic swept sources, introduced by the limited modulation transfer function of the spectrometer. At imaging depths of several millimeters, SS-OCT may therefore exhibit > 10 dB higher sensitivity than its spectrometer-based counterpart. In consequence, the highest speed confocal point scanning OCT systems so far have been SS-OCT systems. The fastest reported SSOCT systems so far use dispersive stretching of ultrashort pulses propagating through a fiber. – These OCT systems are currently limited by missing fast enough data acquisition boards to sample the stretched ultrashort pulses running at up to 100 MHz. The highest voxel rates are reported for SS OCT systems employing a so-called circular ranging technique, which uses a frequency comb spectrum leading after Fourier transform to degenerate depth ranges sampled in parallel. The most convincing performance for in vivo imaging so far has been demonstrated with systems powered by Fourier domain mode locked lasers, although vertically VCSEL-based systems are gradually closing in concerning speed and bandwidth performance. Such high speeds, however, come at the price of decreased sensitivity, at least when imaging light sensitive samples in which the illumination power cannot be arbitrarily increased, such as the human eye. Ophthalmic OCT systems therefore rely on fast safety circuits, which monitor the motion of the scanning beam and the illumination power to quickly shut off the laser in case of a failure. This permits treating the scanned beam as an extended source and thereby higher permissible light exposure than with a stationary beam. However, because it takes time to detect an unintended slowdown of the scanners, the maximum applicable power with confocal point scanning systems will soon be reached. Another factor limiting the speed of point scanning devices is the requirement for fast scanners. To minimize strain of the scanners and maximize scan speed, sinusoidal or spiral scan patterns may be applied; however, this introduces the need for a resampling step in postprocessing. To continue the trend of ever-increasing imaging speed, we see a shift from single-beam confocal point scanning systems toward parallel systems. – These include systems that illuminate the sample with multiple confocal beams in parallel, often referred to as multibeam OCT systems, and systems that illuminate a line or an area on the sample, called line field and full-field OCT (FFOCT) systems, respectively . 2.1.1 Multibeam OCT Using a parallel interferometer and multiple confocal illumination spots, one can multiply the acquisition speed of an OCT system by the number of spots. In fiber-optic implementations, this requires multiple interferometers, detectors, and data acquisition channels, as well as a powerful light source. Although it seems to be a straightforward approach at first glance, the implementation of such systems is not trivial. The coherence gate of the different interferometers ideally should overlap in the sample plane with high precision to image the same depth in all channels. This can be achieved using a variable delay in each interferometer, which however adds significant cost and complexity. In bulk optic interferometers, the multiple beams may share a common interferometer and hence may have inherently matched pathlengths. Implementations based on photonic integrated circuits (PIC) can rely on the high precision of the lithographic manufacturing processes to control pathlength differences. PICs in general are very attractive for multibeam systems because multiplying the interferometer only costs wafer space, which is cheaper than additional fiber interferometers. From a laser safety perspective, for ophthalmic OCT systems, one can argue that each beam is illuminating a different location on the retina. However, in the anterior segment, the beams are stationary and overlapping. Depending on the combined energy in this “hot spot,” damaging the iris or lens may become a concern. Another challenge with multibeam systems is merging the acquired multichannel data in postprecessing. In particular, when montaging not only 2D images, i.e, en face or B-scans, but also the full volumetric data sets. 2.1.2 Line-field OCT Line-field OCT (LFOCT) comes at all flavors of OCT: TD-OCT, spectral domain OCT (SD-OCT) and swept source OCT (SS-OCT) implementations have been demonstrated. , – Its line illumination has a major advantage: because an entire B-scan is captured at once, only one scanner is required to acquire a volume scan. In most cases, this scanner can even have a lower performance than typical galvanometric scanners used in point scanning systems as the scan in the orthogonal direction relative to the B-scan is typically relatively slow. Further, a line illumination maintains confocality in one dimension and never focuses to a spot. This is beneficial for the suppression of multiply scattered photons and permits high illumination powers when imaging the human retina. TD LFOCT particularly allows for keeping the confocal gate aligned with the coherence gate. Using a high-resolution system with tight coherence gating, such confocal LFOCT, has enabled the production of impressive images of human skin that efficiently suppress scattering . In SD-OCT configurations, B-scan rates of several kHz can be achieved by employing standard off-the-shelf 2D cameras. , Such high B-scan rates make LFOCT attractive for functional extensions that require fast repeated scans, such as elastography, OCTA, or Doppler OCT (see Sec. ). However, high acquisition speed in general is beneficial for achieving high phase stability, making LFOCT also a candidate for phase sensitive extensions, such as computational adaptive optics , , dynamic OCT, or functional OCT (see Sec. ). SS-OCT implementations require very fast line scan cameras. The fastest suitable off-the-shelf line scan cameras reach line rates of ∼ 300 kHz . Assuming 1000 spectral sampling points, this results in a B-scan rate of 300 Hz. The number of sampling points can be reduced using an holographic off-axis approach, resulting in full range imaging with up to a 1 kHz B-scan rate . Yet, the lower axial sampling poses limitations on its practical use for clinical imaging. Although the B-scan rate is comparable to state-of-the-art commercial point scanning OCT systems, the low spectral sampling rate may pose problems in the case of fast sample motion. It introduces a phase shift across the spectral interferogram, which results in a point spread function broadening, similar to a dispersion mismatch between reference and sample arm. For example, for retinal line-field imaging, using B-scan rates of several kHz has been recommended to avoid axial blurring. Recently, a high-speed CMOS camera has been applied for fast line field sensing to overcome the motion limitation, but at increased costs for the sensor. , The advantages of LFOCT and its technical feasibility using readily available components make it the most promising candidate for parallel OCT embodiments and put it closest to market translation. 2.1.3 Full-field OCT FFOCT permits very simple system designs. Without the need for scanning devices, a 2D array camera records the backscattered light from the sample as well as from the reference arm. Additional mechanisms however are necessary for extracting the coherently depth gated cross correlation signal between sample and reference light, comprising the OCT signal. TD-FFOCT is equivalent to holography with a broadband source. , The OCT signal retrieval is achieved either by phase-shifting techniques in an in-line configuration or by off-axis using spatial filtering in postprocessing. The in-line approach has the advantage of exploiting the full sampling provided by the 2D array pixels, but comes with the drawback that several phase-shifted image copies are needed for OCT reconstruction. Although the focal plane can be locked to the coherence gate in TD-FFOCT, this advantage is lost in FD-FFOCT. Another advantage of time domain implementation is that it can be cheap, using readily available area cameras. The advantage of the Fourier domain version on the other hand is its speed, but it requires high-speed cameras, capable of several hundred kHz frame rate, which are still very expensive. An important advantage of FFOCT is its intrinsic phase stability across the full en face FOV. This makes it especially interesting for phase sensitive extensions of OCT, in which fluctuations in the phase or complex signal are measured over time across repeated en face images or volume acquisitions. These include dynamic OCT, which provides a cell type specific contrast by detecting small oscillations of subcellular components (see Sec. ), functional OCT, in which changes in the optical length of neural cells in the retina are measured in response to light stimuli (see Sec. ), or computational adaptive optics, in which the phase slope of the wavefront is extracted to measure and correct aberrations (see Sec. ). In particular, TD-FFOCT implementations often use spatially incoherent light sources that provide intrinsically aberration free imaging over the full FOV . They further suppress cross-talk present in systems using spatially coherent sources, which is beneficial for imaging highly scattering samples, such as brain tissue. To overcome the missing confocal gating mechanism in FD-FFOCT and suppress multiply scattered light, it has been demonstrated to be advantageous to deteriorating the spatial coherence. , , This can be achieved using rotating scattering discs, spatial light modulators, or multimode fiber mode scramblers. Although FFOCT systems typically illuminate a large area on the sample and thereby enable a substantial increase in illumination power when imaging light sensitive tissue, special attention must be paid when the sample is the human retina. To illuminate a large area on the retina, a focus forms in the anterior segment. Critical energy densities are reached in this hot spot soon before the maximum permissible exposure for the retina can be reached. This severely limits the benefit of FFOCT’s large degree of parallelism relative to an LFOCT system when imaging the human retina.
Multibeam OCT Using a parallel interferometer and multiple confocal illumination spots, one can multiply the acquisition speed of an OCT system by the number of spots. In fiber-optic implementations, this requires multiple interferometers, detectors, and data acquisition channels, as well as a powerful light source. Although it seems to be a straightforward approach at first glance, the implementation of such systems is not trivial. The coherence gate of the different interferometers ideally should overlap in the sample plane with high precision to image the same depth in all channels. This can be achieved using a variable delay in each interferometer, which however adds significant cost and complexity. In bulk optic interferometers, the multiple beams may share a common interferometer and hence may have inherently matched pathlengths. Implementations based on photonic integrated circuits (PIC) can rely on the high precision of the lithographic manufacturing processes to control pathlength differences. PICs in general are very attractive for multibeam systems because multiplying the interferometer only costs wafer space, which is cheaper than additional fiber interferometers. From a laser safety perspective, for ophthalmic OCT systems, one can argue that each beam is illuminating a different location on the retina. However, in the anterior segment, the beams are stationary and overlapping. Depending on the combined energy in this “hot spot,” damaging the iris or lens may become a concern. Another challenge with multibeam systems is merging the acquired multichannel data in postprecessing. In particular, when montaging not only 2D images, i.e, en face or B-scans, but also the full volumetric data sets.
Line-field OCT Line-field OCT (LFOCT) comes at all flavors of OCT: TD-OCT, spectral domain OCT (SD-OCT) and swept source OCT (SS-OCT) implementations have been demonstrated. , – Its line illumination has a major advantage: because an entire B-scan is captured at once, only one scanner is required to acquire a volume scan. In most cases, this scanner can even have a lower performance than typical galvanometric scanners used in point scanning systems as the scan in the orthogonal direction relative to the B-scan is typically relatively slow. Further, a line illumination maintains confocality in one dimension and never focuses to a spot. This is beneficial for the suppression of multiply scattered photons and permits high illumination powers when imaging the human retina. TD LFOCT particularly allows for keeping the confocal gate aligned with the coherence gate. Using a high-resolution system with tight coherence gating, such confocal LFOCT, has enabled the production of impressive images of human skin that efficiently suppress scattering . In SD-OCT configurations, B-scan rates of several kHz can be achieved by employing standard off-the-shelf 2D cameras. , Such high B-scan rates make LFOCT attractive for functional extensions that require fast repeated scans, such as elastography, OCTA, or Doppler OCT (see Sec. ). However, high acquisition speed in general is beneficial for achieving high phase stability, making LFOCT also a candidate for phase sensitive extensions, such as computational adaptive optics , , dynamic OCT, or functional OCT (see Sec. ). SS-OCT implementations require very fast line scan cameras. The fastest suitable off-the-shelf line scan cameras reach line rates of ∼ 300 kHz . Assuming 1000 spectral sampling points, this results in a B-scan rate of 300 Hz. The number of sampling points can be reduced using an holographic off-axis approach, resulting in full range imaging with up to a 1 kHz B-scan rate . Yet, the lower axial sampling poses limitations on its practical use for clinical imaging. Although the B-scan rate is comparable to state-of-the-art commercial point scanning OCT systems, the low spectral sampling rate may pose problems in the case of fast sample motion. It introduces a phase shift across the spectral interferogram, which results in a point spread function broadening, similar to a dispersion mismatch between reference and sample arm. For example, for retinal line-field imaging, using B-scan rates of several kHz has been recommended to avoid axial blurring. Recently, a high-speed CMOS camera has been applied for fast line field sensing to overcome the motion limitation, but at increased costs for the sensor. , The advantages of LFOCT and its technical feasibility using readily available components make it the most promising candidate for parallel OCT embodiments and put it closest to market translation.
Full-field OCT FFOCT permits very simple system designs. Without the need for scanning devices, a 2D array camera records the backscattered light from the sample as well as from the reference arm. Additional mechanisms however are necessary for extracting the coherently depth gated cross correlation signal between sample and reference light, comprising the OCT signal. TD-FFOCT is equivalent to holography with a broadband source. , The OCT signal retrieval is achieved either by phase-shifting techniques in an in-line configuration or by off-axis using spatial filtering in postprocessing. The in-line approach has the advantage of exploiting the full sampling provided by the 2D array pixels, but comes with the drawback that several phase-shifted image copies are needed for OCT reconstruction. Although the focal plane can be locked to the coherence gate in TD-FFOCT, this advantage is lost in FD-FFOCT. Another advantage of time domain implementation is that it can be cheap, using readily available area cameras. The advantage of the Fourier domain version on the other hand is its speed, but it requires high-speed cameras, capable of several hundred kHz frame rate, which are still very expensive. An important advantage of FFOCT is its intrinsic phase stability across the full en face FOV. This makes it especially interesting for phase sensitive extensions of OCT, in which fluctuations in the phase or complex signal are measured over time across repeated en face images or volume acquisitions. These include dynamic OCT, which provides a cell type specific contrast by detecting small oscillations of subcellular components (see Sec. ), functional OCT, in which changes in the optical length of neural cells in the retina are measured in response to light stimuli (see Sec. ), or computational adaptive optics, in which the phase slope of the wavefront is extracted to measure and correct aberrations (see Sec. ). In particular, TD-FFOCT implementations often use spatially incoherent light sources that provide intrinsically aberration free imaging over the full FOV . They further suppress cross-talk present in systems using spatially coherent sources, which is beneficial for imaging highly scattering samples, such as brain tissue. To overcome the missing confocal gating mechanism in FD-FFOCT and suppress multiply scattered light, it has been demonstrated to be advantageous to deteriorating the spatial coherence. , , This can be achieved using rotating scattering discs, spatial light modulators, or multimode fiber mode scramblers. Although FFOCT systems typically illuminate a large area on the sample and thereby enable a substantial increase in illumination power when imaging light sensitive tissue, special attention must be paid when the sample is the human retina. To illuminate a large area on the retina, a focus forms in the anterior segment. Critical energy densities are reached in this hot spot soon before the maximum permissible exposure for the retina can be reached. This severely limits the benefit of FFOCT’s large degree of parallelism relative to an LFOCT system when imaging the human retina.
Lateral Resolution in OCT The lateral resolution of OCT systems is given by the numerical aperture (NA) of the imaging optics. In contrast to, for example, confocal microscopy, it is decoupled from its axial resolution (see Sec. ). Most FD-OCT systems are therefore designed with a comparably low NA to create a large depth of focus and thereby enable an instantaneous imaging depth of several millimeters. Diffraction limited resolution can be achieved when the sample itself does not introduce wavefront aberrations. However, especially when imaging the human retina, the imperfect optics of the eye introduces large wavefront errors that prevent diffraction limited resolution when making use of their full NA. It has been shown that the diffraction limited resolution can be recovered by the use of adaptive optics, using deformable mirrors, or computationally by using the interferometric phase that different approaches have reported, ranging from algorithms from diffraction tomography to iterative and non-iterative approaches to extract and manipulate the wavefront shape. This enables the resolution of individual cells in some retinal layers, i.e., photoreceptors and retinal pigment epithelium (RPE) cells. Although other retinal cells, in theory, are large enough to be resolved even by standard OCT systems, such as ganglion cells, they often remain hidden due to limited contrast. However, it has been shown that averaging a large number of acquisitions or applying dynamic contrast methods helps to reveal them even in the living human eye. In confocal systems, hardware-based adaptive optics has the advantage of correcting the wavefront optically before the light is coupled back into a single-mode fiber, thereby maximizing the signal. Deformable mirrors, especially ones with a large number of elements, are costly, which so far has prevented their use in commercial OCT systems and makes computational approaches more attractive. To overcome the prohibitive cost of hardware-based adaptive optics OCT on the one hand and the limited collection efficiency of confocal computational adaptive optics OCT systems on the other hand, more basic deformable mirrors may be used to correct low-order aberrations optically and higher orders numerically. The detection of an aberrated wavefront is not a concern in FFOCT, as long as the detector has sufficient resolution to resolve the wavefront’s phase slope. Because computational wavefront correction algorithms can propagate the focal plane to any depth, they can realize a depth invariant lateral resolution, whereas high NA hardware-based adaptive optics OCT systems are limited to a depth of focus of only a few micrometers. Cellular and subcellular resolution is the field of optical coherence microscopy (OCM). TD OCT is a natural candidate for OCM since the tight confocal gate can be dynamically aligned with the coherence gate during depth scanning. For FD OCT configurations with a fixed reference arm, other means are needed to extend the FOV beyond the tight confocal gate. Again, computational methods have shown their merit for OCM by extending the focus depth. , These include hardware-based methods used depth fusion approaches, Bessel beams, structured illumination, or employed metalenses.
Axial Resolution in OCT The axial resolution of OCT is given by the center wavelength and spectral bandwidth of the illumination. The most prominent wavelength band of OCT systems lies at 840 nm. This is a result of OCT’s success in ophthalmology. The near-infrared light permits good penetration through the water-like filled eye to the retina, while not blinding the patient and still maintaining good detection efficiency with silicon cameras. Most OCT in this wavelength band are SD-OCT systems using super-luminescence diodes or Titanium:sapphire lasers. With full-width half-maximum bandwidths of up to 180 nm, an axial resolution down to 1 μ m in tissue can be achieved. However, commercial ophthalmic SD-OCT systems typically employ sources with a much narrower spectrum, realizing an axial resolution of ∼ 5 μ m in tissue. If an axial resolution below 1 μ m in tissue is desired, super-continuum sources with spectral bandwidths of several hundred nanometers that stretch far into the visible spectrum can be used (see Sec. ). Most SS-OCT systems operate at longer center wavelengths, 1060 nm for imaging the posterior segment of the human eye, and 1310 and 1550 nm for imaging more strongly scattering samples, such as skin or brain tissue. The achievable resolution at 1060 nm is typically set by the water absorption window, which limits the useful bandwidth to ∼ 100 nm , resulting in a typical axial resolution of ∼ 7 μ m in tissue. At 1310 and 1550 nm swept-sources with a broader tuning range are available; however, the achievable axial resolution is similar due to the higher central wavelength.
Multimodal Optical Coherence Tomography Multimodal imaging or multiplexed/hybrid imaging refers to the assessment of signals of more than one imaging technique. In multimodal imaging, one of the driving motivations is to combine morpho-functional information—enabling the “best of both/all worlds.” This can be accomplished by either acquiring images at different times (asynchronous) and fusing them through digital image manipulation techniques or simultaneously acquiring images (synchronous) and merging them automatically. Main goals of multimodal or multiplexed imaging are to improve early detection and localization of cancer and better understanding of cancerogenesis. Furthermore, multimodal imaging enables examining more than one molecule or molecular and morphologic information at a time, so cellular events may be examined simultaneously or the progression of these events can be followed in real time. Clinical optical multimodal imaging has so far been successfully applied in ophthalmic diagnosis including color fundus photography, fundus autofluorescence, OCT, en face OCT, OCT-angiography, B-scan ultrasonography, fluorescein angiography, and indocyanine green angiography. In cardiology, morphological features of NIR spectroscopy-detected lipid-rich plaques using OCT and intravascular US are performed in patients undergoing percutaneous coronary intervention for treatment of an acute coronary syndrome. Multimodal optical imaging in this perspective not only combines OCT with complementary optical imaging methods but also compensates for the deficits of OCT (metabolic, molecular sensitivity, penetration depth, and limited contrast). In this context, OCT will act (in contrast to other microscopy imaging techniques) like a GPS by prescreening the tissue at a wide FOV with microscopic resolution and then other techniques will zoom in at the subcellular or molecular level to enable obtaining morpho-molecular or morpho-metabolic tissue information. 3.1 Non-linear Optical Microscopy and Spectroscopy: Subcellular, Biochemical, and Metabolic Detection of structural information at the cellular level expands the understanding of tissue environment for in vivo studies, but the lack of molecular specificity hampers differentiation between pathologic and healthy tissues with comparable scattering or structural properties. Structural alterations in tissues and cells usually take place only after carcinogenic biochemical changes. OCT contrast can be improved by various implementations. However, molecular specificity including metabolic information at the cellular level is still not easily accessible. Therefore, despite the power of OCT, the sensitivity and specificity to detect pathologic tissue are limited. This weakness limits the ongoing success of this technology. One solution to overcome this limitation and to address current needs in the life sciences and in the clinical practice is to combine OCT with other non-invasive molecular specific modalities. Label-free spectroscopic and microscopic optical imaging technologies such as Raman spectroscopy (RS) and MPM , that complement OCT have been established and extensively applied over the past years. These modalities present comparable contrast to standard histopathological methods, but no single modality can play the role alone. Indeed, integrated multimodal imaging provides the possibility of fusing morphological information with metabolic-molecular information in a label-free way, complementing basic observation with multiple specific contrast mechanisms to gain a complete picture of disease, but it is still challenging due to different optics and hardware requirements. MPM has become an essential instrument for biological and medical research with inherent 3D sectioning capability, subcellular resolution, high sensitivity, molecular and metabolic specificity, and deep tissue penetration compared with confocal microscopy, but compared with OCT achievable FOVs, penetration depths and acquisition speeds are restricted. This weakness can be overcome with novel high-speed MPM approaches achieving kilohertz frame rates by implementing pulse-modulated, rapidly wavelength-swept lasers, and inertia-free beam steering via angular dispersion. In the future, this could help to match the different needs of OCT and MPM, thus facilitating the combination of these complementary techniques in a single co-registered platform. Usually, the key technologies to add molecular sensitivity to OCT are RS and coherent Raman spectroscopy. RS allows for full molecular fingerprinting of tissue offers high specificity. Several variants including non-linear vibrational imaging with different sophisticated laser sources , and single-laser source approaches – have been proposed, but the main deficit is that real-world applications are often missing due to special treatment of the sample—thin slices of transparent samples with high Raman cross sections to be investigated in transmission or reflection mode. Coherent anti-Stokes Raman scattering efficiently provides images with label-free molecular information from DNA, lipids, proteins, and collagen. Recently, stimulated Raman scattering-spectroscopic OCT was introduced to leverage the spatial and spectral multiplexing capabilities of OCT with the molecular specificity and sensitivity of SRS for label-free fast 3D molecular imaging with a single laser on a single platform. Two-photon excitation fluorescence (TPEF) microscopy – is another powerful OCT add-on that can intrinsically be merged with SHG , – or fluorescence lifetime imaging microscopy (FLIM), – showing augmented contrasts with the same FOV and resolution for all modalities. TPEF microscopy can bring unique additional insight into the mechanisms underlying immune system dynamics and function as cellular motility within the native environment in vivo . TPEF microscopy and FLIM achieve ultrahigh isotropic subcellular resolution, enhance chromophore contrast via excitation of fluorescent biomolecules, improve sectioning compared with conventional one photon fluorescence, and metabolic information by imaging endogenous metabolites such as nicotinamide adenine dinucleotide and hydrogen/flavin adenine dinucleotide. Pleomorphism (cell nuclei versus cell size ratio) can be detected with subcellular resolution imaging, and grade classification can be performed. Co-registered OCT and TPEF microscopy has the ability to link specific cellular phenotypes and functions as revealed by TPEF to tissue morphology, thus paving the way between basic research knowledge and clinical observations. SHG provides contrast from non-centrosymmetric molecules such as collagen, which mainly appears in the extracellular matrix as distinct morphological feature. The supramolecular organization can be revealed. In vivo skin imaging on a cellular level proves the potential for dermatology. – THG microscopy provides cellular morphological information in real-time with acceptable penetration depth and ultrahigh isotropic subcellular resolution, but reduced penetration depth and remarkable smaller FOV compared with OCT . The problems with these multimodal optical imaging approaches with MPM are the need for very high-photon concentration in space and time and subsequent requirement of extremely high near infrared (NIR) laser intensities. Ultra-short laser pulses provide high-peak powers necessary to achieve appropriate excitation powers for MPM signal generation with moderate time-averaged illumination doses. Ultra-broadband Titanium:sapphire lasers, which are proven and well-established light sources for MPM, are a challenge in the commercialization of such combined platform since they introduced high costs and complexity. – Alternative stable and cost-effective light sources are required. Direct diode-pumping of mode-locked Titanium:sapphire lasers and scaling up of the achievable output power could pave the way toward more widespread application of this technology beyond scientific research. Recently, advancements in soliton-based photonic integrated frequency comb soliton microcombs have accelerated the development of broadband and low-noise chip scale frequency comb sources with the potential for high-resolution OCT deep tissue imaging at 1300 nm. Combining OCT with MPM at these longer wavelengths or even at 1700 nm can enhance tissue penetration. The key enabling elements to improve the imaging penetration depth, depth of focus, and spatial resolution simultaneously are the laser wavelengths and pulse energy, beam shaping concepts, detection schemes, and real-time AI algorithms. First, deploying longer wavelengths, e.g., 1700 nm for OCT, TPEF, SHG, and THG, the penetration depth for imaging is significantly improved, facilitated by the novel ultrafast laser wavelength agility. Second, novel beam shaping allows for propagating invariant light fields that achieve increased depth, thereby improving penetration and retaining high resolution. Third, to compensate for attenuation intrinsically present in tissue, absorption correction is applied, and, more importantly, dynamic changes from the strong optical scattering are compensated for by so-called computational adaptive optics. The latter relies on OCT motility contrast as a measure of the wavefront for correcting the input and real-time data processing. Penetration depth could be even further improved using light sources at longer wavelengths. Recently mid-infrared OCT could be demonstrated with an axial resolution of 8.6 μ m . Detection could be performed with a standard CCD camera upon implementation of an upconversion module. One major consideration for future development of the multimodal morpho-molecular metabolic imaging platforms lies in the capability of performing fast OCT and successive simultaneous MPM in the backward propagation direction without affecting one modality to interfere with the others, thus compromising image quality. Hence, one solution in multimodal diagnostic imaging is the combination of a wide-field high-resolution imaging platform including OCT and advanced microspectroscopic imaging techniques and an automated software to extract and classify the morpho-molecular metabolic patterns with the aim to see what can be seen in immunohistochemistry from the macroscopic level to the highly specific microscopic level. With deep learning, automatized full tissue characterization on a multiparametric level can reveal the early onset of disease and improve understanding. However, deep optical imaging, such as deep brain imaging in vivo , at high resolution still poses a great challenge beyond the light source development. Adaptive optics based on direct wavefront sensing can recover diffraction-limited resolution corrupted when achieving deep optical imaging. Successful implementation of adaptive optics in any optical system is always an engineering challenge and often makes the overall system complex and economically expensive. The subaperture correlation-based computational adaptive optics method, which is the computational equivalent of the Shack–Hartmann wavefront sensor (SHWS), can achieve near diffraction-limited performance in FF-SS OCT. The advantage of this method is that, unlike other optimization-based techniques, it is non-iterative in nature and it does not require a priori knowledge of any system parameters such as wavelength, focal length, NA, or detector pixel size. This method can be also extended to region of interest (ROI)-based aberration correction to achieve diffraction-limited lateral resolution beyond the isoplanatic patch in high-resolution point scanning OCT with high NA. A computational sensorless adaptive optics strategy including OCT could play a critical role in correcting aberrations over large volumes and enabling rapid random-access multiplane imaging without highly sophisticated precompensation, SHWS, or electron-multiplying charge-coupled device. AI-supported denoising and deconvolution of images to increase sharpness, resolution, or brightness are currently implemented at some microscopy platforms. However, it is often limited to a single modality and leaves the user patching different AI systems together for various use scenarios. At the moment, each imaging method needs a specific deep learning architecture with little similarities between each architecture. Moreover, to achieve a good level of validity, one needs a high number of training data to train an AI. One main problem for achieving the needed quality for detection and pixel-based quantification through deep learning lies in the lack of quality in ground truth data and the lack of a ground truth management system. By invoking a novel ground truth management system, an efficient AI system can be trained using only a few training data sets. Once the AI has been trained for one modality, the gained “experience” can be used to significantly speed up the training for other modalities through new transfer learning techniques, i.e., passing on experience. Active learning and knowledge transfer can improve learning speed and accuracy. This will apply to resolution enhancement as well as automatic annotations for ROIs. Therefore, in a unified approach in which the AI system supports OCT and MPM, radically improved learning speed and accuracy can be provided to establish novel multiparametric biomarkers. By developing and deploying novel beam shaping concepts, supported by advanced AI algorithms in combination with real-time data processing, critical parameters for the imaging performance in terms of penetration depth, acquisition speed, and spatial resolution are vastly improved, which could pave the way toward a compact multimodal biophotonics platform for advanced real-time 3D intrasurgical morphological, metabolic, and molecular imaging platform with increased sensitivity and specificity. 3.2 Photoacoustic Microscopy and Tomography: Absorption, Molecular Contrast, and Seeing Deeper OCT as an optical imaging modality that relies on the optical scattering properties of samples has its inherent limitations in terms of contrast generation. The strong scattering of many biological tissues further restricts the penetration depth of OCT due to its dependence on ballistic photon detection. To alleviate these problems, combining OCT with PAI has been explored by various groups over the past decade. Our previous review paper covered this topic for scientific works up to 2014. This perspective focuses on an update on dual modality OCT/PAI system configurations published recently as well as an outlook focusing on their application in molecular imaging. 3.2.1 System configurations for dual modality OCT-PAI Combining OCT and PAI can be categorized into three major implementation schemes: OCT with photoacoustic microscopy (OC-PAM), OCT with photoacoustic tomography (OC-PAT), and OCT with photoacoustic endoscopy (OC-PAE). Each of these schemes is briefly discussed below. In terms of OC-PAM, ever since the first realization of this technique, piezoelectric transducers have been the go-to solution for photoacoustic signal detection. Over the past few years, we can still see the piezoelectric transducers being used in OC-PAM configurations. Among these piezoelectric transducers, needle transducers are most commonly used. So far, OC-PAM using needle transducers has been applied in choroidal and retinal imaging – extensively. Some technical advancements of needle-transducer-based OC-PAM systems have also been reported such as for dynamic focusing , and for incorporating additional imaging modalities. However, due to the opaque nature of the needle transducer and knowing that these needle transducers are normally unfocused, alternatives for OC-PAM implementation have been explored. One direct approach is to make the transducer transparent, which was recently demonstrated in an OC-PAM system and applied in different disease or pathological models. Another approach would be to use optical detection for the photoacoustic waves. Using Michelson interferometry, OC-PAM was achieved and characterized. Using the principle of Fabry–Perot interferometry, an akinetic photoacoustic sensor was demonstrated and henceforth applied in OC-PAM imaging. , For OC-PAT, the implementation is still based on a system using a polymer film sensor. After the successful application of this system in chick embryo imaging and human skin imaging, the functional extension of OCTA was added and demonstrated in clinical settings. – The current development is to increase the speed of acquisition to match the two modalities’ acquisition time. Other photoacoustic pulse sensing methods, such as a microring resonator, were also explored to be incorporated into OC-PAT systems. As for OC-PAE, after the first published configuration using a transducer, an improved version of the probe was introduced as a proof-of-concept design. Using all optical detection, an OC-PAE probe for intravascular imaging was demonstrated. A more detailed review on dual-modality imaging using OCT and PAI was recently published. 3.2.2 Contrast agents in OCT and PAI Endogenous contrast is not sufficient for fully exploiting PAI’s great potential for the visualization of physiology and pathology at the molecular level. Therefore, the development of imaging probes became an utterly important field for research. The use of specific multimodal OCT-PAI probes is often not necessary since PAI’s molecular imaging capabilities nicely complement OCT’s superiority in morphological imaging. Signal compounds for PAI can be divided into three broad classes: small-molecule dyes, inorganic, and organic nanostructures. Organic nanostructures and especially semiconducting polymer nanoparticles gained elevated interest since they can be easily functionalized and are of relatively low cost and potentially biosafe. , In addition, they possess excellent photostability and a high mass absorption coefficient. PAI probes can be used to image deeper into tissue to, e.g., allow for whole body mouse, rat, and human organ imaging, , , – to enhance the signal-to-background ratio, for phototherapy and photoactivation, , and for molecularly targeted imaging. , , Molecular targeting can involve the qualitative or quantitative detection of potential biomarkers such as reactive oxygen species, , pH, , Ca 2 + , – matrix metalloproteinases, and granzyme B. Biomarker imaging has mainly been demonstrated in animal models for various types of cancer, sentinel lymph nodes, liver dysfunction, and PAI of T lymphocytes, whereas intraoperative multimodal pancreatic cancer detection was already performed in humans. The combination of OCT with molecular PAI is still in its infancy, but it can offer new insights into pathophysiological processes. Targeting drug tolerant persister cells with signaling compounds in animal models and organoids might be a promising application for a combination of PAI and OCT for both tomography and ultrahigh-resolution imaging to aid cancer therapy. , , , Molecular PAI can be exploited to investigate a recently discovered fluid drainage pathway in the eye. , Monitoring of the ocular drainage rate into the lymphatic system can potentially be used as a measure for the effectiveness of existing and novel glaucoma treatments, , and a combination with OCT and retinal blood flow measurements could promote our understanding of glaucomatous optic neuropathy. 3.2.3 Outlook of OCT-PAI A major technological limitation of current OCT-PAI systems is the imaging speed mismatch between the two modalities. , Although modern OCT technology permits video rate imaging, PAI systems, especially when PAT is applied, are much slower. Recent advances in high-speed PAI have pointed the way for novel real-time OCT-PAT systems. First, as the speed of PAI has been largely confined by the limited repetition rate of current pulsed laser sources, high repetition rate light sources such as pulsed laser diodes and light emitting diodes , have been applied for in vivo PAI. However, the low fluence from these alternative sources has resulted in imaging results with a poor contrast, which could be potentially improved by emerging methods such as deep learning , . Another way toward real-time OCT-PAI systems is applying multiple transducers and parallel data acquisition for PAI, which has demonstrated 2D PAI for large objects , and 3D PAI for a smaller FOV. However, currently most photoacoustic detectors are conventional piezoelectric transducers, which are opaque to OCT detection beams. Therefore, all optical US detectors, due to their optical transparency, are especially interesting for OCT-PAI systems. Using a planar Fabry–Perot etalon, a multibeam scanner for simultaneous interrogation of multiple points was demonstrated. This parallel detection reduces the 3D PAI time to a few seconds. Increasing photoacoustic interrogation beams will further increase imaging speed. However, the parallel detection also greatly increases system costs. A new trend in high-speed PAI is to reduce acoustic detection points and adopt novel algorithms for image reconstruction using the obtained sparse data. These methods can be classified as iterative reconstruction algorithms – and deep learning methods. For the former, prior knowledge of photoacoustic images, such as smoothness, sparsity, or total variation constraints, are added in the iterative algorithms. For the latter, a priori training is necessary to reconstruct high-quality images from sparse data. Furthermore, in the latest breakthrough to speed up PAI, the number of required transducers for a large area 3D imaging was reduced to one single detector. To do this, an acoustic relay cavity is placed between the imaged object and the detector. The propagation of photoacoustic waves in this cavity creates unique stretched acoustic pulse signatures for each point in the FOV. Therefore, upon full field illumination, the signal of the single detector is the combination of stretched pulses from the whole FOV; thus the optical absorption at each point can be unmixed based on the acoustic pulse signature. Although more research is needed for this method, together with all progress in achieving high-speed PAI, these breakthroughs have paved the way to future real-time OCT-PAI technologies. 3.3 Multimodal Endoscopic OCT: More Comprehensive Access to Internal Body Organs In addition to its success story in ophthalmology, OCT can also provide exquisite cross-sectional morphological information of organs that are not easily accessible, such as coronary arteries, intestines, or the brain. OCT imaging penetration suffers from light attenuation in tissue, especially due to high scattering at the near-infrared wavelengths (800 to 1300 nm). Penetration depths of ∼ 0.5 to 2 mm prevent OCT from acting as a full-body imaging modality but enable tissue information up to comparable depths of those accomplished with conventional biopsies. In the past 30 years, research and industry have focused on the development of optical probes to endoscopically access internal organs with OCT. Two major approaches have been realized: sideward and forward imaging devices. Luminal organs, such as vessels, airways, or the esophagus, can be imaged by sideward viewing probes, realized with scanning mechanisms based on micromotor-based distal rotation of a reflector or proximal scanning of rotary joints. Larger hollow organs, such as the urinary bladder, stomach, or cervix, are accessible via a forward viewing probe placed in front of the ROI. Beam scanning is achieved using microelectromechanical systems (MEMS), such as piezoelectric actuators , or mirrors. , Also other forward scanning schemes have been reported on paired GRIN lenses or optical fiber bundles, although fiber bundles have not yet shown sufficient OCT performance and reduce probe bending flexibility for proper clinical applications. During the development process of such probes, general optical and mechanical requirements have to be met: overall mechanical diameter, taking safety measures into account for electrical isolation, electromagnetic shielding, bending protection, and sealing; the necessary rigid distal length of the probe to fit clinical instrumentation, which has often insertion angles on the proximal end; or a careful micro-optical design to reach best optical performance. For the lateral resolution, approaches have been proposed to access development parameters already in the biomarker identification phase using microscope setups. Additional obligatory clinical requirements regarding sterilizability or biocompatibility must be taken into account. Furthermore, orientation is key for performing biopsies at a location identified with endoscopic OCT for proofing diagnosis or resecting identified malignant lesions. A proposed approach in esophageal endoscopic OCT is using laser landmarks. , Not only is the change toward a combined diagnostic and therapeutic tool of high interest, but also new approaches in probe design and development have been fostered recently. Concepts based on diffractive lenses were reported by Xi et al. Although the construction size is still considerably large, diffractive lenses are overcoming the compromised optical performance if OCT is implemented in endoscopic probes. Improved image performance was demonstrated by Pahlevaninezhad et al. in 2018 using metalenses for developing nano-optic endoscopes. These specially designed metalenses were shown to precisely control the light phase, thus reducing spherical aberrations and astigmatism. Therefore, increased depth of focus in parallel to high resolving power is achieved. This technique could furthermore be beneficial for other endoscopic imaging modalities. As 3D printing currently is available for metal and glass material, the development and research are going toward 3D printed glass surfaces with optical quality. This enables freeform optics manufacturing of optical components and even multilens objectives. Implementing this technology in optical endoscopic probes allows for direct printing on optical fiber facets with freeform optical elements, such as a freeform total internal reflection mirror for sideward imaging endoscopic OCT. In addition, microstructuring concepts will most likely lead to implemented anti-reflection behavior of the optical elements and tailored optical properties using different photoresists to customize optical properties at a micrometer scale . Endoscopic OCT on its own has great potential in providing cross-sectional morphological information. Nevertheless, it lacks molecular or metabolic tissue contrast. Intramodal multimodal imaging using Doppler OCT, polarization sensitive OCT (PS-OCT), OCE, or spectroscopic OCT may provide additional contrast, but its clinical impact is still unclear. As an additional extension, endoscopic OCTA for perfusion and angiogenetic contrast is of increasing interest as well. First realized in sideward viewing probes, forward endoscopic OCTA has recently been successfully applied, , demonstrating promising advantages compared with narrow band imaging with respect to 3D visualization and increased depth. Increasing clinical endoscopic OCTA usability will require even further stabilization, robust acquisition modes, and image co-registration. – Imaging speed is certainly an important factor for its easy adaption. MHz OCT was reported for intravascular imaging to overcome heartbeat artifacts during imaging. Multi-MHz OCT/OCTA was reported recently and enables video rate OCT/OCTA at impressive imaging performance. , In the near future, multimodal endoscopic OCT will demonstrate significant potential to unleash the full capability of accessing complementary morpho-functional and/or morpho-molecular tissue information needed for improved clinical diagnosis and therapy monitoring. For example, reports on a probe combining OCT and fluorescence imaging providing additional molecular contrast and on a probe combining OCT, PAI, and US have been published. There are still challenges to be solved for a multimodal endoscopic OCT combination: the optic design needs to combine and find the best solution to fulfill the various optical requirements coming from the different image technologies in the scope of limited physical space within an endoscope. The acquisition times for the different modalities differ and are limited by biological constraints such as peristaltic movement, heartbeat, or breathing. Co-registered information is critical to retrieving the correct clinical information, especially if FOVs of the combined techniques are different. Research has been conducted toward the full cross-link of OCT and RS, despite remaining challenges. To investigate clinical validity, large clinical studies, preferably multicentral studies, are absolutely necessary. Toward real-time displaying of the relevant information, the complementary techniques should be processed and visualized in a way to permit in situ clinical understanding and finally diagnostic decision. Therefore, each single modality needs to be optimized for detecting/characterizing the disease. Data analysis speed and robustness have to be optimized, enabled by the full capacity of classification algorithms dealing with multivariant analysis. In the near future, computer science involvement will be the major topic for bringing endoscopic OCT (with or without other imaging technologies) to the patient bedside and into daily clinical practice. Techniques such as unsupervised classification for biomarker identification may be promising approaches. Morpho-molecular augmented painting, as presented by Alfonso-Garcia et al., with autofluorescence lifetime imaging during neurosurgery, would be an intuitive real-time information display for guiding clinicians to detect the malignant tissue. Finally, this technique would lead to an augmented map for resecting malignant tissue inside human organs based on morphological, molecular, and functional contrast. From a clinical point of view, the use of the described imaging devices—capable of multimodal endoscopic OCT—should preferably be applicable in an outpatient department setting, where typically no stationary stay of the patient is required, no general anesthesia is necessary, and immediate diagnostic information is needed. To achieve this, further miniaturization and increased usability with minimum patient discomfort are key. A quantum leap in diagnostic imaging of the gastrointestinal (GI) tract, for instance, may be swallowable low-cost imaging units transmitting reports of the GI tract to the patient’s cell phone or even to a centralized data analysis facility. Further development may go toward personalized medicine available at home to everybody for various internal organ diagnostics.
Non-linear Optical Microscopy and Spectroscopy: Subcellular, Biochemical, and Metabolic Detection of structural information at the cellular level expands the understanding of tissue environment for in vivo studies, but the lack of molecular specificity hampers differentiation between pathologic and healthy tissues with comparable scattering or structural properties. Structural alterations in tissues and cells usually take place only after carcinogenic biochemical changes. OCT contrast can be improved by various implementations. However, molecular specificity including metabolic information at the cellular level is still not easily accessible. Therefore, despite the power of OCT, the sensitivity and specificity to detect pathologic tissue are limited. This weakness limits the ongoing success of this technology. One solution to overcome this limitation and to address current needs in the life sciences and in the clinical practice is to combine OCT with other non-invasive molecular specific modalities. Label-free spectroscopic and microscopic optical imaging technologies such as Raman spectroscopy (RS) and MPM , that complement OCT have been established and extensively applied over the past years. These modalities present comparable contrast to standard histopathological methods, but no single modality can play the role alone. Indeed, integrated multimodal imaging provides the possibility of fusing morphological information with metabolic-molecular information in a label-free way, complementing basic observation with multiple specific contrast mechanisms to gain a complete picture of disease, but it is still challenging due to different optics and hardware requirements. MPM has become an essential instrument for biological and medical research with inherent 3D sectioning capability, subcellular resolution, high sensitivity, molecular and metabolic specificity, and deep tissue penetration compared with confocal microscopy, but compared with OCT achievable FOVs, penetration depths and acquisition speeds are restricted. This weakness can be overcome with novel high-speed MPM approaches achieving kilohertz frame rates by implementing pulse-modulated, rapidly wavelength-swept lasers, and inertia-free beam steering via angular dispersion. In the future, this could help to match the different needs of OCT and MPM, thus facilitating the combination of these complementary techniques in a single co-registered platform. Usually, the key technologies to add molecular sensitivity to OCT are RS and coherent Raman spectroscopy. RS allows for full molecular fingerprinting of tissue offers high specificity. Several variants including non-linear vibrational imaging with different sophisticated laser sources , and single-laser source approaches – have been proposed, but the main deficit is that real-world applications are often missing due to special treatment of the sample—thin slices of transparent samples with high Raman cross sections to be investigated in transmission or reflection mode. Coherent anti-Stokes Raman scattering efficiently provides images with label-free molecular information from DNA, lipids, proteins, and collagen. Recently, stimulated Raman scattering-spectroscopic OCT was introduced to leverage the spatial and spectral multiplexing capabilities of OCT with the molecular specificity and sensitivity of SRS for label-free fast 3D molecular imaging with a single laser on a single platform. Two-photon excitation fluorescence (TPEF) microscopy – is another powerful OCT add-on that can intrinsically be merged with SHG , – or fluorescence lifetime imaging microscopy (FLIM), – showing augmented contrasts with the same FOV and resolution for all modalities. TPEF microscopy can bring unique additional insight into the mechanisms underlying immune system dynamics and function as cellular motility within the native environment in vivo . TPEF microscopy and FLIM achieve ultrahigh isotropic subcellular resolution, enhance chromophore contrast via excitation of fluorescent biomolecules, improve sectioning compared with conventional one photon fluorescence, and metabolic information by imaging endogenous metabolites such as nicotinamide adenine dinucleotide and hydrogen/flavin adenine dinucleotide. Pleomorphism (cell nuclei versus cell size ratio) can be detected with subcellular resolution imaging, and grade classification can be performed. Co-registered OCT and TPEF microscopy has the ability to link specific cellular phenotypes and functions as revealed by TPEF to tissue morphology, thus paving the way between basic research knowledge and clinical observations. SHG provides contrast from non-centrosymmetric molecules such as collagen, which mainly appears in the extracellular matrix as distinct morphological feature. The supramolecular organization can be revealed. In vivo skin imaging on a cellular level proves the potential for dermatology. – THG microscopy provides cellular morphological information in real-time with acceptable penetration depth and ultrahigh isotropic subcellular resolution, but reduced penetration depth and remarkable smaller FOV compared with OCT . The problems with these multimodal optical imaging approaches with MPM are the need for very high-photon concentration in space and time and subsequent requirement of extremely high near infrared (NIR) laser intensities. Ultra-short laser pulses provide high-peak powers necessary to achieve appropriate excitation powers for MPM signal generation with moderate time-averaged illumination doses. Ultra-broadband Titanium:sapphire lasers, which are proven and well-established light sources for MPM, are a challenge in the commercialization of such combined platform since they introduced high costs and complexity. – Alternative stable and cost-effective light sources are required. Direct diode-pumping of mode-locked Titanium:sapphire lasers and scaling up of the achievable output power could pave the way toward more widespread application of this technology beyond scientific research. Recently, advancements in soliton-based photonic integrated frequency comb soliton microcombs have accelerated the development of broadband and low-noise chip scale frequency comb sources with the potential for high-resolution OCT deep tissue imaging at 1300 nm. Combining OCT with MPM at these longer wavelengths or even at 1700 nm can enhance tissue penetration. The key enabling elements to improve the imaging penetration depth, depth of focus, and spatial resolution simultaneously are the laser wavelengths and pulse energy, beam shaping concepts, detection schemes, and real-time AI algorithms. First, deploying longer wavelengths, e.g., 1700 nm for OCT, TPEF, SHG, and THG, the penetration depth for imaging is significantly improved, facilitated by the novel ultrafast laser wavelength agility. Second, novel beam shaping allows for propagating invariant light fields that achieve increased depth, thereby improving penetration and retaining high resolution. Third, to compensate for attenuation intrinsically present in tissue, absorption correction is applied, and, more importantly, dynamic changes from the strong optical scattering are compensated for by so-called computational adaptive optics. The latter relies on OCT motility contrast as a measure of the wavefront for correcting the input and real-time data processing. Penetration depth could be even further improved using light sources at longer wavelengths. Recently mid-infrared OCT could be demonstrated with an axial resolution of 8.6 μ m . Detection could be performed with a standard CCD camera upon implementation of an upconversion module. One major consideration for future development of the multimodal morpho-molecular metabolic imaging platforms lies in the capability of performing fast OCT and successive simultaneous MPM in the backward propagation direction without affecting one modality to interfere with the others, thus compromising image quality. Hence, one solution in multimodal diagnostic imaging is the combination of a wide-field high-resolution imaging platform including OCT and advanced microspectroscopic imaging techniques and an automated software to extract and classify the morpho-molecular metabolic patterns with the aim to see what can be seen in immunohistochemistry from the macroscopic level to the highly specific microscopic level. With deep learning, automatized full tissue characterization on a multiparametric level can reveal the early onset of disease and improve understanding. However, deep optical imaging, such as deep brain imaging in vivo , at high resolution still poses a great challenge beyond the light source development. Adaptive optics based on direct wavefront sensing can recover diffraction-limited resolution corrupted when achieving deep optical imaging. Successful implementation of adaptive optics in any optical system is always an engineering challenge and often makes the overall system complex and economically expensive. The subaperture correlation-based computational adaptive optics method, which is the computational equivalent of the Shack–Hartmann wavefront sensor (SHWS), can achieve near diffraction-limited performance in FF-SS OCT. The advantage of this method is that, unlike other optimization-based techniques, it is non-iterative in nature and it does not require a priori knowledge of any system parameters such as wavelength, focal length, NA, or detector pixel size. This method can be also extended to region of interest (ROI)-based aberration correction to achieve diffraction-limited lateral resolution beyond the isoplanatic patch in high-resolution point scanning OCT with high NA. A computational sensorless adaptive optics strategy including OCT could play a critical role in correcting aberrations over large volumes and enabling rapid random-access multiplane imaging without highly sophisticated precompensation, SHWS, or electron-multiplying charge-coupled device. AI-supported denoising and deconvolution of images to increase sharpness, resolution, or brightness are currently implemented at some microscopy platforms. However, it is often limited to a single modality and leaves the user patching different AI systems together for various use scenarios. At the moment, each imaging method needs a specific deep learning architecture with little similarities between each architecture. Moreover, to achieve a good level of validity, one needs a high number of training data to train an AI. One main problem for achieving the needed quality for detection and pixel-based quantification through deep learning lies in the lack of quality in ground truth data and the lack of a ground truth management system. By invoking a novel ground truth management system, an efficient AI system can be trained using only a few training data sets. Once the AI has been trained for one modality, the gained “experience” can be used to significantly speed up the training for other modalities through new transfer learning techniques, i.e., passing on experience. Active learning and knowledge transfer can improve learning speed and accuracy. This will apply to resolution enhancement as well as automatic annotations for ROIs. Therefore, in a unified approach in which the AI system supports OCT and MPM, radically improved learning speed and accuracy can be provided to establish novel multiparametric biomarkers. By developing and deploying novel beam shaping concepts, supported by advanced AI algorithms in combination with real-time data processing, critical parameters for the imaging performance in terms of penetration depth, acquisition speed, and spatial resolution are vastly improved, which could pave the way toward a compact multimodal biophotonics platform for advanced real-time 3D intrasurgical morphological, metabolic, and molecular imaging platform with increased sensitivity and specificity.
Photoacoustic Microscopy and Tomography: Absorption, Molecular Contrast, and Seeing Deeper OCT as an optical imaging modality that relies on the optical scattering properties of samples has its inherent limitations in terms of contrast generation. The strong scattering of many biological tissues further restricts the penetration depth of OCT due to its dependence on ballistic photon detection. To alleviate these problems, combining OCT with PAI has been explored by various groups over the past decade. Our previous review paper covered this topic for scientific works up to 2014. This perspective focuses on an update on dual modality OCT/PAI system configurations published recently as well as an outlook focusing on their application in molecular imaging. 3.2.1 System configurations for dual modality OCT-PAI Combining OCT and PAI can be categorized into three major implementation schemes: OCT with photoacoustic microscopy (OC-PAM), OCT with photoacoustic tomography (OC-PAT), and OCT with photoacoustic endoscopy (OC-PAE). Each of these schemes is briefly discussed below. In terms of OC-PAM, ever since the first realization of this technique, piezoelectric transducers have been the go-to solution for photoacoustic signal detection. Over the past few years, we can still see the piezoelectric transducers being used in OC-PAM configurations. Among these piezoelectric transducers, needle transducers are most commonly used. So far, OC-PAM using needle transducers has been applied in choroidal and retinal imaging – extensively. Some technical advancements of needle-transducer-based OC-PAM systems have also been reported such as for dynamic focusing , and for incorporating additional imaging modalities. However, due to the opaque nature of the needle transducer and knowing that these needle transducers are normally unfocused, alternatives for OC-PAM implementation have been explored. One direct approach is to make the transducer transparent, which was recently demonstrated in an OC-PAM system and applied in different disease or pathological models. Another approach would be to use optical detection for the photoacoustic waves. Using Michelson interferometry, OC-PAM was achieved and characterized. Using the principle of Fabry–Perot interferometry, an akinetic photoacoustic sensor was demonstrated and henceforth applied in OC-PAM imaging. , For OC-PAT, the implementation is still based on a system using a polymer film sensor. After the successful application of this system in chick embryo imaging and human skin imaging, the functional extension of OCTA was added and demonstrated in clinical settings. – The current development is to increase the speed of acquisition to match the two modalities’ acquisition time. Other photoacoustic pulse sensing methods, such as a microring resonator, were also explored to be incorporated into OC-PAT systems. As for OC-PAE, after the first published configuration using a transducer, an improved version of the probe was introduced as a proof-of-concept design. Using all optical detection, an OC-PAE probe for intravascular imaging was demonstrated. A more detailed review on dual-modality imaging using OCT and PAI was recently published. 3.2.2 Contrast agents in OCT and PAI Endogenous contrast is not sufficient for fully exploiting PAI’s great potential for the visualization of physiology and pathology at the molecular level. Therefore, the development of imaging probes became an utterly important field for research. The use of specific multimodal OCT-PAI probes is often not necessary since PAI’s molecular imaging capabilities nicely complement OCT’s superiority in morphological imaging. Signal compounds for PAI can be divided into three broad classes: small-molecule dyes, inorganic, and organic nanostructures. Organic nanostructures and especially semiconducting polymer nanoparticles gained elevated interest since they can be easily functionalized and are of relatively low cost and potentially biosafe. , In addition, they possess excellent photostability and a high mass absorption coefficient. PAI probes can be used to image deeper into tissue to, e.g., allow for whole body mouse, rat, and human organ imaging, , , – to enhance the signal-to-background ratio, for phototherapy and photoactivation, , and for molecularly targeted imaging. , , Molecular targeting can involve the qualitative or quantitative detection of potential biomarkers such as reactive oxygen species, , pH, , Ca 2 + , – matrix metalloproteinases, and granzyme B. Biomarker imaging has mainly been demonstrated in animal models for various types of cancer, sentinel lymph nodes, liver dysfunction, and PAI of T lymphocytes, whereas intraoperative multimodal pancreatic cancer detection was already performed in humans. The combination of OCT with molecular PAI is still in its infancy, but it can offer new insights into pathophysiological processes. Targeting drug tolerant persister cells with signaling compounds in animal models and organoids might be a promising application for a combination of PAI and OCT for both tomography and ultrahigh-resolution imaging to aid cancer therapy. , , , Molecular PAI can be exploited to investigate a recently discovered fluid drainage pathway in the eye. , Monitoring of the ocular drainage rate into the lymphatic system can potentially be used as a measure for the effectiveness of existing and novel glaucoma treatments, , and a combination with OCT and retinal blood flow measurements could promote our understanding of glaucomatous optic neuropathy. 3.2.3 Outlook of OCT-PAI A major technological limitation of current OCT-PAI systems is the imaging speed mismatch between the two modalities. , Although modern OCT technology permits video rate imaging, PAI systems, especially when PAT is applied, are much slower. Recent advances in high-speed PAI have pointed the way for novel real-time OCT-PAT systems. First, as the speed of PAI has been largely confined by the limited repetition rate of current pulsed laser sources, high repetition rate light sources such as pulsed laser diodes and light emitting diodes , have been applied for in vivo PAI. However, the low fluence from these alternative sources has resulted in imaging results with a poor contrast, which could be potentially improved by emerging methods such as deep learning , . Another way toward real-time OCT-PAI systems is applying multiple transducers and parallel data acquisition for PAI, which has demonstrated 2D PAI for large objects , and 3D PAI for a smaller FOV. However, currently most photoacoustic detectors are conventional piezoelectric transducers, which are opaque to OCT detection beams. Therefore, all optical US detectors, due to their optical transparency, are especially interesting for OCT-PAI systems. Using a planar Fabry–Perot etalon, a multibeam scanner for simultaneous interrogation of multiple points was demonstrated. This parallel detection reduces the 3D PAI time to a few seconds. Increasing photoacoustic interrogation beams will further increase imaging speed. However, the parallel detection also greatly increases system costs. A new trend in high-speed PAI is to reduce acoustic detection points and adopt novel algorithms for image reconstruction using the obtained sparse data. These methods can be classified as iterative reconstruction algorithms – and deep learning methods. For the former, prior knowledge of photoacoustic images, such as smoothness, sparsity, or total variation constraints, are added in the iterative algorithms. For the latter, a priori training is necessary to reconstruct high-quality images from sparse data. Furthermore, in the latest breakthrough to speed up PAI, the number of required transducers for a large area 3D imaging was reduced to one single detector. To do this, an acoustic relay cavity is placed between the imaged object and the detector. The propagation of photoacoustic waves in this cavity creates unique stretched acoustic pulse signatures for each point in the FOV. Therefore, upon full field illumination, the signal of the single detector is the combination of stretched pulses from the whole FOV; thus the optical absorption at each point can be unmixed based on the acoustic pulse signature. Although more research is needed for this method, together with all progress in achieving high-speed PAI, these breakthroughs have paved the way to future real-time OCT-PAI technologies.
System configurations for dual modality OCT-PAI Combining OCT and PAI can be categorized into three major implementation schemes: OCT with photoacoustic microscopy (OC-PAM), OCT with photoacoustic tomography (OC-PAT), and OCT with photoacoustic endoscopy (OC-PAE). Each of these schemes is briefly discussed below. In terms of OC-PAM, ever since the first realization of this technique, piezoelectric transducers have been the go-to solution for photoacoustic signal detection. Over the past few years, we can still see the piezoelectric transducers being used in OC-PAM configurations. Among these piezoelectric transducers, needle transducers are most commonly used. So far, OC-PAM using needle transducers has been applied in choroidal and retinal imaging – extensively. Some technical advancements of needle-transducer-based OC-PAM systems have also been reported such as for dynamic focusing , and for incorporating additional imaging modalities. However, due to the opaque nature of the needle transducer and knowing that these needle transducers are normally unfocused, alternatives for OC-PAM implementation have been explored. One direct approach is to make the transducer transparent, which was recently demonstrated in an OC-PAM system and applied in different disease or pathological models. Another approach would be to use optical detection for the photoacoustic waves. Using Michelson interferometry, OC-PAM was achieved and characterized. Using the principle of Fabry–Perot interferometry, an akinetic photoacoustic sensor was demonstrated and henceforth applied in OC-PAM imaging. , For OC-PAT, the implementation is still based on a system using a polymer film sensor. After the successful application of this system in chick embryo imaging and human skin imaging, the functional extension of OCTA was added and demonstrated in clinical settings. – The current development is to increase the speed of acquisition to match the two modalities’ acquisition time. Other photoacoustic pulse sensing methods, such as a microring resonator, were also explored to be incorporated into OC-PAT systems. As for OC-PAE, after the first published configuration using a transducer, an improved version of the probe was introduced as a proof-of-concept design. Using all optical detection, an OC-PAE probe for intravascular imaging was demonstrated. A more detailed review on dual-modality imaging using OCT and PAI was recently published.
Contrast agents in OCT and PAI Endogenous contrast is not sufficient for fully exploiting PAI’s great potential for the visualization of physiology and pathology at the molecular level. Therefore, the development of imaging probes became an utterly important field for research. The use of specific multimodal OCT-PAI probes is often not necessary since PAI’s molecular imaging capabilities nicely complement OCT’s superiority in morphological imaging. Signal compounds for PAI can be divided into three broad classes: small-molecule dyes, inorganic, and organic nanostructures. Organic nanostructures and especially semiconducting polymer nanoparticles gained elevated interest since they can be easily functionalized and are of relatively low cost and potentially biosafe. , In addition, they possess excellent photostability and a high mass absorption coefficient. PAI probes can be used to image deeper into tissue to, e.g., allow for whole body mouse, rat, and human organ imaging, , , – to enhance the signal-to-background ratio, for phototherapy and photoactivation, , and for molecularly targeted imaging. , , Molecular targeting can involve the qualitative or quantitative detection of potential biomarkers such as reactive oxygen species, , pH, , Ca 2 + , – matrix metalloproteinases, and granzyme B. Biomarker imaging has mainly been demonstrated in animal models for various types of cancer, sentinel lymph nodes, liver dysfunction, and PAI of T lymphocytes, whereas intraoperative multimodal pancreatic cancer detection was already performed in humans. The combination of OCT with molecular PAI is still in its infancy, but it can offer new insights into pathophysiological processes. Targeting drug tolerant persister cells with signaling compounds in animal models and organoids might be a promising application for a combination of PAI and OCT for both tomography and ultrahigh-resolution imaging to aid cancer therapy. , , , Molecular PAI can be exploited to investigate a recently discovered fluid drainage pathway in the eye. , Monitoring of the ocular drainage rate into the lymphatic system can potentially be used as a measure for the effectiveness of existing and novel glaucoma treatments, , and a combination with OCT and retinal blood flow measurements could promote our understanding of glaucomatous optic neuropathy.
Outlook of OCT-PAI A major technological limitation of current OCT-PAI systems is the imaging speed mismatch between the two modalities. , Although modern OCT technology permits video rate imaging, PAI systems, especially when PAT is applied, are much slower. Recent advances in high-speed PAI have pointed the way for novel real-time OCT-PAT systems. First, as the speed of PAI has been largely confined by the limited repetition rate of current pulsed laser sources, high repetition rate light sources such as pulsed laser diodes and light emitting diodes , have been applied for in vivo PAI. However, the low fluence from these alternative sources has resulted in imaging results with a poor contrast, which could be potentially improved by emerging methods such as deep learning , . Another way toward real-time OCT-PAI systems is applying multiple transducers and parallel data acquisition for PAI, which has demonstrated 2D PAI for large objects , and 3D PAI for a smaller FOV. However, currently most photoacoustic detectors are conventional piezoelectric transducers, which are opaque to OCT detection beams. Therefore, all optical US detectors, due to their optical transparency, are especially interesting for OCT-PAI systems. Using a planar Fabry–Perot etalon, a multibeam scanner for simultaneous interrogation of multiple points was demonstrated. This parallel detection reduces the 3D PAI time to a few seconds. Increasing photoacoustic interrogation beams will further increase imaging speed. However, the parallel detection also greatly increases system costs. A new trend in high-speed PAI is to reduce acoustic detection points and adopt novel algorithms for image reconstruction using the obtained sparse data. These methods can be classified as iterative reconstruction algorithms – and deep learning methods. For the former, prior knowledge of photoacoustic images, such as smoothness, sparsity, or total variation constraints, are added in the iterative algorithms. For the latter, a priori training is necessary to reconstruct high-quality images from sparse data. Furthermore, in the latest breakthrough to speed up PAI, the number of required transducers for a large area 3D imaging was reduced to one single detector. To do this, an acoustic relay cavity is placed between the imaged object and the detector. The propagation of photoacoustic waves in this cavity creates unique stretched acoustic pulse signatures for each point in the FOV. Therefore, upon full field illumination, the signal of the single detector is the combination of stretched pulses from the whole FOV; thus the optical absorption at each point can be unmixed based on the acoustic pulse signature. Although more research is needed for this method, together with all progress in achieving high-speed PAI, these breakthroughs have paved the way to future real-time OCT-PAI technologies.
Multimodal Endoscopic OCT: More Comprehensive Access to Internal Body Organs In addition to its success story in ophthalmology, OCT can also provide exquisite cross-sectional morphological information of organs that are not easily accessible, such as coronary arteries, intestines, or the brain. OCT imaging penetration suffers from light attenuation in tissue, especially due to high scattering at the near-infrared wavelengths (800 to 1300 nm). Penetration depths of ∼ 0.5 to 2 mm prevent OCT from acting as a full-body imaging modality but enable tissue information up to comparable depths of those accomplished with conventional biopsies. In the past 30 years, research and industry have focused on the development of optical probes to endoscopically access internal organs with OCT. Two major approaches have been realized: sideward and forward imaging devices. Luminal organs, such as vessels, airways, or the esophagus, can be imaged by sideward viewing probes, realized with scanning mechanisms based on micromotor-based distal rotation of a reflector or proximal scanning of rotary joints. Larger hollow organs, such as the urinary bladder, stomach, or cervix, are accessible via a forward viewing probe placed in front of the ROI. Beam scanning is achieved using microelectromechanical systems (MEMS), such as piezoelectric actuators , or mirrors. , Also other forward scanning schemes have been reported on paired GRIN lenses or optical fiber bundles, although fiber bundles have not yet shown sufficient OCT performance and reduce probe bending flexibility for proper clinical applications. During the development process of such probes, general optical and mechanical requirements have to be met: overall mechanical diameter, taking safety measures into account for electrical isolation, electromagnetic shielding, bending protection, and sealing; the necessary rigid distal length of the probe to fit clinical instrumentation, which has often insertion angles on the proximal end; or a careful micro-optical design to reach best optical performance. For the lateral resolution, approaches have been proposed to access development parameters already in the biomarker identification phase using microscope setups. Additional obligatory clinical requirements regarding sterilizability or biocompatibility must be taken into account. Furthermore, orientation is key for performing biopsies at a location identified with endoscopic OCT for proofing diagnosis or resecting identified malignant lesions. A proposed approach in esophageal endoscopic OCT is using laser landmarks. , Not only is the change toward a combined diagnostic and therapeutic tool of high interest, but also new approaches in probe design and development have been fostered recently. Concepts based on diffractive lenses were reported by Xi et al. Although the construction size is still considerably large, diffractive lenses are overcoming the compromised optical performance if OCT is implemented in endoscopic probes. Improved image performance was demonstrated by Pahlevaninezhad et al. in 2018 using metalenses for developing nano-optic endoscopes. These specially designed metalenses were shown to precisely control the light phase, thus reducing spherical aberrations and astigmatism. Therefore, increased depth of focus in parallel to high resolving power is achieved. This technique could furthermore be beneficial for other endoscopic imaging modalities. As 3D printing currently is available for metal and glass material, the development and research are going toward 3D printed glass surfaces with optical quality. This enables freeform optics manufacturing of optical components and even multilens objectives. Implementing this technology in optical endoscopic probes allows for direct printing on optical fiber facets with freeform optical elements, such as a freeform total internal reflection mirror for sideward imaging endoscopic OCT. In addition, microstructuring concepts will most likely lead to implemented anti-reflection behavior of the optical elements and tailored optical properties using different photoresists to customize optical properties at a micrometer scale . Endoscopic OCT on its own has great potential in providing cross-sectional morphological information. Nevertheless, it lacks molecular or metabolic tissue contrast. Intramodal multimodal imaging using Doppler OCT, polarization sensitive OCT (PS-OCT), OCE, or spectroscopic OCT may provide additional contrast, but its clinical impact is still unclear. As an additional extension, endoscopic OCTA for perfusion and angiogenetic contrast is of increasing interest as well. First realized in sideward viewing probes, forward endoscopic OCTA has recently been successfully applied, , demonstrating promising advantages compared with narrow band imaging with respect to 3D visualization and increased depth. Increasing clinical endoscopic OCTA usability will require even further stabilization, robust acquisition modes, and image co-registration. – Imaging speed is certainly an important factor for its easy adaption. MHz OCT was reported for intravascular imaging to overcome heartbeat artifacts during imaging. Multi-MHz OCT/OCTA was reported recently and enables video rate OCT/OCTA at impressive imaging performance. , In the near future, multimodal endoscopic OCT will demonstrate significant potential to unleash the full capability of accessing complementary morpho-functional and/or morpho-molecular tissue information needed for improved clinical diagnosis and therapy monitoring. For example, reports on a probe combining OCT and fluorescence imaging providing additional molecular contrast and on a probe combining OCT, PAI, and US have been published. There are still challenges to be solved for a multimodal endoscopic OCT combination: the optic design needs to combine and find the best solution to fulfill the various optical requirements coming from the different image technologies in the scope of limited physical space within an endoscope. The acquisition times for the different modalities differ and are limited by biological constraints such as peristaltic movement, heartbeat, or breathing. Co-registered information is critical to retrieving the correct clinical information, especially if FOVs of the combined techniques are different. Research has been conducted toward the full cross-link of OCT and RS, despite remaining challenges. To investigate clinical validity, large clinical studies, preferably multicentral studies, are absolutely necessary. Toward real-time displaying of the relevant information, the complementary techniques should be processed and visualized in a way to permit in situ clinical understanding and finally diagnostic decision. Therefore, each single modality needs to be optimized for detecting/characterizing the disease. Data analysis speed and robustness have to be optimized, enabled by the full capacity of classification algorithms dealing with multivariant analysis. In the near future, computer science involvement will be the major topic for bringing endoscopic OCT (with or without other imaging technologies) to the patient bedside and into daily clinical practice. Techniques such as unsupervised classification for biomarker identification may be promising approaches. Morpho-molecular augmented painting, as presented by Alfonso-Garcia et al., with autofluorescence lifetime imaging during neurosurgery, would be an intuitive real-time information display for guiding clinicians to detect the malignant tissue. Finally, this technique would lead to an augmented map for resecting malignant tissue inside human organs based on morphological, molecular, and functional contrast. From a clinical point of view, the use of the described imaging devices—capable of multimodal endoscopic OCT—should preferably be applicable in an outpatient department setting, where typically no stationary stay of the patient is required, no general anesthesia is necessary, and immediate diagnostic information is needed. To achieve this, further miniaturization and increased usability with minimum patient discomfort are key. A quantum leap in diagnostic imaging of the gastrointestinal (GI) tract, for instance, may be swallowable low-cost imaging units transmitting reports of the GI tract to the patient’s cell phone or even to a centralized data analysis facility. Further development may go toward personalized medicine available at home to everybody for various internal organ diagnostics.
Extensions of Optical Coherence Tomography Alike in other (especially microscopic) imaging technologies, numerous functional and contrast enhancing OCT extensions have been developed in the last 30 years immediately after its invention. In the case of OCT, these additional functional and contrast enhanced tissue information come with OCT’s exquisite micrometer depth axial resolution as opposed to an integration over the entire depth penetration. In academia, several successful functional and contrast enhancing OCT extensions have been initiated, but aside from OCTA, a label-free motion-contrast-based functional OCT extension providing perfusion and hence angiogenetic information, no other functional or contrast enhancing OCT extension has accomplished comparable clinical and industrial impacts. One of the first OCT extensions enhancing tissue contrast by collecting light resolved by polarization and thus revealing tissue birefringence is PS-OCT. In 1992, Hee et al. demonstrated a polarization-sensitive low-coherence reflectometer and characterized the birefringence of a wave plate and ex vivo calf coronary artery tissue. More than 500 publications in this field by numerous academic groups demonstrated the great potential of this OCT extension especially in the eye and the skin, , – but so far it has not been successfully translated to a commercial system or proven its diagnostic impact. Catheter, endoscopy, and needle-based PS-OCT might, in the near future, turn out to be an extremely interesting clinical application for this contrast enhancing OCT extension. – Before OCTA, Doppler optical coherence tomography (DOCT) was the first – and most extensively used functional OCT extension determining the speed of moving particles in the tissue by measuring the frequency shift imparted on light scattered by the particles and already setting out to produce three-dimensional maps of tissue perfusion. , The classic example of Doppler shifts is the increase in frequency of an approaching train whistle followed by the decrease in frequency as it passes and departs. Higher sensitivity was achieved by phase sensitive Doppler OCT, which in combination with higher speed of FD OCT ultimately allowed for measurement of blood flow in a large range of retinal vessels with high sensitivity. As with other laser Doppler flow measurement techniques, DOCT has several challenges, the most critical being that the accurate measurement of velocity requires knowledge of the angle between the OCT beam and the direction of the velocity in the sample. The first paper introducing the notion of optical coherence angiography applied known methods of DOCT to produce retinal angiographic maps. Later work established the intuitive notion of OCTA for perfusion mapping. With the persistent split of pure structural angiographic mapping as OCTA from the originally overarching notion of DOCT, DOCT’s scientific output (more than 4000 for OCTA and about 450 for DOCT ) and hence commercialization [Thorlabs (Newton, New Jersey) and Optovue, Inc. (Fremont, California)] was consequently reduced. 4.1 Optical Coherence Angiography OCTA is a label-free non-invasive OCT extension that uses blood cell motion contrast for high-resolution imaging of volumetric blood flow information generating angiographic images—hence providing both structural and functional (i.e., blood flow/perfusion) tissue information. Such angiographic maps in 3D have already been demonstrated by FD OCT-based Doppler OCT by several groups. However, the visibility of small capillary vessels was critically improved by comparing signals of adjacent B-scans rather than A-scans. Instead of quantifying the correlation between signals, OCTA compares the decorrelation signal between sequential OCT B-scans taken at the same cross-sectional location to construct a map of blood flow. Emerging from Doppler OCT, between 2004 and 2012, at least 10 different research groups published different versions of OCTA, the majority of them claiming its invention and producing new acronyms for OCTA. , , The majority of the 4000 publications are in the field of ophthalmic diagnosis. – However, OCTA has also been successfully demonstrated for detecting angiogenetic biomarkers in cancer diagnosis and therapy monitoring as well as in endoscopic applications. , The success in ophthalmic applications and in clinical translation of this technique lies in its technological simplicity, moderate additional engineering as compared with conventional OCT systems, and extremely significant clinical impact—slowly replacing fluorescein angiography and indocyanine green angiography in clinical routine. To eliminate patient or organ movement induced artifacts, OCTA requires higher imaging speeds than most currently available OCT systems. It is noteworthy that OCTA provides 3D qualitative flow information at a fixed point in time. Therefore, vessel leakage is not detectable by OCTA. Furthermore, exact automated segmentation of all diagnostically important intraretinal layers is of essence to avoid artifacts in the OCT angiograms of the respective layers. Consequently, exact segmentation necessitates sufficient system sensitivity, axial resolution, and contrast. Retinal blood flow on OCTA can be obscured by hemorrhage as this decreases the ability of light to penetrate into the deeper layers of the eye. Despite the rapid, tremendous commercial and clinical success of OCTA, some (at least relative) blood flow quantification will be needed in the near future. – Improved and reproducible quantitative OCTA is definitely also of significant clinical interest as is the correct visualization and quantification of choriocapillaris , , . Another important future clinical role enabled by ultrahigh speed swept sources will be wide-field OCTA for the detection of neovascularization of the disc and elsewhere, microaneurysms, changes of the foveal avascular zone, intraretinal microvascular abnormalities, and capillary non-perfusion. , This advancement of OCTA technology in clinical research will ultimately lead to enhancement of individualized management of diabetic retinopathy and prevention of visual impairment in patients with diabetes. Using the eye and especially the retina as a part of the central nervous system diagnostically as a window to the brain started in the late 1970s, and about 400 papers since then have covered diagnostic methods in the posterior pole of the eye for early diagnosis of brain diseases. An important prerequisite for successful OCTA-based diagnosis in neurodegenerative diseases and other clinical applications will be accurate and reproducible quantitative OCTA. Quantitative analysis of OCTA is essential to standardize objective interpretations of clinical outcomes. Indeed, a concerted effort has been put forth to understand how Alzheimer’s disease (AD) pathology may manifest in the retina as a means to assess the state of the AD brain. – OCTA has also been successfully evaluated as a tool to assess retinal changes in Parkinson’s disease and both schizophrenia and bipolar disorder. 4.2 Optophysiology/Optoretinography: Non-Invasive Detection of Intrinsic Optical Signals Modern medical diagnosis significantly benefits from extracting functional tissue information from structural imaging data (“structure–function correlation”). This is especially important in organs that cannot be biopsied, like the human retina. Retinal function has long been studied with psychophysical methods in humans, e.g., with electrophysiology and electroretinograms. Non-contact, depth-resolved, optical probing of retinal response to visual stimulation was introduced as optophysiology—an optical analog to electrophysiology. This method takes advantage of the fact that physiological changes in dark-adapted retinas caused by light stimulation can result in local variation of the tissue reflectivity. At that time, optophysiology could only be demonstrated in isolated rabbit retinas. Ophthalmic OCT technology back then was not sufficiently fast at longer wavelengths performing at sufficiently high sensitivity and resolution to be successfully applied in living animals or humans. A decade later, light-driven signals of photoreceptors in vivo could be measured. Visible light stimulation over a 200-fold intensity range caused correlated rod outer segment (OS) elongation and increased light scattering in wild-type mice, but not in mice lacking the rod G-protein alpha subunit, transducin (Gα(t)), revealing these responses to be triggered by phototransduction. The diurnal variation in rod OS length in mice was measured using optophysiology, being consistent with prior histological investigations demonstrating that rodent rod discs are phagocytosed by the RPE maximally over several hours around the time of normal light onset. The rate of recovery of rod OSs to baseline length before normal light onset was consistent with the hypothesis that disc membrane synthesis is fairly constant over the diurnal cycle . Fast intrinsic optical signal (IOS), which arises before light-evoked pupillary response, promises to be a unique biomarker for photoreceptor physiology for objective optoretinography with high resolution. In another study, depth-resolved optophysiology verified OS as the anatomic origin of fast photoreceptor-IOS. Dynamic IOS changes were primarily confined at OS boundaries connected with inner segment and RPE, supporting transient OS shrinkage due to phototransduction process as the mechanism of the fast photoreceptor-IOS response. Non-invasive, objective measurement of light-evoked, functional responses of human rods and cones, measured non-invasively using a synchronized adaptive optics OCT and scanning light ophthalmoscopy system have also been reported recently. Another recent study revealed that the onset of phototransduction is accompanied by a rapid ( < 5 ms ), nanometer-scale electromechanical deformation in individual human cone photoreceptors. Characterizing this biophysical phenomenon associated with phototransduction in vivo was enabled by high-speed phase-resolved optical LFOCT that allowed for sufficient spatiotemporal resolution to visualize the nanometer/millisecond-scale light-induced shape change in photoreceptors. 4.3 Visible Light OCT: Unprecedented Axial Resolution and Enhanced OCT Access to Absorption OCT in the visible wavelength range with unprecedented submicrometer axial resolution achieved by employing a photonic crystal fiber in combination with a sub-15 fs Titanium:sapphire laser was first demonstrated in the beginning of this millennium. , Visible light OCT theoretically provides higher axial resolution than NIR OCT for a given wavelength and bandwidth. To realize this potential in the human retina in vivo , the unique technical challenges of visible light OCT must be addressed: incorporating a grating light valve spatial light modulator spectral shaping stage to modify the source spectrum; developing a novel, Fourier transform-free, software axial motion tracking algorithm with fast, magnetically actuated stage to maintain near-optimal axial resolution and sensitivity in the presence of eye motion; and implementing spatially dependent numerical dispersion compensation for the first time in the human eye in vivo . Wavelength-dependent images of the outer retina suggest that, beyond merely improving the axial resolution, shorter wavelength visible light may also provide unique advantages for visualizing Bruch’s membrane (BM). Furthermore, it seems that shorter visible wavelengths improve the visualization of BM in pigmented eyes, where it is located behind a highly scattering layer of melanosomes in the RPE. Monte Carlo simulations of radiative transport suggest that, while absorption and scattering are higher at shorter wavelengths, detected multiply scattered light from the RPE is preferentially attenuated relative to detected backscattered light from BM. Using visible light OCT, accurate and robust non-invasive measurement of retinal oxygen metabolic rate ( rMRO 2 ) in rat eyes was demonstrated. Both oxygen delivery and rMRO 2 increased from the highly regulated retinal circulation under hypoxia. The increased oxygen extraction compensated for the deficient oxygen supply from the poorly regulated choroidal circulation. These results have the potential to reveal the fundamental role of oxygen metabolism in various retinal diseases such as age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma. Oximetry saturation sO 2 measurements were also recently extended to capillaries and investigated in all three retinal vascular plexuses by amplifying and extracting the spectroscopic signal from each capillary segment under the guidance of OCTA. Using this approach, capillary sO 2 in the retinal circulation in rats was measured. In vivo depth resolved human imaging of oxygenation in retinal capillaries was recently demonstrated. In addition, first visible light OCTA with a 100-kHz A-line rate for human retinal imaging was also demonstrated recently, enabling accurate localization of microvasculature down to the capillary level and thus enabling oximetry at vessels < 100 μ m in diameter. Microvascular hemoglobin oxygen saturation ( sO 2 ) at the feeding and draining vessels at the perifoveal region was demonstrated, allowing for future studies on the role of microvascular oxygen in various retinal pathologies . Another technique enabling OCT access to absorption is photothermal OCT, which monitors changes in the optical path length caused by the photothermal effect. Like in PAI in the photothermal effect, photons are absorbed by chromophores within a sample, causing a localized rise in temperature. Thermoelastic expansion caused by the photothermal effect generates isolated variations in the refractive index, which in turn generates a variation in the optical path length. The optical path length variations typically generated by the photothermal effect, often nanometer in scale, can be resolved with phase-sensitive OCT. This approach might be extremely attractive for non-destructive 3D molecular imaging deep ( ∼ 2 mm ) within biological samples with a sensitivity of 14 parts per million (weight/weight) nanoparticles in the sample. In addition, photothermal OCT could quantify changes in pigmentation that occur in retinal diseases. , In vivo photothermal OCT was also demonstrated for cross-sectional in human skin measurement with endogenous absorption agents. Recently, a swept source dual-wavelength photothermal OCT system was demonstrated for quantitative imaging of microvasculature oxygen saturation and measuring of microvasculature sO 2 levels in phantom blood vessels with a range of blood flow speeds (0 to 17 mm / s ). 4.4 Dynamic Contrast OCT Recently, an extremely powerful new contrast enhancing OCT extension was introduced. It employs a new endogenous approach to reveal subcellular metabolic contrast in fresh ex vivo tissues, taking advantage of the time dependence of FF OCT interferometric signals. This method reveals signals linked with local activity of the endogenous scattering elements that can reveal cells where other OCT-based techniques fail or need exogenous contrast agents. Using high-transverse resolution to image intracellular features, the time dependence to identify different dynamics at the millisecond scale on a wide range of organs in normal or pathological conditions is used. Dynamic contrast OCT has also been applied in freshly excised human esophageal and cervical biopsy samples. Depth-resolved dynamic contrast OCT images of intact tissue show that intracellular dynamics provides a new contrast mechanism that highlights subcellular morphology and activity in epithelial surface maturation patterns . This technique has also been used to combine static, dynamic, and fluorescence contrasts to achieve label-free high-resolution imaging of the living retina and anterior eye with temporal resolution from milliseconds to several hours, allowing for probing biological activity at subcellular scales inside 3D bulk tissue. By evaluating signal fluctuations, a significant contrast enhancement was demonstrated using TD FFOCT, which makes cellular and subcellular structures visible. The putative cause of the dynamic OCT signal is the site-dependent active motion of cellular structures in the submicrometer range, which provides histology-like contrast. In vivo dynamic contrast OCT was used to quantify layer-resolved microvascular blood flow and volume across the full depth of the mouse neocortex. Finally, speckle variations induced by intracellular motion in the urothelium were used as a dynamic contrast to segment the urothelium with only two sequential OCT images. This new method opens the possibility of tracking the distribution of the urothelial cells to identify the microinvasion of bladder tumors. This contrast may provide a new mechanism for OCT to diagnose the invasion of urothelial cancerous cells for the better staging of bladder cancer. Another interesting contrast enhancing OCT extension that gained a lot of attention recently is using the extraction of the optical attenuation coefficient, an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. With current studies showing attenuation coefficient analysis as a promising technique, further efforts in the development of methods to accurately extract the attenuation coefficient and to explore its potential use for more extensive clinical applications are desired. 4.5 Optical Coherence Elastography: Depth Resolved Optical Palpation An extremely promising extension of OCT is OCE. The original idea of elastography is not only to exploit the stiffness changes within soft tissue for diagnosis, much like a physician would during palpation, but also to exactly localize and quantify them. The capability of OCT to give 3D insight into tissue is used to visualize the reaction of a sample to a mechanical force. Multiple methods for deriving this reaction from the OCT data have been presented, e.g., image cross correlation, feature or speckle tracking, optical flow, combinations thereof, and phase difference analysis. From this reaction, the underlying mechanical tissue parameters can be obtained and used for diagnosis. The technology first emerged in US imaging, where systems capable of elastography have been commercially available since the 2000s. Elastography in general is a relative straight forward add-on to OCT, enabling biomechanical contrast at a slightly increased imaging time and data processing complexity. Although a lot of promising approaches and methods utilizing OCE have been published, two major applications are at the moment competing for clinical in vivo diagnosis . In this sense, the ophthalmic application of OCE is the most advanced, likely because it could build upon decades of OCT experience in this field, which already addressed issues like motion correction and speed. The only novel aspect from an engineering perspective is mechanical loading, which has to be performed cautiously and preferably contactless. Proposed solutions rage from contact shaker excitation, over microscale air-pulses, and acoustic radiation pulses , to heartbeat driven tissue deformation. , De Stefano et al. demonstrated the feasibility of OCE for identification of keratoconic corneas in humans in vivo using a dynamic compressional approach with intensity-based speckle tracking. Since the compression is applied via a motorized stage, direct contact to the cornea is needed, but quantitative analysis also is enabled. In May 2020, Lan et al. quantified the effects of respiration and heartbeat on patient eye motion as a source of perturbation for OCE in vivo and mentioned the idea that this perturbation could also be used as a passive loading method. Only a month later, Nair et al. gave another indication for the feasibility of non-contact heartbeat ophthalmic OCE in an ex vivo porcine eye model with controlled intraocular pressure changes. In January 2021, Nair et al. achieved heartbeat OCE in an in vivo rabbit model, but the method was not completely non-contact as a glass imaging window was used to minimize bulk motion. The heart pulse compressed the corneal tissue against this imaging window, resulting in the desired displacement. OCE data were acquired as multiple 2D B-scans at the same position, which were synchronized with the rabbit’s heartbeat later in postprocessing. The resulting 2D strain maps clearly show the difference between compression and relaxation induced by the pulse. In addition, they were able to differentiate between an untreated cornea and a cornea stiffened via the Dresden protocol. Although these are already very promising first results, some challenges for clinical in vivo patient imaging still remain to be addressed. Since pulse waves travel at a limited speed, they affect different regions in the FOV at different points in time, which can lead to underestimation of the resulting strain and is a challenge for synchronization. For clinical diagnosis, en face images and 3D stiffness maps are much more useful than single B-scans. 3D imaging would not only highly increase imaging time but also make the synchronization even more complicated. One also has to be aware that, without the possibility of quantifying the pressure perceived by the investigated tissue, only qualitative OCE results can be expected and quantifying the pressure excited by a heartbeat at every point in the FOV seems impossible at this point in time. However, the potential of ophthalmic OCE for clinical application is huge. The feasibility for diagnosing keratoconus has been shown in the examples above, but also corneal dystrophy or corneal ectasia due to surgical complications are obvious topics in which OCE can deliver fast and uncomplicated diagnosis, as well as in the diagnosis of AMD in which early diagnosis is especially important, as presented by Qian et al. When it comes to the field of cancer detection and diagnosis, current literature focuses on biopsy images as proof of concept. Not only is cancer often accompanied by significant changes in stiffness, but also the shape of the outlines of cancer has diagnostic potential. A good example is given by Kennedy et al., who showed that cancer margin detection with OCE yields a 24% higher sensitivity than with OCT only. Multiple tumor types have been investigated, and OCE proved to be an accurate predictor of malignancy for all of them. A phase-sensitive, quasi-static compression OCE system was used. The future of OCE lies in intraoperative in vivo imaging for determining tumor margins of cancerous tissue to be removed, requiring not only high-speed OCT imaging to minimize the influence of motion artifacts but also high-speed processing to enable real-time view. Depending on the chosen biomechanical model and processing approach, this task requires expensive hardware and well-versed software implementation. Another challenge to keep in mind is OCE’s vulnerability to laser and system instabilities, which are even more difficult to control in a surgical environment. Nonetheless, surgical applications of OCE are close. Plekhanov et al. presented a phase-sensitive, quasi-static compressional OCE method that is capable of segmenting cancerous regions in a mouse model in vivo . They were able to differentiate between viable, dystrophic, and necrotic tumor cells as well as edema zones and validated their findings via comparison with histological results. A 9-day study, comparing the effect of two different chemotherapeutics with untreated control, was performed as well. In a similar study, the combination of OCE with OCTA was shown to be an easy way to add functional information, improving the quality of chemotherapeutic treatment efficiency studies. As can be seen in the aforementioned examples, quasi-static compression OCE, mostly phase-sensitive with some sort of compliance layer as stress sensor, is currently the most advanced OCE method. In the last few years, other approaches rose to the horizon of feasibility, e.g., vibrational OCE, , which uses OCT to record the reaction of a sample to a variation of vibration frequencies. With this, a 3D resonant frequency map of the sample can be generated and viscoelastic behavior can be investigated. Another proposed application, although more focused on usage in studies than for clinical diagnosis, is in intravascular OCE. , Since atherosclerosis is the leading cause of human death worldwide, continued effort is put into understanding the generation, buildup, and rupture of intravascular plaques. Overall OCE has come far, and routine clinical usage especially in the ophthalmic field is to be expected in the next few years. The next steps to this goal are achieving faster imaging and data processing and even better motion correction. Although some OCE experts and clinicians argue that there is no need for quantifying tissue stiffness, as long as there is qualitative biomechanical contrast, in the long term it might make a lot of clinical sense to find a quantitative stiffness atlas, which allows for diagnostic guidance.
Optical Coherence Angiography OCTA is a label-free non-invasive OCT extension that uses blood cell motion contrast for high-resolution imaging of volumetric blood flow information generating angiographic images—hence providing both structural and functional (i.e., blood flow/perfusion) tissue information. Such angiographic maps in 3D have already been demonstrated by FD OCT-based Doppler OCT by several groups. However, the visibility of small capillary vessels was critically improved by comparing signals of adjacent B-scans rather than A-scans. Instead of quantifying the correlation between signals, OCTA compares the decorrelation signal between sequential OCT B-scans taken at the same cross-sectional location to construct a map of blood flow. Emerging from Doppler OCT, between 2004 and 2012, at least 10 different research groups published different versions of OCTA, the majority of them claiming its invention and producing new acronyms for OCTA. , , The majority of the 4000 publications are in the field of ophthalmic diagnosis. – However, OCTA has also been successfully demonstrated for detecting angiogenetic biomarkers in cancer diagnosis and therapy monitoring as well as in endoscopic applications. , The success in ophthalmic applications and in clinical translation of this technique lies in its technological simplicity, moderate additional engineering as compared with conventional OCT systems, and extremely significant clinical impact—slowly replacing fluorescein angiography and indocyanine green angiography in clinical routine. To eliminate patient or organ movement induced artifacts, OCTA requires higher imaging speeds than most currently available OCT systems. It is noteworthy that OCTA provides 3D qualitative flow information at a fixed point in time. Therefore, vessel leakage is not detectable by OCTA. Furthermore, exact automated segmentation of all diagnostically important intraretinal layers is of essence to avoid artifacts in the OCT angiograms of the respective layers. Consequently, exact segmentation necessitates sufficient system sensitivity, axial resolution, and contrast. Retinal blood flow on OCTA can be obscured by hemorrhage as this decreases the ability of light to penetrate into the deeper layers of the eye. Despite the rapid, tremendous commercial and clinical success of OCTA, some (at least relative) blood flow quantification will be needed in the near future. – Improved and reproducible quantitative OCTA is definitely also of significant clinical interest as is the correct visualization and quantification of choriocapillaris , , . Another important future clinical role enabled by ultrahigh speed swept sources will be wide-field OCTA for the detection of neovascularization of the disc and elsewhere, microaneurysms, changes of the foveal avascular zone, intraretinal microvascular abnormalities, and capillary non-perfusion. , This advancement of OCTA technology in clinical research will ultimately lead to enhancement of individualized management of diabetic retinopathy and prevention of visual impairment in patients with diabetes. Using the eye and especially the retina as a part of the central nervous system diagnostically as a window to the brain started in the late 1970s, and about 400 papers since then have covered diagnostic methods in the posterior pole of the eye for early diagnosis of brain diseases. An important prerequisite for successful OCTA-based diagnosis in neurodegenerative diseases and other clinical applications will be accurate and reproducible quantitative OCTA. Quantitative analysis of OCTA is essential to standardize objective interpretations of clinical outcomes. Indeed, a concerted effort has been put forth to understand how Alzheimer’s disease (AD) pathology may manifest in the retina as a means to assess the state of the AD brain. – OCTA has also been successfully evaluated as a tool to assess retinal changes in Parkinson’s disease and both schizophrenia and bipolar disorder.
Optophysiology/Optoretinography: Non-Invasive Detection of Intrinsic Optical Signals Modern medical diagnosis significantly benefits from extracting functional tissue information from structural imaging data (“structure–function correlation”). This is especially important in organs that cannot be biopsied, like the human retina. Retinal function has long been studied with psychophysical methods in humans, e.g., with electrophysiology and electroretinograms. Non-contact, depth-resolved, optical probing of retinal response to visual stimulation was introduced as optophysiology—an optical analog to electrophysiology. This method takes advantage of the fact that physiological changes in dark-adapted retinas caused by light stimulation can result in local variation of the tissue reflectivity. At that time, optophysiology could only be demonstrated in isolated rabbit retinas. Ophthalmic OCT technology back then was not sufficiently fast at longer wavelengths performing at sufficiently high sensitivity and resolution to be successfully applied in living animals or humans. A decade later, light-driven signals of photoreceptors in vivo could be measured. Visible light stimulation over a 200-fold intensity range caused correlated rod outer segment (OS) elongation and increased light scattering in wild-type mice, but not in mice lacking the rod G-protein alpha subunit, transducin (Gα(t)), revealing these responses to be triggered by phototransduction. The diurnal variation in rod OS length in mice was measured using optophysiology, being consistent with prior histological investigations demonstrating that rodent rod discs are phagocytosed by the RPE maximally over several hours around the time of normal light onset. The rate of recovery of rod OSs to baseline length before normal light onset was consistent with the hypothesis that disc membrane synthesis is fairly constant over the diurnal cycle . Fast intrinsic optical signal (IOS), which arises before light-evoked pupillary response, promises to be a unique biomarker for photoreceptor physiology for objective optoretinography with high resolution. In another study, depth-resolved optophysiology verified OS as the anatomic origin of fast photoreceptor-IOS. Dynamic IOS changes were primarily confined at OS boundaries connected with inner segment and RPE, supporting transient OS shrinkage due to phototransduction process as the mechanism of the fast photoreceptor-IOS response. Non-invasive, objective measurement of light-evoked, functional responses of human rods and cones, measured non-invasively using a synchronized adaptive optics OCT and scanning light ophthalmoscopy system have also been reported recently. Another recent study revealed that the onset of phototransduction is accompanied by a rapid ( < 5 ms ), nanometer-scale electromechanical deformation in individual human cone photoreceptors. Characterizing this biophysical phenomenon associated with phototransduction in vivo was enabled by high-speed phase-resolved optical LFOCT that allowed for sufficient spatiotemporal resolution to visualize the nanometer/millisecond-scale light-induced shape change in photoreceptors.
Visible Light OCT: Unprecedented Axial Resolution and Enhanced OCT Access to Absorption OCT in the visible wavelength range with unprecedented submicrometer axial resolution achieved by employing a photonic crystal fiber in combination with a sub-15 fs Titanium:sapphire laser was first demonstrated in the beginning of this millennium. , Visible light OCT theoretically provides higher axial resolution than NIR OCT for a given wavelength and bandwidth. To realize this potential in the human retina in vivo , the unique technical challenges of visible light OCT must be addressed: incorporating a grating light valve spatial light modulator spectral shaping stage to modify the source spectrum; developing a novel, Fourier transform-free, software axial motion tracking algorithm with fast, magnetically actuated stage to maintain near-optimal axial resolution and sensitivity in the presence of eye motion; and implementing spatially dependent numerical dispersion compensation for the first time in the human eye in vivo . Wavelength-dependent images of the outer retina suggest that, beyond merely improving the axial resolution, shorter wavelength visible light may also provide unique advantages for visualizing Bruch’s membrane (BM). Furthermore, it seems that shorter visible wavelengths improve the visualization of BM in pigmented eyes, where it is located behind a highly scattering layer of melanosomes in the RPE. Monte Carlo simulations of radiative transport suggest that, while absorption and scattering are higher at shorter wavelengths, detected multiply scattered light from the RPE is preferentially attenuated relative to detected backscattered light from BM. Using visible light OCT, accurate and robust non-invasive measurement of retinal oxygen metabolic rate ( rMRO 2 ) in rat eyes was demonstrated. Both oxygen delivery and rMRO 2 increased from the highly regulated retinal circulation under hypoxia. The increased oxygen extraction compensated for the deficient oxygen supply from the poorly regulated choroidal circulation. These results have the potential to reveal the fundamental role of oxygen metabolism in various retinal diseases such as age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma. Oximetry saturation sO 2 measurements were also recently extended to capillaries and investigated in all three retinal vascular plexuses by amplifying and extracting the spectroscopic signal from each capillary segment under the guidance of OCTA. Using this approach, capillary sO 2 in the retinal circulation in rats was measured. In vivo depth resolved human imaging of oxygenation in retinal capillaries was recently demonstrated. In addition, first visible light OCTA with a 100-kHz A-line rate for human retinal imaging was also demonstrated recently, enabling accurate localization of microvasculature down to the capillary level and thus enabling oximetry at vessels < 100 μ m in diameter. Microvascular hemoglobin oxygen saturation ( sO 2 ) at the feeding and draining vessels at the perifoveal region was demonstrated, allowing for future studies on the role of microvascular oxygen in various retinal pathologies . Another technique enabling OCT access to absorption is photothermal OCT, which monitors changes in the optical path length caused by the photothermal effect. Like in PAI in the photothermal effect, photons are absorbed by chromophores within a sample, causing a localized rise in temperature. Thermoelastic expansion caused by the photothermal effect generates isolated variations in the refractive index, which in turn generates a variation in the optical path length. The optical path length variations typically generated by the photothermal effect, often nanometer in scale, can be resolved with phase-sensitive OCT. This approach might be extremely attractive for non-destructive 3D molecular imaging deep ( ∼ 2 mm ) within biological samples with a sensitivity of 14 parts per million (weight/weight) nanoparticles in the sample. In addition, photothermal OCT could quantify changes in pigmentation that occur in retinal diseases. , In vivo photothermal OCT was also demonstrated for cross-sectional in human skin measurement with endogenous absorption agents. Recently, a swept source dual-wavelength photothermal OCT system was demonstrated for quantitative imaging of microvasculature oxygen saturation and measuring of microvasculature sO 2 levels in phantom blood vessels with a range of blood flow speeds (0 to 17 mm / s ).
Dynamic Contrast OCT Recently, an extremely powerful new contrast enhancing OCT extension was introduced. It employs a new endogenous approach to reveal subcellular metabolic contrast in fresh ex vivo tissues, taking advantage of the time dependence of FF OCT interferometric signals. This method reveals signals linked with local activity of the endogenous scattering elements that can reveal cells where other OCT-based techniques fail or need exogenous contrast agents. Using high-transverse resolution to image intracellular features, the time dependence to identify different dynamics at the millisecond scale on a wide range of organs in normal or pathological conditions is used. Dynamic contrast OCT has also been applied in freshly excised human esophageal and cervical biopsy samples. Depth-resolved dynamic contrast OCT images of intact tissue show that intracellular dynamics provides a new contrast mechanism that highlights subcellular morphology and activity in epithelial surface maturation patterns . This technique has also been used to combine static, dynamic, and fluorescence contrasts to achieve label-free high-resolution imaging of the living retina and anterior eye with temporal resolution from milliseconds to several hours, allowing for probing biological activity at subcellular scales inside 3D bulk tissue. By evaluating signal fluctuations, a significant contrast enhancement was demonstrated using TD FFOCT, which makes cellular and subcellular structures visible. The putative cause of the dynamic OCT signal is the site-dependent active motion of cellular structures in the submicrometer range, which provides histology-like contrast. In vivo dynamic contrast OCT was used to quantify layer-resolved microvascular blood flow and volume across the full depth of the mouse neocortex. Finally, speckle variations induced by intracellular motion in the urothelium were used as a dynamic contrast to segment the urothelium with only two sequential OCT images. This new method opens the possibility of tracking the distribution of the urothelial cells to identify the microinvasion of bladder tumors. This contrast may provide a new mechanism for OCT to diagnose the invasion of urothelial cancerous cells for the better staging of bladder cancer. Another interesting contrast enhancing OCT extension that gained a lot of attention recently is using the extraction of the optical attenuation coefficient, an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. With current studies showing attenuation coefficient analysis as a promising technique, further efforts in the development of methods to accurately extract the attenuation coefficient and to explore its potential use for more extensive clinical applications are desired.
Optical Coherence Elastography: Depth Resolved Optical Palpation An extremely promising extension of OCT is OCE. The original idea of elastography is not only to exploit the stiffness changes within soft tissue for diagnosis, much like a physician would during palpation, but also to exactly localize and quantify them. The capability of OCT to give 3D insight into tissue is used to visualize the reaction of a sample to a mechanical force. Multiple methods for deriving this reaction from the OCT data have been presented, e.g., image cross correlation, feature or speckle tracking, optical flow, combinations thereof, and phase difference analysis. From this reaction, the underlying mechanical tissue parameters can be obtained and used for diagnosis. The technology first emerged in US imaging, where systems capable of elastography have been commercially available since the 2000s. Elastography in general is a relative straight forward add-on to OCT, enabling biomechanical contrast at a slightly increased imaging time and data processing complexity. Although a lot of promising approaches and methods utilizing OCE have been published, two major applications are at the moment competing for clinical in vivo diagnosis . In this sense, the ophthalmic application of OCE is the most advanced, likely because it could build upon decades of OCT experience in this field, which already addressed issues like motion correction and speed. The only novel aspect from an engineering perspective is mechanical loading, which has to be performed cautiously and preferably contactless. Proposed solutions rage from contact shaker excitation, over microscale air-pulses, and acoustic radiation pulses , to heartbeat driven tissue deformation. , De Stefano et al. demonstrated the feasibility of OCE for identification of keratoconic corneas in humans in vivo using a dynamic compressional approach with intensity-based speckle tracking. Since the compression is applied via a motorized stage, direct contact to the cornea is needed, but quantitative analysis also is enabled. In May 2020, Lan et al. quantified the effects of respiration and heartbeat on patient eye motion as a source of perturbation for OCE in vivo and mentioned the idea that this perturbation could also be used as a passive loading method. Only a month later, Nair et al. gave another indication for the feasibility of non-contact heartbeat ophthalmic OCE in an ex vivo porcine eye model with controlled intraocular pressure changes. In January 2021, Nair et al. achieved heartbeat OCE in an in vivo rabbit model, but the method was not completely non-contact as a glass imaging window was used to minimize bulk motion. The heart pulse compressed the corneal tissue against this imaging window, resulting in the desired displacement. OCE data were acquired as multiple 2D B-scans at the same position, which were synchronized with the rabbit’s heartbeat later in postprocessing. The resulting 2D strain maps clearly show the difference between compression and relaxation induced by the pulse. In addition, they were able to differentiate between an untreated cornea and a cornea stiffened via the Dresden protocol. Although these are already very promising first results, some challenges for clinical in vivo patient imaging still remain to be addressed. Since pulse waves travel at a limited speed, they affect different regions in the FOV at different points in time, which can lead to underestimation of the resulting strain and is a challenge for synchronization. For clinical diagnosis, en face images and 3D stiffness maps are much more useful than single B-scans. 3D imaging would not only highly increase imaging time but also make the synchronization even more complicated. One also has to be aware that, without the possibility of quantifying the pressure perceived by the investigated tissue, only qualitative OCE results can be expected and quantifying the pressure excited by a heartbeat at every point in the FOV seems impossible at this point in time. However, the potential of ophthalmic OCE for clinical application is huge. The feasibility for diagnosing keratoconus has been shown in the examples above, but also corneal dystrophy or corneal ectasia due to surgical complications are obvious topics in which OCE can deliver fast and uncomplicated diagnosis, as well as in the diagnosis of AMD in which early diagnosis is especially important, as presented by Qian et al. When it comes to the field of cancer detection and diagnosis, current literature focuses on biopsy images as proof of concept. Not only is cancer often accompanied by significant changes in stiffness, but also the shape of the outlines of cancer has diagnostic potential. A good example is given by Kennedy et al., who showed that cancer margin detection with OCE yields a 24% higher sensitivity than with OCT only. Multiple tumor types have been investigated, and OCE proved to be an accurate predictor of malignancy for all of them. A phase-sensitive, quasi-static compression OCE system was used. The future of OCE lies in intraoperative in vivo imaging for determining tumor margins of cancerous tissue to be removed, requiring not only high-speed OCT imaging to minimize the influence of motion artifacts but also high-speed processing to enable real-time view. Depending on the chosen biomechanical model and processing approach, this task requires expensive hardware and well-versed software implementation. Another challenge to keep in mind is OCE’s vulnerability to laser and system instabilities, which are even more difficult to control in a surgical environment. Nonetheless, surgical applications of OCE are close. Plekhanov et al. presented a phase-sensitive, quasi-static compressional OCE method that is capable of segmenting cancerous regions in a mouse model in vivo . They were able to differentiate between viable, dystrophic, and necrotic tumor cells as well as edema zones and validated their findings via comparison with histological results. A 9-day study, comparing the effect of two different chemotherapeutics with untreated control, was performed as well. In a similar study, the combination of OCE with OCTA was shown to be an easy way to add functional information, improving the quality of chemotherapeutic treatment efficiency studies. As can be seen in the aforementioned examples, quasi-static compression OCE, mostly phase-sensitive with some sort of compliance layer as stress sensor, is currently the most advanced OCE method. In the last few years, other approaches rose to the horizon of feasibility, e.g., vibrational OCE, , which uses OCT to record the reaction of a sample to a variation of vibration frequencies. With this, a 3D resonant frequency map of the sample can be generated and viscoelastic behavior can be investigated. Another proposed application, although more focused on usage in studies than for clinical diagnosis, is in intravascular OCE. , Since atherosclerosis is the leading cause of human death worldwide, continued effort is put into understanding the generation, buildup, and rupture of intravascular plaques. Overall OCE has come far, and routine clinical usage especially in the ophthalmic field is to be expected in the next few years. The next steps to this goal are achieving faster imaging and data processing and even better motion correction. Although some OCE experts and clinicians argue that there is no need for quantifying tissue stiffness, as long as there is qualitative biomechanical contrast, in the long term it might make a lot of clinical sense to find a quantitative stiffness atlas, which allows for diagnostic guidance.
OCT and Deep Learning, Neural Networks, and Artificial Intelligence Since its introduction in 1959, AI technology has evolved rapidly and helped benefit research, industry, and medicine. The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using telehealth supported by digital innovations. These digital innovations include AI, 5th generation (5G) telecommunication networks, and the Internet of Things (IoT), which create an interdependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Deep learning, as a process of AI, is used in radiology, ophthalmology, and in increasingly more other medical fields for data analysis, segmentation, automated diagnosis, and possible prognosis. The association of deep learning and OCT technologies has proven reliable, and about 400 papers have been published in this field, with more than half of them published in the last 3 years. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Telehealth and AI provide synchronous solutions to challenges faced by ophthalmologists and healthcare providers worldwide. AI definitely has potential and will be part of the decision-making progress regarding the scientific investigation, diagnosis, and therapeutic management. Hence, AI-enhanced OCT has recently been used for the detection of retinal diseases and improving the diagnostic performance of the eye’s posterior segment diseases – . In addition to AI-enhanced OCT application enabling improved OCT image quality or enhancing OCT segmentation, functional prediction of organs from morphological OCT data will be of significant future clinical interest. Several recent studies have reported high-diagnostic performances of AI models. However, significant methodological challenges still exist in applying these models in real-world clinical practice. Lack of large image datasets from multiple OCT devices, non-standardized imaging or postprocessing protocols between devices, limited graphics processing unit capabilities for exploiting 3D features, and inconsistency in the reporting metrics are major hurdles in enabling AI for OCT analyses. , Furthermore, machine learning and AI for health must be reproducible to ensure reliable clinical use. Recent evaluations found that machine learning for health fared poorly compared with other areas regarding reproducibility metrics, such as dataset and code accessibility. ,
Miniaturized, Cost-Effective, and Portable OCT: OCT on a Chip, Home-OCT, and Self-OCT Most commercial OCT devices currently have a footprint of ∼ 1 2 m and cost up to USD 180.000, which usually inhibits its widespread availability and limits usage of OCT to clinics or large ophthalmic practices. In a typical diagnostic ophthalmic OCT setting, the patient has to remain in an upright position with his head placed on a chin rest and fixating on a target. Certain retinal diseases such as AMD, glaucoma, or diabetic retinopathy require a regular screening to monitor the disease and schedule or monitor therapy. These diseases normally affect elderly immobile or even bedridden patients for whom going to the hospital or practices for OCT diagnosis is challenging. For diagnosis of retinopathy of prematurity, a disease affecting newborn premature infants as well as for younger children in general, current commercial OCT devices are also not suitable. The same holds for space-related neuro-ocular syndrome describing ocular pathological changes that occur during space flight and exposure to microgravity, respectively. Commercially available ophthalmic OCT technology has been used in the past, but it is too bulky and time-consuming to be used in outer space. Hence, light weighted, cost-effective, and compact (ideally handheld) OCT devices would be required for early diagnosis and proper therapy management of all of the abovementioned retinal diseases. It is noteworthy that recent market reports predict (for the first time in such reports) separate compound annual growth rates for handheld and integrated OCT systems. Interestingly, compound annual growth rates (CAGR) is 8.9% for the next 7 years despite COVID-19 and for OCT in ophthalmology globally about 5% to 7% depending on the region. In addition, “home-OCT” or “self-OCT” are terms that have evolved to describe the need for a compact, easy to use, and cost-effective OCT device that could be used unsupervised by patients at home or astronauts in space. The term “miniaturized OCT” therefore describes more than solely the reduction of size but also a reduction of costs. An increase of flexibility of OCT devices is ultimately a highly desirable goal for extending the application and availability of OCT and exploring potential new markets for OCT. Point-of-care diagnostics, home-based disease monitoring, extension of medical care in third-world countries and low-recourse settings, and even extra-terrestrial health care are application fields that would benefit from a compact, cost-effective, mobile, handheld, and even patient operated OCT system . Beyond ophthalmologic care, there is a strong need for flexible and compact OCT devices as well. Dermatologic care, oral cavity, or inner ear imaging are only a few examples of OCT applications that require at least a flexible (handheld) probe. As a broad screening device, a general practitioner might benefit from an OCT device that is capable of imaging several areas of the human body. This could be achieved by exchangeable sample arm adapters as recently proposed, a system capable of imaging ophthalmic, inner ear, and other tissues by exchangeable sample arm adapters. Currently, there are three promising approaches to miniaturizing OCT. 1. The development of flexible handheld probes for OCT, being motivated by immobile patients or simply the anatomical nature of the sample location. To date, they come with a mobile cart with a footprint of ∼ 1 m 2 . 2. The use of already available off-the-shelf micro-optical components to miniaturize OCT systems by smart and compact packaging. 3. Finally, PIC as a platform that has its origin in telecommunications. Using the same fabrication plants as those for CMOS electronics to grow these chips, PICs guide and manipulate light just as commonly used fiber-based systems but can be produced at a significant smaller size as well as costs in addition to be maintenance free. The need for a mobile OCT device has been partly met by industry as devices are equipped with mobile carts, which permit mobility within the clinics. Some companies offer handheld probe solutions for more flexibility in terms of bringing the scanning probe to the patient. – However, these systems are still rather bulky, the handheld probes are fairly heavy (1.5 to 2.2 kg), and the weight of these systems ( ∼ 30 kg ) challenge easy mobility but especially portability. Demonstrations of (partly) miniaturized OCT systems in research have been accomplished in ophthalmic care using handheld probes, , – off-the-shelf micro-optical components , , or PICs , , for dermatologic care using handheld probes, – compact packaging of off-the-shelf components, PICs, , – and handheld probes for oral and for inner ear – imaging. The usage of off-the-shelf microcomponents seems to be the most mature technique for miniaturized OCT at the moment. Very compact and mobile OCT systems with acceptable imaging performance have been accomplished. , , Historically, many medical applications have benefited from the development of components for telecom and entertainment applications, respectively. The miniaturization of OCT has benefited from these developments as well. MEMS mirrors were originally developed in smart phones and CCDs that were produced for multimedia, smartphones, and entertainment; they are components that are produced at scale and can be adapted to the needs of OCT applications. Likewise, the telecom-driven development of PICs supports the miniaturization of OCT. With the increasing need for more powerful telecom and entertainment devices, the industry invested in alternatives for electronical data transfer and manipulation. This technology is still in its infancy, and the first in vivo human retinal imaging was shown in . Another example is a battery driven, tablet-like OCT system for dermatologic application that has been commercialized. These are promising results for the future of miniaturized OCT using PICs. In addition to its small form factor, multiple functional photonic building blocks can be printed on a single chip, which opens up new and/or easier realizable possibilities for OCT system designs, such as multichannel sample arm configuration/parallelized imaging as proposed recently. Several sample arm paths could scan the sample in parallel, which would increase the effective A-scan rate without sacrificing imaging performance. Detection and postprocessing electronics can be co-integrated on the same chip, retaining a small form factor of the full OCT engine. Optical FPGAs, i.e., programmable PICs , are an exciting research field that could establish a universal OCT engine, programmable to specific needs of an OCT system. With the outbreak of the Covid-19 pandemic in 2020 and the need to reduce social interaction, non-urgent medical appointments were cancelled and postponed. To counteract the reduced medical care, the use of telemedicine was rapidly incorporated, which reduced costs and was more effective and therefore has the potential to become the “new normal.” , Miniaturized, low-cost, mobile, and automated OCT will play a significant role in the successful adaption toward increased use and acceptance of telemedicine. However, there are many aspects that need to be considered and solved, regardless of the technique used to miniaturize OCT. Weight and size have to be light and small enough for a patient to transport. The device needs to be simple and easy to use, comfortable for the patient, effectively performing, and secure. A secure data transfer has to be ensured and a timely diagnosis/feedback to the patient has to be guaranteed for optimum willingness to use the device. Audio instructions, automated sample alignment, and optimized ergonomic design can help increase the patient compliance. AI , and cloud-based computing are promising platforms to increase regular monitoring and simultaneously reduce the need for computationally intensive and expensive equipment. At the same time, these might relax power consumption of the device, which could enable battery driven devices, which in turn increases flexibility and mobility even further. In conclusion, the technology of miniaturized OCT is still young and foreshadows an exciting future of more widespread, mainstream, automated, intelligent, and smart point-of-care devices for early detection of pathological changes.
Clinical Translation of Optical Coherence Tomography OCT has revolutionized ophthalmology over the past two to three decades. Its unique ability to resolve the retina’s layered structure was a gamechanger for diagnosing many retinal diseases and monitoring their treatment. Although clinical benefit could also be demonstrated early on in other medical fields such as cardiology, dermatology, and endoscopy, its widespread adoption in these fields is still lacking. This is mostly due to OCT’s lower benefit/cost ratio in these fields and competition with other, often much cheaper, imaging modalities. With OCT becoming cheaper over time, enabled by technological advancements like photonic integration and the availability of cheaper swept-source lasers, we expect OCT also to become more prevalent in the clinical routine in many fields outside ophthalmology and outside the traditional clinical setting. AI algorithms for image quality enhancements, self-alignment, and clinical decision support will enable a new level of usability, much more comparable to consumer electronic devices than sophisticated imaging devices that required expert operators. This will pave the way for OCT systems out of medical specialist’s offices to general practitioners, pharmacies, and even patients’ homes. This trend has the potential to lower health care costs in developed countries but is foremost going to have a huge impact on the quality of life of immobile patients, patients in rural regions, or low-resource countries. At the same time, we expect OCT’s performance and application to continue to expand at a rapid rate. OCTA was most likely only the first functional extension that boosted the clinical value of OCT. MEMS tunable VCSELs are going to enable commercial OCT systems at hundreds of kHz to MHz A-scan rates. Such speeds favor additional functional methods in vivo , such as, for example, the non-invasive, objective measurement of retinal function. MHz speeds are further going to enable the live observation of dynamic processes, making it a great visualization tool for ophthalmic surgery. Such a comprehensive live 3D view of the surgical scene will help in developing robot assisted surgery and will eventually even make autonomous robotic surgery a reality. Once the “speed-limitations” of single-point scanning OCT are reached, we expect a shift to parallel OCT configurations. LFOCT has the potential to become the implementation of choice due to its advantages with respect to laser safety, ability to suppress multiply scattered light, and availability of components. Endoscopic OCT may be another area that will greatly benefit from the miniaturization of OCT. It will eventually allow for movement away from traditional endoscopes to self-contained capsular devices that will be swallowed by the patient and collect and transmit data to external devices autonomously. On the other hand, the combination of OCT with other imaging modalities still has to prove its clinical added value to justify the increased complexity and cost. Closest to clinical translation might be the combination of OCT with complementary spectroscopy methods such as infrared spectroscopy used in intravascular probes or RS. Fast translation of new developments to their commercial exploitation and ultimately to the benefit of patients critically depends on the regulatory ecosystem. 7.1 Medical Device Regulations Europe currently sees the transition from the medical device directives to the medical device regulation as a need to be implemented as national law by each member state. They provide a tight framework not only for medical device industries but also for academic institutions, affecting research and development of new technologies already at its very roots. Clearly, regulatory approval is essentially needed for safe applications on human beings. Academic entities are therefore now challenged to allocate sufficient resources and to build supporting structures to enable internationally competitive research to harmonize the high flexibility needed at early research stages with regulatory demands. Novel technologies need to be convincing enough for industry to pick them up for further development, which needs already substantive validation in a clinical setting with all of the required regulatory hurdles. Only with proper support can a widening of the “valley of depth” be avoided. 7.2 Standardization A translation of promising OCT technologies to market standardization is an important topic as discussed by Waterhouse et al. For example, the question of appropriate laser power levels for internal organ tissue is not yet covered by laser safety standards. The current assumption is that all internal organs respond similar to the laser exposure. However, already the tissue texture leaves the impression of major differences between the tissue types. With a general standardization on given performance parameters, for instance, the relation to an appropriate standard would be possible at an early stage of translational research. This aims furthermore at the repeatability and reproducibility within multicentral clinical trials. Assessment of performance parameters at an early development stage is difficult because little or no validated ex vivo models are present to benchmark performances of a newly developed device. Most of these arguments merge into the argument of cost-effectiveness during research and development. Having standardized benchmarking steps and milestones alongside the development processes in academia or industry may save resources. Translational research actually is facing more than one “valley of death:” the first one arises from translating laboratory systems and findings to the patient bedside and the second one occurs during the attempt to bring the gained knowledge into clinical practice and health decision-making procedures. With clear standards for benchmarking, there might be a higher chance for seeding product development and streamlining translational research to finally appear next to the patient.
Medical Device Regulations Europe currently sees the transition from the medical device directives to the medical device regulation as a need to be implemented as national law by each member state. They provide a tight framework not only for medical device industries but also for academic institutions, affecting research and development of new technologies already at its very roots. Clearly, regulatory approval is essentially needed for safe applications on human beings. Academic entities are therefore now challenged to allocate sufficient resources and to build supporting structures to enable internationally competitive research to harmonize the high flexibility needed at early research stages with regulatory demands. Novel technologies need to be convincing enough for industry to pick them up for further development, which needs already substantive validation in a clinical setting with all of the required regulatory hurdles. Only with proper support can a widening of the “valley of depth” be avoided.
Standardization A translation of promising OCT technologies to market standardization is an important topic as discussed by Waterhouse et al. For example, the question of appropriate laser power levels for internal organ tissue is not yet covered by laser safety standards. The current assumption is that all internal organs respond similar to the laser exposure. However, already the tissue texture leaves the impression of major differences between the tissue types. With a general standardization on given performance parameters, for instance, the relation to an appropriate standard would be possible at an early stage of translational research. This aims furthermore at the repeatability and reproducibility within multicentral clinical trials. Assessment of performance parameters at an early development stage is difficult because little or no validated ex vivo models are present to benchmark performances of a newly developed device. Most of these arguments merge into the argument of cost-effectiveness during research and development. Having standardized benchmarking steps and milestones alongside the development processes in academia or industry may save resources. Translational research actually is facing more than one “valley of death:” the first one arises from translating laboratory systems and findings to the patient bedside and the second one occurs during the attempt to bring the gained knowledge into clinical practice and health decision-making procedures. With clear standards for benchmarking, there might be a higher chance for seeding product development and streamlining translational research to finally appear next to the patient.
Conclusion OCT has existed for 30 years and is definitely here to stay, to keep scientists and engineers busy, and to significantly support clinicians and life scientists in their daily routine work. It is absolutely noteworthy that OCT has not been completely exploited and has considerable growth potential. This is especially important for younger scientists choosing their scientific topic and academic or industrial career field. From a scientific point of view, the last three decades have shown a continuous increase of scientific output. With novel disruptive technologies on the horizon perfectly matching those needed by OCT, it is very unlikely that this will change in the near future. Extrapolating publishing performance of the last 20 years, a saturation of yearly publication output at very high level of about 9500 can be expected in around 10 years from now—if ever. From an industrial point of view, recent market reports indicate a global market perspective of about USD 1.5 billion in 2023. It is noteworthy that these recent market reports predict (for the first time in such reports) separate compound annual growth rates for handheld and integrated OCT system. Interestingly, CAGR is 8.9% for the next 7 years despite COVID-19 and for OCT in ophthalmology globally about 5% to 7% depending on the region. As of now, miniaturized OCT is one of the most prominent OCT market trends picking up pace in global industry. Rising interest in miniature, low-cost portable OCT indicates the huge opportunity in the years to come, with miniaturization and improvements in device designing and packaging currently being the key focus areas. As a result, it is expected that the handheld OCT devices segment can make significant progress in the years ahead, entering new larger unexploited markets for OCT. Another important key-technological prerequisite for not only miniaturized, portable OCT but also for nearly all other OCT applications is imaging speed. Cost-effective swept source laser technology and/or efficient parallelized scanning schemes (multiple single beams, line-field, and full-field) will enable OCT A-scan rates beyond 1 MHz in the very near future as a standard OCT specification. This will be especially essential for handheld OCT to avoid motion artifacts, will enable large FOVs (e.g., wide-field OCT and OCTA, high-speed catheters/capsules), will permit the detection of fast signals (e.g., IOSs), and will foster 4D OCT for intraoperative, surgical guidance or high-speed imaging in life sciences. It will also enable proper sampling, especially with increasing FOVs and improved transverse OCT resolution. With the recent successful initiation of visible light OCT, the future will not reveal significantly new additional wavelength regions for OCT. The UV and MID-IR regions are theoretically interesting in terms of resolution and absorption but are inherently challenging in terms of light sources, optics, and detection and hence may not be widely translated to (bio)medical and clinical applications. The momentary successful trend in clinical imaging to combine complementary imaging modalities to get “the best of both/all worlds” will—regarding multimodal OCT setups—continue and significantly increase—not only at the microscopy level but also at the endoscopy/optical needle level. Multimodal optical imaging incorporating OCT will especially compensate for the deficits of OCT (metabolism, molecular sensitivity, penetration depth, and loss of contrast). OCT will act like a GPS by prescreening the tissue at a wide FOV with microscopic resolution and then other techniques will zoom in at the subcellular or molecular level for enabling morpho-molecular or morpho-metabolic tissue information. OCT’s top (bio)medical application will stay in ophthalmology with cardiology following. Oncologic diagnosis in different organs (e.g., skin, GI tract, and others) will increase due to multimodal imaging approaches. The future will also see improved microscopic OCT performance due to speed, multimodality, and enhanced contrast. This improved microscopic OCT performance will also foster intraoperative OCT guidance—especially in ophthalmology and neurosurgery. On the other hand, a lack of favorable medical reimbursement schemes and limited clinical data are top deterrents in the global market for OCT. From a technological perspective, SD OCT will, for the near future, stay dominant mainly in the 800-nm wavelength region (in addition to the visible light OCT segment) because of the availability of mature cost-effective light source and detector technology—enabling high resolution with moderate optical bandwidths and good contrast. From a perspective point of view SS OCT should be the dominant choice for years. This will only take place if easy to use, cost-effective swept sources that do not shift complexity into detection will be available. Functional technologies are always much more challenging than pure morphology-based techniques. Successful future contrast enhancing OCT extensions must be technologically simple and easy to interpret and must have significant realistic clinical impact. OCTA is an exquisite example of providing label-free perfusion information acting as a non-invasive angiography technique. Manual palpation is one of the first diagnostic techniques in mankind—hence OCE might be successful in the near future as an optical analog. When it comes to correlated tissue structure and function optophysiology/optoretinography has huge diagnostic potential due to the retina being easily optically accessible, performing non-invasive detection of IOSs, and providing access to the brain. The future might also enable the establishment of new diagnostic biomarkers empowered by depth resolved tissue contrast due to dynamic contrast OCT or quantification of tissue attenuation. With either, the future of OCT and in general of biophotonics is bright due to numerous upcoming disruptive cost-effective technologies that will enable industry and academia to continuously improve the performance and hence diagnostic capability of existing optical techniques or to establish new ones.
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Diagnostic Accuracy of Immunohistochemistry for HER2-Positive Breast Cancer | 0089618f-7fef-4d3a-94c8-279170ff0163 | 10909106 | Anatomy[mh] | Breast cancer is the most frequent female malignancy in the world, and also in Thailand. This cancer is the leading cause of death, and a significant economic and social concern. In Thailand in 2020, there will be 22,158 new breast cancer diagnoses and 8,266 deaths (Arnold et al., 2022). Despite the great efficacy of screening and early detection methods such as mammograms and breast self-examination in Thailand, the prevalence of breast cancer has been gradually growing (Lakha et al., 2020). Furthermore, 10% to 30% of all breast cancer cases have HER2 protein overexpression or gene amplification (Iqbal and Iqbal, 2014). The human epidermal growth factor receptor (HER2), also known as HER2/neu, is one of the epidermal growth factor receptors (ErbB) tyrosine kinase receptors (Type I tyrosine kinase receptors). This gene is situated at 17q12 on chromosome 17 (Krishnamurti and Silverman, 2014). HER2 is an oncogene that has a role in cell proliferation and differentiation (Iqbal and Iqbal, 2014). It was involved in the pathogenesis of breast cancer (Ishikawa et al., 2014). HER2 amplification and/or overexpression in breast cancer patients related to aggressive behavior in breast cancer patients, including, poor prognosis, a short disease-free period, and a short survival period (Burstein, 2005; Wang et al., 2015; Cong et al., 2020). In Thailand, the HER2 status of all breast cancer cases will be evaluated before receiving therapy. The evaluation of HER2/neu involves employing two distinct methods: immunohistochemistry (IHC) to detect protein expression, and fluorescence in situ hybridization (FISH) or dual in situ hybridization (DISH) to measure gene amplification (Gordian-Arroyo et al., 2019). The IHC scored membrane HER2 level as 1+, 2+ and 3+ whereas the ISH measured HER2 amplification as positive and negative. Both approaches followed the 2018 recommendations of the American Society of Clinical Oncologists and College of American Pathologists (ASCO/CAP) (Gordian-Arroyo et al., 2019). In cases of HER2 amplification positivity, the National Health Society of Thailand (NHSO) recommends a targeted therapy regimen including anti-HER2 family medications such as Pertuzumab and Trastuzumab (Lewis Phillips et al., 2008; Gianni et al., 2011; Higgins and Baselga, 2011; Den Hollander et al., 2013; Doval et al., 2021). In practice, all patients must first be screened for IHC. In the case of IHC 2+ or 3+, DISH will be done. Since IHC is cheap, quicker, and simpler, ISH is twenty times more complicated, time-consuming, and costly. In situations where there is a lack of ISH confirmation, as often found in developing countries, the results can be enhanced by exclusively depending on IHC. Consequently, this study aimed to determine the concordance rates between IHC scores 2+ and 3+ and HER2 gene amplification. The findings revealed that IHC techniques with a score of 3+ demonstrate comparable results to HER2 amplification, suggesting their potential utility alone without an ISH result.
Sample Recruitment The research utilized formalin-fixed paraffin-embedded (FFPE) tissue blocks obtained from breast cancer tumor cases that had undergone both HER2 IHC and HER2 DISH procedures. These FFPE samples were derived from biopsy specimens taken during the preoperative treatment stage of patients diagnosed with breast cancer. The patients included in the study had primary tumors and had not undergone any previous radiation therapy or chemotherapy. Exclusion criteria were applied for cases with low amounts of pathologic tissue and a lack of clinical data. The diagnosis of invasive ductal carcinoma, histological subtype, estrogen receptor (ER), and progesterone receptor (PR) status were confirmed by KS and SC. display examples of hematoxylin and eosin (H&E) staining. Clinical data were obtained from the patients’ clinical chart records, and all the relevant clinical and histological information is presented in . A total of 510 breast cancer cases were initially recruited from the Department of Pathology at Rajavithi Hospital in Bangkok, Thailand, between January 1st, 2022, and May 31st, 2023. After careful selection, 156 breast cancer tissue samples were included for analysis. This hospital-based study protocol was approved by the Institutional Review Board of Rajavithi in Bangkok, Thailand (IRB no. 009/2566), and written informed consent was obtained from all participating patients. IHC For IHC, the HER2/neu primary antibodies (4B5) were used. The FFPE blocks were cut into sections with a thickness of 3 µm. The slides were then stained with the HER2/neu (4B5) primary monoclonal antibody (6 µg/100 µl, Ventana Medical Systems, catalog number 790-2991) using an automated slide strainer, the BenchMark Ultra (Ventana Medical Systems, Inc., Arizona, United States). The staining process was conducted at 37°C for 16 minutes. The detection of the HER2 protein was performed using the Ultraview Universal DAB Detection Kit (Ventana-Roche Diagnostics, Meylan, France). Subsequently, the slides were counterstained with Hematoxylin II® (ab245880, Abcam, United Kingdom) for 8 minutes and Bluing Reagent® for 4 minutes (BR-OT, Biogenost, Croatia, EU). To ensure the accuracy and validity of the staining procedure, positive controls consisting of breast tissue samples known to be HER2-positive were included in each examination. The staining scores were determined by evaluating membrane staining in tumor cells. Based on the 2018 ASCO/CAP criteria, the IHC scores were classified as negative (score of 0 or 1+), equivocal (score of 2+), or positive (score of 3+) (Gordian-Arroyo et al., 2019). KS and SC conducted blind evaluations and provided scores. illustrates an example of an IHC score of 3+, while demonstrates an example of an IHC score of 2+. DISH The FFPE blocks were cut into sections with a thickness of 3 mm. The HER2 gene amplification was determined using the inform HER2 DISH DNA probed cocktail assay (catalog number 800-6043) on the automated VENTANA BenchMark ULTRA platform (Ventana Medical Systems Inc., Tucson, AZ, USA). The procedure involved several steps, including deparaffinization, tissue adjustment, proteinase treatment, and DNA denaturation by heating at 80°C for 8 minutes. Subsequently, the slides were incubated with the VENTANA Silver ISH DNP Detection Kit for HER2 copies (black color) for 48 minutes, followed by the VENTANA Red ISH DIG Detection Kit for chromosome 17 (red color) for 56 minutes. Finally, the slides were counterstained with Hematoxylin II® (ab245880, Abcam, United Kingdom) for 8 minutes and Bluing Reagent® (BR-OT, Biogenost, Croatia, EU) for 8 minutes to enhance visibility and provide contrast. The DISH analysis was conducted by ST and KS under a microscope. In (DISH positive) and 1F (DISH negative), the red signal represents the probe targeting the chromosome 17 centromere (CEP17), serving as an internal control. The black signal corresponds to the HER2 probe on chromosome 17. The results were evaluated based on the ratio of HER2 signals to CEP17 signals and the average HER2 copy number in the cancer cells, following the criteria set by ASCO/CAP (Gordian-Arroyo et al., 2019). HER2 gene amplification was classified as “positive” if the HER2/CEP17 signal count ratio was 2.0 or greater, or if the ratio was less than 2.0 but the average number of HER2 signals per cell was 6.0 or higher. A score of “equivocal” was assigned if the HER2/CEP17 signal count ratio was less than 2.0, and the average number of HER2 signals per cell ranged from 4.0 to less than 6.0. A score of “negative” was given if the HER2/CEP17 signal count ratio was less than 2.0, and the average number of HER2 signals per cell was less than 4.0 (Nishimura et al., 2016). KS and SC carried out blind evaluations and provided scores. Statistics Analyses The statistical analysis was conducted using version 22.0 of the SPSS software (IBM Corp., Armonk, N.Y., USA). The evaluation of the diagnostic test for IHC positivity (score of 3+) was performed using HER2 amplification as a gold standard, following the 2018 ASCO/CAP guidelines. With a 95% confidence interval, the following parameters were calculated: sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) to measure the diagnostic test’s accuracy and reliability.
Clinical Characteristics A total of 510 breast cancer carcinoma tissue samples obtained from Rajavithi Hospital in Bangkok, Thailand, underwent HER2 IHC testing. Among these samples, only those with HER2 IHC scores of 2+ and 3+ were selected to undergo further investigation using DISH. Ultimately, 156 cases met the criteria and were included for further analysis. Out of the 156 cases, 58 samples had an equivocal IHC score of 2+ (indicating equivocal HER2 protein expression), while 98 samples showed a positive IHC score of 3+ (indicating strong HER2 protein expression). These samples were chosen for further investigation, suggesting a focus on cases with significant or uncertain levels of HER2 protein expression for subsequent analysis using DISH. presents a summary of the clinical and pathological findings from the patient cohort. A total of 156 Thai patients diagnosed with breast cancer participated in this study. The patients’ median age was 54 years, with an interquartile range (IQR) of 45 to 63 years. Lesions were located on the right side in 45.5% of cases and on the left side in 54.4% of cases. The median tumor size was 3 cm, with an IQR of 1.8 to 4.5 cm. Concerning histological subtypes, the majority (91%) of cases were classified as invasive ductal carcinoma. Histological grading revealed that grade 2 accounted for the largest proportion (37.8%), followed closely by grade 3 (39.7%), and grade 1 (4.49%). In terms of receptor status, the distribution of ER and PR was as follows: ER+PR+ (44.2%), ER-PR- (34%), ER+PR- (16%), and ER-PR+ (5.8%). HER2 IHC and DISH results A total of 510 cases of invasive ductal carcinoma were examined by IHC. Among them, 58 cases were classified as HER2 IHC 2+, and 98 cases were categorized as HER2 IHC 3+. This distribution is illustrated in , representing HER2 IHC equivocal (score 2+) and HER2 IHC positive (score 3+) cases, respectively. Subsequently, the 156 cases underwent DISH analysis, with the results indicating the average HER2 copy number according to the ASCO/CAP 2018 criteria. Following this analysis, 48 cases were categorized as having positive HER2 amplification, while 108 cases showed negative HER2 amplification. These categories are visualized in , representing positive and negative HER2 amplification, respectively. To provide a contextual visualization, present the associated H&E stain images of the cases being discussed. Diagnostic value of HER2 IHC We used HER2 amplification from the ASCO/CAP 2018 guidelines as a gold standard. There are 156 cases in total, of which 95 are true positive (HER2 IHC3+/positive HER2 amplification), 45 are true negative (HER2 IHC2+/negative HER2 amplification), three are false positive (HER2 IHC3+/negative HER2 amplification), and thirteen are false negative (HER2 IHC2+/positive HER2 amplification). After calculating the diagnostic test for the HER2 IHC method, presents all diagnostic values. The sensitivity, specificity, positive predictive values, negative predictive values, and likelihood ratio positive were very high (87.06%, 93.75%, 77.59%, 96.94%, and 14.07, respectively). In contrast, the likelihood ratio negative was very low (0.13), indicating a strong capability to use HER2 IHC as a screening and diagnostic test. Overall, the accuracy of HER2 IHC in diagnosing HER2 amplification was also high (89.74%), suggesting that we can use the IHC technique as a comparable alternative to DISH to diagnose HER2 amplification. When examining subgroup criteria such as age, tumor laterality, tumor size, histological subtype, histological grade, ER, and PR statuses, the IHC HER2 technique demonstrates remarkable effectiveness in terms of sensitivity and specificity, ranging from 75% to 100% across all subgroup analyses . Moreover, the IHC HER2 approach has a very high efficiency, especially in cases of metastatic breast cancer, with 96 % sensitivity and 95 % specificity. Following the likelihood ratio calculation, the HER2 IHC screening was employed to estimate the probability of the individual having the HER2 amplification case. For HER 2 IHC score 3+, the posterior probability of DISH positivity is 97% (with a 95% confidence interval of 91% to 99%). On the other hand, for HER2 IHC score 2+, the posterior probability of DISH positivity is 23% (with a 95% confidence interval of 15% to 32%), as illustrated in .
IHC assesses the presence of the HER2 protein on tumor cell surfaces. This cost-effective method is readily available in local pathology labs. However, it has certain limitations, including factors influencing results, subjective interpretation, and a notable false positive rate (Pauletti et al., 2000; Tubbs et al., 2001; De Matos et al., 2010). Conversely, FISH or DISH differentiates HER2 copy counts by employing fluorescent-labeled oligonucleotide probes that adhere to precise DNA sections. This genetic methodology yields dependable outcomes with reduced susceptibility to discrepancies among observers. Nonetheless, it constitutes a fee-based analysis and currently entails notable expenses. Furthermore, the turnaround time for results is longer in contrast to IHC. Currently, in Thailand, targeted therapies like Trastuzumab are employed for treating breast cancer patients. To be eligible for such therapies, patients must have an equivocal (score 2+) or positive (score 3+) HER 2 tests through IHC, which should be confirmed by an ISH test like FISH or DISH with a positive outcome. One limitation of this study is that the IHC scores for HER2 can exhibit variability across different laboratories. This technique can vary due to factors such as the availability of commercial primary antibodies, the time of tissue fixation, and the level of expertise in interpreting HER2 immunostaining (Magaki et al., 2019). For our study, we employed the pathological laboratory at Rajavithi Hospital. The inter-laboratory and intra-laboratory control of the machines and techniques is regularly supervised by the Royal College of Pathologists of Thailand. Using IHC to detect the HER2 gene yielded a positive result (score 3+) with a specificity of 93.75 %, which is deemed satisfactory. Additionally, it showed high specificity in some clinicopathological subgroups. Previous studies (Gown et al., 2008; Nitta et al., 2008) also demonstrated a strong agreement between IHC and ISH, with an average agreement rate of over 90%. The high specificity of the IHC technique may be due to the revised criteria for reporting and interpreting HER2 IHC by the ASCO/CAP in 2018 (Pasricha et al., 2020). Before 2013, it was not clear what HER2 staining in IHC meant (score 2+). This meant that the tumor cells were slightly to moderately stained, but the cell membrane was not completely stained. But in 2013, the criteria changed to include cancer cells with light to moderately stained areas around the cell membrane. In 2018, the equivocal classification was taken out of in situ hybridization reporting, and only positive and negative classifications were used. Because of these changes, there was less confusing reporting and more accurate reporting ultimately (Gordian-Arroyo et al., 2019; Pasricha et al., 2020). Anti-Her2 therapies are extensively used and are especially advantageous in situations of breast cancer with negative ER and PR. HER2 status is of utmost clinical significance especially in the case with It serves as a crucial marker for determining whether breast cancer patients should receive trastuzumab, a targeted therapy. False-negative results in HER2-negative breast cancer patients may lead to the omission of targeted therapy, thereby depriving these patients of potentially beneficial treatment. On the other hand, false-positive results can also pose challenges, as treating too many HER2-negative patients with trastuzumab can result in significant side effects and unnecessary resource waste. Furthermore, anti-HER2 medication is a targeted therapy that is effective in treating HER2-positive metastatic breast cancer. Our findings indicate that the IHC HER2 approach is highly effective in detecting HER2-positive metastatic cases, underscoring the benefits of this technique. This study demonstrated the agreement between IHC and DISH techniques. The utilization of IHC alone could assist healthcare professionals in the timely and appropriate administration of trastuzumab. This knowledge holds relevance, especially in resource-constrained developing nations. Furthermore, Her2 amplification and/or overexpression have been noted in other malignancies (Menard et al., 2001), implying potential applicability across diverse tumors. We also found a few incidences of false positives and false negatives from the IHC technique. These can occur at any stage of IHC or tissue fixation, processing, or artifact formation. To combat this, we are attempting to implement more quality controls, such as protocol, antibody, and lab setting. Furthermore, it is crucial to strengthen these findings through the inclusion of larger sample sizes and more diverse cohorts. Expanding our understanding of breast cancer pathogenesis should also involve the incorporation of additional biomarkers such as PIK3CA and P53 mutations, as highlighted in previous studies (Ogeni et al., 2021; Ali et al., 2022). This approach will provide deeper insights into the administration of targeted therapies, leading to improved patient outcomes and a more effective allocation of healthcare resources.
ST, KS and NK designed the study as well as analyzed, and interpreted data. ST, SC and KS performed the experiments. ST drafted manuscript. NK reviewed and edited the manuscript. All authors read and approved the final manuscript.
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Caplacizumab Model‐Based Dosing Recommendations in Pediatric Patients With Acquired Thrombotic Thrombocytopenic Purpura | fbb71eee-ad7f-4b99-bb8e-cded8f4b14c9 | 9255589 | Pediatrics[mh] | Simulations were performed to establish a suitable dosing regimen in adolescents and children aged >2 years, and were based on the PK/PD model previously developed in adults , as well as on data from the literature for demographic factors in a pediatric population. Adult Model Data Used for the Development of the PK/PD Model in Adults Data from 7 studies (of which some included substudies) was used to develop the PK/PD model already described in adults , : Two phase I studies in healthy subjects and one phase I study in patients with stable angina undergoing PCI, conducted to characterize the pharmacokinetics, pharmacodynamics, safety, and tolerability of caplacizumab. In these studies, caplacizumab was administered in single and multiple doses by IV infusion (ALX‐0081‐01/06, 2006‐006502‐28; ALX‐0081‐1.2/08a/08b/08c OLE, 2007‐007263‐24), or in single and multiple doses by SC injection (ALX0681‐1.1/08 first and second part, 2008‐006624‐60). One phase I study in healthy subjects to evaluate the bioequivalence of a new reconstituted lyophilized formulation with the liquid formulation of caplacizumab used in previous studies (ALX‐0681‐C102, 2014‐001294‐13/NCT02189733). One phase II study (ALX‐0081‐2.1/09, 2009‐012206‐39/NCT01020383) in high‐risk patients undergoing PCI, conducted to evaluate the safety, tolerability, and efficacy of caplacizumab compared with that of the glycoprotein IIb/IIIa inhibitor ReoPro. Two studies in patients with aTTP: 1 phase II study (ALX0681‐2.1/10, TITAN, 2010‐019375‐30/NCT01151423) and 1 phase III study (ALX0681‐C301, HERCULES, 2015‐001098‐42/NCT02553317), both performed to evaluate the safety, tolerability, and efficacy of caplacizumab as an adjunct to PE treatment. Pooling data from these trials generated a study population of 541 subjects: 317 males and 224 females with ages ranging from 18 to 85 years, body weight ranging from 46.5 to 150 kg, and a creatinine clearance ranging from 11.9 to 244 mL/min. Of the 541 subjects, 100 were healthy volunteers, 225 patients with stable angina (PCI group), and 216 patients with aTTP. The pooled data generated a total of 3629 PK and 6295 PD observations (vWF:Ag), which were used to inform the modeling. Pooling of these observations was justified by in vitro and in vivo data showing that caplacizumab interacts similarly with normal multimers of vWF (observed in healthy volunteers and patients undergoing PCI) and with UL‐vWF multimers (observed in patients with aTTP). The large, pooled data set offered the best possibility to characterize the caplacizumab‐vWF:Ag interaction and the associated covariates. At the same time, during model development, differences among the 3 subject groups, for example, disease progression, baseline characteristics, and effects of standard of care, were explored and characterized. When applying the model for the simulations, only the characteristics of patients with aTTP were considered (as specified below). Development of the PK/PD Model in Adults The population PK/PD analysis was conducted by nonlinear mixed‐effects modeling using NONMEM, version 7.3.0 (ICON Development Solutions, Hanover, Maryland). The model was developed stepwise. Initially, a subset of the data set, including only data from healthy volunteers and PCI patients, was used for the model development. In a second step, the model was updated to describe the specific characteristics related to the aTTP disease status and standard of care (ie, PE). For this purpose, only the subset of the data set including patients with aTTP was used. Finally, the effects of the covariates age, sex, race, blood group, body weight, creatinine clearance (CrCl), antidrug antibodies, and concomitant treatment were evaluated. During model development, discrimination between models was mainly based on the inspection of graphical and numerical diagnostics, including standard goodness‐of‐fit plots and prediction‐corrected visual predictive checks, as well as changes in the objective function value provided by NONMEM. Final Population PK/PD Model Used for Simulation in Children The final population PK/PD model characterizing the interaction between caplacizumab and vWF:Ag in different adult populations following IV and SC administration was based on a full target‐mediated drug disposition model structure (Figure ). The model included a 2‐compartment drug disposition model with first‐order linear elimination of free drug and two parallel first‐order absorption processes following SC dosing of caplacizumab. The model described the formation of drug‐vWF complexes with the ability to form both dimers and trimers. The production, maturation, and release of vWF:Ag were described by transit compartments and a vWF:Ag pool with feedback effects stimulating the production and release of vWF:Ag when vWF:Ag decreased below the subject's baseline level. For patients with aTTP, disease progression, and the effects of PE treatment were adequately captured by (1) a time‐dependent disease progression model and (2) removal of free vWF:Ag, free drug, and drug‐vWF complexes by PE. The final population PK/PD model was used to support the approval of caplacizumab in the adult population. Reviewers from both the EMA and the FDA deemed the model appropriate for the intended use. Simulations were performed using the final model only for patients with aTTP, to evaluate the effect of, among others, change in doses and patient body weight. Model‐Based Simulations in Children Generation of Simulated Populations A simulated adult population of 1000 patients with aTTP was generated by assuming the same covariate distribution as that observed in the 2 clinical studies in patients with aTTP included in the PK/PD analysis (TITAN and HERCULES ). From these studies, complete covariate vectors (ie, removing all individuals with missing covariates) were extracted for the following covariates: body weight, body mass index, CrCl, age, and sex. From these unique covariate vectors (n = 197), 1000 samples were taken with replacement. The 1000 sampled vectors had median and/or mean values similar to those of the original covariates. The original and resampled means (with standard deviation) for body weight were, respectively, 83.62 (21.35) kg and 82.54 (20.83) kg; for CrCl they were 107.02 (54.56) mL/min and 102.54 (48.97) mL/min; and for age they were 44.42 (13.04) years and 44.56 (13.21) years. A simulated population of 8000 children was generated from data sampled from the National Health and Nutrition Examination Survey III database. Overall, 1000 children were randomly sampled for each age category (ie, 2‐year slots from the age of 2 years up to and including 17 years of age). Demographics of the simulated pediatric population are reported in the Results section. Simulated Treatment Regimen The treatment regimen simulated in the pediatric population is schematically represented in Figure and consisted of: IV loading dose (with the same dose level as for the maintenance dose) One‐hour daily PE treatment for 7 days (PE starting 3 hours after the IV loading dose) SC once‐daily dosing of caplacizumab for 40 days (injection starting 4 hours after the IV loading dose, that is, at the end of PE treatment) Follow‐up for 60 additional days Predictions of caplacizumab concentrations were simulated at 0.5, 1, 1.5, 2, 3, and 4 hours after the initial IV dose (Figure ). Predictions of vWF:Ag concentrations were simulated at the same time points listed above, with an additional baseline measurement (Figure ). Special care was taken to always predict concentrations immediately before and after PE treatment, that is, just before the SC dose. After SC caplacizumab administration (days 1‐40), both types of predictions were simulated at the following postdose hours: 2, 4, 6, 8, 10, 12, 14, 16, 18, and 23 (Figure ). A prediction was then made 24 hours after caplacizumab dosing was halted, and then every 48 hours for the remaining follow‐up period (29 predictions over 58 days). All simulations were performed for a total of 100 days. Pediatric Population: Simulation Settings and Assumptions Based on data from the literature, the following parameters in children with aTTP were assumed to be similar to those in adults with aTTP: expression of vWF (baseline vWF:Ag levels) (with a median of 65.6 nM [164 IU/dL], range of 9‐224 nM [22.5‐560 IU/dL], in agreement with Ablynx , ), affinity of caplacizumab to the vWF target, and distribution of patients with aTTP between sexes. With regard to body weight, the simulated pediatric population had a similar body composition as that of US children in the National Health and Nutrition Examination Survey database, and the body weight distribution in the simulated adult population was assumed to be similar to the studied aTTP adult population. In addition, CrCl, as well as the typical clearance, intercompartmental clearance, central volume of distribution, and peripheral volume of distribution values in children were allometrically scaled to adults with an assumed normal renal function for a 70‐kg subject of 120 mL/min. Software Used for the Analysis The simulations were performed using NONMEM version 7.3.0 installed on a Xeon‐based server (Intel, Santa Clara, California) running Scientific Linux 6.3. NONMEM runs were performed using the gfortran compiler, version 4.4.6. Data management and further processing of NONMEM output were performed using R version 3.3.3 (2017‐03‐06; R Foundation for Statistical Computing, Vienna, Austria).
Data Used for the Development of the PK/PD Model in Adults Data from 7 studies (of which some included substudies) was used to develop the PK/PD model already described in adults , : Two phase I studies in healthy subjects and one phase I study in patients with stable angina undergoing PCI, conducted to characterize the pharmacokinetics, pharmacodynamics, safety, and tolerability of caplacizumab. In these studies, caplacizumab was administered in single and multiple doses by IV infusion (ALX‐0081‐01/06, 2006‐006502‐28; ALX‐0081‐1.2/08a/08b/08c OLE, 2007‐007263‐24), or in single and multiple doses by SC injection (ALX0681‐1.1/08 first and second part, 2008‐006624‐60). One phase I study in healthy subjects to evaluate the bioequivalence of a new reconstituted lyophilized formulation with the liquid formulation of caplacizumab used in previous studies (ALX‐0681‐C102, 2014‐001294‐13/NCT02189733). One phase II study (ALX‐0081‐2.1/09, 2009‐012206‐39/NCT01020383) in high‐risk patients undergoing PCI, conducted to evaluate the safety, tolerability, and efficacy of caplacizumab compared with that of the glycoprotein IIb/IIIa inhibitor ReoPro. Two studies in patients with aTTP: 1 phase II study (ALX0681‐2.1/10, TITAN, 2010‐019375‐30/NCT01151423) and 1 phase III study (ALX0681‐C301, HERCULES, 2015‐001098‐42/NCT02553317), both performed to evaluate the safety, tolerability, and efficacy of caplacizumab as an adjunct to PE treatment. Pooling data from these trials generated a study population of 541 subjects: 317 males and 224 females with ages ranging from 18 to 85 years, body weight ranging from 46.5 to 150 kg, and a creatinine clearance ranging from 11.9 to 244 mL/min. Of the 541 subjects, 100 were healthy volunteers, 225 patients with stable angina (PCI group), and 216 patients with aTTP. The pooled data generated a total of 3629 PK and 6295 PD observations (vWF:Ag), which were used to inform the modeling. Pooling of these observations was justified by in vitro and in vivo data showing that caplacizumab interacts similarly with normal multimers of vWF (observed in healthy volunteers and patients undergoing PCI) and with UL‐vWF multimers (observed in patients with aTTP). The large, pooled data set offered the best possibility to characterize the caplacizumab‐vWF:Ag interaction and the associated covariates. At the same time, during model development, differences among the 3 subject groups, for example, disease progression, baseline characteristics, and effects of standard of care, were explored and characterized. When applying the model for the simulations, only the characteristics of patients with aTTP were considered (as specified below). Development of the PK/PD Model in Adults The population PK/PD analysis was conducted by nonlinear mixed‐effects modeling using NONMEM, version 7.3.0 (ICON Development Solutions, Hanover, Maryland). The model was developed stepwise. Initially, a subset of the data set, including only data from healthy volunteers and PCI patients, was used for the model development. In a second step, the model was updated to describe the specific characteristics related to the aTTP disease status and standard of care (ie, PE). For this purpose, only the subset of the data set including patients with aTTP was used. Finally, the effects of the covariates age, sex, race, blood group, body weight, creatinine clearance (CrCl), antidrug antibodies, and concomitant treatment were evaluated. During model development, discrimination between models was mainly based on the inspection of graphical and numerical diagnostics, including standard goodness‐of‐fit plots and prediction‐corrected visual predictive checks, as well as changes in the objective function value provided by NONMEM.
Data from 7 studies (of which some included substudies) was used to develop the PK/PD model already described in adults , : Two phase I studies in healthy subjects and one phase I study in patients with stable angina undergoing PCI, conducted to characterize the pharmacokinetics, pharmacodynamics, safety, and tolerability of caplacizumab. In these studies, caplacizumab was administered in single and multiple doses by IV infusion (ALX‐0081‐01/06, 2006‐006502‐28; ALX‐0081‐1.2/08a/08b/08c OLE, 2007‐007263‐24), or in single and multiple doses by SC injection (ALX0681‐1.1/08 first and second part, 2008‐006624‐60). One phase I study in healthy subjects to evaluate the bioequivalence of a new reconstituted lyophilized formulation with the liquid formulation of caplacizumab used in previous studies (ALX‐0681‐C102, 2014‐001294‐13/NCT02189733). One phase II study (ALX‐0081‐2.1/09, 2009‐012206‐39/NCT01020383) in high‐risk patients undergoing PCI, conducted to evaluate the safety, tolerability, and efficacy of caplacizumab compared with that of the glycoprotein IIb/IIIa inhibitor ReoPro. Two studies in patients with aTTP: 1 phase II study (ALX0681‐2.1/10, TITAN, 2010‐019375‐30/NCT01151423) and 1 phase III study (ALX0681‐C301, HERCULES, 2015‐001098‐42/NCT02553317), both performed to evaluate the safety, tolerability, and efficacy of caplacizumab as an adjunct to PE treatment. Pooling data from these trials generated a study population of 541 subjects: 317 males and 224 females with ages ranging from 18 to 85 years, body weight ranging from 46.5 to 150 kg, and a creatinine clearance ranging from 11.9 to 244 mL/min. Of the 541 subjects, 100 were healthy volunteers, 225 patients with stable angina (PCI group), and 216 patients with aTTP. The pooled data generated a total of 3629 PK and 6295 PD observations (vWF:Ag), which were used to inform the modeling. Pooling of these observations was justified by in vitro and in vivo data showing that caplacizumab interacts similarly with normal multimers of vWF (observed in healthy volunteers and patients undergoing PCI) and with UL‐vWF multimers (observed in patients with aTTP). The large, pooled data set offered the best possibility to characterize the caplacizumab‐vWF:Ag interaction and the associated covariates. At the same time, during model development, differences among the 3 subject groups, for example, disease progression, baseline characteristics, and effects of standard of care, were explored and characterized. When applying the model for the simulations, only the characteristics of patients with aTTP were considered (as specified below).
The population PK/PD analysis was conducted by nonlinear mixed‐effects modeling using NONMEM, version 7.3.0 (ICON Development Solutions, Hanover, Maryland). The model was developed stepwise. Initially, a subset of the data set, including only data from healthy volunteers and PCI patients, was used for the model development. In a second step, the model was updated to describe the specific characteristics related to the aTTP disease status and standard of care (ie, PE). For this purpose, only the subset of the data set including patients with aTTP was used. Finally, the effects of the covariates age, sex, race, blood group, body weight, creatinine clearance (CrCl), antidrug antibodies, and concomitant treatment were evaluated. During model development, discrimination between models was mainly based on the inspection of graphical and numerical diagnostics, including standard goodness‐of‐fit plots and prediction‐corrected visual predictive checks, as well as changes in the objective function value provided by NONMEM.
The final population PK/PD model characterizing the interaction between caplacizumab and vWF:Ag in different adult populations following IV and SC administration was based on a full target‐mediated drug disposition model structure (Figure ). The model included a 2‐compartment drug disposition model with first‐order linear elimination of free drug and two parallel first‐order absorption processes following SC dosing of caplacizumab. The model described the formation of drug‐vWF complexes with the ability to form both dimers and trimers. The production, maturation, and release of vWF:Ag were described by transit compartments and a vWF:Ag pool with feedback effects stimulating the production and release of vWF:Ag when vWF:Ag decreased below the subject's baseline level. For patients with aTTP, disease progression, and the effects of PE treatment were adequately captured by (1) a time‐dependent disease progression model and (2) removal of free vWF:Ag, free drug, and drug‐vWF complexes by PE. The final population PK/PD model was used to support the approval of caplacizumab in the adult population. Reviewers from both the EMA and the FDA deemed the model appropriate for the intended use. Simulations were performed using the final model only for patients with aTTP, to evaluate the effect of, among others, change in doses and patient body weight.
Generation of Simulated Populations A simulated adult population of 1000 patients with aTTP was generated by assuming the same covariate distribution as that observed in the 2 clinical studies in patients with aTTP included in the PK/PD analysis (TITAN and HERCULES ). From these studies, complete covariate vectors (ie, removing all individuals with missing covariates) were extracted for the following covariates: body weight, body mass index, CrCl, age, and sex. From these unique covariate vectors (n = 197), 1000 samples were taken with replacement. The 1000 sampled vectors had median and/or mean values similar to those of the original covariates. The original and resampled means (with standard deviation) for body weight were, respectively, 83.62 (21.35) kg and 82.54 (20.83) kg; for CrCl they were 107.02 (54.56) mL/min and 102.54 (48.97) mL/min; and for age they were 44.42 (13.04) years and 44.56 (13.21) years. A simulated population of 8000 children was generated from data sampled from the National Health and Nutrition Examination Survey III database. Overall, 1000 children were randomly sampled for each age category (ie, 2‐year slots from the age of 2 years up to and including 17 years of age). Demographics of the simulated pediatric population are reported in the Results section. Simulated Treatment Regimen The treatment regimen simulated in the pediatric population is schematically represented in Figure and consisted of: IV loading dose (with the same dose level as for the maintenance dose) One‐hour daily PE treatment for 7 days (PE starting 3 hours after the IV loading dose) SC once‐daily dosing of caplacizumab for 40 days (injection starting 4 hours after the IV loading dose, that is, at the end of PE treatment) Follow‐up for 60 additional days Predictions of caplacizumab concentrations were simulated at 0.5, 1, 1.5, 2, 3, and 4 hours after the initial IV dose (Figure ). Predictions of vWF:Ag concentrations were simulated at the same time points listed above, with an additional baseline measurement (Figure ). Special care was taken to always predict concentrations immediately before and after PE treatment, that is, just before the SC dose. After SC caplacizumab administration (days 1‐40), both types of predictions were simulated at the following postdose hours: 2, 4, 6, 8, 10, 12, 14, 16, 18, and 23 (Figure ). A prediction was then made 24 hours after caplacizumab dosing was halted, and then every 48 hours for the remaining follow‐up period (29 predictions over 58 days). All simulations were performed for a total of 100 days.
A simulated adult population of 1000 patients with aTTP was generated by assuming the same covariate distribution as that observed in the 2 clinical studies in patients with aTTP included in the PK/PD analysis (TITAN and HERCULES ). From these studies, complete covariate vectors (ie, removing all individuals with missing covariates) were extracted for the following covariates: body weight, body mass index, CrCl, age, and sex. From these unique covariate vectors (n = 197), 1000 samples were taken with replacement. The 1000 sampled vectors had median and/or mean values similar to those of the original covariates. The original and resampled means (with standard deviation) for body weight were, respectively, 83.62 (21.35) kg and 82.54 (20.83) kg; for CrCl they were 107.02 (54.56) mL/min and 102.54 (48.97) mL/min; and for age they were 44.42 (13.04) years and 44.56 (13.21) years. A simulated population of 8000 children was generated from data sampled from the National Health and Nutrition Examination Survey III database. Overall, 1000 children were randomly sampled for each age category (ie, 2‐year slots from the age of 2 years up to and including 17 years of age). Demographics of the simulated pediatric population are reported in the Results section.
The treatment regimen simulated in the pediatric population is schematically represented in Figure and consisted of: IV loading dose (with the same dose level as for the maintenance dose) One‐hour daily PE treatment for 7 days (PE starting 3 hours after the IV loading dose) SC once‐daily dosing of caplacizumab for 40 days (injection starting 4 hours after the IV loading dose, that is, at the end of PE treatment) Follow‐up for 60 additional days Predictions of caplacizumab concentrations were simulated at 0.5, 1, 1.5, 2, 3, and 4 hours after the initial IV dose (Figure ). Predictions of vWF:Ag concentrations were simulated at the same time points listed above, with an additional baseline measurement (Figure ). Special care was taken to always predict concentrations immediately before and after PE treatment, that is, just before the SC dose. After SC caplacizumab administration (days 1‐40), both types of predictions were simulated at the following postdose hours: 2, 4, 6, 8, 10, 12, 14, 16, 18, and 23 (Figure ). A prediction was then made 24 hours after caplacizumab dosing was halted, and then every 48 hours for the remaining follow‐up period (29 predictions over 58 days). All simulations were performed for a total of 100 days.
Based on data from the literature, the following parameters in children with aTTP were assumed to be similar to those in adults with aTTP: expression of vWF (baseline vWF:Ag levels) (with a median of 65.6 nM [164 IU/dL], range of 9‐224 nM [22.5‐560 IU/dL], in agreement with Ablynx , ), affinity of caplacizumab to the vWF target, and distribution of patients with aTTP between sexes. With regard to body weight, the simulated pediatric population had a similar body composition as that of US children in the National Health and Nutrition Examination Survey database, and the body weight distribution in the simulated adult population was assumed to be similar to the studied aTTP adult population. In addition, CrCl, as well as the typical clearance, intercompartmental clearance, central volume of distribution, and peripheral volume of distribution values in children were allometrically scaled to adults with an assumed normal renal function for a 70‐kg subject of 120 mL/min.
The simulations were performed using NONMEM version 7.3.0 installed on a Xeon‐based server (Intel, Santa Clara, California) running Scientific Linux 6.3. NONMEM runs were performed using the gfortran compiler, version 4.4.6. Data management and further processing of NONMEM output were performed using R version 3.3.3 (2017‐03‐06; R Foundation for Statistical Computing, Vienna, Austria).
Subject Demographics and Characteristics The demographic characteristics for each age category of the simulated pediatric population are reported in Table . The pediatric population included a total of 8000 children divided into 8 age categories. In addition, a simulated adult population of 1000 patients with aTTP was generated by assuming the same covariate distribution as that observed in the 2 clinical studies in patients with aTTP included in the previous PK/PD analysis (see Methods section for details). Simulations of Different Dosing Strategies: Flat vs Weight‐Based Dosing All individual steady‐state area under the plasma concentration–time curve (AUC ss ) values were derived at day 40 for each age category and are displayed using box plots (Figure ). Emphasis on outliers was toned down in these plots as outliers are generally dependent on the number of subjects/simulations per age category and do not contribute to the comparison of the general tendencies in the different groups. When simulating a flat dosing strategy of 10 mg of caplacizumab, given daily SC for 40 days, including an IV loading dose and a 1‐hour PE treatment during the first 7 days (Figure ), caplacizumab concentrations indicated a higher exposure for lower age categories (Figure ). This trend of increased AUC ss for the lower age categories was further confirmed when comparing other parameters. For lower age categories, also maximum concentration at steady state (C ss,max ) and minimum concentration at steady state (C ss,min ) were higher than those in the reference adult population (data not shown), thus confirming the need for a dose reduction in low‐weight pediatric patients. Simulations of the weight‐based dosing strategy followed the same treatment schedule as the flat dosing (Figure ) but differed in that pediatric patients with body weight <40 kg were treated with 5 mg daily caplacizumab and those with body weight of at least 40 kg (or adults) received 10 mg daily. The results show that with the proposed weight‐based dosing approach, similar AUC ss could be obtained across the different pediatric age groups (Figure ). Furthermore, these AUC ss predictions did not show clear deviations from the AUC ss predicted in the adult population. When considering the median AUC ss (Figure ), C ss,max , and C ss,min (data not shown) for each age group, we noticed a trend indicating a slight decrease in the median values of these parameters in the first 3 age categories. However, this downward trend was not evident in the subsequent age groups (group 4, ≥8 to <10 years; and group 5, ≥10 to <12 years), in which an increasing number of children received the 10‐mg caplacizumab dose (Table ). These observations were confirmed when the parameters AUC ss , C ss,max , and C ss,min were summarized by 2 larger weight categories (ie, <40 or ≥40 kg) (Table ). When these 2 groups of children were compared to the adult group, all parameters showed slightly lower median levels in children weighing <40 kg and slightly higher levels in children weighing at least 40 kg (Table ). We then analyzed the relationship between the simulated AUC ss of each subject and their body weight (Figure ) or age (Figure ). When simulations were plotted against body weight, the AUC ss showed a gradually decreasing trend in young pediatric patients with body weight <40 kg (Figure ). The AUC ss values became closer to those in adults as pediatric patients received the 10‐mg dose when they reached a weight ≥40 kg (Figure and Table ). When simulated exposures were plotted against children's specific age (Figure ), rather than age categories (Figure ), the AUC ss were similar and relatively stable across ages. Similar trends, related to both weight and age, were also observed for C ss,max (data not shown). Simulation of the Effects of Weight‐Based Dosing on Disease Progression (vWF:Ag Time Course) In the first part of this study, we established that a weight‐based dosing is needed for pediatric patients with aTTP to ensure caplacizumab exposures similar to those observed in adult patients with aTTP receiving the recommended daily SC 10‐mg dosing regimen. We then proceeded by using the previously developed PK/PD model to, first, determine the model‐predicted total plasma concentrations of caplacizumab in children, and then assess the PD response, quantified in terms of total vWF:Ag levels. When plotting the simulated median caplacizumab concentration time‐course for each age category (Figure ), we confirmed that similar plasma concentration levels are predicted across the different age groups. In addition, when plotting the vWF:Ag levels as change from baseline (Figure ), our predictions suggested that similar caplacizumab exposures lead to similar levels of vWF:Ag suppression for the different age categories. Also, a faster return to baseline vWF:Ag concentrations was generally predicted for younger age groups.
The demographic characteristics for each age category of the simulated pediatric population are reported in Table . The pediatric population included a total of 8000 children divided into 8 age categories. In addition, a simulated adult population of 1000 patients with aTTP was generated by assuming the same covariate distribution as that observed in the 2 clinical studies in patients with aTTP included in the previous PK/PD analysis (see Methods section for details).
All individual steady‐state area under the plasma concentration–time curve (AUC ss ) values were derived at day 40 for each age category and are displayed using box plots (Figure ). Emphasis on outliers was toned down in these plots as outliers are generally dependent on the number of subjects/simulations per age category and do not contribute to the comparison of the general tendencies in the different groups. When simulating a flat dosing strategy of 10 mg of caplacizumab, given daily SC for 40 days, including an IV loading dose and a 1‐hour PE treatment during the first 7 days (Figure ), caplacizumab concentrations indicated a higher exposure for lower age categories (Figure ). This trend of increased AUC ss for the lower age categories was further confirmed when comparing other parameters. For lower age categories, also maximum concentration at steady state (C ss,max ) and minimum concentration at steady state (C ss,min ) were higher than those in the reference adult population (data not shown), thus confirming the need for a dose reduction in low‐weight pediatric patients. Simulations of the weight‐based dosing strategy followed the same treatment schedule as the flat dosing (Figure ) but differed in that pediatric patients with body weight <40 kg were treated with 5 mg daily caplacizumab and those with body weight of at least 40 kg (or adults) received 10 mg daily. The results show that with the proposed weight‐based dosing approach, similar AUC ss could be obtained across the different pediatric age groups (Figure ). Furthermore, these AUC ss predictions did not show clear deviations from the AUC ss predicted in the adult population. When considering the median AUC ss (Figure ), C ss,max , and C ss,min (data not shown) for each age group, we noticed a trend indicating a slight decrease in the median values of these parameters in the first 3 age categories. However, this downward trend was not evident in the subsequent age groups (group 4, ≥8 to <10 years; and group 5, ≥10 to <12 years), in which an increasing number of children received the 10‐mg caplacizumab dose (Table ). These observations were confirmed when the parameters AUC ss , C ss,max , and C ss,min were summarized by 2 larger weight categories (ie, <40 or ≥40 kg) (Table ). When these 2 groups of children were compared to the adult group, all parameters showed slightly lower median levels in children weighing <40 kg and slightly higher levels in children weighing at least 40 kg (Table ). We then analyzed the relationship between the simulated AUC ss of each subject and their body weight (Figure ) or age (Figure ). When simulations were plotted against body weight, the AUC ss showed a gradually decreasing trend in young pediatric patients with body weight <40 kg (Figure ). The AUC ss values became closer to those in adults as pediatric patients received the 10‐mg dose when they reached a weight ≥40 kg (Figure and Table ). When simulated exposures were plotted against children's specific age (Figure ), rather than age categories (Figure ), the AUC ss were similar and relatively stable across ages. Similar trends, related to both weight and age, were also observed for C ss,max (data not shown).
In the first part of this study, we established that a weight‐based dosing is needed for pediatric patients with aTTP to ensure caplacizumab exposures similar to those observed in adult patients with aTTP receiving the recommended daily SC 10‐mg dosing regimen. We then proceeded by using the previously developed PK/PD model to, first, determine the model‐predicted total plasma concentrations of caplacizumab in children, and then assess the PD response, quantified in terms of total vWF:Ag levels. When plotting the simulated median caplacizumab concentration time‐course for each age category (Figure ), we confirmed that similar plasma concentration levels are predicted across the different age groups. In addition, when plotting the vWF:Ag levels as change from baseline (Figure ), our predictions suggested that similar caplacizumab exposures lead to similar levels of vWF:Ag suppression for the different age categories. Also, a faster return to baseline vWF:Ag concentrations was generally predicted for younger age groups.
This article describes a population PK/PD model‐based simulation aimed at establishing a suitable dosing regimen for caplacizumab in children with aTTP aged >2 years. According to our results, a suitable dose in children is −5 mg if body weight is <40 kg and 10 mg if body weight is at least 40 kg. The simulation for this dosing, given with the same regimen as that recommended for adults, resulted in similar caplacizumab exposures and vWF:Ag suppression as those observed in the adult aTTP patient population. The results of this analysis were submitted to the EMA with the application for a type II variation to support a pediatric label change. Based on this analysis, and without the request of pediatric clinical trial data, the EMA extended the indication and corresponding dose recommendations of caplacizumab to adolescents aged >12 years and with body weight of at least 40 kg. Additionally, Section 5.2 of the prescribing information (reporting the PK properties) was updated with the results of the present modeling and simulation study. In children, 2 forms of TTP have been described: a congenital form (accounting for about one‐third of the cases, usually manifesting already in neonates, and often chronic) and an acquired form (accounting for the remaining two‐thirds of the cases). Both forms are characterized by severe ADAMTS‐13 deficiency and are life threatening. The course of aTTP is similar across ages, from childhood to adulthood. Demographic characteristics of adults and children with aTTP are also similar, , with more cases occurring in female patients and the first episode of aTTP occurring between ages 4 months and 17 years (median, 13 years). In a French pediatric cohort, the mortality rate of aTTP was reported to be 9% and the clinical relapse rate ≈25%. , As in adults, the onset of aTTP in children also needs rapid diagnosis and therapeutic management. The first‐line treatment in children is based on daily plasma replacement therapy (plasma infusion or PE) and usually steroid treatment. Some children, especially those refractory to treatment, may need immunomodulation with rituximab. However, the effects of rituximab are normally detectable 2 weeks after the first infusion and thus may not be able to prevent early death; furthermore, daily PE needs to be continued during the course of rituximab administration. Published studies discussing the management of aTTP in children report that current aTTP treatment needs improvement and that children would clearly benefit from the introduction of innovative therapeutic drugs, such as caplacizumab. A few case reports of children with aTTP using caplacizumab have been published, and all showed that pediatric patients responded well to therapy, with few or no side effects reported and no new safety findings. , , , , However, despite the efforts, clinical studies involving a sufficient number of children have proven not feasible, leaving modeling and simulation studies the only option to explore pediatric dosing. Caplacizumab is an orphan drug for which a PK/PD model has already been developed for a population of adult patients with aTTP. This PK/PD model was used to support the approval of caplacizumab in adults, and reviewers from both the EMA and the FDA deemed the model appropriate for the intended use. For the current study, the following parameters in children with aTTP were assumed to be similar to those in adults with aTTP, based on data from the literature: expression of vWF (baseline vWF:Ag levels), affinity of caplacizumab to the vWF target, distribution of patients with aTTP between sexes. In addition, CrCl, as well as the typical clearance, intercompartmental clearance, central volume of distribution, and peripheral volume of distribution values in children were allometrically scaled to adults with an assumed normal renal function for a 70‐kg subject of 120 mL/min. These considerations allowed using the previously developed population PK/PD model to perform simulations and, finally, suggest an appropriate dosing regimen in children. A recent publication by Gill et al indicates that the expression of vWF may on average be somewhat lower in young healthy children undergoing tonsillectomy (being ≈20% lower in children under 3 years compared to teenagers). This difference is small in relation to the wide variability observed for baseline vWF:Ag levels in patients with aTTP. The simulations here performed assumed a wide range of variability for baseline vWF:Ag levels: median of 63 nM (157 IU/dL) and a 90% prediction interval of 36.9 to 116 nM (92‐290 IU/dL). In general, baseline vWF:Ag levels have been shown to be higher in patients with aTTP than in healthy subjects, and currently no arguments suggest that this should not be the case for children. The importance of baseline vWF:Ag levels was explored while creating the original PK/PD model that supported the adult indication. In that modeling analysis, lower baseline vWF:Ag levels were found to be associated with lower caplacizumab plasma concentrations and, consequently, with a less pronounced reduction in vWF (% reduction). However, these effects were not considered to be of a magnitude that warranted any dose adaptations. Based on our simulations, we concluded that the weight‐based dosing regimen in children results in similar caplacizumab exposures and similar vWF:Ag suppression as those observed in adult subjects with aTTP receiving caplacizumab 10 mg daily. The specific treatment regimen that was used for the simulations is described in the Methods section and reflects the actual posology of caplacizumab in adults (Figure ). During an initial exploratory stage, alternative dosing strategies have been investigated, until the 2 more adequate strategies were found: the 10‐mg flat dosing and the weight‐based one, implying a 50% dose reduction in children weighing <40 kg. As expected, the simulations of exposure following a flat dosing (10 mg for all subjects) clearly indicated that this regimen determines a higher exposure in children with a low body weight, that is, primarily children aged <10 years and thereby average body weight <40 kg (Figure , Table ). On the other hand, a dose adjustment to 5 mg in children with a body weight <40 kg resulted in similar predicted exposures across age and weight groups (Figures and ; and Table ). With this dose adjustment, the predicted median for AUC ss and C ss,max in each 2‐year age category is expected to be within ±8% of the median value for the adult population. The predicted median C ss,min for children aged 6 to 8 years is 14% lower than the median in adults, but the predicted lower 5th percentile is only 4% lower than the equivalent adult percentile. Our results show that similar caplacizumab exposures lead to similar vWF:Ag suppression levels for the different age categories (Figure ). Noticeably, a faster return to baseline vWF:Ag concentrations is predicted for younger age groups. Given the mechanism of action of caplacizumab and the current knowledge of aTTP in the pediatric population, efficacy and safety of caplacizumab in children are likely to be similar to those in adults. Furthermore, similar caplacizumab exposures in children and adults are assumed to elicit comparable effects in both populations. While the modeling and simulation study reported here refers to children between ages 2 and 18 years, pediatric label change for caplacizumab has been approved by the EMA only for adolescents aged >12 years and with body weight of at least 40 kg. For the remaining pediatric population, the PK properties of caplacizumab have been reported in Section 5.2 of the prescribing information and can be used as guidance for clinicians that need to treat younger patients. Regarding the specific population of infants and children from birth up to 2 years, the EMA issued a waiver based on the consideration that “the specific medicinal product does not represent a significant therapeutic benefit as clinical studies are not feasible.” Besides, the clinical characteristics of the condition presenting at this early age may require specific management, for example, in the rare, congenital form of TTP, prophylactic plasma therapy is the only therapeutic option currently available. To the best of our knowledge, this represents a rare case in which regulatory authorities have deemed simulation studies sufficiently robust to support a pediatric indication and posology, in absence of clinical study data. ,
The PK/PD model previously developed for caplacizumab in adults was used to perform a simulation analysis in a population of 8000 children with aTTP. According to the results, the recommended dose in children (aged 2‐18 years) was 5‐mg caplacizumab if body weight is <40 kg, and 10 mg if body weight is at least 40 kg. The modeling and simulation data that were presented here have been submitted to the EMA via a type II variation. Despite the absence of clinical study data, the EMA deemed the results sufficiently robust to approve an extension of the indication for caplacizumab, which now includes the recommended posology of 10 mg for pediatric patients aged >12 years and weighing over 40 kg.
M.B. and E.H. are employees of Pharmetheus AB, contracted as external consultants by Ablynx/Sanofi‐Aventis Group. B.D., F.C., R.D.P.S., M.L.S.‐M. are all employees of Sanofi‐Aventis Group and may hold shares and/or stock options in the company. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
This work was funded by Sanofi‐Aventis Group.
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A study on the compressive strength of three-dimensional direct printing aligner material for specific designing of clear aligners | f6a1a254-6c46-4028-bb48-8749945514c3 | 11747087 | Dentistry[mh] | With the increasing general interest in appearance, the demand for treatments using clear aligners has been gradually increasing to meet the esthetic needs of patients . Unlike fixed appliances, clear aligners do not require the attachment of brackets to the teeth and offer greater esthetic advantages owing to their transparent material composition. Although high patient compliance for continuous force exertion on the teeth, combined with the practitioner’s biomechanical knowledge is critical, clear aligners can function effectively as esthetic devices in orthodontics with the formulation of a well-designed treatment plan and proper adherence to the practitioner’s instructions , . In orthodontic treatment using clear aligners, the presence of attachments is a critical factor for the efficient correction of rotated and displaced teeth , . However, attachments tend to detach easily and compromise the esthetics . Therefore, bonding methods and techniques should be improved to ensure more effective attachment adhesion and develop attachment designs that facilitate efficient tooth movement. Meanwhile, instead of using attachments bonded directly to the teeth, altering the design of clear aligners can enable effective tooth movement and efficient orthodontic treatment. Practically, clear aligners, such as Invisalign ® (Align Technology, Tempe, USA), utilize modified designs such as the Power Ridge for the correction of displaced teeth. McKay et al. demonstrated that the creation of Pressure Columns enables effective tooth movement in an in vitro study, which compared and analyzed the mechanical properties of three-dimensional direct-printing aligners (3DPA) with those of traditional thermoforming aligners (TFA). The 3DPA has the significant advantage of starting with a thinner pressure area in the initial stages of treatment and gradually increasing the thickness, thereby approximating the optimized force required for tooth movement. This study aimed to test whether specific design features of the 3DPA, such as the rectangular pressure area (RPA) and customized pressure region (CPR), function at a clinically significant level for correcting malposed teeth. The research involved the use of relevant measurement tools and programs to study the material properties. The RPA is a non-customized ridge area on the clear aligner intended to promote tooth movement, similar in concept to Invisalign ® ’s Power Ridge. In contrast, the CPR is an improved version of the RPA, defined as the ridge area on a clear aligner customized to correspond to the individual shape of each tooth for facilitating more efficient tooth movement. A recent study investigated the changes in the force applied to teeth and rotational inertia by varying the outer thickness, but not the inner thickness, of clear aligners. A previous study compared the effects of a power ridge and attachments using the finite element method for lingual root torque ; however, it did not involve 3D printing with shape memory material. Therefore, the present study aimed to investigate the changes in the mechanical properties of shape memory 3DPA by applying repeated pressure while varying the inner thickness in specific areas where force is assumed to be applied, and explore the clinical applicability of these findings. Our study aimed to experimentally compare the mechanical properties of the 3DPA material, TC-85 (Graphy, Seoul, Korea), and the TFA material, glycol-modified polyethylene terephthalate (PETG), by repeatedly measuring their characteristics under different compression stresses in vitro, which will help identify the differences between these materials. Our research will serve as a starting point for the future design of customized inner surfaces of clear aligners and more efficient and effective orthodontic treatments. The null hypothesis of the study was “there is no difference in the compressive force due to the difference in material and thickness for each specimen.” The specimens used in this experiment were made of PETG and a 3D direct-printing photocurable resin. The PETG specimens were prepared using 3 A MEDES Co.‘s 3 A GS030 (Thickness: 0.75 mm, Korea). Orthodontic aligners were directly printed with a 3D printer using TC-85 DAC (Graphy Inc., Korea). The manufacturing process for each specimen was as follows. For the PETG specimens, a PETG sheet was placed on MINISTAR S (SCHEU-DENTAL, Iserlohn, Germany) and heated for 30 s, with the maximum surface temperature of the PETG sheet maintained below 60 °C. A vacuum pressure of 3.7 bar was applied to the prepared model, followed by cooling for 1 min. After trimming the edges of the model, the specimens were trimmed to the appropriate size for each sample. For the 3D direct-printed clear aligner specimens, a TC-85 DAC was used with an LCD-type 3D printer Slash2 4 K (Uniz Inc., China) to print the experimental specimens directly. Post-curing was performed using THC (Graphy Inc., Korea) under nitrogen for 20 min with a total energy exposure of 480 J at an ultraviolet wavelength of 405 nm. Assuming a situation in which compressive force is transmitted to specific areas of the teeth, the experimental group used TC-85, which was fabricated in the form of a rectangular protrusion termed RPA, with a thickness of 1 mm (Fig. right panel, TC-85 full). This is not a strictly customized form that follows the curvature of individual teeth in the strict sense of CPR. For a comparative study of mechanical properties, rectangular protrusions similar to the commonly used power ridges in traditional clear aligners were fabricated using different materials. The experimental and control group 2 (Fig. , left panel) used TC-85 and were shaped into rectangular protrusions. Control group 1 used PETG. The models with RPA were printed with a 3D printer. Then, using a vacuum form with a PETG sheet, a thermoformed sheet was created which was cut to 7 × 8 mm rectangular specimen for the cyclic compression test. (Fig. , right panel). The experimental and control group 2 used the same material and shape; however, the experimental group had filled embossed areas, whereas Control Group 2 did not. Because TC-85 (experimental group and control group 2) is a 3D printing material, it can be printed with inclined surfaces, allowing selective pressure application to specific areas in a clinical setting. A compression-cycle experiment was conducted using an LTM 3 h electrodynamic testing machine (Zwick Roell, Germany). The crosshead speed of the cycle-testing equipment was fixed at 1 mm/s. In this study, the number of specimens and compression cycles were determined based on the results of previous studies. First, the number of specimens was referenced from a previous study that investigated the thermo-mechanical properties of the same material used in this study . That study used approximately 3 to 6 specimens, providing reasonable evidence within a 10% margin of error. In this study, employing 3–5 specimens per group and depth combination was deemed suitable to minimize the risk of errors in mechanical properties that might occur with the use of a single specimen, while also avoiding unnecessary duplication of specimens. The average values of these specimens were used, and there was no statistical significance in the variation between specimens. Regarding the number of compression cycles based on depth, a previous in vitro study examining the impact of thermocycling on clear aligners made from polyurethane recommended 600 cycles, equivalent to 20 cycles per day over a period of 30 days, to adequately simulate daily usage in the oral environment . Although 3D-printed aligners, when produced in-house, can be replaced within days, adjustments to the setup or orders from external manufacturers may extend the replacement time to 3–4 weeks. Given that an aligner might remain in use for this duration, conducting 500 cycles was considered clinically reasonable to mirror the typical usage period. Additionally, to estimate the necessary sample size of the specimens for this study, a power analysis was performed using G*Power 3.1.9.4. Given the need for comparisons between different groups, ANOVA was selected from the F-tests category. The analysis indicated that a minimum of 42 samples (14 per group) would suffice to detect statistical significance at a p-value of < 0.05 and a confidence level of 80%. To accommodate potential drop-outs due to compression pressure, an additional 20% of samples were included, resulting in a final recommendation of at least 17 samples per group. Additionally, the study began with 20 specimens per group to account for any specimens that could not be mounted on the electrodynamic testing machine due to volume defects. The compression depths were set at 100, 300, 500, and 700 µm, respectively. The greatest advantage of DPA is the ability to start with a low thickness variation and gradually increase to a higher thickness variation, so four different thicknesses were selected. Considering in-house 3D printing, the resolution of 3D printers is generally around 100 µm, so the specimen thickness was increased in increments of 200 µm, starting at 100 µm. The average thickness of human PDL is approximately 150–380 µm . To prevent necrosis due to exceeding the biological limit of compressing the PDL thickness by more than twice in one step, the thickest specimen was designed at 700 µm. For the PETG group (Control group 1), five specimens were used for a compression depth of 100 µm, and five specimens each for 300, 500, and 700 µm, totaling 20 specimens for the experiment. For the TC-85 blank group (Control group 2), three specimens were used for a compression depth of 100 µm, four specimens for 300 µm, and five specimens each for 500 and 700 µm, totaling 17 specimens for the experiment. As predicted, it was observed that the greatest volume defects occurred in the small, hollow protruding specimens. In the TC-85 full group (experimental group), five specimens were used for a compression depth of 100 µm, four specimens for 300 µm, and five specimens each for 500 and 700 µm, totaling 19 specimens for the experiment. To evaluate the consistency in specimen thickness, measurements were conducted for each specimen using a digital caliper (GAU-178.00, Eurotool, Inc., USA), following the methods described in a previous study that used the same materials . Statistical analysis Statistical analysis of the experimental data was performed using the SPSS software (IBM SPSS Statistics Version 25.0). Because all the linear data exhibited non-normality, the Kruskal–Wallis test was conducted, followed by post-hoc testing using the Bonferroni correction. Statistical analysis of the experimental data was performed using the SPSS software (IBM SPSS Statistics Version 25.0). Because all the linear data exhibited non-normality, the Kruskal–Wallis test was conducted, followed by post-hoc testing using the Bonferroni correction. As shown in Table ; Fig. (a), when pressure is applied with a compression depth of 100 µm (0.1 mm), the compressive force measured for the PETG specimens is approximately 16 N. When applying pressure with a compression depth of 300 µm, the compressive force measured is approximately 50 N, followed by force decay, resulting in a relatively consistent compressive force of approximately 47 N. At a compression depth of 500 µm, the compressive force measured is approximately 90 N, and after repeated cycles, force decay occurs, leading to a relatively consistent compressive force of approximately 80 N. At a compression depth of 700 µm, the compressive force measured is 130 N, and after repeated cycles, force decay occurs, resulting in a relatively consistent compressive force of approximately 115 N. As shown in Table ; Fig. (b), when pressure is applied with a compression depth of 100 µm, the compressive force measured for the TC-85 blank specimens is approximately 20 N. When applying pressure with a compression depth of 300 µm, the compressive force measured is approximately 300 N, followed by force decay, resulting in a relatively consistent compressive force of approximately 205 N. At a compression depth of 500 µm, the compressive force measured is approximately 450 N, and after repeated cycles, force decay occurs, leading to a relatively consistent compressive force of approximately 310 N. At a compression depth of 700 µm, the compressive force measured is approximately 485 N, and after repeated cycles, force decay occurs, resulting in a relatively consistent compressive force of approximately 325 N. As shown in Table ; Fig. (c), when applying pressure with a compression depth of 100 µm, the compressive force measured for the TC-85 full specimens is approximately 28 N (2.8 kg). When applying pressure with a compression depth of 300 µm, the compressive force measured is approximately 320 N (32 kg), followed by force decay, resulting in a relatively consistent compressive force of approximately 240 N. At a compression depth of 500 µm, the compressive force measured is approximately 520 N (52 kg), and after repeated cycles, force decay occurs, leading to a relatively consistent compressive force of approximately 390 N. At a compression depth of 700 µm, the compressive force measured is approximately 625 N (62.5 kg), and after repeated cycles, force decay occurs, resulting in a relatively consistent compressive force of approximately 455 N. As shown in Fig. (a), when compressed to a depth of 100 µm, the compressive forces of the three specimens over the cycles were as follows: the PETG specimens exhibited a compressive force of approximately 15 N. The TC-85 blank specimen initially exhibited a compressive force of less than 25 N, which decreased to less than 20 N as the number of cycles increased. The TC-85 full specimens exhibited an initial compressive force of approximately 30 N and experienced force decay. As shown in Fig. (b), when compressed to a depth of 300 µm, the compressive forces of the three specimens over the cycles were as follows: the PETG specimens exhibited a compressive force of approximately 50 N. The TC-85 blank specimen initially exhibited a compressive force of more than 300 N, which decreased to approximately 200 N as the number of cycles increased. The TC-85 full specimens demonstrated an initial compressive force of more than 300 N, which decayed to less than 250 N. As shown in Fig. (c), when compressed to a depth of 500 µm, the compressive forces of the three specimens over the cycles were as follows: the PETG specimens exhibited a compressive force of less than 100 N. The TC-85 blank specimen initially exhibited a compressive force of approximately 400 N, which decreased to approximately 310 N as the number of cycles increased. The TC-85 full specimens exhibited an initial compressive force of approximately 400–500 N and experienced force decay. As shown in Fig. (d), when compressed to a depth of 700 µm, the compressive forces of the three specimens over the cycles were as follows: the PETG specimens exhibited a compressive force of more than 100 N. The TC-85 blank specimen initially exhibited a compressive force of less than 500 N, which decreased to more than 300 N as the number of cycles increased. The TC-85 full specimens showed an initial compressive force of more than 600 N, which decayed to more than 450 N. In this study, the differences in materials and thicknesses were determined, and the changes in compressive force over the cycles were measured. Based on the statistical analysis results and the graphs in Figs. and , the null hypothesis of the study, “there is no difference in the compressive force due to the difference in material and thickness for each specimen,” was rejected. When comparing the results on the graph, TC-85 blank and TC-85 full showed relatively smaller differences than PETG, implying that the effect of the difference in the material was greater than the difference in thickness. When measuring compressive force with varying thicknesses of the same material (TC-85), the significant change in compressive force observed at 300 µm suggests that a thickness of 0.3 mm should be considered when designing the inner surface. However, applying a strictly customized CPR design that follows the curvature of specific teeth in a clinical setting may yield different results. The experimental results revealed that, compared to the TFA PETG specimens (Control group 1), the 3DPA TC-85 specimens (Experimental group and Control group 2) exhibited a wide range of compressive strength differences owing to the material thickness and higher compressive endurance. By utilizing a broad spectrum of compressive strengths, TC-85 demonstrated superior applicability for clinical purposes by allowing the design of devices with varying inner thicknesses for application to individual teeth (Fig. ). When the thickness of the TC-85 specimens was varied, similar results were observed for both the specimens with unfilled embossed areas (TC-85 blank; Control group 2) and those with filled embossed areas (TC-85 full; Experimental group). Planned tooth movement requires customized changes in the thickness of the embossed areas within the device itself, and the experimental results suggest that 3DPA can facilitate this. The fact that the 3DPA material (TC-85) exhibited better mechanical properties than the TFA material (PETG) under compressive force indicates that the 3DPA material has a high potential to maintain consistent mechanical properties, such as masticatory pressure, under compression. This finding suggests that the 3DPA can withstand a wide range of variations in the oral environment (stability). Additionally, the TC-85 full specimens demonstrated the highest values within the clinical masticatory pressure range of 500–600 N, indicating that the force transmitted through biting can be applied for posterior intrusion. This would be beneficial in cases involving an anterior open bite due to posterior extrusion, as it can be favorably applied to the formation of posterior bite blocks for posterior intrusion. Furthermore, appropriately designing the 3DPA as a retainer could help maintain an occlusion established through treatment for an extended period and prevent relapse of the open bite. Suggesting the application of CPR modeling for the treatment of an anterior open bite, Fig. shows how the posterior bite block can be formed using a 3D modeling program (Materialize Magics 25.01). The areas requiring the posterior bite block (indicated in light green) were selected and given a negative offset of 500 µm. As shown in the orange-marked area on the left, a posterior bite block of 500 µm could be formed on the inner surface of the clear aligner. According to Lee et al. , 3DPA exhibits weaker and more flexible characteristics in terms of tensile strength than TFA. This, combined with our experimental results showing that the 3DPA exhibited stronger mechanical properties under compressive force, suggests that specific areas of the clear aligner designed to induce tooth movement can be made strong and rigid, whereas the overall strength of the clear aligner, besides these specific areas, can be made flexible and soft to promote physiological tooth movement. However, as the specimen thickness increases, rigidity also increases, which could lead to patient discomfort and excessive force on the teeth. Clinicians should carefully select a customized and optimized thickness based on tooth movement speed, mobility, and safety. The pressure measured in the specimens represents the force exerted by the teeth on the clear aligner when the device is worn and, conversely, the reaction force with which the clear aligner presses back on the teeth, transferring pressure to the periodontal ligament. In clinical situations where no additional strong external forces, such as occlusal forces, are applied, the actual force delivered to the teeth is expected to be lower than the experimental values presented. In addition to the direct occlusal force shown in Fig. , which is transmitted as a compressive force to the teeth, the compressive force applied to the buccal and lingual surfaces should also be considered. The compressive force exerted on the clear aligner corresponded to the reaction force as the teeth moved to their planned positions in the setup. Although the direct measurement of this force is challenging, the use of materials with mechanical properties capable of accommodating a broad range of compressive forces is expected to facilitate efficient tooth movement in various clinical scenarios. Because this study was not conducted in vivo with actual teeth and oral environments, the results cannot be directly correlated with real clinical situations. Further studies are warranted to determine the ideal form and thickness of clear aligners for achieving planned tooth movements, such as tooth inclination and bodily movement, as intended by the practitioner. This study investigated the mechanical properties of two dental materials (PETG and TC-85) used in clear aligners. Future research should focus on the forces measured on teeth during tooth movement with clear aligners (in vivo), according to the different patterns of tooth movement. The shape of the teeth varies widely, and malformed teeth deviate from typical forms. For instance, the diminutive shape of the maxillary lateral incisors is known to occur in approximately 1.8% of the population . The presence of attachments or ridged areas on the appliance is essential . The results of this study suggest that the 3DPA can be custom-designed for the efficient movement of individual teeth. Unlike TFA, 3DPA allows for the design of appliances that meet the practitioner’s plan (comparison of PETG and TC-85 full). In typical thermoforming, a printed model shaped according to the desired tooth movement is required, and a clear aligner is produced by thermoforming a transparent sheet over this model . Therefore, the shapes and sizes of the inner surfaces of the aligners are limited. In contrast, the 3D direct printing method has no such limitations, making it more advantageous , . Therefore, the advantages of the direct printing method in producing customized clear aligners for efficient movement of each tooth are expected to be significant. In the future, the primary tasks of orthodontists will likely involve developing and selecting optimized designs that are more effective for desired tooth movements, such as tooth rotation, tipping, and bodily movement, while considering the shape of the teeth. Additionally, considering the results of this study, changes in the inner surface design (RPA and CPR) are expected to function effectively without using the attachments for posterior intrusion or anterior rotation and torque control. This can possibly reduce the number of attachments required adopting CPR (Fig. ). However, this hypothesis requires in vivo validation in follow-up studies to confirm its practical application and effectiveness in orthodontic treatment. In addition to not being an in vivo experiment, another limitation of this study was that the specimen shapes were standardized for quantitative comparison, indicating that strictly defined CPR specimens were not created. Clear aligner designs were not modified to match the unique shapes of individual teeth. However, by varying the thickness of the RPA (comparison of the TC-85 blank and TC-85 full), the potential superiority of the CPR was identified. The solid specimens (TC-85 full) exhibited a wide range of compressive and maximum strengths, suggesting that customized CPR-shaped designs tailored to the unique shapes of individual teeth could exert optimized forces on each tooth. Further in vivo research is essential to explore the impact of factors such as the intraoral environment, cyclic loading in various orientations, and patient-specific variability. Future studies should incorporate clinical trials to validate the compressive strength benefits of 3DPA materials under realistic conditions, taking into account the variability in tooth morphology and the complexity of treatment. 3DPA allows for the adjustment of the device’s shape and inner thickness corresponding to specific teeth according to the practitioner’s plan for the planned movement of certain teeth, and it can create ridged areas (RPA and CPR) on specific parts. Compressive strength measurements of the three specimens (PETG, TC-85 blank, and TC-85 full) based on thickness indicated that TC-85 full exhibited the broadest range and highest compressive strength, suggesting the highest potential for application in various clinical situations. Changes in the inner thickness of the device and the creation of ridged areas can apply a selective force for the targeted tooth surface. Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6 Supplementary Material 7 Supplementary Material 8 Supplementary Material 9 Supplementary Material 10 |
Telehealth in a paediatric developmental metropolitan assessment clinic: Perspectives and experiences of families and clinicians | fdc688b1-0d25-4689-ad4d-22b06d219057 | 9615062 | Pediatrics[mh] | TELEHEALTH IN PAEDIATRIC OUTPATIENT CONSULTATIONS There has been increase in research examining the acceptability and effectiveness of telehealth in the paediatric healthcare setting. Many paediatric outpatient clinics, for example, ophthalmology, orthopaedics and pre‐ and postoperative clinics, include history taking and clinical interview as part of their service. Though ordinarily conducted face to face, this can be easily delivered via telehealth. Telehealth consultations have been found to be highly accepted by families and clinicians for outpatient appointments in many countries such as Australia, Canada, the United Kingdom and the United States. , , , , , , , Patients, clinicians and referrers of paediatric outpatient services have expressed a willingness to use telehealth, with the advantages relating to convenience and cost savings. , However, the potential technical difficulties, concerns about child participation in the telehealth session, lack of physical interaction and preference for face‐to‐face appointments were reported to be the main barriers to telehealth uptake. , , , , Due to the circumstances surrounding COVID‐19, there has been an increased willingness to use telehealth, recognizing the importance of balancing the need for accessing services while adhering to physical distancing guidelines. There is a need to address these impediments, which, if mitigated, could increase the ability of clinical services to be delivered via telehealth in the context of increasing acceptability by families and clinicians.
TELEHEALTH DIAGNOSTIC ASSESSMENT OF DEVELOPMENTAL DISORDERS Diagnostic assessments for children for whom there are developmental concerns have traditionally been conducted in the face‐to‐face setting and can take many hours to complete. Such assessments require expertise and utilize a multidisciplinary approach to understand the complex and dynamic nature of the child–environment interaction on development. The challenge of using telehealth in diagnosing developmental disabilities is manyfold. Issues specific to telehealth diagnostic processes pertain to missing out nuances of child responses, not being able to completely assess parental psychological and emotional states and not being able to directly play and interact, as well as interruptions due to connectivity and technical glitches. Evidence on the use of telehealth for diagnostic and developmental assessments is slowly emerging, but still limited. Research has shown that diagnostic interviews can be conducted via telehealth such as The Autism Diagnostic Interview‐Revised and Developmental, Dimensional and Diagnostic Interview. , Novel telehealth diagnostic assessments of autism spectrum disorder (ASD), including the Brief Observation of Symptoms of Autism, Tele‐ASD‐Peds and the Naturalistic Observation Diagnostic Assessment, have been developed and demonstrate promise through preliminary findings. , , , Telehealth‐delivered standardized cognitive and language assessments for children have demonstrated high fidelity, reliability and acceptability. , , However, further work is needed to understand parents' and clinicians' perceptions and confidence in using telehealth within the clinical setting.
DEVELOPMENT OF A HYBRID SERVICE MODEL The onset of the COVID‐19 pandemic brought a great deal of uncertainty and difficulty in predicting the return of face‐to‐face assessments. Consequently, many paediatric developmental diagnostic services have been faced with increasing waitlists of children with developmental, behavioural and psychosocial issues. It has become apparent that to maintain service delivery, new approaches are needed. The current study was conducted within a tertiary paediatric developmental assessment unit covering the Western Sydney Local Health District and offering a statewide service for children who do not have access to a local developmental assessment service within New South Wales, Australia. As this unit has contributed significantly to telehealth research in assessments of children , , with language and learning difficulties predating COVID‐19, it has existing infrastructure including technology and trained staff accustomed to the use of telehealth. This meant that during the first COVID‐19 lockdown in Australia, the service was able to shift service delivery from face‐to‐face clinics to telehealth. With restrictions imposed on face‐to‐face clinical appointments, the team planned to replace face‐to‐face with telehealth‐only consultations for 3 months (from April to June 2020), with a view to an additional face‐to‐face appointment when restrictions eased. From July 2020, the unit commenced a hybrid clinic model (see Figure ) developed as a planned response to the pandemic restrictions. Face‐to‐face appointments were conducted in accordance with the public health and hospital regulations around wearing masks, hand sanitization, sanitization of equipment and limiting the number of people per room, as well as reducing assessment duration to a maximum of 2 hours.
CURRENT STUDY Quality improvement initiatives have long been used for the ascertainment of the efficacy, reliability and safety of health services. As telehealth appointments were introduced with all families before face‐to‐face assessment, it was critical to ascertain the acceptability from the perspective of the participants. This project, therefore, aimed to obtain the perspectives of families and staff members regarding the use of telehealth as part of the service model within a developmental assessment clinic.
METHODS 5.1 The Plan Do Study Act cycle To inform future service development, evaluation using the Plan Do Study Act (PDSA) cycle (see Figure ) was implemented between 14 May 2021 and 15 July 2021. 5.1.1 Plan The unit developed a hybrid service delivery model in response to public health restrictions imposed on face‐to‐face interactions. This study was submitted and approved as a Quality Improvement project by the relevant Clinical Governance Unit (QIE‐2021‐02‐25) to assess the acceptability of the new clinic model and identify enablers and barriers. The parent/carer survey was developed by the Sydney Children's Hospitals Network to study the experiences and acceptance of patients/families using telehealth in outpatient clinics across the COVID‐19 period. The survey contained 24 questions and focused on 5 key areas: the ease of use, usefulness, patient/family experience, technical quality and usage intention. Multiple‐choice questions and Likert scales were used in the survey. 5.1.2 Do The unit implemented the hybrid service delivery model from July 2020. The hybrid clinic adopted by the unit was conducted over 2–3 separate occasions of service as follows: 1. Conducting multidisciplinary team clinical interview via telehealth. The Vineland Adaptive Behaviour Scales, Third Edition (Vineland‐3), was also administered if suitable. 2. Contacting school or preschool and allied health professionals between telehealth and face‐to‐face appointments. 3. Partial completion of the report before the face‐to‐face assessment. 4. Providing time‐limited, face‐to‐face standardized assessments such as the Wechsler Intelligence Scales for Children–Fifth Edition, the Wechsler Preschool and Primary Scale of Intelligence—Fourth Edition, Mullen Scales of Early Learning, Stanford–Binet Scales of Intelligence‐Fifth Edition, the Wechsler Adult Intelligence Scale‐Fourth Edition, the Wechsler Individual Achievement Test‐Third Edition and the Autism Diagnostic Observation Schedule‐Second Edition. 5. Feedback of assessment outcome to families via telehealth or face to face. Parents/carers of children aged between 0 and 18 years, who had a telehealth appointment as part of the diagnostic assessment within the unit between June 2020 and July 2021, were given information about the evaluation study. Towards the end of the assessment, verbal consent was obtained from parents/carers to email them the link to the survey. Participation in the survey was optional and anonymous. In addition, parents/carers not requiring an interpreter were asked if they were willing to be contacted by authors D. B. and E. C. at a later stage for a telephone interview to gain further feedback about the hybrid model of care. The interviews were approximately 10–15 min each. All interviews were voice‐recorded and followed a script (Table ), which were then transcribed verbatim. All identifiable information was removed at transcription. Demographic information regarding the children and families who completed the survey is shown in Table . Staff members were also invited to provide their feedback and experience of the hybrid service delivery model in a focus group. The focus group was led by an independent facilitator who did not work within the unit. Before commencing, all participants (14 staff members in total, comprising 2 paediatricians, 1 paediatric registrar, 2 neuropsychologists, 2 speech pathologists, 2 social workers, 1 clinical nurse consultant, 2 occupational therapists and 2 administrative officers) received an information sheet about the focus group and completed a written consent form. The focus group was conducted over 2 days, with each session lasting 2 hours. The focus group was voice‐recorded for later transcription. All identifiable information was removed at transcription. 5.1.3 Study The data collected from the parents/carers survey were analysed descriptively. The parents'/carers' interviews and staff focus group feedback were analysed thematically using the Framework approach. After transcription, authors D. B. and E. C. familiarized and inductively coded the transcripts independently. It is noteworthy that authors D. B., E. C. and N. O. did not actively take part in the focus group. Authors D. B., E. C. and N. O. then subsequently discussed and reviewed the codes, before grouping them into categories. Consensus agreement was reached by all authors that saturation was reached. 5.1.4 Act The themes derived from the parents'/carers' interviews and staff focus group by using the Framework approach informed the enablers and barriers of integrating telehealth into the hybrid diagnostic assessment process. Service delivery improvements were implemented according to the themes, which are described in the discussion section.
The Plan Do Study Act cycle To inform future service development, evaluation using the Plan Do Study Act (PDSA) cycle (see Figure ) was implemented between 14 May 2021 and 15 July 2021. 5.1.1 Plan The unit developed a hybrid service delivery model in response to public health restrictions imposed on face‐to‐face interactions. This study was submitted and approved as a Quality Improvement project by the relevant Clinical Governance Unit (QIE‐2021‐02‐25) to assess the acceptability of the new clinic model and identify enablers and barriers. The parent/carer survey was developed by the Sydney Children's Hospitals Network to study the experiences and acceptance of patients/families using telehealth in outpatient clinics across the COVID‐19 period. The survey contained 24 questions and focused on 5 key areas: the ease of use, usefulness, patient/family experience, technical quality and usage intention. Multiple‐choice questions and Likert scales were used in the survey. 5.1.2 Do The unit implemented the hybrid service delivery model from July 2020. The hybrid clinic adopted by the unit was conducted over 2–3 separate occasions of service as follows: 1. Conducting multidisciplinary team clinical interview via telehealth. The Vineland Adaptive Behaviour Scales, Third Edition (Vineland‐3), was also administered if suitable. 2. Contacting school or preschool and allied health professionals between telehealth and face‐to‐face appointments. 3. Partial completion of the report before the face‐to‐face assessment. 4. Providing time‐limited, face‐to‐face standardized assessments such as the Wechsler Intelligence Scales for Children–Fifth Edition, the Wechsler Preschool and Primary Scale of Intelligence—Fourth Edition, Mullen Scales of Early Learning, Stanford–Binet Scales of Intelligence‐Fifth Edition, the Wechsler Adult Intelligence Scale‐Fourth Edition, the Wechsler Individual Achievement Test‐Third Edition and the Autism Diagnostic Observation Schedule‐Second Edition. 5. Feedback of assessment outcome to families via telehealth or face to face. Parents/carers of children aged between 0 and 18 years, who had a telehealth appointment as part of the diagnostic assessment within the unit between June 2020 and July 2021, were given information about the evaluation study. Towards the end of the assessment, verbal consent was obtained from parents/carers to email them the link to the survey. Participation in the survey was optional and anonymous. In addition, parents/carers not requiring an interpreter were asked if they were willing to be contacted by authors D. B. and E. C. at a later stage for a telephone interview to gain further feedback about the hybrid model of care. The interviews were approximately 10–15 min each. All interviews were voice‐recorded and followed a script (Table ), which were then transcribed verbatim. All identifiable information was removed at transcription. Demographic information regarding the children and families who completed the survey is shown in Table . Staff members were also invited to provide their feedback and experience of the hybrid service delivery model in a focus group. The focus group was led by an independent facilitator who did not work within the unit. Before commencing, all participants (14 staff members in total, comprising 2 paediatricians, 1 paediatric registrar, 2 neuropsychologists, 2 speech pathologists, 2 social workers, 1 clinical nurse consultant, 2 occupational therapists and 2 administrative officers) received an information sheet about the focus group and completed a written consent form. The focus group was conducted over 2 days, with each session lasting 2 hours. The focus group was voice‐recorded for later transcription. All identifiable information was removed at transcription. 5.1.3 Study The data collected from the parents/carers survey were analysed descriptively. The parents'/carers' interviews and staff focus group feedback were analysed thematically using the Framework approach. After transcription, authors D. B. and E. C. familiarized and inductively coded the transcripts independently. It is noteworthy that authors D. B., E. C. and N. O. did not actively take part in the focus group. Authors D. B., E. C. and N. O. then subsequently discussed and reviewed the codes, before grouping them into categories. Consensus agreement was reached by all authors that saturation was reached. 5.1.4 Act The themes derived from the parents'/carers' interviews and staff focus group by using the Framework approach informed the enablers and barriers of integrating telehealth into the hybrid diagnostic assessment process. Service delivery improvements were implemented according to the themes, which are described in the discussion section.
Plan The unit developed a hybrid service delivery model in response to public health restrictions imposed on face‐to‐face interactions. This study was submitted and approved as a Quality Improvement project by the relevant Clinical Governance Unit (QIE‐2021‐02‐25) to assess the acceptability of the new clinic model and identify enablers and barriers. The parent/carer survey was developed by the Sydney Children's Hospitals Network to study the experiences and acceptance of patients/families using telehealth in outpatient clinics across the COVID‐19 period. The survey contained 24 questions and focused on 5 key areas: the ease of use, usefulness, patient/family experience, technical quality and usage intention. Multiple‐choice questions and Likert scales were used in the survey.
Do The unit implemented the hybrid service delivery model from July 2020. The hybrid clinic adopted by the unit was conducted over 2–3 separate occasions of service as follows: 1. Conducting multidisciplinary team clinical interview via telehealth. The Vineland Adaptive Behaviour Scales, Third Edition (Vineland‐3), was also administered if suitable. 2. Contacting school or preschool and allied health professionals between telehealth and face‐to‐face appointments. 3. Partial completion of the report before the face‐to‐face assessment. 4. Providing time‐limited, face‐to‐face standardized assessments such as the Wechsler Intelligence Scales for Children–Fifth Edition, the Wechsler Preschool and Primary Scale of Intelligence—Fourth Edition, Mullen Scales of Early Learning, Stanford–Binet Scales of Intelligence‐Fifth Edition, the Wechsler Adult Intelligence Scale‐Fourth Edition, the Wechsler Individual Achievement Test‐Third Edition and the Autism Diagnostic Observation Schedule‐Second Edition. 5. Feedback of assessment outcome to families via telehealth or face to face. Parents/carers of children aged between 0 and 18 years, who had a telehealth appointment as part of the diagnostic assessment within the unit between June 2020 and July 2021, were given information about the evaluation study. Towards the end of the assessment, verbal consent was obtained from parents/carers to email them the link to the survey. Participation in the survey was optional and anonymous. In addition, parents/carers not requiring an interpreter were asked if they were willing to be contacted by authors D. B. and E. C. at a later stage for a telephone interview to gain further feedback about the hybrid model of care. The interviews were approximately 10–15 min each. All interviews were voice‐recorded and followed a script (Table ), which were then transcribed verbatim. All identifiable information was removed at transcription. Demographic information regarding the children and families who completed the survey is shown in Table . Staff members were also invited to provide their feedback and experience of the hybrid service delivery model in a focus group. The focus group was led by an independent facilitator who did not work within the unit. Before commencing, all participants (14 staff members in total, comprising 2 paediatricians, 1 paediatric registrar, 2 neuropsychologists, 2 speech pathologists, 2 social workers, 1 clinical nurse consultant, 2 occupational therapists and 2 administrative officers) received an information sheet about the focus group and completed a written consent form. The focus group was conducted over 2 days, with each session lasting 2 hours. The focus group was voice‐recorded for later transcription. All identifiable information was removed at transcription.
Study The data collected from the parents/carers survey were analysed descriptively. The parents'/carers' interviews and staff focus group feedback were analysed thematically using the Framework approach. After transcription, authors D. B. and E. C. familiarized and inductively coded the transcripts independently. It is noteworthy that authors D. B., E. C. and N. O. did not actively take part in the focus group. Authors D. B., E. C. and N. O. then subsequently discussed and reviewed the codes, before grouping them into categories. Consensus agreement was reached by all authors that saturation was reached.
Act The themes derived from the parents'/carers' interviews and staff focus group by using the Framework approach informed the enablers and barriers of integrating telehealth into the hybrid diagnostic assessment process. Service delivery improvements were implemented according to the themes, which are described in the discussion section.
RESULTS 6.1 Parents'/carers' evaluation survey The online survey was sent to 61 parents/carers and 27 responses (44.3%) were received. Two surveys were excluded from the current study due to invalid responses, resulting in the inclusion of a total of 25 surveys in the analysis. Results indicated that 56.0% of parents/carers used telehealth for the first time (see Table ). Only 12.0% of the telehealth appointments took more than 10 min to set up and three telehealth appointments were unsuccessful. Two telehealth appointments required switching telehealth platforms due to poor visual and audio quality. The majority of parents/carers agreed that they were involved in decisions about their child's care and treatment (92%), felt that their child was treated respectfully (96%) and all parents/carers reported that the clinicians explained things in a way they could understand. Furthermore, 64% of parents/carers believed that their children felt comfortable during the telehealth appointment, while 28% of them were unsure about how comfortable their children felt. Most parents/carers (92.0%) were happy with the service their children received. Parents/carers perceived convenience, time saving and allowing for social distancing as the top three advantages of telehealth appointments. More than half (52%) of the respondents suggested that there were no disadvantages of having appointments via telehealth. Forty‐eight percent of parents/carers indicated that they were extremely likely to recommend telehealth to friends and family, with only 20% not so likely to recommend to others. However, 64% of parents or carers reported that they would use telehealth again and 12% were unsure. 6.2 Parents'/carers' semi‐structured interview A random sample of 11 parents/carers participated in the semi‐structured interview (see Table ). The age of the children ranged from 3 to 17 years (63.6% male). An overall positive experience was reported by families, even though some technical issues were present during the telehealth appointment: ‘I didn't really have anything negative besides when there are interruptions that you cannot help it’ (Child B). Families also commented that the staff were attentive, polite, thorough and respectful in the appointments: ‘Over the phone they were always respectful towards her, they listened to what we were saying’ (Child E). 6.2.1 Advantages of the split service delivery model Convenience and flexibility Families enjoyed the telehealth appointment for its convenience (see Figure ), as indicated by their report of being able to attend the appointment from anywhere: ‘we can go back and do the work because it is online… It was easy to fit around work. I don't need to take leave and my husband to be on that day’ (Child J). Families can save travel time to the hospital, be more flexible with their time and reduce financial cost: ‘We did not have to travel because (the appointment was) on a working day. I just had to take the time out… otherwise I have to plan for it and take another 2 or 3 h (off work and spend) 40 min there and 40 back and 1 h at the hospital. It did save commute time’ (Child C); ‘I think it was very efficient time wise. Both of us could be there to the hour, there is no travelling time and it was cheaper’ (Child I). Access to service during the pandemic Parents/carers valued the telehealth appointment because it continued to provide access to services amid physical distancing, lockdown and geographical distance: ‘Obviously due to COVID it was helpful. We didn't have to go out in the community and put ourselves at risk. Yes, so that was definitely helpful’ (Child E). Support to families Parents/carers indicated that they were being supported by clinicians during the telehealth appointments: ‘I wrote a lot of the stuff down like the questions we wanted to get answered and they answered everything we needed to know and put us in the direction that we needed to go’ (Child F). Parents/carers also expressed that the hybrid service delivery model during the pandemic allowed for the initiation of the assessment process and access to early intervention to commence before a face‐to‐face appointment: ‘It is a chance to clear the air or his progress and where he is up to and doctor explained… therapies needed to be done. It was clearly explained about my situation in both my child and everything went well with telehealth at home’ (Child H). 6.2.2 Disadvantages of the split service delivery model Technical issues Poor internet connectivity, audio issues and glitches on telehealth platforms were reported to be the common challenges that parents/carers encountered during the telehealth appointment: ‘The platform was difficult to get into’ (Child A); ‘There were a few hiccups with the freezing of the screen and things like that here and there but (the clinician) picked up where we left off when it came back to normal again during the time’ (Child B). Disengagement in telehealth appointment Children's attention was reported to vary, with some being more distractible when attending this style of appointment, while others were more focused: ‘I think (the clinician) can get a much better understanding of my child in particular from being in person rather than on a computer on a platform… he doesn't know the difference between the video call right at the end of the day but he video calls his father twice a day… and to him it's a game, it wasn't serious’ (Child A); ‘We are in a safe environment and they are comfortable and they are focussed on the screen’ (Child B). Limited direct observation of the child Parents/carers expressed concerns about completing the assessment with their child using only telehealth. They believed that the clinicians are not able to complete all assessments via telehealth or to fully observe and understand their child when observed through the computer: ‘I feel (the clinician) can't really assess, face to face is better so they can really assess my child’ (Child H). Limited experience of using telehealth Unfamiliarity with the telehealth platform and technology was also reported to be a challenge for this hybrid service delivery model. Some families had limited experience in using the technology: ‘I think there are people that are not very tech. It might be a bit difficult to get on line and log on and do’ (Child B). 6.2.3 Preference of appointment type Overall, despite the convenience, flexibility and opportunity to access the service during a pandemic, face‐to‐face appointments were perceived by parents/carers as being preferable over telehealth for engaging their child to gain a full understanding of their complex presentation: ‘For my daughter, I don't speak for other family, she can't really talk much because she can say some words she doesn't know how to talk on the phone you need to see her in person’ (Child G). The personal interaction that occurs in the context of in‐person appointments was also seen as preferable: ‘I think all in all I would prefer the in person even though it saves me a drive down there, I like to look at somebody in the eye and be in the same room when I talk to them as much as possible’ (Child D). Appointments for clinical interviews, assessment feedback and any follow‐up sessions that did not involve direct assessment of the child were perceived as being more suited to telehealth: ‘If you just want to know what is the feedback, what is the current state of things then I think telehealth is better’ (Child C); ‘It depends on what it is. If you are being tested obviously in person but if it is just catching up then telehealth would be fine with me’ (Child I); ‘I think it depends on what it is for. If it is a bit more hard to explain or you need to see the child in person. Sometimes it is a bit difficult if you on a screen or on a phone but I think it just varies depending on the appointment’ (Child B). While still having a positive experience in the telehealth appointment, some families where English was a second language preferred face‐to‐face appointment as it was easier for them to communicate in that context: ‘Overall it was positive but I have a little bit language barrier because I am not an English native speaker so I prefer face‐to‐face’ (Child K). Other families from a culturally and linguistically diverse background favoured a combination of face‐to‐face and telehealth appointments. There was no clear difference in the preference of appointment type between cultural and language backgrounds. There was also no particular trend in the preference of appointment type based on the age of the child, diagnostic outcomes or assessment completed. Nearly half of the families reported that a combination of telehealth and face‐to‐face appointments was preferable, with the type of appointment dependent on the context of the consultation, availability and participants involved in the appointment. 6.2.4 Areas of improvement While most families did not offer suggestions for improving the telehealth experience, a few parents/carers commented that improving the quality of the telehealth platform and providing clearer instructions for navigating the telehealth appointments would be beneficial: ‘…as long as people have the information of what to do and how to do it prior… if it was in advance then step by step, go to this, click on this, log onto this or a link. I just think that being prepared in advance would help a lot especially for those that are not sure and they can jump on and figure it out…’ (Child B). 6.3 Staff focus group 6.3.1 Advantages of the split service delivery model Convenience Staff members reported that some families appeared more comfortable with the telehealth appointments as they could remain at home and the reduction in hospital visits was perceived as convenient. The hybrid model was perceived to enable easier service access for families in rural and remote areas (see Figure ). Flexibility Clinicians indicated that utilizing telehealth promotes flexibility in clinical practice, work location and use of time. Clinicians felt that they could more easily make appropriate arrangements to meet the needs of families: ‘People have been able to work from home to do the interviews and some feedbacks. Parents that aren't able to spend the whole day can join in for just important parts or relevant parts of the assessment’. Some staff also commented that the hybrid model allowed them to work from home if they had slight physical symptoms, or were required to isolate, therefore allowing appointments to continue. Improved clinical service Clinicians perceived that the use of telehealth increased the engagement of different stakeholders such as caseworkers and other healthcare professionals involved in the care of the child, school staff and parents: ‘It allows the dad to be more involved within the feedback session or if split families to be able to attend it, mum and dad in the same space to give feedback to both parents at the same time without being physically together. We have also had good success with foster parents and the caseworker online with us to give feedback. That was fantastic’. Clinicians felt that they had the opportunity to gather more information after the initial telehealth consultation and therefore were better prepared for the upcoming face‐to‐face appointment with the families: ‘some of the clinicians, particularly the doctors who take the history like that they might have two weeks between history and the appointment to contact schools’. Comprehensive assessment and better communication between the children's care providers can be achieved. Improved assessment skills Staff have noted that over time, there has been improvement to service delivery using the hybrid model of assessment. This has included staff realizing that they have adapted communication styles and assessment techniques when relating to families online, resulting in what has been perceived to be an increase in parent and child engagement during telehealth. 6.3.2 Disadvantages of the hybrid service delivery model Technical issues Technology challenges from the hospital and family's end were reported to be a disadvantage of the hybrid delivery service model. Staff experienced different technical glitches when conducting telehealth appointments with families: ‘Often families were in poor internet connection areas. Our internet connection was quite poor as well’. They also reported that some families had bandwidth issues, ‘Even sometimes trying to get them on a mobile phone or a telephone could be difficult’, or that families were not financially able to upgrade their mobile data plan for more seamless telehealth appointments: ‘parents often ran out of money and then they didn't have access to the phone’. Challenges to engage with families Clinicians perceived that it is more difficult to get to know the child via telehealth, and that additional time is required to build rapport and trust with families when compared to face‐to‐face appointments. Reading body language and subtle behaviours of the child and family members was also more difficult with telehealth, resulting in challenges when building personal connection and providing emotional support: ‘I think we underestimate how much or how important that [rapport] is in building a relationship with our families and you know some of the gestures we use or the support we can offer them with a box of tissues or a warm word or stroke their arm or something. We can't do any of that to support them or even asking them questions and then becoming distressed so I miss that physical contact’. Distractions within the home could also affect rapport: ‘Parents were often at home stuck with kids not at school so there were a lot of other distractions going on at home’. Team cohesiveness Staff members reflected that since the hybrid model divides the assessment service into multiple appointments and team members may be connecting to appointments from different physical locations, there is an increase in disconnection amongst the group: ‘we check in with each other and [need] to find out what happened which we didn't have to do before’. Staff members reported that communication among the team has become more challenging under the hybrid service delivery model ‘now there is a lot more communication required from different members of the team’. Longer waitlist and increased staff workload The only appointments where clinicians felt an increase in workload and time were those involving interpreters. However, the administrative staff's workload did increase due to managing multiple bookings and cancellations. The current electronic booking systems did not enable them to alter appointments easily, resulting in more time and effort for rescheduling.
Parents'/carers' evaluation survey The online survey was sent to 61 parents/carers and 27 responses (44.3%) were received. Two surveys were excluded from the current study due to invalid responses, resulting in the inclusion of a total of 25 surveys in the analysis. Results indicated that 56.0% of parents/carers used telehealth for the first time (see Table ). Only 12.0% of the telehealth appointments took more than 10 min to set up and three telehealth appointments were unsuccessful. Two telehealth appointments required switching telehealth platforms due to poor visual and audio quality. The majority of parents/carers agreed that they were involved in decisions about their child's care and treatment (92%), felt that their child was treated respectfully (96%) and all parents/carers reported that the clinicians explained things in a way they could understand. Furthermore, 64% of parents/carers believed that their children felt comfortable during the telehealth appointment, while 28% of them were unsure about how comfortable their children felt. Most parents/carers (92.0%) were happy with the service their children received. Parents/carers perceived convenience, time saving and allowing for social distancing as the top three advantages of telehealth appointments. More than half (52%) of the respondents suggested that there were no disadvantages of having appointments via telehealth. Forty‐eight percent of parents/carers indicated that they were extremely likely to recommend telehealth to friends and family, with only 20% not so likely to recommend to others. However, 64% of parents or carers reported that they would use telehealth again and 12% were unsure.
Parents'/carers' semi‐structured interview A random sample of 11 parents/carers participated in the semi‐structured interview (see Table ). The age of the children ranged from 3 to 17 years (63.6% male). An overall positive experience was reported by families, even though some technical issues were present during the telehealth appointment: ‘I didn't really have anything negative besides when there are interruptions that you cannot help it’ (Child B). Families also commented that the staff were attentive, polite, thorough and respectful in the appointments: ‘Over the phone they were always respectful towards her, they listened to what we were saying’ (Child E). 6.2.1 Advantages of the split service delivery model Convenience and flexibility Families enjoyed the telehealth appointment for its convenience (see Figure ), as indicated by their report of being able to attend the appointment from anywhere: ‘we can go back and do the work because it is online… It was easy to fit around work. I don't need to take leave and my husband to be on that day’ (Child J). Families can save travel time to the hospital, be more flexible with their time and reduce financial cost: ‘We did not have to travel because (the appointment was) on a working day. I just had to take the time out… otherwise I have to plan for it and take another 2 or 3 h (off work and spend) 40 min there and 40 back and 1 h at the hospital. It did save commute time’ (Child C); ‘I think it was very efficient time wise. Both of us could be there to the hour, there is no travelling time and it was cheaper’ (Child I). Access to service during the pandemic Parents/carers valued the telehealth appointment because it continued to provide access to services amid physical distancing, lockdown and geographical distance: ‘Obviously due to COVID it was helpful. We didn't have to go out in the community and put ourselves at risk. Yes, so that was definitely helpful’ (Child E). Support to families Parents/carers indicated that they were being supported by clinicians during the telehealth appointments: ‘I wrote a lot of the stuff down like the questions we wanted to get answered and they answered everything we needed to know and put us in the direction that we needed to go’ (Child F). Parents/carers also expressed that the hybrid service delivery model during the pandemic allowed for the initiation of the assessment process and access to early intervention to commence before a face‐to‐face appointment: ‘It is a chance to clear the air or his progress and where he is up to and doctor explained… therapies needed to be done. It was clearly explained about my situation in both my child and everything went well with telehealth at home’ (Child H). 6.2.2 Disadvantages of the split service delivery model Technical issues Poor internet connectivity, audio issues and glitches on telehealth platforms were reported to be the common challenges that parents/carers encountered during the telehealth appointment: ‘The platform was difficult to get into’ (Child A); ‘There were a few hiccups with the freezing of the screen and things like that here and there but (the clinician) picked up where we left off when it came back to normal again during the time’ (Child B). Disengagement in telehealth appointment Children's attention was reported to vary, with some being more distractible when attending this style of appointment, while others were more focused: ‘I think (the clinician) can get a much better understanding of my child in particular from being in person rather than on a computer on a platform… he doesn't know the difference between the video call right at the end of the day but he video calls his father twice a day… and to him it's a game, it wasn't serious’ (Child A); ‘We are in a safe environment and they are comfortable and they are focussed on the screen’ (Child B). Limited direct observation of the child Parents/carers expressed concerns about completing the assessment with their child using only telehealth. They believed that the clinicians are not able to complete all assessments via telehealth or to fully observe and understand their child when observed through the computer: ‘I feel (the clinician) can't really assess, face to face is better so they can really assess my child’ (Child H). Limited experience of using telehealth Unfamiliarity with the telehealth platform and technology was also reported to be a challenge for this hybrid service delivery model. Some families had limited experience in using the technology: ‘I think there are people that are not very tech. It might be a bit difficult to get on line and log on and do’ (Child B). 6.2.3 Preference of appointment type Overall, despite the convenience, flexibility and opportunity to access the service during a pandemic, face‐to‐face appointments were perceived by parents/carers as being preferable over telehealth for engaging their child to gain a full understanding of their complex presentation: ‘For my daughter, I don't speak for other family, she can't really talk much because she can say some words she doesn't know how to talk on the phone you need to see her in person’ (Child G). The personal interaction that occurs in the context of in‐person appointments was also seen as preferable: ‘I think all in all I would prefer the in person even though it saves me a drive down there, I like to look at somebody in the eye and be in the same room when I talk to them as much as possible’ (Child D). Appointments for clinical interviews, assessment feedback and any follow‐up sessions that did not involve direct assessment of the child were perceived as being more suited to telehealth: ‘If you just want to know what is the feedback, what is the current state of things then I think telehealth is better’ (Child C); ‘It depends on what it is. If you are being tested obviously in person but if it is just catching up then telehealth would be fine with me’ (Child I); ‘I think it depends on what it is for. If it is a bit more hard to explain or you need to see the child in person. Sometimes it is a bit difficult if you on a screen or on a phone but I think it just varies depending on the appointment’ (Child B). While still having a positive experience in the telehealth appointment, some families where English was a second language preferred face‐to‐face appointment as it was easier for them to communicate in that context: ‘Overall it was positive but I have a little bit language barrier because I am not an English native speaker so I prefer face‐to‐face’ (Child K). Other families from a culturally and linguistically diverse background favoured a combination of face‐to‐face and telehealth appointments. There was no clear difference in the preference of appointment type between cultural and language backgrounds. There was also no particular trend in the preference of appointment type based on the age of the child, diagnostic outcomes or assessment completed. Nearly half of the families reported that a combination of telehealth and face‐to‐face appointments was preferable, with the type of appointment dependent on the context of the consultation, availability and participants involved in the appointment. 6.2.4 Areas of improvement While most families did not offer suggestions for improving the telehealth experience, a few parents/carers commented that improving the quality of the telehealth platform and providing clearer instructions for navigating the telehealth appointments would be beneficial: ‘…as long as people have the information of what to do and how to do it prior… if it was in advance then step by step, go to this, click on this, log onto this or a link. I just think that being prepared in advance would help a lot especially for those that are not sure and they can jump on and figure it out…’ (Child B).
Advantages of the split service delivery model Convenience and flexibility Families enjoyed the telehealth appointment for its convenience (see Figure ), as indicated by their report of being able to attend the appointment from anywhere: ‘we can go back and do the work because it is online… It was easy to fit around work. I don't need to take leave and my husband to be on that day’ (Child J). Families can save travel time to the hospital, be more flexible with their time and reduce financial cost: ‘We did not have to travel because (the appointment was) on a working day. I just had to take the time out… otherwise I have to plan for it and take another 2 or 3 h (off work and spend) 40 min there and 40 back and 1 h at the hospital. It did save commute time’ (Child C); ‘I think it was very efficient time wise. Both of us could be there to the hour, there is no travelling time and it was cheaper’ (Child I). Access to service during the pandemic Parents/carers valued the telehealth appointment because it continued to provide access to services amid physical distancing, lockdown and geographical distance: ‘Obviously due to COVID it was helpful. We didn't have to go out in the community and put ourselves at risk. Yes, so that was definitely helpful’ (Child E). Support to families Parents/carers indicated that they were being supported by clinicians during the telehealth appointments: ‘I wrote a lot of the stuff down like the questions we wanted to get answered and they answered everything we needed to know and put us in the direction that we needed to go’ (Child F). Parents/carers also expressed that the hybrid service delivery model during the pandemic allowed for the initiation of the assessment process and access to early intervention to commence before a face‐to‐face appointment: ‘It is a chance to clear the air or his progress and where he is up to and doctor explained… therapies needed to be done. It was clearly explained about my situation in both my child and everything went well with telehealth at home’ (Child H).
Families enjoyed the telehealth appointment for its convenience (see Figure ), as indicated by their report of being able to attend the appointment from anywhere: ‘we can go back and do the work because it is online… It was easy to fit around work. I don't need to take leave and my husband to be on that day’ (Child J). Families can save travel time to the hospital, be more flexible with their time and reduce financial cost: ‘We did not have to travel because (the appointment was) on a working day. I just had to take the time out… otherwise I have to plan for it and take another 2 or 3 h (off work and spend) 40 min there and 40 back and 1 h at the hospital. It did save commute time’ (Child C); ‘I think it was very efficient time wise. Both of us could be there to the hour, there is no travelling time and it was cheaper’ (Child I).
Parents/carers valued the telehealth appointment because it continued to provide access to services amid physical distancing, lockdown and geographical distance: ‘Obviously due to COVID it was helpful. We didn't have to go out in the community and put ourselves at risk. Yes, so that was definitely helpful’ (Child E).
Parents/carers indicated that they were being supported by clinicians during the telehealth appointments: ‘I wrote a lot of the stuff down like the questions we wanted to get answered and they answered everything we needed to know and put us in the direction that we needed to go’ (Child F). Parents/carers also expressed that the hybrid service delivery model during the pandemic allowed for the initiation of the assessment process and access to early intervention to commence before a face‐to‐face appointment: ‘It is a chance to clear the air or his progress and where he is up to and doctor explained… therapies needed to be done. It was clearly explained about my situation in both my child and everything went well with telehealth at home’ (Child H).
Disadvantages of the split service delivery model Technical issues Poor internet connectivity, audio issues and glitches on telehealth platforms were reported to be the common challenges that parents/carers encountered during the telehealth appointment: ‘The platform was difficult to get into’ (Child A); ‘There were a few hiccups with the freezing of the screen and things like that here and there but (the clinician) picked up where we left off when it came back to normal again during the time’ (Child B). Disengagement in telehealth appointment Children's attention was reported to vary, with some being more distractible when attending this style of appointment, while others were more focused: ‘I think (the clinician) can get a much better understanding of my child in particular from being in person rather than on a computer on a platform… he doesn't know the difference between the video call right at the end of the day but he video calls his father twice a day… and to him it's a game, it wasn't serious’ (Child A); ‘We are in a safe environment and they are comfortable and they are focussed on the screen’ (Child B). Limited direct observation of the child Parents/carers expressed concerns about completing the assessment with their child using only telehealth. They believed that the clinicians are not able to complete all assessments via telehealth or to fully observe and understand their child when observed through the computer: ‘I feel (the clinician) can't really assess, face to face is better so they can really assess my child’ (Child H). Limited experience of using telehealth Unfamiliarity with the telehealth platform and technology was also reported to be a challenge for this hybrid service delivery model. Some families had limited experience in using the technology: ‘I think there are people that are not very tech. It might be a bit difficult to get on line and log on and do’ (Child B).
Poor internet connectivity, audio issues and glitches on telehealth platforms were reported to be the common challenges that parents/carers encountered during the telehealth appointment: ‘The platform was difficult to get into’ (Child A); ‘There were a few hiccups with the freezing of the screen and things like that here and there but (the clinician) picked up where we left off when it came back to normal again during the time’ (Child B).
Children's attention was reported to vary, with some being more distractible when attending this style of appointment, while others were more focused: ‘I think (the clinician) can get a much better understanding of my child in particular from being in person rather than on a computer on a platform… he doesn't know the difference between the video call right at the end of the day but he video calls his father twice a day… and to him it's a game, it wasn't serious’ (Child A); ‘We are in a safe environment and they are comfortable and they are focussed on the screen’ (Child B).
Parents/carers expressed concerns about completing the assessment with their child using only telehealth. They believed that the clinicians are not able to complete all assessments via telehealth or to fully observe and understand their child when observed through the computer: ‘I feel (the clinician) can't really assess, face to face is better so they can really assess my child’ (Child H).
Unfamiliarity with the telehealth platform and technology was also reported to be a challenge for this hybrid service delivery model. Some families had limited experience in using the technology: ‘I think there are people that are not very tech. It might be a bit difficult to get on line and log on and do’ (Child B).
Preference of appointment type Overall, despite the convenience, flexibility and opportunity to access the service during a pandemic, face‐to‐face appointments were perceived by parents/carers as being preferable over telehealth for engaging their child to gain a full understanding of their complex presentation: ‘For my daughter, I don't speak for other family, she can't really talk much because she can say some words she doesn't know how to talk on the phone you need to see her in person’ (Child G). The personal interaction that occurs in the context of in‐person appointments was also seen as preferable: ‘I think all in all I would prefer the in person even though it saves me a drive down there, I like to look at somebody in the eye and be in the same room when I talk to them as much as possible’ (Child D). Appointments for clinical interviews, assessment feedback and any follow‐up sessions that did not involve direct assessment of the child were perceived as being more suited to telehealth: ‘If you just want to know what is the feedback, what is the current state of things then I think telehealth is better’ (Child C); ‘It depends on what it is. If you are being tested obviously in person but if it is just catching up then telehealth would be fine with me’ (Child I); ‘I think it depends on what it is for. If it is a bit more hard to explain or you need to see the child in person. Sometimes it is a bit difficult if you on a screen or on a phone but I think it just varies depending on the appointment’ (Child B). While still having a positive experience in the telehealth appointment, some families where English was a second language preferred face‐to‐face appointment as it was easier for them to communicate in that context: ‘Overall it was positive but I have a little bit language barrier because I am not an English native speaker so I prefer face‐to‐face’ (Child K). Other families from a culturally and linguistically diverse background favoured a combination of face‐to‐face and telehealth appointments. There was no clear difference in the preference of appointment type between cultural and language backgrounds. There was also no particular trend in the preference of appointment type based on the age of the child, diagnostic outcomes or assessment completed. Nearly half of the families reported that a combination of telehealth and face‐to‐face appointments was preferable, with the type of appointment dependent on the context of the consultation, availability and participants involved in the appointment.
Areas of improvement While most families did not offer suggestions for improving the telehealth experience, a few parents/carers commented that improving the quality of the telehealth platform and providing clearer instructions for navigating the telehealth appointments would be beneficial: ‘…as long as people have the information of what to do and how to do it prior… if it was in advance then step by step, go to this, click on this, log onto this or a link. I just think that being prepared in advance would help a lot especially for those that are not sure and they can jump on and figure it out…’ (Child B).
Staff focus group 6.3.1 Advantages of the split service delivery model Convenience Staff members reported that some families appeared more comfortable with the telehealth appointments as they could remain at home and the reduction in hospital visits was perceived as convenient. The hybrid model was perceived to enable easier service access for families in rural and remote areas (see Figure ). Flexibility Clinicians indicated that utilizing telehealth promotes flexibility in clinical practice, work location and use of time. Clinicians felt that they could more easily make appropriate arrangements to meet the needs of families: ‘People have been able to work from home to do the interviews and some feedbacks. Parents that aren't able to spend the whole day can join in for just important parts or relevant parts of the assessment’. Some staff also commented that the hybrid model allowed them to work from home if they had slight physical symptoms, or were required to isolate, therefore allowing appointments to continue. Improved clinical service Clinicians perceived that the use of telehealth increased the engagement of different stakeholders such as caseworkers and other healthcare professionals involved in the care of the child, school staff and parents: ‘It allows the dad to be more involved within the feedback session or if split families to be able to attend it, mum and dad in the same space to give feedback to both parents at the same time without being physically together. We have also had good success with foster parents and the caseworker online with us to give feedback. That was fantastic’. Clinicians felt that they had the opportunity to gather more information after the initial telehealth consultation and therefore were better prepared for the upcoming face‐to‐face appointment with the families: ‘some of the clinicians, particularly the doctors who take the history like that they might have two weeks between history and the appointment to contact schools’. Comprehensive assessment and better communication between the children's care providers can be achieved. Improved assessment skills Staff have noted that over time, there has been improvement to service delivery using the hybrid model of assessment. This has included staff realizing that they have adapted communication styles and assessment techniques when relating to families online, resulting in what has been perceived to be an increase in parent and child engagement during telehealth. 6.3.2 Disadvantages of the hybrid service delivery model Technical issues Technology challenges from the hospital and family's end were reported to be a disadvantage of the hybrid delivery service model. Staff experienced different technical glitches when conducting telehealth appointments with families: ‘Often families were in poor internet connection areas. Our internet connection was quite poor as well’. They also reported that some families had bandwidth issues, ‘Even sometimes trying to get them on a mobile phone or a telephone could be difficult’, or that families were not financially able to upgrade their mobile data plan for more seamless telehealth appointments: ‘parents often ran out of money and then they didn't have access to the phone’. Challenges to engage with families Clinicians perceived that it is more difficult to get to know the child via telehealth, and that additional time is required to build rapport and trust with families when compared to face‐to‐face appointments. Reading body language and subtle behaviours of the child and family members was also more difficult with telehealth, resulting in challenges when building personal connection and providing emotional support: ‘I think we underestimate how much or how important that [rapport] is in building a relationship with our families and you know some of the gestures we use or the support we can offer them with a box of tissues or a warm word or stroke their arm or something. We can't do any of that to support them or even asking them questions and then becoming distressed so I miss that physical contact’. Distractions within the home could also affect rapport: ‘Parents were often at home stuck with kids not at school so there were a lot of other distractions going on at home’. Team cohesiveness Staff members reflected that since the hybrid model divides the assessment service into multiple appointments and team members may be connecting to appointments from different physical locations, there is an increase in disconnection amongst the group: ‘we check in with each other and [need] to find out what happened which we didn't have to do before’. Staff members reported that communication among the team has become more challenging under the hybrid service delivery model ‘now there is a lot more communication required from different members of the team’. Longer waitlist and increased staff workload The only appointments where clinicians felt an increase in workload and time were those involving interpreters. However, the administrative staff's workload did increase due to managing multiple bookings and cancellations. The current electronic booking systems did not enable them to alter appointments easily, resulting in more time and effort for rescheduling.
Advantages of the split service delivery model Convenience Staff members reported that some families appeared more comfortable with the telehealth appointments as they could remain at home and the reduction in hospital visits was perceived as convenient. The hybrid model was perceived to enable easier service access for families in rural and remote areas (see Figure ). Flexibility Clinicians indicated that utilizing telehealth promotes flexibility in clinical practice, work location and use of time. Clinicians felt that they could more easily make appropriate arrangements to meet the needs of families: ‘People have been able to work from home to do the interviews and some feedbacks. Parents that aren't able to spend the whole day can join in for just important parts or relevant parts of the assessment’. Some staff also commented that the hybrid model allowed them to work from home if they had slight physical symptoms, or were required to isolate, therefore allowing appointments to continue. Improved clinical service Clinicians perceived that the use of telehealth increased the engagement of different stakeholders such as caseworkers and other healthcare professionals involved in the care of the child, school staff and parents: ‘It allows the dad to be more involved within the feedback session or if split families to be able to attend it, mum and dad in the same space to give feedback to both parents at the same time without being physically together. We have also had good success with foster parents and the caseworker online with us to give feedback. That was fantastic’. Clinicians felt that they had the opportunity to gather more information after the initial telehealth consultation and therefore were better prepared for the upcoming face‐to‐face appointment with the families: ‘some of the clinicians, particularly the doctors who take the history like that they might have two weeks between history and the appointment to contact schools’. Comprehensive assessment and better communication between the children's care providers can be achieved. Improved assessment skills Staff have noted that over time, there has been improvement to service delivery using the hybrid model of assessment. This has included staff realizing that they have adapted communication styles and assessment techniques when relating to families online, resulting in what has been perceived to be an increase in parent and child engagement during telehealth.
Staff members reported that some families appeared more comfortable with the telehealth appointments as they could remain at home and the reduction in hospital visits was perceived as convenient. The hybrid model was perceived to enable easier service access for families in rural and remote areas (see Figure ).
Clinicians indicated that utilizing telehealth promotes flexibility in clinical practice, work location and use of time. Clinicians felt that they could more easily make appropriate arrangements to meet the needs of families: ‘People have been able to work from home to do the interviews and some feedbacks. Parents that aren't able to spend the whole day can join in for just important parts or relevant parts of the assessment’. Some staff also commented that the hybrid model allowed them to work from home if they had slight physical symptoms, or were required to isolate, therefore allowing appointments to continue.
Clinicians perceived that the use of telehealth increased the engagement of different stakeholders such as caseworkers and other healthcare professionals involved in the care of the child, school staff and parents: ‘It allows the dad to be more involved within the feedback session or if split families to be able to attend it, mum and dad in the same space to give feedback to both parents at the same time without being physically together. We have also had good success with foster parents and the caseworker online with us to give feedback. That was fantastic’. Clinicians felt that they had the opportunity to gather more information after the initial telehealth consultation and therefore were better prepared for the upcoming face‐to‐face appointment with the families: ‘some of the clinicians, particularly the doctors who take the history like that they might have two weeks between history and the appointment to contact schools’. Comprehensive assessment and better communication between the children's care providers can be achieved.
Staff have noted that over time, there has been improvement to service delivery using the hybrid model of assessment. This has included staff realizing that they have adapted communication styles and assessment techniques when relating to families online, resulting in what has been perceived to be an increase in parent and child engagement during telehealth.
Disadvantages of the hybrid service delivery model Technical issues Technology challenges from the hospital and family's end were reported to be a disadvantage of the hybrid delivery service model. Staff experienced different technical glitches when conducting telehealth appointments with families: ‘Often families were in poor internet connection areas. Our internet connection was quite poor as well’. They also reported that some families had bandwidth issues, ‘Even sometimes trying to get them on a mobile phone or a telephone could be difficult’, or that families were not financially able to upgrade their mobile data plan for more seamless telehealth appointments: ‘parents often ran out of money and then they didn't have access to the phone’. Challenges to engage with families Clinicians perceived that it is more difficult to get to know the child via telehealth, and that additional time is required to build rapport and trust with families when compared to face‐to‐face appointments. Reading body language and subtle behaviours of the child and family members was also more difficult with telehealth, resulting in challenges when building personal connection and providing emotional support: ‘I think we underestimate how much or how important that [rapport] is in building a relationship with our families and you know some of the gestures we use or the support we can offer them with a box of tissues or a warm word or stroke their arm or something. We can't do any of that to support them or even asking them questions and then becoming distressed so I miss that physical contact’. Distractions within the home could also affect rapport: ‘Parents were often at home stuck with kids not at school so there were a lot of other distractions going on at home’. Team cohesiveness Staff members reflected that since the hybrid model divides the assessment service into multiple appointments and team members may be connecting to appointments from different physical locations, there is an increase in disconnection amongst the group: ‘we check in with each other and [need] to find out what happened which we didn't have to do before’. Staff members reported that communication among the team has become more challenging under the hybrid service delivery model ‘now there is a lot more communication required from different members of the team’. Longer waitlist and increased staff workload The only appointments where clinicians felt an increase in workload and time were those involving interpreters. However, the administrative staff's workload did increase due to managing multiple bookings and cancellations. The current electronic booking systems did not enable them to alter appointments easily, resulting in more time and effort for rescheduling.
Technology challenges from the hospital and family's end were reported to be a disadvantage of the hybrid delivery service model. Staff experienced different technical glitches when conducting telehealth appointments with families: ‘Often families were in poor internet connection areas. Our internet connection was quite poor as well’. They also reported that some families had bandwidth issues, ‘Even sometimes trying to get them on a mobile phone or a telephone could be difficult’, or that families were not financially able to upgrade their mobile data plan for more seamless telehealth appointments: ‘parents often ran out of money and then they didn't have access to the phone’.
Clinicians perceived that it is more difficult to get to know the child via telehealth, and that additional time is required to build rapport and trust with families when compared to face‐to‐face appointments. Reading body language and subtle behaviours of the child and family members was also more difficult with telehealth, resulting in challenges when building personal connection and providing emotional support: ‘I think we underestimate how much or how important that [rapport] is in building a relationship with our families and you know some of the gestures we use or the support we can offer them with a box of tissues or a warm word or stroke their arm or something. We can't do any of that to support them or even asking them questions and then becoming distressed so I miss that physical contact’. Distractions within the home could also affect rapport: ‘Parents were often at home stuck with kids not at school so there were a lot of other distractions going on at home’.
Staff members reflected that since the hybrid model divides the assessment service into multiple appointments and team members may be connecting to appointments from different physical locations, there is an increase in disconnection amongst the group: ‘we check in with each other and [need] to find out what happened which we didn't have to do before’. Staff members reported that communication among the team has become more challenging under the hybrid service delivery model ‘now there is a lot more communication required from different members of the team’.
The only appointments where clinicians felt an increase in workload and time were those involving interpreters. However, the administrative staff's workload did increase due to managing multiple bookings and cancellations. The current electronic booking systems did not enable them to alter appointments easily, resulting in more time and effort for rescheduling.
DISCUSSION This study was a quality improvement project looking at the perceptions of parents/carers and staff on the use of telehealth and the development of a hybrid service delivery model at a metropolitan developmental assessment clinic by utilizing the PDSA cycle. This study was developed to understand the experience of families and staff while adapting to a hybrid model for the administration of complex developmental diagnostic assessments (plan). The hybrid model was implemented to ensure service continuity despite pandemic restrictions (do). The hybrid model provided families with an alternative means to gain an understanding of their child's needs and to empower them to advocate for appropriate early intervention funding and services to be initiated in a timely manner. The new service delivery model was studied (do) to examine facilitators and barriers with the intention of improving future patient experience (study). The findings of this study demonstrated high acceptability of the integration of telehealth into the developmental diagnostic assessment service. The convenience and flexibility of telehealth appointments were commonly reported by families and staff. Families appreciated the continuation of services and support via telehealth during the COVID‐19 pandemic, whereas staff valued the application of telehealth to improve clinical service and professional skills. The feedback from families and staff informed the refinement and development of this service delivery model within the clinic (act). Our findings highlighted the importance of preparing parents and children and managing parent expectations before the telehealth appointment. Accordingly, information sheets were given and preappointment phone calls were made to families to explain the clinician's goals within the telehealth appointment and how they would complement face‐to‐face appointments within the hybrid service delivery model. This study also informed the need to reduce the burden on administrative staff in implementing online processes; identified unwieldy booking systems; and used the hybrid model to create a greater variety of appointment types. This has increased the number of patients who can be fully assessed over a set period of time. As time progresses and with increased familiarity, systems will be further refined to increase the efficiency of administrative and clinical procedures. Furthermore, our findings highlighted the need to increase staff proficiency and comfort levels using telehealth for developmental diagnostic assessment. The conversational aspects of the assessment process were identified as being more readily transferable to the telehealth environment, with more work needing to be done to determine when telehealth may provide an appropriate alternative option to face‐to‐face assessment while maintaining high fidelity and reliability over time. Hence, our clinicians have received additional training on diagnostic assessments that can be reliably conducted via telehealth. This is not only beneficial for overcoming pandemic‐related barriers but also for children and families living in rural and/or remote regions of Australia, where access to such services is limited. Due to the diagnostic complexity of the population who attend developmental services, there is no ‘one size fits all’ approach. While this study focussed on parental and staff perceptions and experiences, ongoing advancements in telehealth for direct developmental assessments will mean that more research is needed to explore online protocols for developmental and autism assessments; the profile of children and families who best suit these assessments; ways to ensure the reliability/validity of the assessments; and increase uptake by referrers and parents/carers. Accordingly, our research team has been developing new projects to further evaluate the acceptability of the telehealth diagnostic assessment and consumers' feedback on the assessment process. There is a need to explore the relationship between sociocultural, educational and practice‐related factors that influence comfort levels of clinicians and administrators towards the uptake, utilization and dissemination of telehealth in clinical practice. 7.1 Limitations There are some limitations to this quality improvement project, which include the small sample size of parents/carers who completed the online telehealth questionnaire and interviews. A larger sample size would draw on a greater range of experiences. Those parents/carers who completed the questionnaire and were interviewed had adequate English skills to effectively communicate with the research team and no interpreter was used. Only those parents who opted for telehealth assessment were included in the study. The latter two factors reflect possible bias in the sampling and therefore may not identify the full range of issues and complexities faced by families from culturally and linguistically diverse groups and the broader population when engaging in telehealth services. Additionally, the interviews with parents/carers were completed within a range of 1 week to 5 months post telehealth appointments. This variation and hence reliance on parent/carer memory could influence the quality and specificity of the information obtained.
Limitations There are some limitations to this quality improvement project, which include the small sample size of parents/carers who completed the online telehealth questionnaire and interviews. A larger sample size would draw on a greater range of experiences. Those parents/carers who completed the questionnaire and were interviewed had adequate English skills to effectively communicate with the research team and no interpreter was used. Only those parents who opted for telehealth assessment were included in the study. The latter two factors reflect possible bias in the sampling and therefore may not identify the full range of issues and complexities faced by families from culturally and linguistically diverse groups and the broader population when engaging in telehealth services. Additionally, the interviews with parents/carers were completed within a range of 1 week to 5 months post telehealth appointments. This variation and hence reliance on parent/carer memory could influence the quality and specificity of the information obtained.
CONCLUSION The importance of being able to connect with and access health services during a time of public health restrictions forbidding prolonged face‐to‐face contact is reflected in the feedback received from both parents/carers and staff. In this study, factors that contributed to the successful delivery of telehealth services were identified by both parents/carers and clinicians. This mode of service delivery received high acceptance from both groups. The identification of barriers, such as technical issues, limited ability to build rapport between families/clinicians and limited opportunities for direct assessment of the child, provides clinicians with the opportunity to put strategies in place to reduce these barriers and further increase the success of telehealth within this clinical setting. Further studies and research into effective means of directly observing and using standardized assessments via telehealth would be most valuable to increase the scope, validity and reliability of the use of telehealth within a paediatric diagnostic developmental service. There is also the potential to use telehealth for developmental screening programmes enabling families to access relevant services in a timely manner. With increased evidence supporting the equivalence of telehealth and face‐to‐face assessments, it is expected that uptake of telehealth by parents and clinicians will increase. Research should also obtain opinions of those who did not opt for telehealth to determine barriers to uptake of telehealth. Further research into understanding the factors affecting team cohesiveness and client/clinician interactions when working via telehealth would also facilitate improved telehealth service delivery, particularly within a complex clinical service, and result in a continuance of hybrid service delivery beyond the immediate COVID‐19 pandemic. This study indicates that there are many positive aspects of delivering a service via telehealth, even within a complex paediatric setting. Even when public health restrictions forbidding prolonged social contact cease, there is a place for telehealth service delivery to provide the flexibility, convenience and cost‐saving advantages identified by both consumers and clinicians.
All authors have made substantial contributions to the work. Esther Chan, Natalie Ong and Diana Barnett substantially contributed to the study conception, and all authors contributed to the design. Esther Chan, Natalie Ong and Diana Barnett contributed to the data collection, analysis and interpretation of data for the research findings. All authors reviewed drafts of the manuscript and revised the manuscript critically for important intellectual content. All authors have read and approved the final manuscript, and have agreed to the listing order for authors.
The authors, Marie Antoinette Hodge, Suzi Drevensek, Marcia Williamsz and Natalie Silove, were involved in the staff focus group as participants.
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MLPA and DNA index improve the molecular diagnosis of childhood B-cell acute lymphoblastic leukemia | 5f4210aa-93d6-42d6-a4ea-d98894f219da | 7359332 | Pathology[mh] | As the most common pediatric cancer, acute lymphoblastic leukemia (ALL) accounts for approximately 25% of childhood malignancies. With improved risk-directed treatment and supportive care, the overall 5-year event-free survival rates for this disease now exceed 80% in developed countries – . The two major features of risk-directed therapy are based on the genetic alterations of the leukemic cells at diagnosis and the determination of initial treatment response (measured by minimal residual disease, MRD, after induction therapy). The interpretation of MRD levels depends upon the subtype of ALL , . Although karyotyping has been the most common approach for detection of numerical chromosomal changes, molecular methods may enhance their detection in childhood B-ALL. Multiplex Ligation-dependent Probe Amplification (MLPA) is a sensitive method based upon the multiplex polymerase chain reaction and capillary electrophoresis that detects multiple copies of around 50 different genomic DNA targets. It has the advantage of lower price and quicker turn-around time than DNA arrays for identification of the important genetic alterations and is now widely used for detection of the important copy number changes in ALL , . Gain or loss of whole chromosomes (aneuploidy) and intrachromosomal amplification of chromosome 21 (iAMP21) accounts for almost 30% of childhood B-ALL identified by traditional methods. High hyperdiploidy with greater than 50 chromosomes comprises up to 30% of childhood B-ALL and most commonly involves gains of chromosomes X, 4, 10, 14, 17 and 21 . It is associated with a good outcome, even in patients with induction failure . Hypodiploidy with less than 44 chromosomes is less common (found in approximately 3% of cases) and is associated with an inferior outcome. Hypodiploid B-ALL can be further divided into three subgroups according to chromosome number. The most common are near-haploidy with 24–31 chromosomes and low-hypodiploidy with 32–39 chromosomes. High-hypodiploidy with 40–43 chromosomes is rare. Low-hypodiploid ALL has a high incidence of TP53 germline mutations . DNA index (DI) is a well-established method for detection of high hyperdiploidy. The MLPA telomere kit identifies specific gain or loss of individual chromosomes and is suitable for screening for whole chromosome numerical changes , . Masked low hypodiploidy, manifesting as doubling of the low hypodiploid chromosome number, can be difficult to diagnose . Here we show that MLPA and DI are useful in its detection, as confirmed by single-nucleotide polymorphism (SNP) arrays and short tandem repeats (STR). B-ALL patients with iAMP21-ALL were initially shown to have a high relapse risk on standard chemotherapy , . It was later demonstrated that treatment on intensive therapy regimens significantly reduced their risk of relapse – . In childhood B-ALL, SNP arrays have successfully identified copy number abnormalities (CNA) involving several signaling pathways. For example, deletions of a number of genes within the B-cell differentiation pathway were identified, including PAX5 , EFB1 and IKZF1 , . Clinically, IKZF1 alterations have been associated with a poor outcome, particularly in association with Ph-positive (Philadelphia chromosome/ BCR-ABL1 positive), and Ph-like ALL (Philadelphia chromosome/ BCR-ABL1 negative but the expression profiles were similar to Ph-positive ALL) – . Ph-like and iAMP21-ALL have been proposed as novel subtypes of B-ALL in the recent WHO classification of hematologic malignancies, due to their poor prognostic associations . In this project, we have used MLPA and DI to study CNA in B-ALL. We show that these approaches are complementary to cytogenetics in improving detection of genetic alterations in childhood B-ALL. Patients and protocols Diagnostic bone marrow (BM) or peripheral blood was obtained from 233 children with B-ALL from January 2002 to July 2018 at the National Taiwan University Hospital. A total of 108 patients were treated on the Taiwan Pediatric Oncology Group TPOG-ALL-2002 protocol, while 125 were treated on TPOG-ALL-2013. Diagnosis of B-ALL was based on BM morphology and the immunophenotype of leukemic cells was determined by flow cytometry. Conventional cytogenetic analysis was carried out as part of the routine work-up . The risk-directed TPOG protocols consist of multiple chemotherapeutic agents of different intensities. The treatment protocol was intensified if complete remission was not achieved after initial induction therapy. After 2013, MRD levels were added to risk assignment for therapy. Events were defined as any relapse, death, or secondary malignancy. The Institutional Review Board of National Taiwan University Hospital approved the study and all of the participants or their guardians provided written informed consent in accordance with the Declaration of Helsinki. Details of the protocols and risk group assignment have been published elsewhere , , . We have summarized the risk classification of protocols in the . Genomic DNA extraction Lymphoblasts were purified from bone marrow or peripheral blood specimens using the Ficoll-Paque centrifugation method, according to the manufacturer’s instructions (GE Healthcare, Piscataway, NJ, USA). Genomic DNA was extracted from leukemic cells using standard phenol/chloroform-based methods. Briefly, 1 million cells were lysed in 10 mM Tris–HCl, 10 mM NaCl, 10 mM EDTA, 20 μg proteinase K, and 0.5% SDS by incubating at 37 °C for 16 h. Total RNA was further removed by adding 500 μg PureLink RNase A (Invitrogen, USA) and incubating for 10 min at 37 °C. An equal volume of phenol–chloroform–isopropanol (25:24:1) was added to lysates and mixed by shaking vigorously, followed by centrifugation at 16,100 × g at 4 °C for 5 min. The upper aqueous phase was transferred to a fresh tube; genomic DNA was then precipitated by adding 2× volume − 80 °C 100% ethanol. The DNA pellet was washed with 75% ethanol and rehydrated with Tris–EDTA buffer. The concentration of DNA was determined using a NanoDrop 1,000 spectrophotometer (Thermo Fisher Scientific, Waltham, Massachusetts, USA) . MLPA analysis Genomic DNA was analyzed using the SALSA MLPA kit (MRC-Holland, Amsterdam, the Netherlands), according to manufacturer’s instructions. The PCR fragments were separated by capillary electrophoresis on a Life Technologies 3,500 Genetic Analyzer (Thermo Fisher Scientific, Waltham, MA, USA). MLPA data were analyzed using Coffalyser.Net v.140721.1958 (MRC-Holland, Amsterdam, The Netherlands). Probe ratio between 0.75 and 1.3 were considered to be within the normal range. Probe ratio below 0.75 or above 1.3 indicated deletion or gain, respectively. Probe ratio below 0.25 or above 1.8 indicated biallelic deletion or amplification. SALSA MLPA P335 ALL-IKZF1 probemix was used for detection of alterations of EBF1 , IKZF1 , CDKN2A , CDKN2B , PAX5 , ETV6 , RB1 and BTG1 genes. SALSA MLPA P327 iAMP21-ERG probemix was used for detecting alterations of ERG gene and iAMP21. SALSA MLPA P329 CRLF2-CSF2RA-IL3RA probemix was used for detecting P2RY8-CRLF2 (PAR1 deletion). Analysis of ploidy status Ploidy status was evaluated by SALSA MLPA P036 Subtelomeres Mix 1 probe mix. Whole chromosomal gain or loss was defined when two probes targeting p and q arms of the same chromosome were respectively gained or deleted simultaneously. Chromosome 19p deletions were defined when the probe targeted the p arm of chromosome 19 was deleted while q arm was normal. DNA index measured by flow cytometry Freshly prepared or frozen leukemia samples were used for DNA index analysis. Peripheral blood derived from normal healthy individuals was used as controls for diploidy. Mononuclear cells were isolated by Ficoll-Paque (GE Healthcare, Chicago, IL, USA) according to the manufacturer’s instructions. Three cell suspensions were prepared: tube A was a mixture of leukemia cells and normal PBMCs in equal numbers; tubes B and C contained normal PBMCs or leukemia cells alone. Each cell suspension (2 million cells) was fixed with 70% ethanol overnight at – 20 °C. Fixed cells were washed with 1× PBS and then incubated with propidium iodide (50 μg) and RNase (10 μg) for 1 h on ice. Cells were filtered with 100 μm cell strainer and then analyzed by FACSCalibur (BD, Franklin Lakes, NJ, USA). DNA quantity of an individual cell population was determined and DNA index represents the ratio of leukemia sample/normal PBMCs fluorescence calculated from tube A. Tubes B and tube C were used as reference to distinguish the leukemia from PBMC peaks in tube A. Theoretical DNA index (tDI) was calculated using the formula: tDI = chromosome numbers × 0.0202 + 0.0675 . Statistical analysis Pearson's correlations, the coefficient of determination and p-values were carried out between the results of DI and tDI from MLPA and cytogenetics. Fisher’s exact test was performed to evaluate the enrichment of 19p deletion in TCF3 gene rearranged ALL. The log-rank test compared different survival curves between patients with different major genetic subtypes, patient with or without IKZF1 deletion and patients with or without IKZF1 plus . Overall survival (OS) was defined as diagnosis to death. Patients who did not suffer any adverse events within the follow-up period were censored. Event-free survival (EFS) of patients with no response to chemotherapy (refractory), death, and second relapse in induction was set to 0. Univariate and multivariate Cox regression were performed to evaluate hazard ratios (HR) and 95% confidence intervals (CI) of risk factors. All statistical analyses were performed using the Statistical Product and Services Solutions (SPSS) statistical package, v18.0 (IBM, Armonk, NY, USA). Diagnostic bone marrow (BM) or peripheral blood was obtained from 233 children with B-ALL from January 2002 to July 2018 at the National Taiwan University Hospital. A total of 108 patients were treated on the Taiwan Pediatric Oncology Group TPOG-ALL-2002 protocol, while 125 were treated on TPOG-ALL-2013. Diagnosis of B-ALL was based on BM morphology and the immunophenotype of leukemic cells was determined by flow cytometry. Conventional cytogenetic analysis was carried out as part of the routine work-up . The risk-directed TPOG protocols consist of multiple chemotherapeutic agents of different intensities. The treatment protocol was intensified if complete remission was not achieved after initial induction therapy. After 2013, MRD levels were added to risk assignment for therapy. Events were defined as any relapse, death, or secondary malignancy. The Institutional Review Board of National Taiwan University Hospital approved the study and all of the participants or their guardians provided written informed consent in accordance with the Declaration of Helsinki. Details of the protocols and risk group assignment have been published elsewhere , , . We have summarized the risk classification of protocols in the . Lymphoblasts were purified from bone marrow or peripheral blood specimens using the Ficoll-Paque centrifugation method, according to the manufacturer’s instructions (GE Healthcare, Piscataway, NJ, USA). Genomic DNA was extracted from leukemic cells using standard phenol/chloroform-based methods. Briefly, 1 million cells were lysed in 10 mM Tris–HCl, 10 mM NaCl, 10 mM EDTA, 20 μg proteinase K, and 0.5% SDS by incubating at 37 °C for 16 h. Total RNA was further removed by adding 500 μg PureLink RNase A (Invitrogen, USA) and incubating for 10 min at 37 °C. An equal volume of phenol–chloroform–isopropanol (25:24:1) was added to lysates and mixed by shaking vigorously, followed by centrifugation at 16,100 × g at 4 °C for 5 min. The upper aqueous phase was transferred to a fresh tube; genomic DNA was then precipitated by adding 2× volume − 80 °C 100% ethanol. The DNA pellet was washed with 75% ethanol and rehydrated with Tris–EDTA buffer. The concentration of DNA was determined using a NanoDrop 1,000 spectrophotometer (Thermo Fisher Scientific, Waltham, Massachusetts, USA) . Genomic DNA was analyzed using the SALSA MLPA kit (MRC-Holland, Amsterdam, the Netherlands), according to manufacturer’s instructions. The PCR fragments were separated by capillary electrophoresis on a Life Technologies 3,500 Genetic Analyzer (Thermo Fisher Scientific, Waltham, MA, USA). MLPA data were analyzed using Coffalyser.Net v.140721.1958 (MRC-Holland, Amsterdam, The Netherlands). Probe ratio between 0.75 and 1.3 were considered to be within the normal range. Probe ratio below 0.75 or above 1.3 indicated deletion or gain, respectively. Probe ratio below 0.25 or above 1.8 indicated biallelic deletion or amplification. SALSA MLPA P335 ALL-IKZF1 probemix was used for detection of alterations of EBF1 , IKZF1 , CDKN2A , CDKN2B , PAX5 , ETV6 , RB1 and BTG1 genes. SALSA MLPA P327 iAMP21-ERG probemix was used for detecting alterations of ERG gene and iAMP21. SALSA MLPA P329 CRLF2-CSF2RA-IL3RA probemix was used for detecting P2RY8-CRLF2 (PAR1 deletion). Ploidy status was evaluated by SALSA MLPA P036 Subtelomeres Mix 1 probe mix. Whole chromosomal gain or loss was defined when two probes targeting p and q arms of the same chromosome were respectively gained or deleted simultaneously. Chromosome 19p deletions were defined when the probe targeted the p arm of chromosome 19 was deleted while q arm was normal. Freshly prepared or frozen leukemia samples were used for DNA index analysis. Peripheral blood derived from normal healthy individuals was used as controls for diploidy. Mononuclear cells were isolated by Ficoll-Paque (GE Healthcare, Chicago, IL, USA) according to the manufacturer’s instructions. Three cell suspensions were prepared: tube A was a mixture of leukemia cells and normal PBMCs in equal numbers; tubes B and C contained normal PBMCs or leukemia cells alone. Each cell suspension (2 million cells) was fixed with 70% ethanol overnight at – 20 °C. Fixed cells were washed with 1× PBS and then incubated with propidium iodide (50 μg) and RNase (10 μg) for 1 h on ice. Cells were filtered with 100 μm cell strainer and then analyzed by FACSCalibur (BD, Franklin Lakes, NJ, USA). DNA quantity of an individual cell population was determined and DNA index represents the ratio of leukemia sample/normal PBMCs fluorescence calculated from tube A. Tubes B and tube C were used as reference to distinguish the leukemia from PBMC peaks in tube A. Theoretical DNA index (tDI) was calculated using the formula: tDI = chromosome numbers × 0.0202 + 0.0675 . Pearson's correlations, the coefficient of determination and p-values were carried out between the results of DI and tDI from MLPA and cytogenetics. Fisher’s exact test was performed to evaluate the enrichment of 19p deletion in TCF3 gene rearranged ALL. The log-rank test compared different survival curves between patients with different major genetic subtypes, patient with or without IKZF1 deletion and patients with or without IKZF1 plus . Overall survival (OS) was defined as diagnosis to death. Patients who did not suffer any adverse events within the follow-up period were censored. Event-free survival (EFS) of patients with no response to chemotherapy (refractory), death, and second relapse in induction was set to 0. Univariate and multivariate Cox regression were performed to evaluate hazard ratios (HR) and 95% confidence intervals (CI) of risk factors. All statistical analyses were performed using the Statistical Product and Services Solutions (SPSS) statistical package, v18.0 (IBM, Armonk, NY, USA). Frequency of copy number abnormalities in children with B-ALL The demographic, clinical, and laboratory characteristics of 233 children with B-ALL are shown in Table . The median age of the cohort was 5.4 years (range < 0.1–17.9 years); 95.3% of the patients were over 1 year of age. The molecular tests performed were those standardized for B-ALL diagnosis including: ETV6-RUNX1 , TCF3-PBX1 , BCR-ABL1 , P2RY8-CRLF2 and KMT2A-AFF1 for 220 samples. Detailed flow diagram of analysis used in this study is demonstrated in Supplementary Fig. . From MLPA testing, overall, 65.7% of the patients (153/233) harbored at least one abnormality (either deletion or amplification) involving the following genes— IKZF1 , CDKN2A / 2B , PAX5 , EBF1 , ETV6 , BTG1 , RB1 , ERG or PAR1 region, whereas the remaining 34.3% (80/233) of patients had none of these abnormalities. Simultaneous aberrations in different genes were observed. A heatmap listing these CNA in the entire cohort are given in Fig. . Details of the CNA in each major cytogenetic subtype are shown in Supplementary Table . DNA index identifies ploidy status in ALL In 112 samples DNA index analysis was performed; 41 cases showed aneuploidy, of which 35 were high hyperdiploid, 3 were hypodiploid and in 3 cases masked hypodiploidy was indicted, as described below. However, DI cannot identify individual chromosome gain or loss. MLPA compared to DI and cytogenetics Good quality genomic DNA was available from 204 samples for MLPA analysis using the MLPA P036 kit which identified 57 patients with high hyperdiploidy, 7 with hypodiploidy and 140 with diploidy or near-diploidy. The numerical chromosomal alterations determined by this MLPA P036 kit were compared with the karyotype and DI results. These results showed concordance in number of chromosomes (r = 0.9780, P < 0.0001) for the 111 patients with both MLPA and DI data available (Fig. a). There was statistically significant positive correlation between karyotype and DI (r = 0.3308, P = 0.0005) (Fig. b), yet lower than MLPA against DI, among 188 patients with karyotype and MLPA data available. The statistically significant positive correlation was also seen between karyotype and MLPA (r = 0.4428, P < 0.0001) (Fig. c), but lower than MLPA against DI. We found that 45% (29/64) of patients with high hyperdiploidy or hypodiploidy identified either by DI or MLPA P036 were non-informative. Details of karyotype, DI and MLPA of the cohort are listed in Supplementary Table . High hyperdiploidy Among 57 cases with high hyperdiploidy, the majority (94.5%) had gained between 5 and 13 chromosomes (modal chromosome number, MCN, 51–63, inclusive), and the most frequent MCN was 54 chromosomes (Supplementary Fig. a). Chromosome gains were non-random and 8 chromosomes accounted for 82% of all gains: 4 (72.7% of cases), 6 (80.7%), 10 (84.2%), 14 (93.0%), 17 (80.7%), 18 (86.0%), 21 (100%), and X (78.9%) (Supplementary Fig. b). Gains of chromosomes 5, 8, 9, 11, 12, and 22 represented 15% of the total and were present in between 11 and 35% of cases. Gains of chromosomes 1, 2, 3, 7, 13, 15, 16, 19, and 20 were rare, totaling 3% of chromosomes gained. These patterns of chromosomal gains in these high hyperdiploid cases were similar to previous reports. The MLPA pattern of iAMP21 and differentiation between iAMP21 and high hyperdiploidy From their MLPA plots, we identified four patients with iAMP21, as shown in Supplementary Fig. . A characteristic chromosome 21 copy number profile has been previously described for cases of iAMP21-ALL from microarray studies and next generation sequencing. It is described as copy number changes from centromere to telomere along chromosome 21, with the highest level of amplification proximal to a telomeric deletion – . Tsuchiya et al. reported a case in which RUNX1 was not located within the highest region of amplification of chromosome 21 . In this cohort, RUNX1 was observed within the most highly amplified region of chromosome 21, with the exception of one case (Supplementary Fig. ). In high hyperdiploid cases, the DI is usually greater than 1.16 and associated with frequent gains of chromosomes 4, 6, 10, 14, 18, 21 and X. We compared the pattern of chromosome 21 gain in high hyperdiploid and iAMP21-ALL in our cohort. SNP arrays analysis was carried out on two iAMP21-ALL samples diagnosed by MLPA (Supplementary Fig. ). For cases with suspected iAMP21, in the absence of SNP arrays, DI and MLPA P036 and P327 kits can provide the definitive answer. Hypodiploid cases Five patients with low DI were diagnosed with hypodiploidy. Three of them had two peaks in the DI, indicating the presence of hypodiploid clone undergo a doubling of the chromosomes during metaphase. This manifestation is known as masked hypodiploidy. As the diagnosis of masked hypodiploidy requires demonstration of loss of heterozygosity (LOH), these three samples were analyzed by SNP arrays and LOH was seen, as shown in case 984 (Fig. ). DI showed two peaks: the smaller one (FL2-A value = 202) is the true hypodiploidy and the higher one (FL2-A value = 393) indicates the doubled hypodiploid population. These hypodiploid samples were also tested using MLPA P036 kit. By comparing MLPA with the value of DI, we were able to identify the specific losses and retention of each chromosome number. Thus, we were able to confirm that the masked hypodiploid population originated from doubling of the low hypodiploid one. In Fig. , the chromosome gains detected by MLPA P036 corresponded to the retained chromosomes. In contrast, the “normal” chromosomes, for example chromosomes 3, 4, 5, 7, 8, 9, 13, 15, 16, 17 and 20 were shown to be lost. The actual gain or loss of each chromosome cannot be inferred from the DNA index. Using the MLPA P036 kit, we identified another two cases of hypodiploidy (patients 508 and 753) in which LOH was confirmed by STR (see below). Details of these patients are listed in the Table . A Short Tandem Repeat (STR) is a microsatellite, consisting of a unit of two to thirteen nucleotides repeated hundreds of times on a DNA strand. STR analysis measures the precise number of repeating units. STR is used for confirmation of donor engraftment following stem cell transplantations and this test is available in all medical centers . Samples of germline (if available) and tumor were sent for STR analysis in order to confirm LOH identified on SNP arrays. We show the interpretation of STR for patient 984 in Supplementary Fig. and all three cases of masked hypodiploidy by STR are shown in Supplementary Table . STR provides a simple method to confirm the presence of LOH. Based upon these observations, we have proposed a flowchart for diagnosis of masked hypodiploidy (Supplementary Fig. ). 19p deletion by MLPA is an indicator of TCF3 translocations in childhood ALL We identified 7 of 12 cases of TCF3-PBX1 and two cases of TCF3-HLF with 19p loss. This enrichment differs from other subtypes of B-cell ALL (P < 0.0001) (Table ). TCF3 is an important transcriptional factor with multiple fusion partners in ALL. Samples with 19p deletions without evidence of TCF3-PBX1 or TCF3-HLF fusions may carry TCF3-ZNF384 fusions. TCF3-ZNF384 fusions represent another important subtype of B-cell ALL with a specific immunophenotype showing frequent CD10 loss and CD13 and CD33 expression. From these observations, we observed one sample with 19p loss, loss of CD10, CD13 and CD33 expression in which the TCF3-ZNF384 fusions was identified by RT-PCR (Supplementary Fig. ). In this series, among a total of 15 samples with 19p loss, 10 of them had TCF3 fusions. Novel subtypes of ALL, intragenic amplifications of PAX5 ( PAX5 AMP ), IKZF1-plus and ERG deletions Recently two papers have reported two novel high-risk subtypes of childhood ALL, PAX5 AMP and IKZF1 plus , . There were 23 IKZF1 plus patients and 5 patients with PAX5 AMP in this cohort. Nine patients (9/233 = 3.9%) were identified with ERG deletions. These ERG deletions were associated with different subtypes of ALL (Fig. ). Survival analysis Among patients with the major cytogenetic alterations, two with TCF3-HLF relapsed and died within 5 years from diagnosis. Patients with high-risk subtypes (Ph-positive/-like, hypodiploidy, MEF2D -r, KMT2A -r, TCF3-HLF , iAMP21) had inferior 5-year EFS (P < 0.0001) and OS (P < 0.0001) (Fig. a, b). The overall outcome was slightly inferior compared to previous TPOG reports, likely due to many of them being referred from other hospitals after relapse . All patients with iAMP21 were not detected at diagnosis. There is a trend that patients with IKZF1 plus had inferior 5 year-EFS and OS than patients without IKZF1 plus , but it did not reach statistical significance (Fig. c, d). Patients with IKZF1 deletions had inferior 5-year EFS and 5-year OS, but it also did not reach statistical significance (Fig. e, f). In the Cox multivariate regression model, IKZF1 deletions were not a strong predictor of poor outcome (Supplementary Table ). The demographic, clinical, and laboratory characteristics of 233 children with B-ALL are shown in Table . The median age of the cohort was 5.4 years (range < 0.1–17.9 years); 95.3% of the patients were over 1 year of age. The molecular tests performed were those standardized for B-ALL diagnosis including: ETV6-RUNX1 , TCF3-PBX1 , BCR-ABL1 , P2RY8-CRLF2 and KMT2A-AFF1 for 220 samples. Detailed flow diagram of analysis used in this study is demonstrated in Supplementary Fig. . From MLPA testing, overall, 65.7% of the patients (153/233) harbored at least one abnormality (either deletion or amplification) involving the following genes— IKZF1 , CDKN2A / 2B , PAX5 , EBF1 , ETV6 , BTG1 , RB1 , ERG or PAR1 region, whereas the remaining 34.3% (80/233) of patients had none of these abnormalities. Simultaneous aberrations in different genes were observed. A heatmap listing these CNA in the entire cohort are given in Fig. . Details of the CNA in each major cytogenetic subtype are shown in Supplementary Table . In 112 samples DNA index analysis was performed; 41 cases showed aneuploidy, of which 35 were high hyperdiploid, 3 were hypodiploid and in 3 cases masked hypodiploidy was indicted, as described below. However, DI cannot identify individual chromosome gain or loss. Good quality genomic DNA was available from 204 samples for MLPA analysis using the MLPA P036 kit which identified 57 patients with high hyperdiploidy, 7 with hypodiploidy and 140 with diploidy or near-diploidy. The numerical chromosomal alterations determined by this MLPA P036 kit were compared with the karyotype and DI results. These results showed concordance in number of chromosomes (r = 0.9780, P < 0.0001) for the 111 patients with both MLPA and DI data available (Fig. a). There was statistically significant positive correlation between karyotype and DI (r = 0.3308, P = 0.0005) (Fig. b), yet lower than MLPA against DI, among 188 patients with karyotype and MLPA data available. The statistically significant positive correlation was also seen between karyotype and MLPA (r = 0.4428, P < 0.0001) (Fig. c), but lower than MLPA against DI. We found that 45% (29/64) of patients with high hyperdiploidy or hypodiploidy identified either by DI or MLPA P036 were non-informative. Details of karyotype, DI and MLPA of the cohort are listed in Supplementary Table . Among 57 cases with high hyperdiploidy, the majority (94.5%) had gained between 5 and 13 chromosomes (modal chromosome number, MCN, 51–63, inclusive), and the most frequent MCN was 54 chromosomes (Supplementary Fig. a). Chromosome gains were non-random and 8 chromosomes accounted for 82% of all gains: 4 (72.7% of cases), 6 (80.7%), 10 (84.2%), 14 (93.0%), 17 (80.7%), 18 (86.0%), 21 (100%), and X (78.9%) (Supplementary Fig. b). Gains of chromosomes 5, 8, 9, 11, 12, and 22 represented 15% of the total and were present in between 11 and 35% of cases. Gains of chromosomes 1, 2, 3, 7, 13, 15, 16, 19, and 20 were rare, totaling 3% of chromosomes gained. These patterns of chromosomal gains in these high hyperdiploid cases were similar to previous reports. From their MLPA plots, we identified four patients with iAMP21, as shown in Supplementary Fig. . A characteristic chromosome 21 copy number profile has been previously described for cases of iAMP21-ALL from microarray studies and next generation sequencing. It is described as copy number changes from centromere to telomere along chromosome 21, with the highest level of amplification proximal to a telomeric deletion – . Tsuchiya et al. reported a case in which RUNX1 was not located within the highest region of amplification of chromosome 21 . In this cohort, RUNX1 was observed within the most highly amplified region of chromosome 21, with the exception of one case (Supplementary Fig. ). In high hyperdiploid cases, the DI is usually greater than 1.16 and associated with frequent gains of chromosomes 4, 6, 10, 14, 18, 21 and X. We compared the pattern of chromosome 21 gain in high hyperdiploid and iAMP21-ALL in our cohort. SNP arrays analysis was carried out on two iAMP21-ALL samples diagnosed by MLPA (Supplementary Fig. ). For cases with suspected iAMP21, in the absence of SNP arrays, DI and MLPA P036 and P327 kits can provide the definitive answer. Five patients with low DI were diagnosed with hypodiploidy. Three of them had two peaks in the DI, indicating the presence of hypodiploid clone undergo a doubling of the chromosomes during metaphase. This manifestation is known as masked hypodiploidy. As the diagnosis of masked hypodiploidy requires demonstration of loss of heterozygosity (LOH), these three samples were analyzed by SNP arrays and LOH was seen, as shown in case 984 (Fig. ). DI showed two peaks: the smaller one (FL2-A value = 202) is the true hypodiploidy and the higher one (FL2-A value = 393) indicates the doubled hypodiploid population. These hypodiploid samples were also tested using MLPA P036 kit. By comparing MLPA with the value of DI, we were able to identify the specific losses and retention of each chromosome number. Thus, we were able to confirm that the masked hypodiploid population originated from doubling of the low hypodiploid one. In Fig. , the chromosome gains detected by MLPA P036 corresponded to the retained chromosomes. In contrast, the “normal” chromosomes, for example chromosomes 3, 4, 5, 7, 8, 9, 13, 15, 16, 17 and 20 were shown to be lost. The actual gain or loss of each chromosome cannot be inferred from the DNA index. Using the MLPA P036 kit, we identified another two cases of hypodiploidy (patients 508 and 753) in which LOH was confirmed by STR (see below). Details of these patients are listed in the Table . A Short Tandem Repeat (STR) is a microsatellite, consisting of a unit of two to thirteen nucleotides repeated hundreds of times on a DNA strand. STR analysis measures the precise number of repeating units. STR is used for confirmation of donor engraftment following stem cell transplantations and this test is available in all medical centers . Samples of germline (if available) and tumor were sent for STR analysis in order to confirm LOH identified on SNP arrays. We show the interpretation of STR for patient 984 in Supplementary Fig. and all three cases of masked hypodiploidy by STR are shown in Supplementary Table . STR provides a simple method to confirm the presence of LOH. Based upon these observations, we have proposed a flowchart for diagnosis of masked hypodiploidy (Supplementary Fig. ). TCF3 translocations in childhood ALL We identified 7 of 12 cases of TCF3-PBX1 and two cases of TCF3-HLF with 19p loss. This enrichment differs from other subtypes of B-cell ALL (P < 0.0001) (Table ). TCF3 is an important transcriptional factor with multiple fusion partners in ALL. Samples with 19p deletions without evidence of TCF3-PBX1 or TCF3-HLF fusions may carry TCF3-ZNF384 fusions. TCF3-ZNF384 fusions represent another important subtype of B-cell ALL with a specific immunophenotype showing frequent CD10 loss and CD13 and CD33 expression. From these observations, we observed one sample with 19p loss, loss of CD10, CD13 and CD33 expression in which the TCF3-ZNF384 fusions was identified by RT-PCR (Supplementary Fig. ). In this series, among a total of 15 samples with 19p loss, 10 of them had TCF3 fusions. PAX5 ( PAX5 AMP ), IKZF1-plus and ERG deletions Recently two papers have reported two novel high-risk subtypes of childhood ALL, PAX5 AMP and IKZF1 plus , . There were 23 IKZF1 plus patients and 5 patients with PAX5 AMP in this cohort. Nine patients (9/233 = 3.9%) were identified with ERG deletions. These ERG deletions were associated with different subtypes of ALL (Fig. ). Among patients with the major cytogenetic alterations, two with TCF3-HLF relapsed and died within 5 years from diagnosis. Patients with high-risk subtypes (Ph-positive/-like, hypodiploidy, MEF2D -r, KMT2A -r, TCF3-HLF , iAMP21) had inferior 5-year EFS (P < 0.0001) and OS (P < 0.0001) (Fig. a, b). The overall outcome was slightly inferior compared to previous TPOG reports, likely due to many of them being referred from other hospitals after relapse . All patients with iAMP21 were not detected at diagnosis. There is a trend that patients with IKZF1 plus had inferior 5 year-EFS and OS than patients without IKZF1 plus , but it did not reach statistical significance (Fig. c, d). Patients with IKZF1 deletions had inferior 5-year EFS and 5-year OS, but it also did not reach statistical significance (Fig. e, f). In the Cox multivariate regression model, IKZF1 deletions were not a strong predictor of poor outcome (Supplementary Table ). In this retrospective study, the MLPA P036 subtelomeres probemix kit provided accurate detection of aneuploidy in childhood B-cell ALL and good correlation with the results from DI. MLPA and DI are superior to traditional cytogenetics, due to the shorter turn-around time, irrespective of mitotic index and improved sensitivity. Detections of specific gains or losses of each chromosome assist the differential diagnosis of hyperdiploidy from iAMP21. In addition, DI is helpful for diagnosis of masked hypodiploidy and LOH should be confirmed by SNP arrays. STR provides a simple method, available in most medical centers in Taiwan, to document LOH in these masked hypodiploid cases. Around 1.7% (4/233) of B-ALL patients had iAMP21. We also identified some of the novel ALL subtypes, including PAX5 AMP , and IKZF1 plus , . TCF3 rearrangements were frequently associated with 19p deletions. High hyperdiploidy accounts for around 20 ~ 25 percentage of childhood B-cell ALL . In this cohort, the most frequent modal chromosome number was 54 followed by 55. The most frequent gains included chromosomes 4, 6, 10, 18, 16, 17, 18, 21 and X, in agreement with previous reports , , . This incidence of high hyperdiploidy was lower in Taiwan than Caucasian populations , , . Using DI and the MLPA P036 kit, the incidence was around 27% in this cohort. In this study, 45% of high hyperdiploid patients were not detected by cytogenetics, manifesting as normal karyotype. In previous TPOG ALL 2002 report, hyperdiploidy accounted for 13.6% in B-ALL (n = 1,209). The incidence was much lower than that of this report. The reason for this discrepancy might be the relative smaller case numbers in this study. For cases without metaphases or normal karyotype, DI and MLPA can be successfully used for diagnosis of high hyperdiploidy . iAMP21-ALL is a novel subtype of B-ALL proposed by WHO , , , . The initial gold standard for diagnosis was FISH using probes directed to the RUNX1 gene, but array-CGH or SNP arrays are now the main method for diagnosis . One MLPA kit can successfully identify iAMP21 due to the density of probes along the long arm of chromosome 21. We identified 4 cases with iAMP21 by MLPA. In these cases, the level of gain was variable along the length of chromosome 21 with the ratio being more than 3.0, higher than in cases where chromosome 21 is gained as part of a high hyperdiploidy karyotype in which the probe ratio for every probe in the kit being ~ 1.5–2.0. These data correlated with other gains, especially of chromosomes 4, 6, 10, 18, 16, 17, 18 and X. If gains of chromosomes X, 4, 6, 10, 14, 17 and 18 are detected at the same time as gains of 21, it is most likely that the patient has high hyperdiploidy rather than iAMP21-ALL. Masked hypodiploidy can be difficult to diagnose. Another study used a similar MLPA approach to identify the aneuploidy status of relapsed B-cell ALL . Three patients with high hyperdiploidy had the highest number of chromosomal gains (median 11). Gains of the classical high hyperdiploidy pattern were less frequent, but gains of non-classical chromosomes, especially 1, 5, 11, 19 and 22, accounted for 49% of all gains in these patients. All three patient relapse samples carried TP53 mutations, two of which were present in the germline. In all three cases, no underlying hypodiploid clone was detected by DI or cytogenetic analyses, making diagnosis difficult. A recent report by Carroll et al. demonstrated that a considerable proportion (25% or higher) of hypodiploidy in children with B-ALL may have been overlooked in previous studies due to the presence of only a doubled hypodiploid population, mistakenly interpreted as typical high hyperdiploidy associated with a favorable risk . In this cohort, the chromosome number in high hyperdiploidy was mostly in the range of 52 ~ 59, which could overlap with masked hypodiploidy. For masked hypodiploid cases, the MLPA P036 kit results, alongside DNA index, can detect the specific gain or loss of each chromosome. LOH can also be confirmed by STR. TCF3, located to 19p, is rearranged with several genes in childhood ALL. The most frequent is TCF3-PBX1 and rarely the poor risk TCF3-HLF . We observed 19p loss in all TCF3-PBX1 and TCF3-HLF cases. TCF3 has also been identified to be rearranged with ZNF384, a novel fusion recently identified – . In cases with 19p deletions without TCF3-PBX1 or TCF3-HLF detected by RT-PCR or cytogenetics, 19p deletions may point to other TCF3 fusions. TCF3-ZNF384 fusions are also frequently associated with CD10 loss, with the presence of CD13 and CD33 , , . These two characteristics are useful for its identification by RT-PCR. In our cohort, patients with iAMP21 and KMT2A fusions had an inferior 5-year EFS and OS in comparison to patients with ETV6-RUNX1 or high hyperdiploidy. Patients with hypodiploidy also had an inferior 5-year EFS and OS, although most of them were not identified at the time of diagnosis. The outcome for patients with iAMP21-ALL may be improved if detected at diagnosis, so that they may be treated with more intensive chemotherapy. No events were seen in patients with PAX5 AMP , while patents with IKZF1 plus showed a trend towards inferior EFS and OS, although the P -value was not significant. IKZF1 deletions showed a trend towards poorer clinical outcomes, as observed in a number of other studies , , . Due to the relative small case numbers in this study, larger studies are indicated in Taiwan in order to evaluate the clinical impact of these genetic alterations in Taiwan. In conclusion, MLPA and DNA index together can rapidly provide reliable information for identification of aneuploidy of childhood B-ALL. Using these methods, diagnosis of aneuploidy in Taiwan might be improved particularly among those cases currently classified within unknown subtype of B-cell ALL, and especially those without metaphases or normal karyotype. STR provides a simple method to demonstrate LOH if masked hypodiploidy is suspected. Other important abnormalities such as IKZF1 deletions, IKZF1 plus and ERG deletions can also be identified by MLPA. These tools are helpful for the diagnosis of some important subtype of ALL. Supplementary Information. |
Elevated isoleucine may be a protective factor for primary hypertension: A pooled causal effect study | 4776a075-4eab-4c63-ba03-b82c108cbce3 | 11875580 | Biochemistry[mh] | Primary hypertension (PH) is one of the most important risk factors for cardiovascular diseases, stroke, chronic kidney disease as well as dementia. The prevalence of elevated blood pressure has declined substantially in Western high-income regions since 1970s, but keeps rising in East, South and Southeast Asia, sub-Saharan Africa, and Oceania. Asian characteristics differed from the West and led to higher stroke incidence. Masked hypertension is a significant clinical entity of target organ damage and cardiovascular disease. The prevalence of masked hypertension for Asians (16.0%) is higher than European (9%). Regarding Africa, hypertension is common in sub-Saharan Africa, the prevalence significantly varies in different African countries, ranging from 37% to 75%. Approximately one-tenth of adolescents have elevated blood pressure across sub-Saharan Africa. The prevalence of hypertension was high in both rural (27.4%) and urban areas (33.9%) of West Africa. However, the rates of hypertension diagnosis, treatment, and control are markedly low and cause a heavy health and economic burden in both Asia and Africa. The hypertension treatment rates were below 25% for women and less than 20% for men in South Asia and some sub-Saharan African countries. Control rates were lower than 10% in these countries and for men in some countries of North Africa and Central Asia. PH has been regarded as a disorder of the renin–angiotensin–aldosterone system and the sympathetic nervous system (SNS) in tradition. Yet, current treatments aiming at limiting the effects of renin–angiotensin–aldosterone system or SNS on blood pressure fail in about 40% of cases. This implied that other mechanisms may exist. Previous studies found that immune mechanisms can contribute to the development of hypertension. Flavonoids were reported to possess an underlying mechanism to regulate antihypertensive effects. Genetics can drive the occurrence of hypertension in certain patients. Anxiety diagnosis was also reported can cause development or incidence of hypertension, which might be due to the longer exposure to alterations in autonomic mechanisms. In addition, hypertension has been reported to be associated with impaired metabolic homeostasis and can be considered as a metabolic disorder. To date, there have been limited cohort-based causal studies examining the relationship between metabolites and PH, with a particular lack of research on Asian and African populations. If differentially abundant metabolites are risk factors or protective factors for PH, it is meaningful for the prediction of the disease and auxiliary diagnosis based on specific targets, as well as for further treatment. Therefore, our study aims to investigate the causal relationship between metabolism and PH in Asian and African populations using Mendelian randomization (MR). We analyzed serum metabolites and metabolite ratios from genome-wide association studies (GWAS). Applying MR analysis, which mimics the design of randomized-controlled trials (RCTs), we explored the causal effects of these metabolites on PH. We used metabolite-associated single-nucleotide polymorphisms (SNPs) as instrumental variables to assess the causal impact and to elucidate the underlying metabolic pathways.
2.1. Study design The dataset that contains all the data in this study is available to the public on the open website ( http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90199001-GCST90200000 and https://gwas.mrcieu.ac.uk/ ). The GWAS summary statistics have already been published. The ethics committee at each institutional review board authorized all participants’ written informed permission in separate cohort studies. No extra ethical approval or informed consent was required in this study. In the current study, we comprehensively evaluated the relationship between 1091 serum metabolites, 309 metabolite ratios, and PH datasets from East Asian, Middle East, and African populations one by one rigorously based on the MR design. A scientific MR study must include the testing of the following 3 hypotheses: genetic instrumental variables (SNPs) are strongly associated with the serum metabolites level or ratio; genetic instrumental variables should be irrelevant to the PH and independent of any known or unknown confounding factors; and the effect of instrumental variables on the results is mediated only by the serum metabolites level or ratio. Briefly, a causal analysis strategy was employed to select genetically significant SNPs for 1091 human serum metabolites, 309 metabolite ratios, and PH. To avoid sample overlap, metabolites and genetic information of PH were selected from independent GWAS datasets in this study. A schematic of this study is demonstrated in Figure . 2.2. GWAS data for human serum metabolites A genome-wide association aggregate dataset of 1091 human serum metabolites and 309 metabolite ratios involved in this study was obtained by Chen et al These data are publicly available from the GWAS server ( http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90199001-GCST90200000 ). The service platform collects relatively complete human serum metabolomics data. A total of 8299 individuals from the Canadian Longitudinal Study on Aging cohort were included in the GWAS analysis. A total of 248 loci were found to be associated with 690 metabolite levels and 69 loci with 143 metabolite ratios. After integrating metabolite genes and gene expression information, 94 effector genes were identified for 109 metabolites and 48 metabolite ratios. The chemical properties of another 241 unknown or partially characterized metabolites have not been fully determined. 2.3. GWAS data for primary hypertension The GWAS data of PH among East Asia, Middle East, and Africa populations were obtained from the data of the integrative epidemiology unit open GWAS project ( https://gwas.mrcieu.ac.uk/ ). These summary data were collected from the UK-Biobank cohort in 2020 and GWAS ID were ukb-e-401_EAS, ukb-e-401_MID and ukb-e-401_AFR. In this GWAS meta-analysis, the summary data included 5554 PH cases and 10,922 control cases, yielding a total of 15,530,091 SNPs. We extracted SNPs by analyzing visual component framework files shared by the integrative epidemiology unit platform. The patients with PH were diagnosed according to the standard criteria of the World Health Organization and the International Hypertension Alliance. 2.4. Selection of instrumental variables In this MR analysis, the selection of instrumental variables was based on 3 basic assumptions. First, we set P < 1 × 10 −5 as the genome-wide significance threshold to obtain strongly associated SNPs for each metabolite. Second, a clumping procedure implemented in R software was employed to identify the independent variants. R 2 < 0.001 within a 500-kb distance was used to avoid linkage disequilibrium. Third, to quantitatively verify whether the selected SNPs were strongly correlated instruments, we calculated the phenotypic variation explained and the F statistic for each metabolite. Typically, a threshold of F > 10 is suggested for the next operation. 2.5. MR analysis A standard inverse-variance weighted (IVW) method was the prioritized evaluation approach used for causal association exploration between metabolites and PH in this analysis. When the instrumental variables satisfy all 3 major hypotheses, the IVW method can provide a more accurate estimate of the causal effect of metabolite and is considered as the most efficient MR method. However, if some instrument variables do not conform to the instrumental variables hypothesis, the analysis may give inaccurate results. Hence, we conducted the following sensitivity analyses: Q tests were performed using the MR-Egger methods to detect heterogeneity between each instrument variable and the possibility of violating the assumption. The MR–Egger intercept was used to estimate the horizontal pleiotropy, ensuring that the genetic variation was independently related to the metabolite and PH ; additional approaches such as the weighted median and weighted mode were applied to enhance the reliability and stability of hypothesis testing; and the individual SNP analysis and leave-one-out test were conducted to estimate the likelihood of relevance observed by individual SNPs. To ensure there was no direct association with PH or other confounding factors, candidate SNPs were compared against the human reference genome database. 2.6. Metabolic pathway analysis Metabolome enrichment pathways associated with PH were estimated using web-based MetaboAnalyst 5.0. ( https://www.Metaboanalyst.ca/ , Natural Sciences and Engineering Research Council of Canada, Ottawa, Canada). The pathway and enrichment analysis modules were applied to identify probable metabolite clusters or superpathways that may be associated with metabolic processes and the potential association with PH. The Small Molecule Pathway Database and the Kyoto Encyclopedia of Genes and Genomes database were applied for reference. The significance level of the enrichment pathway was 0.05. 2.7. Intersection analysis An intersection such as meta-analysis was introduced to analyze the shared metabolites screened by the 3 PH datasets, in conjunction with potential pathway mechanisms, to evaluate the polymorphism of related metabolites in different races. 2.8. Statistical analysis The MR analysis was conducted using the “TwoSampleMR” package in R (version 4.3.1), developed by Gibran Hemani, Philip Haycock, Jie Zheng, Tom Gaunt, Ben Elsworth, and Tom Palmer (available at https://mrcieu.github.io/TwoSampleMR/ ). P < .05 was considered as statistically significant. The odds ratio was used to estimate the magnitude and direction of the metabolic impact with its corresponding 95% confidence interval. If there was missing data, we have chosen to delete it. The circle heatmap was drawn using ChiPlot ( https://www.chiplot.online/ ) (accessed on September 29, 2023).
The dataset that contains all the data in this study is available to the public on the open website ( http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90199001-GCST90200000 and https://gwas.mrcieu.ac.uk/ ). The GWAS summary statistics have already been published. The ethics committee at each institutional review board authorized all participants’ written informed permission in separate cohort studies. No extra ethical approval or informed consent was required in this study. In the current study, we comprehensively evaluated the relationship between 1091 serum metabolites, 309 metabolite ratios, and PH datasets from East Asian, Middle East, and African populations one by one rigorously based on the MR design. A scientific MR study must include the testing of the following 3 hypotheses: genetic instrumental variables (SNPs) are strongly associated with the serum metabolites level or ratio; genetic instrumental variables should be irrelevant to the PH and independent of any known or unknown confounding factors; and the effect of instrumental variables on the results is mediated only by the serum metabolites level or ratio. Briefly, a causal analysis strategy was employed to select genetically significant SNPs for 1091 human serum metabolites, 309 metabolite ratios, and PH. To avoid sample overlap, metabolites and genetic information of PH were selected from independent GWAS datasets in this study. A schematic of this study is demonstrated in Figure .
A genome-wide association aggregate dataset of 1091 human serum metabolites and 309 metabolite ratios involved in this study was obtained by Chen et al These data are publicly available from the GWAS server ( http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90199001-GCST90200000 ). The service platform collects relatively complete human serum metabolomics data. A total of 8299 individuals from the Canadian Longitudinal Study on Aging cohort were included in the GWAS analysis. A total of 248 loci were found to be associated with 690 metabolite levels and 69 loci with 143 metabolite ratios. After integrating metabolite genes and gene expression information, 94 effector genes were identified for 109 metabolites and 48 metabolite ratios. The chemical properties of another 241 unknown or partially characterized metabolites have not been fully determined.
The GWAS data of PH among East Asia, Middle East, and Africa populations were obtained from the data of the integrative epidemiology unit open GWAS project ( https://gwas.mrcieu.ac.uk/ ). These summary data were collected from the UK-Biobank cohort in 2020 and GWAS ID were ukb-e-401_EAS, ukb-e-401_MID and ukb-e-401_AFR. In this GWAS meta-analysis, the summary data included 5554 PH cases and 10,922 control cases, yielding a total of 15,530,091 SNPs. We extracted SNPs by analyzing visual component framework files shared by the integrative epidemiology unit platform. The patients with PH were diagnosed according to the standard criteria of the World Health Organization and the International Hypertension Alliance.
In this MR analysis, the selection of instrumental variables was based on 3 basic assumptions. First, we set P < 1 × 10 −5 as the genome-wide significance threshold to obtain strongly associated SNPs for each metabolite. Second, a clumping procedure implemented in R software was employed to identify the independent variants. R 2 < 0.001 within a 500-kb distance was used to avoid linkage disequilibrium. Third, to quantitatively verify whether the selected SNPs were strongly correlated instruments, we calculated the phenotypic variation explained and the F statistic for each metabolite. Typically, a threshold of F > 10 is suggested for the next operation.
A standard inverse-variance weighted (IVW) method was the prioritized evaluation approach used for causal association exploration between metabolites and PH in this analysis. When the instrumental variables satisfy all 3 major hypotheses, the IVW method can provide a more accurate estimate of the causal effect of metabolite and is considered as the most efficient MR method. However, if some instrument variables do not conform to the instrumental variables hypothesis, the analysis may give inaccurate results. Hence, we conducted the following sensitivity analyses: Q tests were performed using the MR-Egger methods to detect heterogeneity between each instrument variable and the possibility of violating the assumption. The MR–Egger intercept was used to estimate the horizontal pleiotropy, ensuring that the genetic variation was independently related to the metabolite and PH ; additional approaches such as the weighted median and weighted mode were applied to enhance the reliability and stability of hypothesis testing; and the individual SNP analysis and leave-one-out test were conducted to estimate the likelihood of relevance observed by individual SNPs. To ensure there was no direct association with PH or other confounding factors, candidate SNPs were compared against the human reference genome database.
Metabolome enrichment pathways associated with PH were estimated using web-based MetaboAnalyst 5.0. ( https://www.Metaboanalyst.ca/ , Natural Sciences and Engineering Research Council of Canada, Ottawa, Canada). The pathway and enrichment analysis modules were applied to identify probable metabolite clusters or superpathways that may be associated with metabolic processes and the potential association with PH. The Small Molecule Pathway Database and the Kyoto Encyclopedia of Genes and Genomes database were applied for reference. The significance level of the enrichment pathway was 0.05.
An intersection such as meta-analysis was introduced to analyze the shared metabolites screened by the 3 PH datasets, in conjunction with potential pathway mechanisms, to evaluate the polymorphism of related metabolites in different races.
The MR analysis was conducted using the “TwoSampleMR” package in R (version 4.3.1), developed by Gibran Hemani, Philip Haycock, Jie Zheng, Tom Gaunt, Ben Elsworth, and Tom Palmer (available at https://mrcieu.github.io/TwoSampleMR/ ). P < .05 was considered as statistically significant. The odds ratio was used to estimate the magnitude and direction of the metabolic impact with its corresponding 95% confidence interval. If there was missing data, we have chosen to delete it. The circle heatmap was drawn using ChiPlot ( https://www.chiplot.online/ ) (accessed on September 29, 2023).
3.1. Influence of serum metabolites on PH As the genome-wide significance threshold was P < 1 × 10 −5 to select strongly associated SNPs among 1091 human serum metabolites and 309 metabolite ratios, the instrument variables contained 76,267 SNPs in total, with a median of 17 SNPs. Among them, the East Asian population dataset accounted for 28.80%, the Middle East population dataset accounted for 41.63%, and the African population dataset accounted for 29.57%. The F statistic values were all >10, indicating that weak instrumental bias is not detected. All metabolic analyses used IVW as the primary analytical methodology, with no evidence of heterogeneity and no weak instrument variables. In the East Asian population dataset, 36 significantly associated named metabolites were selected ( P < .05 for IVW), in which 19 were positively associated with PH and 17 were negatively associated with PH. Carnitine to propionyl carnitine (C3) ratio ( P = .0020) was the most significant factor, followed by 4-hydroxychlorothalonil levels ( P = .0046) and histidine to alanine ratio ( P = .0051) (Fig. A). In the Middle East population dataset, 57 significantly associated named metabolites were selected ( P < .05 for IVW), in which 24 were positively associated with PH and 33 were negatively associated with PH. Ethyl malonate levels ( P = .0002) were the most significant factor, followed by spermidine to ergothioneine ratio ( P = .0006) and taurine to glutamate ratio ( P = .0017) (Fig. B). In the African population dataset, 40 significantly associated named metabolites were selected ( P < .05 for IVW), in which 26 were positively associated with PH and 14 were negatively associated with PH. C-glycosyl tryptophan levels ( P = .0003) were the most significant factor, followed by caffeic acid sulfate levels ( P = .0029) and cortolone glucuronide (1) levels ( P = .0030) (Fig. C). Figure exhibited the direction of the potential correlation of metabolic involvement in the 3 populations. The results of the alternative analysis, Q test, and sensitivity analysis for the known metabolites are shown in Table . All instrument variables passed the sensitivity tests ( P > .05). The metabolites significantly associated with PH among 3 populations were entered into the MetaboAnalyst 5.0 platform to determine various underlying metabolic pathways involved in the pathogenesis of PH. In the East Asia dataset, histidine, L-aspartic acid, oxoglutaric acid, pyruvic acid, D-glucose, and phosphate were involved in the metabolic enrichment pathway of ammonia recycling, glucose–alanine cycle, urea cycle, alanine metabolism, malate–aspartate shuttle, and glutamate metabolism ( P < .05). Regarding Middle East dataset, 2-ketobutyric acid, choline, and spermidine were involved in the metabolic enrichment pathway of methionine metabolism ( P < .05). For Africa dataset, myo-inositol, D-fructose, and phosphate were involved in the metabolic enrichment pathway of galactose metabolism and phosphatidylinositol phosphate metabolism ( P < .05) (Table ). The metabolic mechanism formed by the above metabolites may be involved in the pathogenesis of PH. Figure S1A–C, Supplemental Digital Content, http://links.lww.com/MD/O433 exhibits the networks of interactions among the metabolic pathways involved in East Asian, Middle East, and African populations. 3.2. Intersection between East Asian, Middle East, and African populations Intersection analysis was introduced to analyze the shared metabolites screened by the MR analyses. The cross-sectional and meta-analysis of strongly correlated metabolites across the 3 ethnic groups revealed that 7 metabolites were consistently identified, 5 of which were previously known. Among these, isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56–0.96) emerged as a protective factor for PH across all 3 ethnic groups (Figs. and A–E).
As the genome-wide significance threshold was P < 1 × 10 −5 to select strongly associated SNPs among 1091 human serum metabolites and 309 metabolite ratios, the instrument variables contained 76,267 SNPs in total, with a median of 17 SNPs. Among them, the East Asian population dataset accounted for 28.80%, the Middle East population dataset accounted for 41.63%, and the African population dataset accounted for 29.57%. The F statistic values were all >10, indicating that weak instrumental bias is not detected. All metabolic analyses used IVW as the primary analytical methodology, with no evidence of heterogeneity and no weak instrument variables. In the East Asian population dataset, 36 significantly associated named metabolites were selected ( P < .05 for IVW), in which 19 were positively associated with PH and 17 were negatively associated with PH. Carnitine to propionyl carnitine (C3) ratio ( P = .0020) was the most significant factor, followed by 4-hydroxychlorothalonil levels ( P = .0046) and histidine to alanine ratio ( P = .0051) (Fig. A). In the Middle East population dataset, 57 significantly associated named metabolites were selected ( P < .05 for IVW), in which 24 were positively associated with PH and 33 were negatively associated with PH. Ethyl malonate levels ( P = .0002) were the most significant factor, followed by spermidine to ergothioneine ratio ( P = .0006) and taurine to glutamate ratio ( P = .0017) (Fig. B). In the African population dataset, 40 significantly associated named metabolites were selected ( P < .05 for IVW), in which 26 were positively associated with PH and 14 were negatively associated with PH. C-glycosyl tryptophan levels ( P = .0003) were the most significant factor, followed by caffeic acid sulfate levels ( P = .0029) and cortolone glucuronide (1) levels ( P = .0030) (Fig. C). Figure exhibited the direction of the potential correlation of metabolic involvement in the 3 populations. The results of the alternative analysis, Q test, and sensitivity analysis for the known metabolites are shown in Table . All instrument variables passed the sensitivity tests ( P > .05). The metabolites significantly associated with PH among 3 populations were entered into the MetaboAnalyst 5.0 platform to determine various underlying metabolic pathways involved in the pathogenesis of PH. In the East Asia dataset, histidine, L-aspartic acid, oxoglutaric acid, pyruvic acid, D-glucose, and phosphate were involved in the metabolic enrichment pathway of ammonia recycling, glucose–alanine cycle, urea cycle, alanine metabolism, malate–aspartate shuttle, and glutamate metabolism ( P < .05). Regarding Middle East dataset, 2-ketobutyric acid, choline, and spermidine were involved in the metabolic enrichment pathway of methionine metabolism ( P < .05). For Africa dataset, myo-inositol, D-fructose, and phosphate were involved in the metabolic enrichment pathway of galactose metabolism and phosphatidylinositol phosphate metabolism ( P < .05) (Table ). The metabolic mechanism formed by the above metabolites may be involved in the pathogenesis of PH. Figure S1A–C, Supplemental Digital Content, http://links.lww.com/MD/O433 exhibits the networks of interactions among the metabolic pathways involved in East Asian, Middle East, and African populations.
Intersection analysis was introduced to analyze the shared metabolites screened by the MR analyses. The cross-sectional and meta-analysis of strongly correlated metabolites across the 3 ethnic groups revealed that 7 metabolites were consistently identified, 5 of which were previously known. Among these, isoleucine (odds ratio = 0.74, 95% confidence interval: 0.56–0.96) emerged as a protective factor for PH across all 3 ethnic groups (Figs. and A–E).
Our study found 36, 57, and 40 known metabolites were strongly related to PH in East Asian, Middle Eastern, and African populations, respectively. Histidine, L-aspartic acid, oxoglutaric acid, pyruvic acid, D-glucose, and phosphate were found to be involved in the metabolic enrichment pathway of ammonia recycling, glucose–alanine cycle, urea cycle, alanine metabolism, malate–aspartate shuttle, and glutamate metabolism in East Asian population. 2-Ketobutyric acid, choline, and spermidine were involved in the metabolic enrichment pathway of methionine metabolism among the Middle East population. Myo-inositol, D-fructose, and phosphate were found to be involved in the metabolic enrichment pathway of galactose metabolism and phosphatidylinositol phosphate metabolism for African people. Of the metabolites that were found to be strongly correlated among the 3 races in both cross-sectional and meta-analyses, 7 were consistently identified, 5 of which were previously known with name (N-acetyl-aspartyl-glutamate, taurolithocholate 3-sulfate, isoleucine, N-acetyl-2-aminoadipate, and myo-inositol level) L-aspartic acid, oxoglutaric acid, pyruvic acid, and phosphate were crucial metabolites involved in the enrichment pathways in East Asia population. Isoleucine was demonstrated as a protective factor of PH across the 3 populations. N-acetyl-2-aminoadipate was found to be positively associated with PH in the Africa group, and negatively associated with the East Asian and Middle East populations. Myo-inositol was a risk factor for both African and Middle East groups, but a protective factor for the East Asian population. Several studies have reported that alanine involved in the glucose–alanine cycle was associated with reduced ammonia excretion and directly affected the ammonia cycle. Some studies have found dietary alanine was associated with higher systolic blood pressure (SBP) and diastolic blood pressure (DBP). Yet, a cohort study has suggested that alanine tended to diminish the risk of hypertension. Urea cycle disorder can result in hypertension, there is a clear pathophysiological relationship between them. Certain scholars have discovered that the urea cycle may contribute to the availability of precursors for nitric oxide synthesis, ultimately leading to neonatal pulmonary hypertension. Hypertension shared common metabolic patterns with dyslipidemia, including alanine metabolism and glutamate metabolism, suggesting potential intervention targets could be provided to patients with both hypertension and dyslipidemia. It was discovered in the Dahl salt-sensitive rat, a model of salt-sensitive hypertension, that aspartate or malate can increase levels of L-arginine and nitric oxide, thereby reducing hypertension. Another study found that a high salt diet can induce hypertension of liver-Yang hyperactivity syndrome by mediating the microbiota associated with the glutamate/γ-aminobutyric acid–glutamine metabolic cycle via the gut–brain axis. Methionine metabolism was involved in endothelial dysfunction, atherosclerosis, and renal fibrosis. It can cause early hypertensive nephrosclerosis. A previous study proposed that methionine-enriched diet could induce elevated SBP. Galactose ingestion, like glucose, was reported to result in significantly lesser increases in blood pressure compared with fructose ingestion, indicating its involvement in blood pressure regulation through galactose metabolism. Impaired phosphoinositide metabolism has been found linked to calcium-handling abnormalities associated with hypertension. L-aspartic acid has been reported to possess notable clinical significance because of its effectiveness in the treatment of hypertension. It has been observed that 2-oxoglutaric acid had abnormal rhythms and contents in hypertension. Plasma pyruvic acid was found to be associated with pulmonary arterial hypertension. Pyruvate acid could change continuously in hypertension progression. Inorganic phosphate might serve as a crucial dietary risk factor for hypertension. The potential mechanisms could be dietary phosphorus excess induces hypertension including activation of the SNS, impaired endothelial function, increased vascular stiffness, and renal sodium retention. In addition, supplementation of inositol has shown promising results in significantly reducing both SBP and DBP. Moreover, myo-inositol supplementation has demonstrated a notable decrease in the overall incidence of pregnancy-induced hypertension. All these prior findings were aligned with our study, emphasizing these metabolites are really crucial in the enrichment pathways influencing PH. Numerous studies have stated that isoleucine–proline–proline/valine–proline–proline lactotripeptides can significantly reduce office SBP in both Asian and European populations. Another study discovered that the combination of isoleucine–tryptophan with whey protein hydrolysate effectively inhibits plasma angiotensin-1-converting enzyme, leading to antihypertensive effects. These findings highlight the importance of isoleucine as an essential amino acid in managing hypertension. Our study verified the causal correlations between isoleucine and PH among African, Middle East, and East Asian populations based on MR analysis. N-acetyl-2-aminoadipate was found to be a positive predictor on DBP according to another MR analysis focus on the European population. Our study contributes to existing literature by demonstrating that N-acetyl-2-aminoadipate was demonstrated as a risk factor of PH in the African group, but a protective factor in East Asian and Middle East populations. A meta-analysis concluded that inositol supplementation can significantly decrease SBP and DBP, but further large-scale RCTs are still needed to confirm these findings. Interestingly, myo-inositol showed as risk factor in both African and Middle East groups in our study. There are certain limitations in our study. First, our findings need to be verified by clinical trials or longitudinal studies, particularly large-scale RCTs, to explore their therapeutic potential. Second, we must examine the role of specific metabolites in the development of PH to understand the underlying mechanisms. Our next step will involve using multiomics data to analyze and validate potential mediators. Finally, further research is needed on 2 unidentified metabolites that exhibit overlapping characteristics across different racial groups, as they may have important clinical implications.
Our study discovered several metabolites having causal relationships with PH across East Asian, Middle East, and African populations. Isoleucine might be a valuable amino acid in the prevention or treatment for PH.
We are grateful to all the participants and investigators of the study, as well as to all the investigators who contributed to the genome-wide association study of modifiable risk factors.
Funding acquisition: Yi Chen. Writing – original draft: Ying Shi, Hairun Liu. Conceptualization: Yi Chen. Data curation: Yi Chen. Formal analysis: Yi Chen. Writing – review & editing: Yi Chen.
|
Unraveling
the Applicability of LbL Coatings for Drug
Delivery in Dental Implant-Related Infection Treatment | ca083070-1856-4cca-8774-0b51b9f6c20a | 11733916 | Dentistry[mh] | Introduction Periodontal disease has
been reported to affect millions of patients
worldwide according to the World Health Organization (WHO), impacting
up to 1 billion of the global adult population ( www.who.int/news-room/fact-sheets/detail/oral-health ). Periodontitis
(PD), characterized by chronic inflammation of the supporting tissues
around the teeth, develops due to a complex interaction between the
host and parasites, progressively compromising the integrity of the
periodontal tissues. , It is characterized by bacterial-induced
inflammatory responses and the destruction of periodontal tissues,
including the periodontal ligament, cement, and alveolar bone. The
more severe stages of periodontitis (stage III and IV) affect over
700 million people, representing approximately 11% of the global population. Indeed, PD ranks as the sixth most prevalent
chronic condition globally and is considered the leading cause of
tooth loss in adults. , Consequently, PD presents a significant
public health challenge due to its high prevalence and the substantial
burden caused by tooth loss and impaired chewing function, negatively
impacting the quality of life. Importantly, a history of PD
poses a significant risk factor for
peri-implantitis, which refers to the irreversible pathological condition
occurring in tissues around dental implants. Historically, there has been a lack of consensus regarding the true
prevalence of peri-implantitis, with heterogeneity in results attributed
to variations in disease definitions and a lack of standard diagnosis. − However, contrary to previous assumptions, peri-implantitis as a
biological complication has been significantly underestimated for
many years. It was only after the 2017 World Workshop on the Classification
of Periodontal and Peri-Implant Diseases and Conditions that clinical
parameters became better defined, revealing a prevalence of this condition
much higher than expected. As such, recent
studies have reported a troubling prevalence of peri-implantitis,
ranging from 34% to 56% at the patient level within an average time
frame of 2–7.8 years after prosthesis loading. These numbers underline not only the concerns for public
health but also the significant economic burden caused by peri-implantitis.
In view of this, the global peri-implantitis treatment market has
been projected to reach a value of US$ 4.5 billion by 2032. Evidently,
these projections are based on the increasing number of dental implants
that have been and will be used for oral rehabilitation. The alarming
peri-implantitis prevalence percentage further indicates that current
clinical procedures aimed at preventing and treating peri-implantitis
are insufficiently effective. The
primary disease-causing factor for peri-implantitis is the
biofilm accumulated on dental implant components at the tissue–oral
cavity interface. Therefore, nonsurgical supportive therapy involving
biofilm removal is a mandatory step at the initial stage of the peri-implantitis
treatment. The treatment of peri-implantitis ranges from nonsurgical
to surgical procedures, depending on the outcomes of the initial steps. Regardless of the chosen approach, the main
objective of the treatment is to achieve complete resolution of the
inflammation by biofilm removal and microbial agent elimination. In
view of this, several methods have been described to achieve surface
decontamination, such as the use of antiseptics, − local and systemic
antibiotic administration, , and lasers and antimicrobial
photodynamic therapy. , However, the limited number of
studies to support the benefits of adjunctive therapy compromise the
reliability of the evidence and make the valuation of conventional
treatments difficult. , Biomaterials offer a range
of possibilities for developing therapeutic
interventions, from the use of polymeric films with antimicrobial
effects on dental implant surfaces to the use of drug delivery systems
or even using titanium modifications on implant/abutment surfaces
to prevent and/or treat peri-implantitis. − However, despite
the large number of antimicrobial coating approaches discussed by
literature, to date, all proposed surfaces have not reached the commercial
stage. A well-designed review clearly revealed a growing number of published
articles under the antimicrobial coatings field, with potential highlights
on the preclinical studies. This result confirms that the stagnation
in clinical application might be attributed to the complexity of the
factors involved in the antimicrobial coating development, from product
construction to product application. Indeed, problems in translating
preclinical findings to clinical applications can be attributed in
part to cytotoxicity, material behavior, drug release control, and
duration of product antimicrobial activity to make it clinically viable. However, the lack of knowledge about the clinical
purpose of the desired material might directly affect the success
of the antimicrobial coating. In fact, understanding the rationale
behind developing a surface
modification is the initial step toward successfully acquiring new
materials. It is imperative, however, to consider the distinctions
between preventive and treatment approaches in guiding the complexity
of biomaterials. As peri-implantitis is an inflammatory condition
initiated by a dysbiotic biofilm adherent to a substrate, preventive
strategies are related to material development with direct antimicrobial
action, through either contact killing or antifouling surfaces. In this case, the material should be resistant
to pH differences caused by food consumption and withstand the mechanical
action of brushing to maintain its function in the long term. From
a treatment perspective, biomaterial-based coatings should be easily
degraded to directly combat the infection and/or the inflammatory
response, through the release of antimicrobial agents and/or substances
implicated in the inhibition of osteoclastogenesis, and restore the
health of peri-implant tissues in patients diagnosed with peri-implantitis. − To this purpose, drug delivery technologies have enabled the delivery
of a therapeutic to its target site, minimizing off-target accumulation
and facilitating patient compliance. Drug release technology
provides a higher local drug concentration
to specific sites on and around the implant, thereby offering immediate
action against implant-associated infections. The basic idea behind
drug release systems is to create a responsive structure, called a
smart coating, on the surface capable of loading drugs and releasing
them in a regulated manner over time. To this end, chemical cross-linking
processes and layer-by-layer (LbL) systems − constructed using natural and/or synthetic polymers might act as intelligent strategies for releasing
the loaded drugs. Among the techniques for building smart coatings,
here we will focus on LbL assembly as an appealing strategy to immediately
fight against the already installed disease. LbL assembly has many advantages such as the high reproducibility
of film formation in an easy, versatile, flexible and inexpensive
process, nanometer control over film thickness, and a wide variety
of natural and/or synthetic polymeric materials to be used as multivalent
species to build up the film. − Basically, the LbL method involves
the alternating adsorption of complementary multivalent species on
a substrate through electrostatic interactions, hydrogen bonding,
or other secondary interactions, which will work as a structure for
drug incorporation. , While research on LbL technology
has expanded in recent years,
the challenge of translating it into commercial products may stem
from a lack of understanding related to the system limitations, coating
purpose, and the meaning of disease stage for its application. To
the best of our knowledge, this is the first study that breaks down
the barriers of the LbL system description and provides detailed chemical
and biological information to clarify its strict application in terms
of physical site and purpose as antimicrobial coatings. Likewise,
we give a deeper overview of the onset and progression concepts of
the disease to clarify the indications for the LbL system as a coating
for implant abutments aimed at the treatment of peri-implantitis.
Finally, we relate the chemical nature of the LbL system to its functionality
and discuss the oral cavity as an uncontrolled environment that limits
its clinical applicability.
Understanding Peri-implantitis According
to the 2017 World Workshop on the Classification of Periodontal
and Peri-Implant Diseases and Conditions, peri-implantitis is a pathological
condition characterized by inflammation around dental implants with
subsequent loss of supporting bone. , In the clinical
setting, peri-implant mucositis is assumed to precede peri-implantitis,
signaling the initial state of the inflammatory process. The onset
of peri-implant mucositis exhibits clinical signs of red aspects around
the implant with swollen soft tissues and the presence of bleeding
and/or suppuration on probing, yet without bone loss. As a more severe inflammatory condition, peri-implantitis
is influenced and regulated by the immune response. While the inflammatory
reaction contributes to bone resorption around the implant, the dysbiotic
biofilm adherent to the surface consistently triggers the innate response , − . Once the biofilm is well established onto the dental
implant components,
the immune system responds to it leading to immunoinflammatory mediators. , The immune system mobilizes macrophages, neutrophils, and T- and
B-cells, promoting the release of pro-inflammatory cytokines interleukin-1
(IL-1) and tumor necrosis factor-alpha (TNF-α), anti-inflammatory
cytokines, e.g., interleukin-10 (IL-10), and chemokines, e.g., interleukin-8
(IL-8), that lead to osteolysis and inflammatory tissue damage. , , The lesions at peri-implantitis
sites harbor larger proportions of polymorphonuclear leukocytes (PMN)
and M1 macrophages phenotypes when compared to periodontitis. , Macrophage polarization to M1 indicates a strong pro-inflammatory
response with high expression of pro-inflammatory products, such as
IL-1β, IL-6, IL-12, and TNF. The secretion of such cytokines
activates osteoclast precursors and contributes to the bone resorption.
The higher expression of M1 macrophages may be associated with the
faster progression of peri-implantitis compared to periodontitis. − In fact, some individuals exhibit an exacerbated response
to the
inflammatory process, making them more susceptible to developing peri-implant
diseases. , , , Some conditions such as uncontrolled diabetes mellitus,
autoimmune disorders, genetic factors, smoking and alcohol consumption,
and some treatments such as bisphosphonate therapy, head and neck
radiotherapy, chemotherapy, antibiotics use, and anti-inflammatory
medications are known to alter the microbiome and hence the inflammatory
response, which makes these individuals more susceptible to inflammatory
conditions. , , Peri-implantitis is a relatively recent condition, presenting
numerous
challenges in comprehending its risk factors that influence disease
progression and its impact on systemic diseases. For instance, existing literature confirms poor oral hygiene
and a history of periodontitis as significant risk factors for peri-implantitis. , , , Despite longitudinal studies affirming the influence of metabolic
conditions like diabetes and habitual tobacco smoking on periodontitis,
conclusive evidence regarding their effects on peri-implantitis remains
elusive. , However, examining the biological pathways
implicated in smokers, it is apparent that similarities exist in the
inflammatory responses between periodontitis and peri-implantitis,
suggesting potential consequences of inflammatory products. Nicotine, in particular, not only enhances the
production of pro-inflammatory cytokines by osteoblasts, such as IL-6
and TNF-α, known to contribute to bone resorption, but also
plays an important role in decreasing PMN chemotaxis and in the hyperactivation
of macrophages (which secrete considerable pro-inflammatory mediators),
in addition to decreasing vascularization. , , If left untreated, this may lead to peri-implant
diseases and eventual implant loss. However, it is crucial to note
that the absence of evidence may stem from a lack of longitudinal
studies establishing such associations and causality. Evidently,
dental implants are more prone to pathogen invasion
compared to natural teeth due to several factors. Basically, in a
natural tooth, cementum is a sheathlike structure covering the surface
of root dentin and providing anchorage for collagen fibers in a pattern
of perpendicular orientation. Furthermore,
epithelial cells attach to the enamel and cementum via hemismosomes
to achieve epithelial sealing around the teeth. Hemidesmosomes are
a set of highly specialized epithelial attachment apparatus components
responsible for providing stable and firm attachment to the extracellular
matrix, intracellularly filament, and cytoskeleton. , The tight seal at the soft tissue on the alveolar bone and the teeth
surface plays a crucial role in serving as the first protective barrier
to prevent bacterial infiltration. , Unlike a tooth,
the implant lacks structures such as root cementum and periodontal
ligament responsible for connecting the soft tissues to the tooth
through dentoalveolar and dentogingival fibers. , , Even after proper healing, the tissue around
dental implants experiences reduced blood flow due to poor vascularity
and a deeper sulcus, allowing bacteria to penetrate deeper due to
the absence of collagen fibers (known as Sharpey’s fibers)
inserted into the implant structure. The absence of such structures
affects the direction of the collagen fibers. Histologically, collagen
fibers are oriented parallel or circumferentially to the region of
the abutment surfaces, resulting in a weaker connective interface, , lack of soft tissue resistance against the inflammatory response,
and hence rapid disease progression. In view of the differences
in pathology and histological organization
around percutaneous natural teeth and dental implants, it is straightforward
to state that peri-implantitis treatment poses a significant challenge
to clinicians. In this sense, an important question can be raised
to conceptualize the outcome of treating peri-implantitis. From a
clinical standpoint, the diagnosis of peri-implantitis requires clinical
signs such as presence of bleeding and/or suppuration on gentle probing,
increased probing depth compared to previous examinations, and presence
of bone loss beyond crestal bone level changes resulting from initial
bone remodeling. During the treatment
of peri-implantitis, it is not expected to recover the lost bone.
According to the European Federation of Periodontology (EFP) S3 level
clinical practice guideline, 2023, reconstructive
procedures can be used in the management of osseous defects, as a
sequential stage of surgical treatment of peri-implantitis. Surgical
approaches can be employed in the sites with persisting signs of pathology
after nonsurgical therapy, to provide access to the implant surface
and achieve the resolution of the inflammatory lesion. Clinically,
the end points of successful surgical therapy of peri-implantitis
can be translated by ≤1 point of bleeding on probing, absence
of suppuration on probing, probing depth ≤5 mm, and absence
of progressive bone loss compared to pretreatment bone levels to verify
disease resolution. Although the EPF recommends the surgical management
of osseous defects in peri-implantitis patients, through the access
flap with or without reconstructive procedures, no evidence demonstrating
superiority of any specific surgical technique has been identified. In short, researchers in the fields of dentistry,
(material) engineering, and tissue regeneration are confronted with
a substantial clinical problem to address with innovative treatment
approaches. Therefore, understanding and delineating the initiation
and progression of the disease are pivotal initial steps toward devising
effective treatment strategies to be discussed below for this biological
complication.
Why Do We Still Need New Strategies to Treat
Peri-implantitis? While the progressive tissue destruction
caused by peri-implantitis
stems from the host’s inflammatory response, it is the flora
of pathogenic microorganisms within the dysbiotic biofilm that evokes
the initiation of this inflammation. According
to the EFP clinical practice guideline, the initial treatment approach
for peri-implantitis should prioritize nonsurgical methods that focus
on biofilm removal and implant surface decontamination to control
peri-implant biofilms and inflammation. Ideally, decontaminating the implant surface should be performed
through supramarginal and submarginal instrumentation. For the latter,
EFP guidelines recommend performing nonsurgical supra- and submarginal
instrumentation with curets and/or (ultra)sonic devices as the basic
control intervention methods. − However, there is a risk of damaging
the implant surface while attempting to remove the biofilm. , In vitro studies have demonstrated that released
titanium particles following implant surface damage have the potential
to trigger severe inflammatory responses via macrophages and osteoclasts and to modulate the peri-implant biofilm to
a dysbiotic state. To minimize this risk,
curets are now being crafted from softer materials like plastic or
carbon fiber instead of stainless steel. Nevertheless, regardless of material type, curets may not completely
eliminate adhered biofilm since they cannot reach the areas between
the threads of the implants. Moreover,
given the complexity of an already established peri-implant dysbiotic
biofilm, ensuring its successful disorganization in areas with limited
access further complicates treatment. Surgical strategies may be considered when nonsurgical treatments
fail or in cases of moderate or severe peri-implantitis, offering
greater access to peri-implant regions. , According
to evidence-based recommendation, surgical intervention is indicated
for patients diagnosed with peri-implantitis, for whom end points
of nonsurgical therapy (i.e., probing depth ≤5 mm and ≤1
point of bleeding on probing) have not been achieved. The goal of surgical therapy is to provide direct access,
through flap elevation, to facilitate procedures required for implant
surface decontamination and achieve resolution of the inflammatory
process. Although the literature has
presented the use of air-polishing, Er:YAG laser, chlorhexidine or
photodynamic therapy, or even adjunctive local antibiotics, for implant
surface decontamination, the EFP does not recommend these treatments
due to lack of evidence on efficacy. , Despite literature
suggesting that chemical agents can enhance disinfection by reaching
mechanically inaccessible niches, in clinical practice, local antibiotics
are typically administered via irrigation, leading to easy dissolution
of the applied antibiotic and thus limited therapeutic effect. Furthermore, the resident microbiota and its
matrix can impede the access of local antimicrobials, preventing their
penetration into deeper layers of the biofilm. The prescription of antibiotics for systemic treatment
along with
(non)surgical therapies is still a concern and has not been recommended
by the EFP. , , In comparison to planktonic bacteria, those bacteria within biofilms
exhibit greater tolerance to antimicrobial agents, rendering systemic
antibiotics less effective as adjuncts. A recent scoping review further concluded that, although there is
insufficient data to support evidence-based antibiotic protocols for
peri-implantitis, systemic metronidazole adjunct to mechanical debridement
improved the clinical outcomes of nonsurgical treatment. Overall, research on systemic antibiotics for
peri-implantitis treatment is scarce and inconclusive, and due to
the heterogeneous administration protocols reported in the literature,
there is no consensus on any effective antibiotic protocol for treating
peri-implantitis. When indicated, a careful
risk/benefit assessment should be conducted to evaluate the potential
for adverse events (e.g., allergic reactions) and antibiotic resistance. While it can be argued that all available means
should be incorporated into the treatment plan given the difficulty
of achieving successful peri-implantitis treatment, overall antimicrobial
agents should not be used empirically due to the overgrowth of difficult-to-eradicate
opportunistic pathogens. In fact,
the high prevalence of peri-implantitis highlights that
no clinical procedure can yet be considered effective in treating
this pathological condition. Moreover, peri-implantitis might not
only lead to implant loss but also poses a risk of pathogenic bacteria
from the infected oral site reaching the bloodstream, causing significant
morbidity and generating considerable healthcare costs. Recent work
has highlighted the potential links between peri-implant health and
systemic inflammation, including uncontrolled diabetes mellitus, psychological
stress, cardiovascular disease, obesity, and even recent infectious
diseases that caused severe acute respiratory syndrome caused by SARS-CoV-2. Similar to periodontitis, chronic inflammation
around dental implants
harbors pathogenic bacteria and potential pro-inflammatory cytokines
that can influence other systemic inflammatory conditions, such as
cardiovascular diseases. Multiple studies have shown that peri-implantitis
and cardiovascular diseases share common inflammatory pathways, potentially
leading to an increased risk of cardiovascular events in individuals
with untreated peri-implantitis. , − Diabetes is another possible disease that could be influenced by
peri-implantitis due to the fact that this oral disease could bring
a hyperinflammatory state, which could exacerbate insulin resistance,
thus impairing glycemic control and the reparative capacity of the
body. , Although there is insufficient evidence
to confirm such relationships mentioned above, the consequences of
peri-implantitis progression may extend beyond implant loss, underscoring
the need for strategies to stabilize the disease in the short term.
Developing a Drug Delivery System Using Layer-by-Layer
(LbL) Technology to Treat Peri-implantitis LbL assembly is
a promising avenue in the field of peri-implantitis
management due to its applicability with a variety of substances,
in addition to being an easy, versatile, and flexible process for
multilayer formation to act directly in the affected site. , Given that peri-implantitis is already established and requires
prompt treatment, it is crucial to consider therapeutic interventions
that address the inflammatory and infectious nature of the disease.
Controlled and local administration of antimicrobial agents could
help to reduce the local infection and subsequent inflammation, while
substances targeting cells involved in bone resorption could help
halt the progression of tissue loss resulting from peri-implantitis.
In both cases, a drug delivery system capable of releasing therapeutic
agents directly at the target site, such as via abutments, is appealing.
LbL assembly offers a potential solution by serving as a biomaterial-based
surface modification technology that can create a matrix for drug
delivery ( A–C). In the 20th century, Langmuir–Blodgett (LB)
balances were
frequently employed to deposit amphiphilic molecules at the liquid/vapor
interfaces in order to manufacture films. , Although it was initially used only on flat surfaces, this technology
made it possible to create self-assembled films with low mechanical
and thermal stability. In 1960, Iler introduced LbL assembly as an
alternative to overcome the drawbacks of LB films, self-assembling
multilayers into charged colloidal particles. Since then, LbL assembly has been applied in various fields of science
and technology, including the healthcare sector, such as implants, , − wound healing dressings, and tissue engineering. Basically, the deposition method for LbL assembly via electrostatic
interactions involves an alternating sequence of immersing a substrate
in anionic and cationic polyelectrolyte solutions, followed by a washing
step between each solution exchange to ensure the complete removal
of weakly adsorbed polyelectrolytes. Any deviation from this sequence
may lead to nonuniform adsorption of polyelectrolytes, which can compromise
the quality of the manufactured LbL ( B). LbL coatings
can be assembled using a range of chemical interactions, including
hydrogen bonds, charge transfer interactions, molecular recognition,
host–guest, π–π, and biospecific interactions. − From a chemical perspective, understanding the process of structuring
a multilayered coating is complex and involves several factors, including
charge, pH, and ionic strength of the medium. In this sense,
chemical interactions within LbL assemblies, including
covalent and noncovalent interactions, are crucial for determining
the stability, functionality, and drug-release behavior of these films. − Covalent bonds, formed through the sharing of electron pairs, provide
robustness and long-term stability, essential for sustained drug delivery,
often enhanced through cross-linking methods like click chemistry
or disulfide bond formation. − Conversely, noncovalent interactions, such
as electrostatic forces, hydrogen bonding, and van der Waals forces,
drive the dynamic assembly and disassembly of LbL structures, enabling
responsive and controlled drug delivery by facilitating the sequential
buildup of layers with precise control over film thickness and composition. − These interactions might be introduced during the assembly process
by using reactive functional groups on the polymers or molecules that
form the layers. For instance, covalent
cross-linking can be employed to enhance the mechanical strength and
stability of the LbL films, making them more resistant to environmental
conditions such as changes in pH or ionic strength. Cross-linking can be achieved through various chemical
reactions, such as click chemistry, “Schiff” base formation,
or disulfide bond formation. − These covalent bonds provide long-term stability,
which is crucial for applications in which the film must remain intact
for extended periods, such as in sustained drug delivery systems. On the other hand, noncovalent interactions are the primary driving
forces in the formation of LbL films. − These interactions are generally
weaker than covalent bonds but are essential for the dynamic assembly
and disassembly of LbL structures. − For example, electrostatic interactions
are the most commonly utilized forces in LbL assembly, where alternating
layers of positively and negatively charged polyelectrolytes are deposited. The electrostatic attraction between oppositely
charged layers enables the sequential buildup of the film, allowing
for precise control over the film thickness and composition. A LbL coating discloses two possible
configurations: (i) adsorption
in which the charge balance results in electroneutrality, called intrinsic
compensation, and (ii) adsorption that results in an excess net positive
or negative charge, arising from the adsorption of polycations and
polyanions, respectively, called extrinsic compensation , ( A). The
multilayer system becomes unstable due to the excess charges, since
the balance will be altered in favor of stabilizing these loads. Zeta
potential behavior often analyzes these measurements. , , The ionic strength of
polyelectrolyte solutions plays a crucial
role in forming homogeneous layers during LbL coating buildup, and
it is imperative to consider the characteristics and concentration
of the ion(s). The presence of small ions, also known as kosmotropic
ions, results in thin films with low hydration and roughness due to
their low polarization and weak binding with the multilayer systems.
On the other hand, chaotropic ions, which have a higher degree of
polarization, interact more with the multilayers, leading to changes
in the conformation of the polyelectrolytes and affecting the thickness
of the multilayers. , The pH of the medium also has
a significant impact on the formation of multilayers, and it can alter
the degree of ionization of the polyelectrolytes. Consequently, the pH modifies the organization of the multilayers. In short, LbL assembly reveals overriding advantages related to
the low cost, versatility, and simplicity of obtaining well-defined
thickness, composition, and functionality materials. The low cost
is related mainly to the simplicity of the technique. LbL coatings
can be assembled at room temperature without pressure, which means
that this technique will not compromise the integrity of reagents,
such as proteins or drugs. The versatility of LbL assembly as a coating
is due to its ability to vary in composition and its possibility to
create defined sequences of layers. With
regard to the functionality, LbL assembly has found applications within
the biomedical field. In this sense, the multilayers can be purposely
prepared to admit antimicrobial action or can be constructed to receive
the target drug. In this perspective, the literature brings antimicrobial
polyelectrolytes to be applied as a target layer during the LbL system
construction. , The explanation of the antimicrobial
properties of specific polyelectrolytes is related to their hydrophobicity. The antimicrobial capacity of hydrophobic polyelectrolytes has
long been exploited as a replacement for conventional antibiotics. , The antimicrobial effects of the polyelectrolytes are related to
the nature of hydrophobic groups, polyelectrolyte composition, and
length for a series of antimicrobial block polyelectrolytes. Interestingly, although cationic groups also
contribute to the antimicrobial activity of the material, the hydrophobicity
within the polyelectrolytes is the driving component for lipid membrane
binding and pore formation which in turn causes cell death through
a membrane-disruption mechanism. , For instance,
the use of poly(ethylenimine) (PEI) as a strong cationic polyelectrolyte
provides inherent bactericidal activity via its cationic groups. , These bind to phospholipids in cell membranes through electrostatic
interactions, leading to membrane ruptures. The bactericidal
activity of modified PEIs was further enhanced
by the addition of hydrophobic alkyl groups and a more positive charge
density. It was found that linear N , N -dodecyl-ethyl poly(ethylenimine) and poly(acrylic acid) LbL coatings
demonstrate strong antiviral activity against influenza A/WSN (H1N1)
and bactericidal activity against Staphylococcus aureus and Escherichia coli . The balance between cationic groups and hydrophobic
side chains on different sides of overall polyelectrolytes has been
recognized for disrupting bacterial cell membranes and causing membrane
leakage and eventually cell death. , From this
knowledge, the literature suggests a correct balance between hydrophobicity
and hydrophilicity properties within biomaterial polyelectrolytes
to achieve an antimicrobial interaction with bacterial membranes without
causing cytotoxicity or cell repeal. In order to enhance the
interaction between film and substrate
and optimize the antibacterial properties of titanium surfaces, another
study combined ε-polylysine (ε-PL), a typical cationic
antimicrobial peptide, with arabic gum, a polysaccharide, for LbL
construction. They used polydopamine to covalently graft ε-polylysine
onto anodized titanium. The antimicrobial capacity of this system
was attributed to the strong electrostatic interaction between the
negatively charged acidic phospholipid of bacterial cell membranes
and the positive charge from ε-PL. The wizened and ruptured
morphology of S. aureus and E. coli on coated Ti surfaces suggested that ε-PL
effectively killed bacteria by destroying their cell membranes. However,
the limited amount of ε-PL covalently conjugated on the surface
affected the antibacterial efficiency. Interestingly, decreased bacterial
adhesion was found on the surface along with increased layers of ε-PL
and GA, suggesting that these reagents, bound by electrostatic adsorption,
might dissolve into the solution during the bacterial incubation process ( A–B). Despite the apparent advantages provided by the
LbL assembly, it
is important to highlight the inherent limitations of LbL assembly.
The most common method for LbL assembly is the sequential dipping
method, which does not allow for substantial control over the orientation
of the adsorbed components in the multilayers. Basically, different polyelectrolyte solutions are used
to fill individual containers, and a specimen is immersed sequentially/repetitively
in these solutions, with intermediate washing steps, until the desired
number of layers is achieved. Although
the LbL process is time-consuming due to the time required to reach
equilibrium adsorption for each coating step, this system allows a
sustained drug release overtime. Another way to buildup the LbL system
is by using sequential spraying of the specimens instead of dipping.
This method encompasses the advantage of nanometer control over film
thickness without the disadvantages mentioned above. Moreover, spray-based
LbL assembly is faster and smoother than dipping and can even be performed
without a rinsing step. However, spray-based LbL assembly can lead
to vastly rapid release of an incorporated drug ( B). 4.1 LbL Self-Assembly System as a Feasibility
Tool for Drug Release The LbL system as a thin film can also
be designed in the field of biomedical science to work on drug delivery
processes. Importantly, there are specific factors related to the
effective incorporation of the drug and subsequent drug release by
the LbL system: First, the nontoxicity property of the target drugs
and the film material should be confirmed before preparing the LbL
system. , Second, the thin film-carrying drugs should
disclose both chemical and physical stability to favor drug incorporation
and its release. , Third, drug release should occur
in the target site. Fourth, the system should ensure a sustained release
instead of a burst release and ensure a safe dose concentration at
the target site. This control can be achieved by managing the
degradation rate of the LbL system, depending on the drug property
to be incorporated, and considering the material and the assembled
method selected for LbL preparation. In this sense, a variety of interactions
and cross-linking chemistry can be employed for loading drugs onto
prefabricated multilayers: overall drugs can be directly loaded onto
prefabricated LbL; the layers can be built using drugs as building
blocks; and finally, overall drugs can be also modified with cargoes,
for protecting the drug by a shell of a stable chemical structure
and preventing undesirable decomposition. , Contrary to the concepts discussed in the present Review, a recent
study developed a quaternary ammonium carboxymethyl chitosan, collagen,
and hydroxyapatite multilayer coating via the LbL technique by polymerizing
dopamine to prevent infections on implant surfaces. Importantly, although
the objective of this study was to use a naturally fragile and degradable
LbL system focusing on prevention for implants, the authors also considered
the likelihood of disease after implantation, different from peri-implantitis.
To achieve antimicrobial properties, the authors used 1-ethyl-3-[3-(dimethylamino)propyl]carbodiimide
hydrochloride (EDC) in the presence of N -hydroxysulfosuccinimide
(sulfo-NHS) to convert carboxyl groups to amine-reactive sulfo-NHS
esters during the construction of the multilayers. EDC/sulfo-NHS were
used as cross-linkers to extend the contact-killing properties and
the release-killing over time ( C–D). With the possibility of using LbL coatings as a carrier matrix
for target biomolecules such as antimicrobial substances or those
that act directly on inflammatory cells, it offers enormous potential
as a drug delivery system. For instance, in a recent study, silver
nanoparticles (AgNPs) were incorporated into LbL coatings based on
oppositely charged amino cellulose (AM) and acylase. The resulting
hybrid system showed an improved antibacterial and antibiofilm effect,
while decreasing cytotoxicity. The beauty
of the LbL assembly lies in the possibility of using it to produce
a hybrid system that can enhance the efficacy of existing drugs. The
capacity of the LbL system to release incorporated drugs occurs because
the multilayered structures are naturally multiresponsive as a consequence
of interactions among the layers, which means that they answer to
different stimuli, such as temperature, pH, and humidity. It is precisely
due to the capacity of the system to respond to multiple stimuli that
LbL assembly displays the ability to incorporate drugs in high concentrations
within a multilayer thin film and release them in a controlled or
uncontrolled manner , ( C). In our previous work, , we demonstrated that
our LbL system changed molecular conformation upon immersion in ultrapure
water and displayed a swelling behavior of the polyelectrolyte matrix.
Our outcomes were also categorical in showing that when samples were
kept in wet conditions, the LbL system with drug incorporated onto
titanium discs displayed the highest roughness, which indicates that
LbL-coating conformational changes contributed to the drug diffusion
process through the multilayered coating. From a clinical perspective,
the physiological environment of the oral cavity would act to disturb
the stimuli-responsive polyelectrolyte of the system and allow the
release of the incorporated drug for local and immediate action. To
understand how the release process occurs and how to control the concentration
of drugs released at the site, it is necessary to understand the chemical
characteristics of both the system and the released agent. To
reach the biological performance of the controlled drug release,
it is required that the system protects the drug, loads the drug,
and releases the drug in a controlled manner for the needed time,
which are all directly influenced by a drug’s molecular structure. Since the electrostatic interactions between
oppositely charged ions from different layers are the most applied
driving force in the LbL assembly, the same principle must be applied
between polyelectrolyte layers and the target drug. An example includes
antibiotics disclosing hydrophilic properties as target drugs, which
are released more quickly upon exposure to the aqueous environment.
This can be explained by the weak interaction between hydrophobic
and hydrophilic molecules from polymers and antibiotics, respectively, which means that there is no driving force
between the molecules from layers and loaders. , To overcome this issue, researchers have studied amphiphilic
inclusion
complexes with overall drugs to enhance the drug capability to entrap
into hydrophobic layers, increase the
interaction between drug and LbL system, and ensure the controlled
drug release overtime. In a recent study, the authors used amphiphilic
molecule anionic beta-cyclodextrin (β-CD) to retain tetracycline,
as a hydrophilic antibiotic, within the LbL-coating titanium substrate
and control TC release from the multilayers up to 30 days ( E–G). The strong interaction between TC and anionic
β-CD and effective loading of the complex within the LbL system
enabled TC retention within the LbL coatings for a prolonged time,
regardless of medium pH. Importantly, the strong antibacterial effect
was observed after 48 h of incubation with more than 5 log reduction
of bacterial growth in comparison to the uncoated titanium surfaces.
The remaining antibacterial activity of the LbL system was confirmed
even up to 30 days, with 2.8 log reduction of S. aureus compared with the same uncoated surfaces. Summarizing, illustrates how LbL
technology can be tailored for specific dental implant applications
by leveraging different stimuli-responsive features. This table and
summary provide a clear overview of how LbL technology is advancing
the field of dental implants by improving their functionality and
clinical outcomes. It is essential to note that the factors that are
involved in the
structuring of the LbL system are also responsible for the responsive
nature of the bioactive compounds. The most prevalent self-defensive
antibacterial LbL films are pH-responsive because they take advantage
of the release of lactic and acetic acid by different bacteria, which
lowers the pH of the infection’s microenvironment. Thus, pH shifts can alter the conformational
state of the layers in LbL coatings, changing the dimension of the
polyelectrolyte mesh and facilitating the release of drugs. A similar effect occurs when the multilayer
system meets the biological environment. The presence of salts results
in the rearrangement of water molecules within the polyelectrolyte
layers, whose driving force is guided by an entropic effect, modifying
the conformation of the polyelectrolyte present. From this perspective, the release rate does not occur
exclusively through drug diffusion and platform degradation, but the
phenomena involved in extrinsic compensation are also responsible
for changes in the physicochemical properties of the LbL system. 4.2 Physical Properties of LbL Coatings for Implant
Abutment Surfaces Implant abutments are essential components
that serve as bridges or extensions attached to implants to secure
artificial teeth. Unlike the implant itself, which is not subject
to mechanical friction during installation, the significance of abutments
lies in their direct contact with surrounding soft tissue. Hence,
any polyelectrolyte coating applied to abutment surfaces should exhibit
sufficient strength to withstand the forces exerted during placement
without being easily being removed. Furthermore, from a clinical point
of view, screw-retained abutments could be easily replaced by coated
ones during disease treatment. It is widely acknowledged that
surface topography significantly influences the biological response
of surrounding tissues to abutments. Numerous studies have demonstrated that rough surfaces tend to accumulate
more plaque, , increasing the risk of plaque-induced
inflammatory reactions in surrounding tissues compared to smoother
surfaces. Therefore, abutments should ideally feature smooth surfaces,
typically less than or around 0.2 μm, , , to facilitate mechanical cleaning
and ensure peri-implant health, especially in patients at risk of
peri-implantitis. Another critical surface property affecting surface
protein adsorption and cell adhesion quality is wettability, with
cells showing a greater propensity to adhere to hydrophilic surfaces. , In essence, any coating-based approach to combat peri-implantitis
should preserve or enhance the inherent properties of the components. For abutments, the primary challenge lies in developing a coating
that maintains the original topography—ensuring it does not
interfere with smoothness and wettability—while adding antimicrobial
properties without adverse effects on human cells. From a dental implant perspective, LbL technology holds
promise for coating implant abutment surfaces. The multilayers assembled onto abutment surfaces allow
precise control of polyelectrolytes’ vertical dispersion at
the nanoscale, thereby achieving the desired roughness based on the
chosen multilayer creation process. , In other
words, LbL-coating properties such as thickness, homogeneity, and
internal structure can be controlled and determined by various LbL
methods. With regards to the wettability,
hydrophilic/hydrophibic potential
of the LbL system is a key factor that influences protein adsorption,
cell adhesion, and the overall interaction between coating and biological
environment. Hydrophilic surfaces may
promote protein adsorption and enhance cellular attachment, which
can be beneficial in the tissue engineering field. Studies have shown that LbL assembly can be used to finely
tune these properties by selecting appropriate materials for the layers. , − For instance, incorporating hydrophilic
polymers such as poly(ethylene glycol) (PEG) can decrease the contact
angle, thus enhancing material hydrophilicity. Owing to the versatility and flexibility of LbL assembly,
coating
surface properties can be easily modified to enhance their biological
response before they come into contact with cells and tissues . However, caution is warranted when considering this technology
for implants themselves due to the risk of displacement or physical
damage to LbL coatings during implant installation. Clearly, LbL assembly
is a system based on a polyelectrolyte responsive to various conditions,
suggesting its susceptibility to mechanical forces.
LbL Self-Assembly System as a Feasibility
Tool for Drug Release The LbL system as a thin film can also
be designed in the field of biomedical science to work on drug delivery
processes. Importantly, there are specific factors related to the
effective incorporation of the drug and subsequent drug release by
the LbL system: First, the nontoxicity property of the target drugs
and the film material should be confirmed before preparing the LbL
system. , Second, the thin film-carrying drugs should
disclose both chemical and physical stability to favor drug incorporation
and its release. , Third, drug release should occur
in the target site. Fourth, the system should ensure a sustained release
instead of a burst release and ensure a safe dose concentration at
the target site. This control can be achieved by managing the
degradation rate of the LbL system, depending on the drug property
to be incorporated, and considering the material and the assembled
method selected for LbL preparation. In this sense, a variety of interactions
and cross-linking chemistry can be employed for loading drugs onto
prefabricated multilayers: overall drugs can be directly loaded onto
prefabricated LbL; the layers can be built using drugs as building
blocks; and finally, overall drugs can be also modified with cargoes,
for protecting the drug by a shell of a stable chemical structure
and preventing undesirable decomposition. , Contrary to the concepts discussed in the present Review, a recent
study developed a quaternary ammonium carboxymethyl chitosan, collagen,
and hydroxyapatite multilayer coating via the LbL technique by polymerizing
dopamine to prevent infections on implant surfaces. Importantly, although
the objective of this study was to use a naturally fragile and degradable
LbL system focusing on prevention for implants, the authors also considered
the likelihood of disease after implantation, different from peri-implantitis.
To achieve antimicrobial properties, the authors used 1-ethyl-3-[3-(dimethylamino)propyl]carbodiimide
hydrochloride (EDC) in the presence of N -hydroxysulfosuccinimide
(sulfo-NHS) to convert carboxyl groups to amine-reactive sulfo-NHS
esters during the construction of the multilayers. EDC/sulfo-NHS were
used as cross-linkers to extend the contact-killing properties and
the release-killing over time ( C–D). With the possibility of using LbL coatings as a carrier matrix
for target biomolecules such as antimicrobial substances or those
that act directly on inflammatory cells, it offers enormous potential
as a drug delivery system. For instance, in a recent study, silver
nanoparticles (AgNPs) were incorporated into LbL coatings based on
oppositely charged amino cellulose (AM) and acylase. The resulting
hybrid system showed an improved antibacterial and antibiofilm effect,
while decreasing cytotoxicity. The beauty
of the LbL assembly lies in the possibility of using it to produce
a hybrid system that can enhance the efficacy of existing drugs. The
capacity of the LbL system to release incorporated drugs occurs because
the multilayered structures are naturally multiresponsive as a consequence
of interactions among the layers, which means that they answer to
different stimuli, such as temperature, pH, and humidity. It is precisely
due to the capacity of the system to respond to multiple stimuli that
LbL assembly displays the ability to incorporate drugs in high concentrations
within a multilayer thin film and release them in a controlled or
uncontrolled manner , ( C). In our previous work, , we demonstrated that
our LbL system changed molecular conformation upon immersion in ultrapure
water and displayed a swelling behavior of the polyelectrolyte matrix.
Our outcomes were also categorical in showing that when samples were
kept in wet conditions, the LbL system with drug incorporated onto
titanium discs displayed the highest roughness, which indicates that
LbL-coating conformational changes contributed to the drug diffusion
process through the multilayered coating. From a clinical perspective,
the physiological environment of the oral cavity would act to disturb
the stimuli-responsive polyelectrolyte of the system and allow the
release of the incorporated drug for local and immediate action. To
understand how the release process occurs and how to control the concentration
of drugs released at the site, it is necessary to understand the chemical
characteristics of both the system and the released agent. To
reach the biological performance of the controlled drug release,
it is required that the system protects the drug, loads the drug,
and releases the drug in a controlled manner for the needed time,
which are all directly influenced by a drug’s molecular structure. Since the electrostatic interactions between
oppositely charged ions from different layers are the most applied
driving force in the LbL assembly, the same principle must be applied
between polyelectrolyte layers and the target drug. An example includes
antibiotics disclosing hydrophilic properties as target drugs, which
are released more quickly upon exposure to the aqueous environment.
This can be explained by the weak interaction between hydrophobic
and hydrophilic molecules from polymers and antibiotics, respectively, which means that there is no driving force
between the molecules from layers and loaders. , To overcome this issue, researchers have studied amphiphilic
inclusion
complexes with overall drugs to enhance the drug capability to entrap
into hydrophobic layers, increase the
interaction between drug and LbL system, and ensure the controlled
drug release overtime. In a recent study, the authors used amphiphilic
molecule anionic beta-cyclodextrin (β-CD) to retain tetracycline,
as a hydrophilic antibiotic, within the LbL-coating titanium substrate
and control TC release from the multilayers up to 30 days ( E–G). The strong interaction between TC and anionic
β-CD and effective loading of the complex within the LbL system
enabled TC retention within the LbL coatings for a prolonged time,
regardless of medium pH. Importantly, the strong antibacterial effect
was observed after 48 h of incubation with more than 5 log reduction
of bacterial growth in comparison to the uncoated titanium surfaces.
The remaining antibacterial activity of the LbL system was confirmed
even up to 30 days, with 2.8 log reduction of S. aureus compared with the same uncoated surfaces. Summarizing, illustrates how LbL
technology can be tailored for specific dental implant applications
by leveraging different stimuli-responsive features. This table and
summary provide a clear overview of how LbL technology is advancing
the field of dental implants by improving their functionality and
clinical outcomes. It is essential to note that the factors that are
involved in the
structuring of the LbL system are also responsible for the responsive
nature of the bioactive compounds. The most prevalent self-defensive
antibacterial LbL films are pH-responsive because they take advantage
of the release of lactic and acetic acid by different bacteria, which
lowers the pH of the infection’s microenvironment. Thus, pH shifts can alter the conformational
state of the layers in LbL coatings, changing the dimension of the
polyelectrolyte mesh and facilitating the release of drugs. A similar effect occurs when the multilayer
system meets the biological environment. The presence of salts results
in the rearrangement of water molecules within the polyelectrolyte
layers, whose driving force is guided by an entropic effect, modifying
the conformation of the polyelectrolyte present. From this perspective, the release rate does not occur
exclusively through drug diffusion and platform degradation, but the
phenomena involved in extrinsic compensation are also responsible
for changes in the physicochemical properties of the LbL system.
Physical Properties of LbL Coatings for Implant
Abutment Surfaces Implant abutments are essential components
that serve as bridges or extensions attached to implants to secure
artificial teeth. Unlike the implant itself, which is not subject
to mechanical friction during installation, the significance of abutments
lies in their direct contact with surrounding soft tissue. Hence,
any polyelectrolyte coating applied to abutment surfaces should exhibit
sufficient strength to withstand the forces exerted during placement
without being easily being removed. Furthermore, from a clinical point
of view, screw-retained abutments could be easily replaced by coated
ones during disease treatment. It is widely acknowledged that
surface topography significantly influences the biological response
of surrounding tissues to abutments. Numerous studies have demonstrated that rough surfaces tend to accumulate
more plaque, , increasing the risk of plaque-induced
inflammatory reactions in surrounding tissues compared to smoother
surfaces. Therefore, abutments should ideally feature smooth surfaces,
typically less than or around 0.2 μm, , , to facilitate mechanical cleaning
and ensure peri-implant health, especially in patients at risk of
peri-implantitis. Another critical surface property affecting surface
protein adsorption and cell adhesion quality is wettability, with
cells showing a greater propensity to adhere to hydrophilic surfaces. , In essence, any coating-based approach to combat peri-implantitis
should preserve or enhance the inherent properties of the components. For abutments, the primary challenge lies in developing a coating
that maintains the original topography—ensuring it does not
interfere with smoothness and wettability—while adding antimicrobial
properties without adverse effects on human cells. From a dental implant perspective, LbL technology holds
promise for coating implant abutment surfaces. The multilayers assembled onto abutment surfaces allow
precise control of polyelectrolytes’ vertical dispersion at
the nanoscale, thereby achieving the desired roughness based on the
chosen multilayer creation process. , In other
words, LbL-coating properties such as thickness, homogeneity, and
internal structure can be controlled and determined by various LbL
methods. With regards to the wettability,
hydrophilic/hydrophibic potential
of the LbL system is a key factor that influences protein adsorption,
cell adhesion, and the overall interaction between coating and biological
environment. Hydrophilic surfaces may
promote protein adsorption and enhance cellular attachment, which
can be beneficial in the tissue engineering field. Studies have shown that LbL assembly can be used to finely
tune these properties by selecting appropriate materials for the layers. , − For instance, incorporating hydrophilic
polymers such as poly(ethylene glycol) (PEG) can decrease the contact
angle, thus enhancing material hydrophilicity. Owing to the versatility and flexibility of LbL assembly,
coating
surface properties can be easily modified to enhance their biological
response before they come into contact with cells and tissues . However, caution is warranted when considering this technology
for implants themselves due to the risk of displacement or physical
damage to LbL coatings during implant installation. Clearly, LbL assembly
is a system based on a polyelectrolyte responsive to various conditions,
suggesting its susceptibility to mechanical forces.
Key Challenges for an LbL-Based System to Fight
Peri-implantitis While the LbL system holds significant potential,
it also faces
several key challenges that must be addressed for its successful implementation: Limited Long-Term Efficacy . One of
the primary challenges with the LBL system is ensuring its long-term
efficacy in preventing peri-implantitis recurrence. The durability
of the coatings and their ability to withstand the oral environment,
mechanical stresses, and microbial challenges over time are crucial
factors. , Researchers are actively investigating new
materials and coating techniques that offer enhanced stability and
long-lasting protection against infection and/or inflammatory processes. , Biocompatibility and Tissue
Response . The biocompatibility of the materials used in LbL
coatings is essential
for promoting tissue integration and minimizing adverse reactions. , Ensuring that the coatings do not trigger inflammation or immune
responses is crucial for the success of the implant. Researchers are
exploring novel biomaterials and surface modifications to improve
biocompatibility and enhance soft tissue integration. , Optimal Coating Thickness and
Composition . Achieving the right balance in coating thickness
and composition
is another challenge. Coatings that are too thin may not provide adequate
protection against bacterial infiltration, while overly thick coatings
can interfere with tissue integration and healing. , Finding the optimal combination of materials and layering techniques
is an ongoing area of research. Control over Drug Release . Achieving
controlled release of a drug at the targeted location for the time
necessary to achieve the effect of the treatment is one of the major
challenges to be addressed. The main goal of LbL-targeted drug delivery
systems is to obtain high enough local concentrations of drugs through
spontaneous physiological processes with low systemic exposure. Moreover,
the high drug concentration incorporated into the system should not
be cytotoxic to human cells and tissue surrounding the implant component. Mouth as a Complex and Uncontrolled
Environment . The human mouth is a complex system constantly
exposed to saliva,
bacteria, enzymes, and biochemical processes related to the pH variation.
The pH is influenced by diet, oral hygiene practices, medical conditions,
and medications. Although saliva plays a pivotal role in maintaining
the pH balance in the mouth, a consistent imbalance in oral pH can
affect the molecular structure of the LbL system. Indeed, saliva is
one of the most important fluids to interact with overall biomaterials
in the first instance. The interaction of saliva compounds with biomaterials
may cause chemical–physical–biological alterations in
biomaterials. , In fact, in the present Review,
we have underlied the LbL system to peri-implantitis treatment due
to its ability to release the target drug over time. LbL biodegradation
governs the process of drug release, and the release profile of the
drugs depends upon the nature of the delivery system. However, in
addition to the chemical factors, physical forces related to the chewing,
swallowing, or brushing can directly affect the degradation process
and accelerate the drug release. Definitely,
LbL may be defined as a limited system by the fact that it can release
only one dose at a period of time. However, within the oral cavity,
its particular physiological conditions can be considered confounding
factors, promoting stimuli for the unexpected degradation of the biomaterial,
reducing the shell life of the system and compromising the applicability
of the coating. Clinical Translation
and Standardization . Moving from laboratory research to clinical
application presents
its own set of challenges. , , Ensuring that LbL coatings can be easily applied during implant
rehabilitation, are cost-effective, and have predictable outcomes
in diverse patient populations is crucial. Standardizing coating techniques
and protocols across different dental practices and implant systems
is essential for widespread adoption. Regulatory Approval and Safety . Before
LbL coatings can be used clinically, they must undergo rigorous testing
for safety and efficacy. , Obtaining regulatory
approval from health authorities requires extensive preclinical and
clinical studies to demonstrate the coatings’ benefits and
safety profiles. Meeting these regulatory standards adds to the challenges
of bringing LbL approaches to the market. A major concern is the new
MDR (medical device regulation) for which any adjustment to an existing/approved
product requires rigorous testing and documentation and high costs
for regulatory approval ( https://commit-global.com/how-does-the-eu-mdr-affect-the-translation-process/ ). Despite these challenges, the LbL system offers exciting
possibilities
for improving the success rates of dental implants and reducing the
incidence of peri-implantitis. , , , , Ongoing research and technological advancements are gradually addressing
these obstacles, paving the way for the development of innovative
coating materials that enhance the longevity and performance of dental
implants. Toward the end of this Review, it is essential to
address the current
progress in translating Layer-by-Layer (LbL) antimicrobial coatings
for dental implants from the laboratory to clinical application. This
section covers the stage of development of LbL coatings, the preclinical
testing models used, and the prospects for clinical translation.
Current Progress in Translating LbL Antimicrobial
Coatings for Implant Abutment Surfaces The development of
LbL to drug delivery has garnered considerable
attention within the dental implant field for the antimicrobial potential
as a coating implant surface. However,
many studies have focused on applying this technology to the implant
itself, which poses challenges due to the mechanical forces and friction
exerted during placement into the bone, potentially compromising the
integrity of the coating, as discussed earlier. − Contrarily to the prevention and treatment concepts, several articles
have described the system as an interesting strategy to prevent infection
. However,
the multilayers built-up on a surface act as a structure to hold the
drug, which means that the LbL needs to be responsive to different
stimuli to enable the release of the drug. The LbL system could be easily prepared on implant
abutment surfaces.
The fact that the system is considered fragile to mechanical action,
which means that it could be easily removed during toothbrushing,
does not invalidate its importance. The main idea of creating a stimulus-responsive
system is to understand that it will be degraded. However, the lifetime
depends on the anionic and cationic reagents used and could be manipulated
to allow the system to remain on the surface for longer, according
to the pharmacological requirement to treat the target disease. Furthermore, implant abutments disclose a different set of challenges
and opportunities for LbL coatings. Developing
antimicrobial coatings for abutments requires specific considerations,
such as to maintain the smoothness and hydrophilicity of the surface,
ensure biocompatibility with soft tissues, prevent bacterial recolonization
at the soft tissue interface, and promote proper tissue integration
without compromising the peri-implant health. − As such, the translation of LbL coatings for implant abutments remains
a distinct and promising avenue of research, with the potential to
significantly improve the clinical outcomes in peri-implantitis treatment.
This is because the LbL coating does not affect the physical properties
and can either maintain the original roughness or make the surface
even more regular. With regard to the wettability, the reagents might
also be selected to reduce the contact angle between surfaces and
water and increase the hydrophilic requested property to abutment
components. Further advancements in this area would likely focus
on optimizing
the durability and efficacy of these coatings under the unique mechanical
and biological conditions encountered by abutments and aligning preclinical
testing models to reflect these specific needs. Several studies have
shown the antimicrobial properties of LbL coatings in vitro , highlighting their ability to inhibit bacterial biofilm formation
and reduce inflammatory responses around dental implants. , However, translating these findings into human clinical practice
requires robust preclinical testing in animal models and further characterization
of the coatings. Preclinical testing is a critical step in understanding
how LbL
coatings perform in biological environments. Most animal studies to
date are targeting the application for implants rather than for abutments,
and they have focused on small-animal models, such as rats and rabbits,
which offer useful insights into biocompatibility and short-term antimicrobial
efficacy. − These studies have demonstrated significant reductions in bacterial
colonization around the coated implants and provided preliminary evidence
of biocompatibility with the surrounding hard tissues. To the best
of our knowledge, with respect to abutment of dental implant applications,
no comprehensive study has yet been conducted on the use of LbL antimicrobial
coatings in animal models. While there is a growing body of research
exploring LbL coatings for various biomedical applications, , , − the translation of this technology is still stuck in the preclinical
phase, mostly because there is a lack of focus on the conceptual issues
involved in the creation process. Specifically for abutments, the
preclinical animal studies remain limited. This gap underscores the
need for further investigation into the efficacy, biocompatibility,
and long-term performance of LbL coatings in vivo , especially in larger and more physiologically relevant animal models. Collaboration between researchers and industry partners is essential
for scaling up production and ensuring cost-effectiveness. Advances in manufacturing processes and materials
are needed to make LbL coatings commercially viable. Ongoing research
aims to refine LbL-coating technologies, optimize drug release mechanisms,
and further validate their clinical efficacy. , − , , Innovations in coating materials and design, along with comprehensive
clinical trials, will be critical for successful translation.
Conclusion A thorough comprehension
of the working mechanism of Layer-by-Layer
(LbL) assembly is crucial for researchers aiming to implement multilayer
strategies within the dental implant field, particularly in the development
of antimicrobial coatings to combat peri-implantitis. Current knowledge
regarding the LbL system highlights its responsiveness to various
chemical and physical stimuli. However, the responsive and degradable
nature of the materials used in assembling the LbL system imposes
limitations on its biomedical application in terms of the physical
site and purpose. From a dental implant perspective, the fragility
of the coating and its susceptibility to physical force necessitate
the application of the LbL system onto abutment surfaces, which are
in direct contact with soft tissue. Moreover, the versatility
of the LbL system in incorporating a
wide range of drugs and its ability to respond to external stimuli
make it a potential strategy for creating comprehensive antimicrobial
coatings focused on treating peri-implantitis. The mechanism of action
of the LbL system primarily involves the controlled release of drugs,
justifying its use when the disease is already present. In contrast,
for prevention purposes, where the aim is to deter the onset of the
condition, a system with a short shelf life would not suffice. Despite efforts to align clinical conditions with the nature of
the LbL system to better indicate its use as a coating, the complexity
of the oral environment—encompassing saliva, enzymes, varying
pH levels, and brushing—remains a significant challenge to
overcome.
|
null | 04053b0a-4f1a-42f4-9902-2ea443da2a10 | 11492556 | Microbiology[mh] | Natural products are essential bioactive compounds that are derived mostly from plants, animals and micro-organisms . These includes a diverse group of unique chemical compounds with a wide range of biological activities . Additionally, bacteria in particular those survive in extreme environments are considered a significant source of bioactive molecules. A class of bacteria known as actinomycetes is capable of producing a wide range of organic compounds as secondary metabolites. For instance, the industrial actinomycete Streptomyces avermitilis and the actinomycete Streptomyces coelicolor A3(2) each have disclosed about 20 secondary metabolite production pathways. Another illustration is Streptomyces griseus , whose genome sequence led to the discovery of 34 secondary metabolites and 5 production pathways . These gene clusters indicate a strong likelihood of finding novel natural compounds. The largest genus of actinomycetes, Streptomyces , is a Gram-positive soil bacterium that is important in the development of natural products. Waksman and Henrici (1948) were the first to propose the genus Streptomyces , which is one of the most diverse and significant species among microbes. Recently, more than 30 additional genera have been created, and the Streptomyces genus now has 787 species and 38 subspecies . Streptomyces thrive in harsh environments and produce secondary metabolites to extend their survival . More than half of the naturally occurring antibiotics and over 75% of commercially utilized antibiotics have both been obtained from Streptomyces . Chronic transfusions may result in iron excess, which, if left untreated, may harm internal organs. Iron overload can be treated with chelation therapy, which also helps to reduce its negative consequences. Excess of iron contributes to redox processes that stimulate the production of reactive oxygen species (ROS) and raise oxidative stress . The development of selective iron (Fe) chelators for the treatment of Fe overload diseases such as β thalassemia is an area of much current interest. Chelation therapy provides a viable method of treating iron overload and minimizing the adverse effects associated with iron overload. Chelation therapy was first used in the early 20th century to treat metal poisoning. The naturally occurring Streptomyces and other bacterial species are diverse and alternate sources of iron chelating compounds which are rarely investigated . The mangrove-derived Streptomyces bacteria known as MUM273b has been evidenced to produce antioxidative compounds with strong iron chelation activities. These natural compounds from bacteria are supposed to prevent protein oxidation and lipid peroxidation thereby protecting the cell damages and downregulating the Haber–Weiss cycle and Fenton pathway . The current efforts in natural product research from plant and microbes portray a significant intents and potential in the field of drug discovery . Keeping in view that most of the sites, and bacteria isolated for natural compounds has the chances of 99% of the repeatability, a lot of attention has been paid to explore the microbes from unique sites . Microbes living in extreme niches are tend to produce secondary metabolites with strong antioxidant and chelation potential to prolong their survival by protecting the radiation-mediated cell damages . In this study, we investigated the significance of the active compounds identified from Streptomyces sp. from the Bahawalpur desert. The ethyl acetate extract was assessed for its phytochemical contents followed by its structural investigation by using analytical techniques. The extract was also evaluated for its potential to quench the superoxide’s and iron chelation capacity and other pharmacological activities. We revealed through GC-MS that the extract has a high content of phenols and ester compounds thereby contributing to its active nature and bioactivities.
Chemicals All chemicals used were of analytical grade (E. Merck, Germany), Methanol, Ascorbic acid, Chloroform, Acetone, Ethanol, Glycerol, n -Hexane, Silica gel, Water for HPLC, TLC plate. Isolation of radio-resistant bacteria In sterile zipper bags, 50 gram of surface soil samples were aseptically taken from the desert in District Bahawalpur, Punjab, (28.5062° N, 71.5724° E) Pakistan, and then transferred to the microbiology laboratory at the National University of Medical Sciences, Rawalpindi, Pakistan maintained at 4 °C. the samples were serially diluted in phosphate buffer saline (PBS) and spread on the surface of agar plates i.e. (trypton glucose yeast extract agar (TGY) medium consisting g/L: trypton, 10; yeast extract, 5; glucose, 1). Prior to incubation, all the plates were irradiated for 5 minutes’ with ultraviolet-B radiation, wavelength of 280 nm to isolate any potent strain with UV resistant . Identification of radio-resistant bacterium Using previously established techniques, Streptomyces strain was identified visually and biochemically based on its great tolerance to UV light . By sequencing the 16 S rRNA gene, molecular identification was accomplished. This was accomplished by isolating the DNA by using an extraction kit from QIAGEN in Hilden, Germany, and amplification of the 16 S rRNA gene sequence by using the bacterial primers 27 F′ (5′-GAGTTTGATCMTGGCTCAG-3′) and 1492R′ (5′-GGYTACCTTGTTACGACTT-3′). The PCR product was sequenced at Macrogen Service Center (Geunchun-gu, Seoul, South Korea). In order to identify the sequence’s closest relatives, the sequence was BLAST (Basic Local Alignment Search Tool) in the National Center for Biotechnology Information (NCBI) database using Molecular Evolutionary Genetic Analysis (MEGA) version 6. Extract preparation of streptomyces strain Fresh Streptomyces strain culture was inoculated into the 1000 mL fermentation medium to start the fermentation process. The selected fermentation media for the Streptomyces strain was the trypton glucose yeast extract (TGY) medium . The TGY was fermented in an Erlenmeyer flask for three to four days at 28 °C in a shaking incubator (Thermo Scientific Heratherm, USA) at 200 rpm. The fermentation medium was centrifuges (Thermo Scientific Sorvall Legend XTR, USA) for 15 min to remove biomass at 12,000 x g, and the supernatant was collected using Whatman filter paper. The supernatant was mixed with an equal volume of ethyl acetate for 72-hours to ensure the bioactive molecules extraction. Using the rotary evaporator (Thermo Scientific Rotary Evaporator R-100, USA) the filtrate includes ethyl acetate was dried out at 40 o C. The residue was then refined with methanol to yield (5.4 g) of light brown crude extract . Chemical analysis Preliminary, qualitative tests of the extract from Streptomyces sp. for identification of alkaloids, flavonoids, glycosides, saponins, tannin, reducing sugars, anthraquinones, and terpenoids were carried out by the method described by Harborne, Saddiqui Cho, and Auwai . Thin layer chromatography (TLC) The extract from Streptomyces sp. was reconstituted in ethyl acetate and spotted on a TLC silica gel (60F254) plate which was used as a stationary phase. N-hexane: ethyl acetate (1:1) was used as a mobile phase for the determination of the eluent with maximum performance. The TLC plates were evacuated from the chamber when the mobile phase was less than 1 cm from their maximum position. The plates were quickly stained with molybdic acid and ceric sulphate and dried in a heating chamber after the solvent fronts were stamped. The TLC plates were visualized with a UV light (254–365 nm) for any possible spots and other dry phytochemical components. Molybdic acid was employed for phenol, steroid, and other compounds, whereas ceric sulphate was used for recognizable flavonoid evidence. On the basis of values for the retardation factor, the affinities of chemicals were computed (RF values). R f [12pt]{minimal}
$$\:=\:\:\:}{Distance\:travelled\:by\:solvent\:front}$$ High performance liquid chromatography The extract of ethyl acetate was analyzed using high-performance liquid chromatography (HPLC Waters™ e2695) to identify the different chemicals and to check their available quantity in multiple concentrations. It was accomplished with the help of a combination of an extract with the exact HPLC grade methanol, then filtering the resulting mixture through a 0.45-millimetre syringe filter to generate a stock solution. The chromatogram was ultimately captured after a number of stock solution dilutions and the injection of 20 µL sample. The sample was analyzed by a 100Å, 5 μm, 4.6 mm X 250 mm, Waters C-18 reverse-phase column that was eluted at a rate of 1 mL/min using a gradient of 80 to 100% methanol, at 470 nm which lasted 30 min. The photodiode array (PDA) detector was used to capture the absorption spectra of all pertinent peaks . Gas chromatography- mass spectrometry To identify and measure the concentration of active compounds the sample was analyzed through gas chromatography-mass spectrometry (GC-MS) using a prescribed methodology with minor adjustments . The sample was examined using THERMO Scientific’s (DSQ11) GC. A 30-meter-long TR-5MS capillary column with a 0.25 nm internal diameter and a 0.25 mm film thickness; installed in the GC. The temperature of the injector and detector was 250 °C with a carrier gas (Helium) at a speed of 1 mL/minute The injector was adjusted in split mode. The sample was injected into the oven at 50 °C for a few minutes, increased to 150 °C at a rate of 8 °C per minute, and then increased to 300 °C at a rate of 15 °C per minute, held for 5 min. By comparing the constituents’ mass spectral data to those in the National Institute of Standards and Technology (NIST) collection, the constituents were identified. Evaluation of anti-oxidant activity DPPH-radical scavenging activity Based on a previously established procedure with slight modifications, the radical scavenging activity of DPPH (2,2-diphenyl-1-picrylhydrazyl) of Streptomyces extract was investigated . Different concentration of the ethanol-diluted extract (10,20 30 and 40 µL) was added to previously prepared 5 mill molar DPPH in a 96-well plate; adjusting the final volume to 200 µL respectively. The mixture was gently mixed and incubated for 30 mints at room temperature. A microplate reader was used to measure the absorbance at 550 nm. The experimental positive control was ascorbic acid. The proportion of DPPH radical scavenging activity was determined using the following formula: %DPPH scavenging activity= [12pt]{minimal}
$$\:\:100$$ Metal chelating activity The extract’s ability to scavenge ferrous ions was investigated using the previously described approach, with minor modifications using ferrozine can quantitatively combine with ferrous iron to produce complexes that are red in color. Different concentration of the samples ranges from 250, 125, and 62.5 µg/mL was transferred in to 96 well plate followed by addition of 70 µL 2 mM FeCl 2 . The mixture was incubated for 10 min at room temperature and finally adding previously prepared 5 mM ferrozine in 10 µM sodium acetate making final volume to 200 µL. The reaction mixture was incubated at room temperature for 30 min. The absorbance was measured at 492 nm while using EDTA as a positive control, which is a strong chelator. All the experiments were performed in triplicate. The metal chelating activity was calculated by the following formula: % Metal chelating activity = [12pt]{minimal}
$$\:\:100$$ Cytotoxicity assay The cytpotoxic activity of the Streptomy ces extract was evaluated by using Hep G2 (Hepatocellular carcinoma) cell lines through a rapid colorimetric test . using MTT [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide]. In a 96-well plate, the Hep G2 cell lines seeded to a density of 10 4 cells/mL for 24 h using DMEM (Dulbecco’s Modified Essential Medium) supplemented with 10% fetal bovine serum (FBS) and 1x penicillin-streptomycin-neomycin to sustain the cells. To test the antiproliferative activity, various concentration ranges between (10–700 µg/mL) were added and incubated at 37 °C for one day using 5% carbon dioxide. To determine the metabolic activity of the cells, 20 µL of MTT solution (0.25 µg/mL), a yellow tetrazole that transforms into purple formazan in living cells, was added. The plates were agitated for 20 min to ensure the proper mixing and avoid any turbulence in the final reading followed by measurement of the optical density at 570 (Bio Rad). Cells without any treatment served as controls for 100% cellular viability. To calculate the accurate values, the average of blank (controls) was substituted using the medium components along with DMSO and finally plotting the cell viability versus time with different concentrations of the tested sample. The percent inhibition was calculated using the following formula. % Inhibition = [12pt]{minimal}
$$\:\:\:-\:\:}{\:\:}\:100$$ Statistical analysis To represent the data, the average across three (3) consecutive readings was taken. By using (IBM SPSS Statistics 29), Student’s t test was performed to assess the significance of the data, the p < 0.05 value was considered to be significant. Percentage scavenging and chelation activity of extract were studied by regression analysis between the percentage of scavenging and their respective concentrations. Single factor and two-way analysis of variance were applied for analysis of between groups and within a single group for MTT and iron chelation assay.
All chemicals used were of analytical grade (E. Merck, Germany), Methanol, Ascorbic acid, Chloroform, Acetone, Ethanol, Glycerol, n -Hexane, Silica gel, Water for HPLC, TLC plate.
In sterile zipper bags, 50 gram of surface soil samples were aseptically taken from the desert in District Bahawalpur, Punjab, (28.5062° N, 71.5724° E) Pakistan, and then transferred to the microbiology laboratory at the National University of Medical Sciences, Rawalpindi, Pakistan maintained at 4 °C. the samples were serially diluted in phosphate buffer saline (PBS) and spread on the surface of agar plates i.e. (trypton glucose yeast extract agar (TGY) medium consisting g/L: trypton, 10; yeast extract, 5; glucose, 1). Prior to incubation, all the plates were irradiated for 5 minutes’ with ultraviolet-B radiation, wavelength of 280 nm to isolate any potent strain with UV resistant .
Using previously established techniques, Streptomyces strain was identified visually and biochemically based on its great tolerance to UV light . By sequencing the 16 S rRNA gene, molecular identification was accomplished. This was accomplished by isolating the DNA by using an extraction kit from QIAGEN in Hilden, Germany, and amplification of the 16 S rRNA gene sequence by using the bacterial primers 27 F′ (5′-GAGTTTGATCMTGGCTCAG-3′) and 1492R′ (5′-GGYTACCTTGTTACGACTT-3′). The PCR product was sequenced at Macrogen Service Center (Geunchun-gu, Seoul, South Korea). In order to identify the sequence’s closest relatives, the sequence was BLAST (Basic Local Alignment Search Tool) in the National Center for Biotechnology Information (NCBI) database using Molecular Evolutionary Genetic Analysis (MEGA) version 6.
streptomyces strain Fresh Streptomyces strain culture was inoculated into the 1000 mL fermentation medium to start the fermentation process. The selected fermentation media for the Streptomyces strain was the trypton glucose yeast extract (TGY) medium . The TGY was fermented in an Erlenmeyer flask for three to four days at 28 °C in a shaking incubator (Thermo Scientific Heratherm, USA) at 200 rpm. The fermentation medium was centrifuges (Thermo Scientific Sorvall Legend XTR, USA) for 15 min to remove biomass at 12,000 x g, and the supernatant was collected using Whatman filter paper. The supernatant was mixed with an equal volume of ethyl acetate for 72-hours to ensure the bioactive molecules extraction. Using the rotary evaporator (Thermo Scientific Rotary Evaporator R-100, USA) the filtrate includes ethyl acetate was dried out at 40 o C. The residue was then refined with methanol to yield (5.4 g) of light brown crude extract .
Preliminary, qualitative tests of the extract from Streptomyces sp. for identification of alkaloids, flavonoids, glycosides, saponins, tannin, reducing sugars, anthraquinones, and terpenoids were carried out by the method described by Harborne, Saddiqui Cho, and Auwai .
The extract from Streptomyces sp. was reconstituted in ethyl acetate and spotted on a TLC silica gel (60F254) plate which was used as a stationary phase. N-hexane: ethyl acetate (1:1) was used as a mobile phase for the determination of the eluent with maximum performance. The TLC plates were evacuated from the chamber when the mobile phase was less than 1 cm from their maximum position. The plates were quickly stained with molybdic acid and ceric sulphate and dried in a heating chamber after the solvent fronts were stamped. The TLC plates were visualized with a UV light (254–365 nm) for any possible spots and other dry phytochemical components. Molybdic acid was employed for phenol, steroid, and other compounds, whereas ceric sulphate was used for recognizable flavonoid evidence. On the basis of values for the retardation factor, the affinities of chemicals were computed (RF values). R f [12pt]{minimal}
$$\:=\:\:\:}{Distance\:travelled\:by\:solvent\:front}$$
The extract of ethyl acetate was analyzed using high-performance liquid chromatography (HPLC Waters™ e2695) to identify the different chemicals and to check their available quantity in multiple concentrations. It was accomplished with the help of a combination of an extract with the exact HPLC grade methanol, then filtering the resulting mixture through a 0.45-millimetre syringe filter to generate a stock solution. The chromatogram was ultimately captured after a number of stock solution dilutions and the injection of 20 µL sample. The sample was analyzed by a 100Å, 5 μm, 4.6 mm X 250 mm, Waters C-18 reverse-phase column that was eluted at a rate of 1 mL/min using a gradient of 80 to 100% methanol, at 470 nm which lasted 30 min. The photodiode array (PDA) detector was used to capture the absorption spectra of all pertinent peaks .
To identify and measure the concentration of active compounds the sample was analyzed through gas chromatography-mass spectrometry (GC-MS) using a prescribed methodology with minor adjustments . The sample was examined using THERMO Scientific’s (DSQ11) GC. A 30-meter-long TR-5MS capillary column with a 0.25 nm internal diameter and a 0.25 mm film thickness; installed in the GC. The temperature of the injector and detector was 250 °C with a carrier gas (Helium) at a speed of 1 mL/minute The injector was adjusted in split mode. The sample was injected into the oven at 50 °C for a few minutes, increased to 150 °C at a rate of 8 °C per minute, and then increased to 300 °C at a rate of 15 °C per minute, held for 5 min. By comparing the constituents’ mass spectral data to those in the National Institute of Standards and Technology (NIST) collection, the constituents were identified.
DPPH-radical scavenging activity Based on a previously established procedure with slight modifications, the radical scavenging activity of DPPH (2,2-diphenyl-1-picrylhydrazyl) of Streptomyces extract was investigated . Different concentration of the ethanol-diluted extract (10,20 30 and 40 µL) was added to previously prepared 5 mill molar DPPH in a 96-well plate; adjusting the final volume to 200 µL respectively. The mixture was gently mixed and incubated for 30 mints at room temperature. A microplate reader was used to measure the absorbance at 550 nm. The experimental positive control was ascorbic acid. The proportion of DPPH radical scavenging activity was determined using the following formula: %DPPH scavenging activity= [12pt]{minimal}
$$\:\:100$$ Metal chelating activity The extract’s ability to scavenge ferrous ions was investigated using the previously described approach, with minor modifications using ferrozine can quantitatively combine with ferrous iron to produce complexes that are red in color. Different concentration of the samples ranges from 250, 125, and 62.5 µg/mL was transferred in to 96 well plate followed by addition of 70 µL 2 mM FeCl 2 . The mixture was incubated for 10 min at room temperature and finally adding previously prepared 5 mM ferrozine in 10 µM sodium acetate making final volume to 200 µL. The reaction mixture was incubated at room temperature for 30 min. The absorbance was measured at 492 nm while using EDTA as a positive control, which is a strong chelator. All the experiments were performed in triplicate. The metal chelating activity was calculated by the following formula: % Metal chelating activity = [12pt]{minimal}
$$\:\:100$$ Cytotoxicity assay The cytpotoxic activity of the Streptomy ces extract was evaluated by using Hep G2 (Hepatocellular carcinoma) cell lines through a rapid colorimetric test . using MTT [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide]. In a 96-well plate, the Hep G2 cell lines seeded to a density of 10 4 cells/mL for 24 h using DMEM (Dulbecco’s Modified Essential Medium) supplemented with 10% fetal bovine serum (FBS) and 1x penicillin-streptomycin-neomycin to sustain the cells. To test the antiproliferative activity, various concentration ranges between (10–700 µg/mL) were added and incubated at 37 °C for one day using 5% carbon dioxide. To determine the metabolic activity of the cells, 20 µL of MTT solution (0.25 µg/mL), a yellow tetrazole that transforms into purple formazan in living cells, was added. The plates were agitated for 20 min to ensure the proper mixing and avoid any turbulence in the final reading followed by measurement of the optical density at 570 (Bio Rad). Cells without any treatment served as controls for 100% cellular viability. To calculate the accurate values, the average of blank (controls) was substituted using the medium components along with DMSO and finally plotting the cell viability versus time with different concentrations of the tested sample. The percent inhibition was calculated using the following formula. % Inhibition = [12pt]{minimal}
$$\:\:\:-\:\:}{\:\:}\:100$$
Based on a previously established procedure with slight modifications, the radical scavenging activity of DPPH (2,2-diphenyl-1-picrylhydrazyl) of Streptomyces extract was investigated . Different concentration of the ethanol-diluted extract (10,20 30 and 40 µL) was added to previously prepared 5 mill molar DPPH in a 96-well plate; adjusting the final volume to 200 µL respectively. The mixture was gently mixed and incubated for 30 mints at room temperature. A microplate reader was used to measure the absorbance at 550 nm. The experimental positive control was ascorbic acid. The proportion of DPPH radical scavenging activity was determined using the following formula: %DPPH scavenging activity= [12pt]{minimal}
$$\:\:100$$
The extract’s ability to scavenge ferrous ions was investigated using the previously described approach, with minor modifications using ferrozine can quantitatively combine with ferrous iron to produce complexes that are red in color. Different concentration of the samples ranges from 250, 125, and 62.5 µg/mL was transferred in to 96 well plate followed by addition of 70 µL 2 mM FeCl 2 . The mixture was incubated for 10 min at room temperature and finally adding previously prepared 5 mM ferrozine in 10 µM sodium acetate making final volume to 200 µL. The reaction mixture was incubated at room temperature for 30 min. The absorbance was measured at 492 nm while using EDTA as a positive control, which is a strong chelator. All the experiments were performed in triplicate. The metal chelating activity was calculated by the following formula: % Metal chelating activity = [12pt]{minimal}
$$\:\:100$$
The cytpotoxic activity of the Streptomy ces extract was evaluated by using Hep G2 (Hepatocellular carcinoma) cell lines through a rapid colorimetric test . using MTT [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide]. In a 96-well plate, the Hep G2 cell lines seeded to a density of 10 4 cells/mL for 24 h using DMEM (Dulbecco’s Modified Essential Medium) supplemented with 10% fetal bovine serum (FBS) and 1x penicillin-streptomycin-neomycin to sustain the cells. To test the antiproliferative activity, various concentration ranges between (10–700 µg/mL) were added and incubated at 37 °C for one day using 5% carbon dioxide. To determine the metabolic activity of the cells, 20 µL of MTT solution (0.25 µg/mL), a yellow tetrazole that transforms into purple formazan in living cells, was added. The plates were agitated for 20 min to ensure the proper mixing and avoid any turbulence in the final reading followed by measurement of the optical density at 570 (Bio Rad). Cells without any treatment served as controls for 100% cellular viability. To calculate the accurate values, the average of blank (controls) was substituted using the medium components along with DMSO and finally plotting the cell viability versus time with different concentrations of the tested sample. The percent inhibition was calculated using the following formula. % Inhibition = [12pt]{minimal}
$$\:\:\:-\:\:}{\:\:}\:100$$
To represent the data, the average across three (3) consecutive readings was taken. By using (IBM SPSS Statistics 29), Student’s t test was performed to assess the significance of the data, the p < 0.05 value was considered to be significant. Percentage scavenging and chelation activity of extract were studied by regression analysis between the percentage of scavenging and their respective concentrations. Single factor and two-way analysis of variance were applied for analysis of between groups and within a single group for MTT and iron chelation assay.
Isolation and identification of the radioresistant strain The studied Streptomyces strain isolated from Bahawalpur deserts was studied microscopically, was found Gram-positive long filamentous rod, with irregular, off-white, raised anddry, colonies on the surface of agar medium. Additionally, the 16 S rRNA sequencing of this strain was performed, which was put together using DNA Baser software, and was put through the BLAST search engine called NCBI. According to the findings, the obtained strain is a member of the Streptomyces genus submitted with accession PP494735. The isolated strain demonstrated 99.95% similarity to Streptomyces sp. https://www.ncbi.nlm.nih.gov/nuccore/PP494735.1/ . The strain showed high UV resistance and was able to sustain at a UV dose of 2,000 J/m 2 . Fermentation extraction from streptomyces culture The cell-free supernatant was pooled with an equal amount of ethyl acetate for extraction The ethyl acetate extracts were combined and concentrated under low pressure, which afforded a dark brown crude extract that was 5.4 g Before proceeding further, the extract was assembled and mixed in dimethyl sulfoxide (DMSO) with a final concentration of 5 mg/mL. Chemical analysis of the extract To verify the existence of major groups of chemical components, a chemical evaluation of the extract from Streptomyces was performed. The data showed that significant chemical groups were present, such as phenolic compounds, diterpenes, triterpenes, alkaloids, flavonoids, glycosides, and carbohydrates (Table ). TLC analysis of crude extract of streptomyces The crude extract upon TLC screening revealed different Rf values which demonstrated that our extract is a combination of several chemicals that were computed. The crude sample exhibited high UV activity, which was analyzed by UV-VISI at 254 and 365 nm to identify unique spot chemicals using a mobile stage (chloroform and ethyl acetate at a 1:1 ratio) (Fig. ). Tables a, b, and c display deferent the Rf values for crude extract. HPLC analysis of streptomyces crude extract The crude ethyl acetate extract of Streptomyces sp. was initially investigated using the RP-HPLC (C-18) column. HPLC, UV analysis of the crude extract displayed two major broad peaks at 254 nm, whereas their intensity was very low at 360 nm which is shown in Fig. a. Moreover, both major peaks displayed shorter retention times with 2.6 and 5.7 min respectively. Furthermore, another HPLC method was developed in which the two major peak retention times were further increased by increasing the concentration of H 2 O during the elution (Fig. b). GC-MS analysis of ethyl acetate extract GC-MS analysis of the ethyl acetate extract of Streptomyces sp. displayed several peaks that highlighted the presence of concerned compounds. The constituents that are present in the extract GC-MS spectra were compared with already reported compounds library, as a result, seven different bioactive chemicals responsible for the given pharmacological activities of the extract were identified as given in Table . Similarly, the mass spectra and chemical structures of the constituents which were detected in the ethyl acetate extract of Streptomyces sp. are displayed in Figs. and . Antioxidant assay DPPH radical scavenging activity Our results revealed that ethyl acetate extract has a significant DPPH radical scavenging activity and the color of diphenyl picrylhydrazine (reduced form) changed from a violet DPPH radical solution to a yellow. The results showed that Streptomyces sp. extract, exhibited an increased activity in a concentration dependent manner when used in a concentration ranges from 0.015625 to 0.5 mg/mL, as shown in Fig. . The IC 50 value was calculated 0.034 mg/mL which indicated potent activity. Similarly, ascorbic acid which was used as a positive control demonstrated an IC 50 at 0.12 mg/mL, as shown in Table . Metal chelating activity The extract showed substantial iron chelation activity when used at 250 and 125 µg/mL concentration that signify its potential in iron chelation therapy. The chelation activity was declined when the sample was used in low concertation i.e. 62.5 g/mL as shown in Fig. . Our study revealed that, in comparison to the control EDTA which is a strong chelator, the crude ethyl acetate extract of Streptomyces sp. demonstrated strong ion chelating activity, which further pointed out the importance of this extract against reactive oxygen species suppression. Cytotoxicity MTT assay By using the MTT assay on 96-well plates, the cytotoxic effects of various doses of ethyl acetate extract on HepG2 cell lines were assessed. The IC 50 values were calculated as 352 µg/mL for HepG2 cell lines. The results revealed that the extract exhibited concentration-dependent inhibition on HepG 2 cells. As illustrated by Fig. , 350 µg/mL of the extract showed 51% cytotoxicity whereas 700 µg/mL inhibited 65% of cell growth. According to the reported IC 50 value, the extract was less harmful to normal cells than it was to cancerous cells. Antiproliferative activity of Streptomyces extract against HepG2 cell line using MTT assay was measured by plotting the dose response curve verses concentration of tested sample and percentage viable cells through linear regression analysis by which the IC 50 was obtained.
The studied Streptomyces strain isolated from Bahawalpur deserts was studied microscopically, was found Gram-positive long filamentous rod, with irregular, off-white, raised anddry, colonies on the surface of agar medium. Additionally, the 16 S rRNA sequencing of this strain was performed, which was put together using DNA Baser software, and was put through the BLAST search engine called NCBI. According to the findings, the obtained strain is a member of the Streptomyces genus submitted with accession PP494735. The isolated strain demonstrated 99.95% similarity to Streptomyces sp. https://www.ncbi.nlm.nih.gov/nuccore/PP494735.1/ . The strain showed high UV resistance and was able to sustain at a UV dose of 2,000 J/m 2 .
streptomyces culture The cell-free supernatant was pooled with an equal amount of ethyl acetate for extraction The ethyl acetate extracts were combined and concentrated under low pressure, which afforded a dark brown crude extract that was 5.4 g Before proceeding further, the extract was assembled and mixed in dimethyl sulfoxide (DMSO) with a final concentration of 5 mg/mL.
To verify the existence of major groups of chemical components, a chemical evaluation of the extract from Streptomyces was performed. The data showed that significant chemical groups were present, such as phenolic compounds, diterpenes, triterpenes, alkaloids, flavonoids, glycosides, and carbohydrates (Table ).
streptomyces The crude extract upon TLC screening revealed different Rf values which demonstrated that our extract is a combination of several chemicals that were computed. The crude sample exhibited high UV activity, which was analyzed by UV-VISI at 254 and 365 nm to identify unique spot chemicals using a mobile stage (chloroform and ethyl acetate at a 1:1 ratio) (Fig. ). Tables a, b, and c display deferent the Rf values for crude extract.
streptomyces crude extract The crude ethyl acetate extract of Streptomyces sp. was initially investigated using the RP-HPLC (C-18) column. HPLC, UV analysis of the crude extract displayed two major broad peaks at 254 nm, whereas their intensity was very low at 360 nm which is shown in Fig. a. Moreover, both major peaks displayed shorter retention times with 2.6 and 5.7 min respectively. Furthermore, another HPLC method was developed in which the two major peak retention times were further increased by increasing the concentration of H 2 O during the elution (Fig. b).
GC-MS analysis of the ethyl acetate extract of Streptomyces sp. displayed several peaks that highlighted the presence of concerned compounds. The constituents that are present in the extract GC-MS spectra were compared with already reported compounds library, as a result, seven different bioactive chemicals responsible for the given pharmacological activities of the extract were identified as given in Table . Similarly, the mass spectra and chemical structures of the constituents which were detected in the ethyl acetate extract of Streptomyces sp. are displayed in Figs. and .
DPPH radical scavenging activity Our results revealed that ethyl acetate extract has a significant DPPH radical scavenging activity and the color of diphenyl picrylhydrazine (reduced form) changed from a violet DPPH radical solution to a yellow. The results showed that Streptomyces sp. extract, exhibited an increased activity in a concentration dependent manner when used in a concentration ranges from 0.015625 to 0.5 mg/mL, as shown in Fig. . The IC 50 value was calculated 0.034 mg/mL which indicated potent activity. Similarly, ascorbic acid which was used as a positive control demonstrated an IC 50 at 0.12 mg/mL, as shown in Table .
Our results revealed that ethyl acetate extract has a significant DPPH radical scavenging activity and the color of diphenyl picrylhydrazine (reduced form) changed from a violet DPPH radical solution to a yellow. The results showed that Streptomyces sp. extract, exhibited an increased activity in a concentration dependent manner when used in a concentration ranges from 0.015625 to 0.5 mg/mL, as shown in Fig. . The IC 50 value was calculated 0.034 mg/mL which indicated potent activity. Similarly, ascorbic acid which was used as a positive control demonstrated an IC 50 at 0.12 mg/mL, as shown in Table .
The extract showed substantial iron chelation activity when used at 250 and 125 µg/mL concentration that signify its potential in iron chelation therapy. The chelation activity was declined when the sample was used in low concertation i.e. 62.5 g/mL as shown in Fig. . Our study revealed that, in comparison to the control EDTA which is a strong chelator, the crude ethyl acetate extract of Streptomyces sp. demonstrated strong ion chelating activity, which further pointed out the importance of this extract against reactive oxygen species suppression.
MTT assay By using the MTT assay on 96-well plates, the cytotoxic effects of various doses of ethyl acetate extract on HepG2 cell lines were assessed. The IC 50 values were calculated as 352 µg/mL for HepG2 cell lines. The results revealed that the extract exhibited concentration-dependent inhibition on HepG 2 cells. As illustrated by Fig. , 350 µg/mL of the extract showed 51% cytotoxicity whereas 700 µg/mL inhibited 65% of cell growth. According to the reported IC 50 value, the extract was less harmful to normal cells than it was to cancerous cells. Antiproliferative activity of Streptomyces extract against HepG2 cell line using MTT assay was measured by plotting the dose response curve verses concentration of tested sample and percentage viable cells through linear regression analysis by which the IC 50 was obtained.
By using the MTT assay on 96-well plates, the cytotoxic effects of various doses of ethyl acetate extract on HepG2 cell lines were assessed. The IC 50 values were calculated as 352 µg/mL for HepG2 cell lines. The results revealed that the extract exhibited concentration-dependent inhibition on HepG 2 cells. As illustrated by Fig. , 350 µg/mL of the extract showed 51% cytotoxicity whereas 700 µg/mL inhibited 65% of cell growth. According to the reported IC 50 value, the extract was less harmful to normal cells than it was to cancerous cells. Antiproliferative activity of Streptomyces extract against HepG2 cell line using MTT assay was measured by plotting the dose response curve verses concentration of tested sample and percentage viable cells through linear regression analysis by which the IC 50 was obtained.
Natural products are usually obtained from different sources including plants animals and microbes. Among the microbes, the extremophiles are getting attention due to their ability to survive in extreme environments and high diversity which consequently lead them to produce diverse biomolecules with potent biological activities . These organisms have biosynthesized various biomolecules such as carotenoids, and compatible solutes as part of their defense mechanisms to extend their survival . Streptomyces , which is the genus of the actinomycetes, is significantly important in the manufacture of therapeutically important compounds such as antibacterial, antifungal, antitumor agents, and immunosuppressants. Interestingly hundreds of compounds have been isolated from Streptomyces , most of which are currently used as allopathic medicine to suppress various ailments . Among the 12 isolates from desert samples, WM-32 was selected based on high UV tolerance and ability to produce high-active compounds. The strain demonstrated 99% of the similarity to the Streptomyces genera through phylogenetic analysis. TGY broth was the choice of fermentation at a small scale for Streptomyces sp. The ethyl acetate extract was further fractionated and finally evaporated using a rotary evaporator having low temperature and high pressure, and a crude extract of 5.4 g was obtained. This whole process unveiled that the targeted bacteria Streptomyces sp. was a good source to produce secondary metabolites. Furthermore, chemical analysis was carried out to determine the presence of different classes of compounds, this analysis disclosed that phenols, flavonoids, terpenoids, and alkaloids class of compounds are present in the extract whereas tannins, steroids, and anthraquinones were not detected. The bioactivities of the extract may be the reason for the resonance double ring structure and phenolic groups, which are able to give free electrons to form stable final products and inhibit the formation of superoxides. This phenomenon is quite justifiable by revealing the different antioxidant activities of the extract from Streptomyces sp. Our analytical analysis i.e. TLC, HPLC, and GC-MS and chromatogram extracted demonstrated a clearer picture of the respective molecules present in the crude extract. The TLC results additionally identified UV active chemicals using spot detection with sulfuric acid and iodine reagent, this led to the discovery of three sites with Rf values of 0.07, 0.75, and 0.88 as well (chloroform: ethyl acetate,1:1). Most of the compounds produced by microbes in extreme environment exhibit a strong coloring potential. The reason might be that those coloring compounds possess a strong chromophore to absorb the toxic UV rays thereby preventing the oxidative damages. The absorption maxima ( λ max ) at 254 and 360 nm detected through HPLC also suggest the presence of strong phenolics, flavonoids, and keto groups . The resonance structure of such molecules is thought to contribute towards the antioxidant and iron chelating potential . The peak resolution and retention time during the HPLC was also improved by addition of H 2 O to the mobile phase which results in the HPLC peaks separating apart . Our GC-MS analysis of the ethyl acetate extract demonstrated 6 different compounds that contributing to the bioactivities. These bioactive compounds are supposed to be produced by extremophiles in harsh environment to prevent desiccation, cell damage and thereby these are also considered as cell factories for bioactive compounds . Based on the NIST database it was predicted that the bioactive molecule is the constituent of seven predominant compounds composed preliminarily of components like alcohols, esters, phenolics, and cyclic terpenoids. The mono-esterified, phenolics and flavonoids from Streptomyces sp. showed a twofold stronger quenching ability of superoxides than has been reported for other active metabolites and β-carotenes. This characteristic may be attributed to the extra keto-group substitution and length of their conjugated double-bond system . The antioxidant potential of bioactive compounds from radio-resistant microbes has been recognized as a contributory factor to the radioprotection offered by different compounds . Recent studies highlighted that the reactive oxygen species (ROS) has a considerable role in different diseases like cancer, autoimmune disorders, `and neurodegenerative diseases . Phenolic compounds and their derivatives are well known for their antioxidant activities. Interestingly the ethyl acetate crude extract exhibited considerable scavenging activity concentration concentration-dependent manner in comparison with the reference compound i.e. ascorbic acid. The potential of any active molecule to scavenge the free radicals is dependent on its capability of donating hydrogen atoms to other radicals thereby producing end stable products . The degree of discoloration of DPPH is strong evidence for any active compound to scavenge free radicals showing that with an increase in concentration of the compound the ability to quench superoxide also increases. Our ethyl acetate extract demonstrated high chelation activity in a concentration-dependent manner. The complex formation of ferrozine with ferrous ion yields a red color. However, any presence of the chelating agent disrupts the formation of complex resulting in decrease in red color formation. The iron chelation activity is of great significance because the transition metal ions are helpful to oxidize agents through fenton pathway which results in oxidative damage in neurodegenerative disorders . The current studied strain isolated from Bahawalpur desert and its bioactive extract offers significant iron chelation potential. Chelation therapy to treat iron overload diseases include thalassemia and other anemic conditions is on rise to neutralize the freely available iron in the body. Exploring the metabolic pathways and further investigation the active ingredients in the extract will open new avenues in chelators from extremophiles . Further we also evaluated the cytotoxic effect by use of MTT assay in 96-well plate on Hep G2 cell lines. Streptomyces sp. is considered as potentially important source of novel bioactive anticancer compounds and capable of producing chemically diverse compounds without any side effects for variety of clinical applications . The cytotoxic mechanism of such natural compounds is to interfere with the basic cellular functions i.e. cell cycle arrest, invasion, inflammation and apoptosis. Many anticancer drugs from the extremophiles and other marine microbes reported to cause cytotoxicity and cell death through apoptosis. Several cytotoxic drugs are available in the market today however most of them lack tumor specificity and can cause damage to the normal tissues as well. Our study revealed that the crude ethyl acetate extract of Streptomyces sp. was a mixture of various bioactive compounds which displayed significant pharmacological activities, especially the antioxidant potential of the crude extract was several fold more effective than the antioxidant effect of ascorbic acid, which was used as a positive control in this study.
It was concluded that Streptomyces sp. is a rich source of several bioactive constituents which were initially highlighted by the presence of various chemical classes such as alkaloids, flavonoids, phenols, and terpenoids. In pharmacological screening, the ethyl acetate crude extract displayed potent antioxidant activities using DPPH. Similarly, the ethyl acetate crude extract also exhibited significant iron-chelation activity and cytotoxic activities against HepG2 cancer cells dose-dependently. These overall results highlighted that Streptomyces sp. is a rich source of important bioactive metabolites and could be a potential source of antioxidant and anti-cancerous compounds to prevent the cells from oxidative damage induced by superoxide’s. Limitations of the study and future work Identifying and characterizing the specific compounds responsible for antioxidant and iron chelating activities is a complex process. The study faced challenges in isolating and purifying these compounds, potentially leading to incomplete identification of bioactive molecules. However, by incorporating these metabolomics-focused future directions, researchers can gain a deeper understanding of the metabolic landscape of Streptomyces sp., optimize the production of valuable bioactive compounds, and explore new applications for antioxidants and iron chelators in various fields.
Identifying and characterizing the specific compounds responsible for antioxidant and iron chelating activities is a complex process. The study faced challenges in isolating and purifying these compounds, potentially leading to incomplete identification of bioactive molecules. However, by incorporating these metabolomics-focused future directions, researchers can gain a deeper understanding of the metabolic landscape of Streptomyces sp., optimize the production of valuable bioactive compounds, and explore new applications for antioxidants and iron chelators in various fields.
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Molecular diagnostic practices for infectious gastroenteritis | c3c2fc19-0b64-40a3-a8bf-7a6f8547df4d | 7339359 | Pathology[mh] | This work was supported by grants from the Collaborative Innovation Center for Translational Medicine at Shanghai Jiao Tong University School of Medicine (No. TM201820 and TM201927), Clinical Science and Technology Innovation Project of Shanghai Shenkang Hospital Development Center (No. SHDC12019X35), and the Interdisciplinary Program of Shanghai Jiao Tong University (No. YG2017QN33). None. |
Molecular Epidemiology, Drug-Resistant Variants, and Therapeutic Implications of Hepatitis B Virus and Hepatitis D Virus Prevalence in Nigeria: A National Study | ee6f45fc-037e-47af-b403-872ba241a2fa | 11768191 | Biochemistry[mh] | Hepatitis B virus (HBV) infection, the commonest human viral hepatitis (VH), is the second leading transmittable cause of mortality on the planet . Currently, HBV has a global prevalence of about 300 million people and an incidence of 1.5 million cases annually, with at least a third of the world population having been infected at different points . The African region (with a prevalence of 6.1%) has been identified as one of the ‘hotspots’ for VH, with an average of one person dying of HBV infection every 2.5 min . Nigeria, with a generally low complete vaccination rate (36.2 to 59.5% in healthcare workers), is reported to be one of the five countries responsible for more than 50% of global hepatitis B infections . In Nigeria, the prevalence of HBV is about five times that of HIV in the 15–64-year age group: 8.1% versus 1.5%. Viral hepatitis is a disease of public health importance that receives little attention in funding, awareness, and treatment in Nigeria . Slowly, but evidently, there is currently less transmission of HBV and more disease (resulting from previous infections of 20–40 years ago) due to epidemiological transmission in Nigeria; hence surveillance, monitoring, and effective therapy become vital as control and management strategies. The plan to eliminate VH (i.e., reduction in incidence by 90% and mortality by 65%) as a public health threat by 2030 as approved by the World Health Assembly (WHA) will prevent about 36 million infections and save about 10 million lives by that year . Achieving this target requires not only preventive measures but also a more effective therapy. Available therapies [including alpha-interferon (IFN) together with six nucleos(t)ide analogues (NAs)] which only suppress HBV replication are not just expensive but have also been variously faulted, including the acquisition of drug resistance-associated variants (DRAVs) of HBV mitigating against the achievement of the WHA 2030 VH goal . The nucleos(t)ide analogues target and suppress the reverse transcriptase (RT) in the pol -gene while interferon has antiviral and immune-modulating properties. Additionally, responses to therapy vary depending on the genotype and the presence or not of multiple genotype/mixed genotype infection. For instance, HBV A+D mixed genotypic infection has been documented to hold up to six times higher risk of progression to hepatocellular carcinoma (HCC) compared with HBV genotype A infection . The distribution pattern of the HBV genotypes, which varies with patients and geographical location worldwide, is associated with disease progression [to liver cirrhosis, HCC, liver failure, and death], the mode of transmission, clinical outcome, and treatment response . For instance, HBV genotypes B and C, found mainly in Asia, are predominantly transmitted vertically. In contrast, other genotypes found in other geographical areas (e.g., genotype E in West Africa and F in South America) tend to be transmitted horizontally. HBV sub-genotypes have also demonstrated defined geographical patterns and clinical outcomes. While A1 has been linked to fast progression to cirrhosis and HCC, A2 progresses more slowly. Also, A1 and B have a high response rate to interferon while C, D, and I have a low response rate in one study . In addition, cases of DRAVs have been reported with the current regime of drugs. Hepatitis B viruses have a life cycle that requires an error-prone reverse transcriptase for replication. This results in tremendous genetic variation in the form of (sub-)genotypes. The error-prone HBV polymerase generates the genetic variability observed as viral quasi-species that can lead to resistance to antiviral agents. Both treatment-naïve and patients who failed treatment can have RAVs, with a large proportion of those who failed antiviral therapy acquiring resistance . In some cases, acquired resistance leads to cross-resistance against other antiviral agents, limiting future options. There are four genes in the HBV genome encoding different proteins. Apart from the pol -gene mentioned above, naturally occurring or therapeutic-induced HBV variants with mutation can occur in other HBV open reading frames (ORFs): the pre-S/S region, leading to vaccine escape mutants (VEMs), viral clearance disturbance for the preS1/preS2 region, non-response to IFN therapy for the pre-C region, decreased HBeAg expression for the C region, and tumorigenesis for X -gene variants . In Nigeria (as in most LMICs), genotyping and baseline resistance testing are not routinely carried out in VH management. Also, only pockets of studies have reported that genotype E is the predominant HBV in these areas of the country. Hepatitis D virus (HDV), which causes the most severe form of viral hepatitis (VH) infection, only occurs in persons who are infected with HBV since HDV depends on HBV for its replication. Although immunisation against HBV in those not infected with the two viruses would protect against both HBV and HDV, the treatment of HBV with currently approved NAs does not influence HDV infection . With no antivirals currently approved against HDV (only 48 weeks of PEG IFN alpha that only suppresses the virus in a quarter of patients is available), the proper understanding of the distribution of HDV in Nigeria is crucial. Recent WHO recommendations for chronic hepatitis B (CHB) treatment have added CHB cases with HDV coinfection. HDV affects nearly 4.5% of people globally. Up to 7.33% of the sub-Saharan African population is affected by HDV, with the national prevalence unknown in Nigeria . For the effective management (including the choice of treatment medications, testing, and vaccine selection) and possible elimination of VH as projected, there is a need to investigate the relationship between HBV genetic variation, and drug treatment in the Nigerian population. Therefore, this study sought to elicit the distinct genetic characterisation of HBV circulating in Nigeria including clinically relevant variants that may influence therapies to guide HBV precision management and HDV prevalence in Nigeria. 2.1. Study Design and Samples This cross-sectional, nationally representative study was nested in the recent Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) study. NAIIS was a two-stage, household cluster study of 15-to-64-year-olds. The survey sampled enumeration areas (EAs) followed by households. The EAs were mutually exclusive and all households in Nigeria had an equal chance of being included in the survey. The first stage of sampling selected 4035 EAs using a probability proportional to size method. The 4035 EAs were stratified by Nigeria’s 36 states and the FCT. The second stage selected a random sample of households within each EA using an equal probability method . All plasma samples and epidemiological data used for this study were retrieved from the biorepository of the NAIIS study at the National Reference Laboratory (NRL) of the Nigeria Centre for Disease Control and Prevention (NCDC) in Gaduwa, Abuja. The 10,653 community participants’ data captured for the VH arm of NAIIS yielded a national prevalence of 8.1%. In total, 777 HBV-positive plasma samples were received from the NCDC NRL for this study . Up to 94.2% (732) of these samples were included in downstream laboratory analyses. From the blood samples collected, HBV screening using the Determine™ HBsAg test kit (Abbott Inc., Chicago, IL, USA) was conducted during NAIIS. The rest of the specimens were processed into plasma aliquots and dried blood spots (DBSs) and stored appropriately . Subjects included in this study were 15–64-year-olds with positive HBsAg tested via the Determine™ HBsAg kit. We excluded participants with inadequate plasma samples (≤200 μL). 2.2. Hepatitis D Virus ELISA The human hepatitis D virus (HDV) antibody (IgG) ELISA Kit (CUSABIO TECHNOLOGY LLC, Houston, USA, catalogue number CSB-E04809h) was used to perform HDV serology on 777 HBV samples (763 plasma and 14 DBSs), according to the manufacturer’s instructions. 2.3. Nucleic Acid Extraction from HBsAg-Positive Blood Samples and Quantitative Polymerase Chain Reaction The HBV DNA extraction was performed on 50 μL of all available HBV plasma samples (763) using the SMITEST EX-R&D kit (catalogue number GS-J0201), MBL, Japan, as per the manufacturer’s instructions . The DBS DNA Isolation Kit by Norgen Biotek, Ontario, Canada (catalogue number 36000) was used to extract HBV DNA from 14 DBS-stored samples, according to the manufacturer . The final elution volume of extracted HBV DNA was 20 μL, all carried out at the NCDC NRL, Abuja, Nigeria. The HBV DNA levels were assessed by a real-time PCR assay using the StepOnePlus real-time PCR system, California, USA (the protocol number for the MicroAmp™ Fast 8-Tube Strip is 4323032) as previously described, with a lower limit of detection of 2.3 IU/mL . 2.4. Amplification of HBV DNA for Sequencing, Sequencing of S- and Pol- Genes, Alignment, and Phylogenetic Analysis, and Mutational Analysis Please refer to for details on these methods. 2.5. Data Analysis Frequencies and percentages were used to describe the characteristics of the samples. The Chi-Square (χ2) test was used to test the differences between groups (or Fishers’ exact test if the cell count was ≤ 5). The obtained values were considered statistically significant at p ≤ 0.05. We employed logistic regression for multivariate analysis to identify factors associated with variants. In the multivariate analysis, we calculated adjusted odds ratios employing a backward stepwise selection. Phylogenetic trees were produced using Geneious Prime software version 2024.0.7 and adjusted visually with the iTOL tool version 7. The trees were aligned with the MAFFT algorithm. This cross-sectional, nationally representative study was nested in the recent Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) study. NAIIS was a two-stage, household cluster study of 15-to-64-year-olds. The survey sampled enumeration areas (EAs) followed by households. The EAs were mutually exclusive and all households in Nigeria had an equal chance of being included in the survey. The first stage of sampling selected 4035 EAs using a probability proportional to size method. The 4035 EAs were stratified by Nigeria’s 36 states and the FCT. The second stage selected a random sample of households within each EA using an equal probability method . All plasma samples and epidemiological data used for this study were retrieved from the biorepository of the NAIIS study at the National Reference Laboratory (NRL) of the Nigeria Centre for Disease Control and Prevention (NCDC) in Gaduwa, Abuja. The 10,653 community participants’ data captured for the VH arm of NAIIS yielded a national prevalence of 8.1%. In total, 777 HBV-positive plasma samples were received from the NCDC NRL for this study . Up to 94.2% (732) of these samples were included in downstream laboratory analyses. From the blood samples collected, HBV screening using the Determine™ HBsAg test kit (Abbott Inc., Chicago, IL, USA) was conducted during NAIIS. The rest of the specimens were processed into plasma aliquots and dried blood spots (DBSs) and stored appropriately . Subjects included in this study were 15–64-year-olds with positive HBsAg tested via the Determine™ HBsAg kit. We excluded participants with inadequate plasma samples (≤200 μL). The human hepatitis D virus (HDV) antibody (IgG) ELISA Kit (CUSABIO TECHNOLOGY LLC, Houston, USA, catalogue number CSB-E04809h) was used to perform HDV serology on 777 HBV samples (763 plasma and 14 DBSs), according to the manufacturer’s instructions. The HBV DNA extraction was performed on 50 μL of all available HBV plasma samples (763) using the SMITEST EX-R&D kit (catalogue number GS-J0201), MBL, Japan, as per the manufacturer’s instructions . The DBS DNA Isolation Kit by Norgen Biotek, Ontario, Canada (catalogue number 36000) was used to extract HBV DNA from 14 DBS-stored samples, according to the manufacturer . The final elution volume of extracted HBV DNA was 20 μL, all carried out at the NCDC NRL, Abuja, Nigeria. The HBV DNA levels were assessed by a real-time PCR assay using the StepOnePlus real-time PCR system, California, USA (the protocol number for the MicroAmp™ Fast 8-Tube Strip is 4323032) as previously described, with a lower limit of detection of 2.3 IU/mL . Please refer to for details on these methods. Frequencies and percentages were used to describe the characteristics of the samples. The Chi-Square (χ2) test was used to test the differences between groups (or Fishers’ exact test if the cell count was ≤ 5). The obtained values were considered statistically significant at p ≤ 0.05. We employed logistic regression for multivariate analysis to identify factors associated with variants. In the multivariate analysis, we calculated adjusted odds ratios employing a backward stepwise selection. Phylogenetic trees were produced using Geneious Prime software version 2024.0.7 and adjusted visually with the iTOL tool version 7. The trees were aligned with the MAFFT algorithm. 3.1. Characteristics of HBV-Positive Respondents and HDV Seroprevalence Out of the 805 subjects that were HBsAg + in NAIIS, 777 samples were available at the biorepository for our study. The median age of HBV-positive respondents was 32.5 years (range: 15, 64) with the 25–29-year age group having the highest proportion of HBV seroprevalence [male = 19.5% (16.0–23.6) %; female = 17.0% (13.4–21.1) %] . A total of 19 states out of the 36 + 1 states had an HBV prevalence of ≥8%, whereas Imo State had <2% ( and ). The northcentral geopolitical zone had the highest prevalence, 10.4% ( p -value <0.001). Up to 66.8% (63.4–70.0) of HBV positives had a detectable viral load (VL) of <300 c/mL, followed by 16.7% (14.3–19.5) with 300–9999 c/mL, and 16.5% (14.0–19.3) with ≥10,000 c/mL. Multivariate analysis revealed that being in the 55–59-year age group, a female, and living in the southeast and southsouth geopolitical zones are relatively lower risks of being infected with HBV in Nigeria . The seroprevalence of HDV among all the 777 HBV-positive subjects was 7.34% [CI: (5.5–9.2)]. Of the 57 HDV-positive persons, males were 40.4% (28.3–53.7); females and the 20–24- and 30–34-year age groups had the highest frequency [17.5% (CI: 9.6–29.9) each]. Up to 19.3% (11, CI: 10.9–31.9) of HDV/HBV-coinfected individuals had HBV VLs of ≥10,000 c/mL. 3.2. Circulating (Sub-)Genotypes in Nigeria Two genotypes were detected from 626 out of 777 analysed samples (80.6%) of successfully sequenced s - and pol -genes: genotypes E, 98.4% (97.1–99.1), and A, 1.6% (0.9–2.9) with A2, A3, C2, D1, D3, E, F4, and G subtypes ( shows the hotspots of genotypes A and E for all samples while shows the phylogenetic tree for samples with F and R reads using the HBV s -gene). The density of genotype E is highest (>20) in the following states: Kano (35), Oyo (33), Niger (32), Benue (32), Kaduna (28), Kebbi (26), Taraba (25), Lagos (25), Bauchi (24), Sokoto (22), Plateau (22), and Adamawa (21). Genotype A was detected in Benue (3), Oyo (2), Bauchi (1), Kebbi (1), Kogi, Lagos (1), and Osun (1) states. 3.3. Therapeutically Important Variants in Nigeria We detected 72 (9.3%) DRAVs and 3 (0.4%) IEVs, altogether accounting for 9.7% (7.8–12.0) out of 777 samples. The DRAVs were against four (Adefovir, Entecavir, Lamivudine, and Telbivudine) out of five nucleos(t)ide analogues with no resistance against Tenofovir. The mutations include 80X, 169X, 173X, 180X, 181X, 184X, 202X, and 204X (DRAVs) and 137X and 145K (IEVs) ( and ). The 169X and 173X mutations have the widest spread (23 states; and ). Two IEVs (137X and 145K) were identified (summary in ). The significance of some of the identified variants is yet to be understood. Only 23.3% [14.9–34.5] of the 73 samples with detected RAVs have one mutation (the remaining 76.7% [65.5–85.1] have >1 RAVs). Residence in the southeast (aOR = 2.6; 95% CI: 1.1–6.4, p = 0.038) and being in the age groups 30–34 years (aOR = 3.5; 95% CI: 1.3–10.3, p = 0.015) and 55–59 years (aOR = 6.7; 95% CI: 1.3–37.5) are predictors of RAVs . Out of the 805 subjects that were HBsAg + in NAIIS, 777 samples were available at the biorepository for our study. The median age of HBV-positive respondents was 32.5 years (range: 15, 64) with the 25–29-year age group having the highest proportion of HBV seroprevalence [male = 19.5% (16.0–23.6) %; female = 17.0% (13.4–21.1) %] . A total of 19 states out of the 36 + 1 states had an HBV prevalence of ≥8%, whereas Imo State had <2% ( and ). The northcentral geopolitical zone had the highest prevalence, 10.4% ( p -value <0.001). Up to 66.8% (63.4–70.0) of HBV positives had a detectable viral load (VL) of <300 c/mL, followed by 16.7% (14.3–19.5) with 300–9999 c/mL, and 16.5% (14.0–19.3) with ≥10,000 c/mL. Multivariate analysis revealed that being in the 55–59-year age group, a female, and living in the southeast and southsouth geopolitical zones are relatively lower risks of being infected with HBV in Nigeria . The seroprevalence of HDV among all the 777 HBV-positive subjects was 7.34% [CI: (5.5–9.2)]. Of the 57 HDV-positive persons, males were 40.4% (28.3–53.7); females and the 20–24- and 30–34-year age groups had the highest frequency [17.5% (CI: 9.6–29.9) each]. Up to 19.3% (11, CI: 10.9–31.9) of HDV/HBV-coinfected individuals had HBV VLs of ≥10,000 c/mL. Two genotypes were detected from 626 out of 777 analysed samples (80.6%) of successfully sequenced s - and pol -genes: genotypes E, 98.4% (97.1–99.1), and A, 1.6% (0.9–2.9) with A2, A3, C2, D1, D3, E, F4, and G subtypes ( shows the hotspots of genotypes A and E for all samples while shows the phylogenetic tree for samples with F and R reads using the HBV s -gene). The density of genotype E is highest (>20) in the following states: Kano (35), Oyo (33), Niger (32), Benue (32), Kaduna (28), Kebbi (26), Taraba (25), Lagos (25), Bauchi (24), Sokoto (22), Plateau (22), and Adamawa (21). Genotype A was detected in Benue (3), Oyo (2), Bauchi (1), Kebbi (1), Kogi, Lagos (1), and Osun (1) states. We detected 72 (9.3%) DRAVs and 3 (0.4%) IEVs, altogether accounting for 9.7% (7.8–12.0) out of 777 samples. The DRAVs were against four (Adefovir, Entecavir, Lamivudine, and Telbivudine) out of five nucleos(t)ide analogues with no resistance against Tenofovir. The mutations include 80X, 169X, 173X, 180X, 181X, 184X, 202X, and 204X (DRAVs) and 137X and 145K (IEVs) ( and ). The 169X and 173X mutations have the widest spread (23 states; and ). Two IEVs (137X and 145K) were identified (summary in ). The significance of some of the identified variants is yet to be understood. Only 23.3% [14.9–34.5] of the 73 samples with detected RAVs have one mutation (the remaining 76.7% [65.5–85.1] have >1 RAVs). Residence in the southeast (aOR = 2.6; 95% CI: 1.1–6.4, p = 0.038) and being in the age groups 30–34 years (aOR = 3.5; 95% CI: 1.3–10.3, p = 0.015) and 55–59 years (aOR = 6.7; 95% CI: 1.3–37.5) are predictors of RAVs . This is the first nationwide, population-based study in Nigeria genetically characterising HBV. We found a high prevalence of HBV (≥8%) in over 50% of the Nigerian states and the northcentral geopolitical zone, with the highest prevalence in the 25–29-year-old age group . This shows that HBV infection remains a public health crisis in most parts of the country, with attendant implications such as sustained transmission, vaccination challenges, disease progression, and an unabated management burden. The northcentral geopolitical zone has been known to have a relatively low vaccine coverage. Other potential factors, such as limited access to healthcare facilities because of being in a hard-to-reach area or on account of population displacement, and cultural practices may play a role. Future research in these settings will be important to determine the risk factors for future preventive measures. A third of the HBV positives had a VL of ≥300 c/mL and half of those had a VL of ≥10,000 c/mL. The chances of disease progression are lower at VLs of <300 c/mL while those with a VL of 10,000 or more should be considered for therapy according to several guidelines . In essence, without the required awareness, testing, and therapy, up to 16.7% of our study participants may continue to transmit HBV while they remain at risk of the sequelae of the infection. Like previous studies, our study shows that being male is a risk factor for HBV infection positivity. Residents of the southeast geopolitical zone have a lower risk of HBV infection. This may not be unrelated to the lower prevalence of HBV observed throughout the five states in this region. Also, those in the 55–59-year age group have a lower risk of HBV infection. The average Nigerian is in the younger age group; hence, most infections may be associated with being in these younger, more sexually active, and other HBV risk-prone age groups. Although no previous nationwide, community-based HBV studies have been conducted in Nigeria, past studies revealed genotype E as the main circulating HBV subtype . We detected two HBV subtypes, A and E, with genotype E being the predominant genotype with most of the burden in ten northern states. Apart from being the predominant strain in West and Central Africa, it has been demonstrated that African emigrants to Europe and other parts of the world who are HBV carriers have genotype E . Genotype E has been associated with higher VL, HBeAg positivity, chronicity, and poor response to interferon relative to other genotypes (apart from genotype C) . The efficacy of NAs to genotype E is unclear since it was not considered in producing current treatment guidelines . Genotype E has a low nucleotide divergence (only two lineages reported and also being related to genotype D and HBV chimpanzee strains), indicating recent advancement to humans . Although its main mode of transmission is horizontal, perinatal transmission has been reported and is important in our study area. Conversely, genotype A, which has been reported to spread mainly horizontally (A1, horizontally; A2, vertically) with persistent HBeAg positivity, responds best to interferon with less aggressive clinical outcomes compared with other genotypes. Genotype A has seven subtypes which are almost equally susceptible to the NAs when compared to other genotypes . The finding of genotype E as the predominant circulating subtype offers an opportunity to have a tailored management approach in Nigeria and the African subregion by starting with an evaluation of the efficacy of current antivirals (to potentially develop drugs specifically targeting HBV genotype E since this genotype was not considered in the generation of current treatment guidelines) while sustaining HBV (sub-)genotype surveillance. Our study is the first national study to report the HBV variant in Nigeria. The national prevalence of the detected HBV DRAVs was 9.3% and that of IEVs was 0.4 (total HBV variant prevalence, 9.7%), with more than 75% of these being HBV multidrug-resistant . Only a country-wide study of this magnitude can provide such valuable information. Disease progression and the lack of viral suppression have been attributed to the presence of DRAVs . The NAs target and suppress the reverse transcriptase (RT) on the pol ORF by mimicking natural nucleosides during viral replication. This inhibits the HBV DNA polymerase activity, leading to the suppression of HBV replication. Naturally occurring or therapeutically induced HBV DRAVs can be clinically relevant. The primary HBV mutations detected in our study include DRAVs 169X, 181X, 184X, 202X, and 204X, where the pivotal codons confer direct resistance on NAs, while 80X, 173X, and 180X are compensatory: the variants compensate for fitness loss associated with primary mutation . It is a concern for treatment options that all the HBV DRAVs detected were resistant to four out of the five NAs on the database considered; only tenofovir remains a susceptible NA and remains indisputably the recommended antiviral of first choice in the country. This study revealed only two types of IEVs (137X and 145K). The two detected IEVs are unknown mutations on a rated position found in the “a” determinant area with potentials for immune escape where vaccinated persons still get infected with HBV . The mutation of HBsAg at positions 137–147 can alter the conformational epitope within the “a” determinant, preventing it from being detected by neutralising anti-HBs (hence undetected by serological investigations too: diagnostic failure) . Since both genotypes A and E circulating in Nigeria have a common conserved “a” determinant area (aa 99–160) in their HBsAg, which (subtype A2) vaccines target, and we recorded a national IEV prevalence of 0.4%, the current HBV vaccine is expected to remain effective in Nigeria, which may in part explain the few IEVs detected in Nigeria. The emergence of HBV variants can be influenced by host factors (host immune pressure, VL, and coinfections), viral factors (fitness and errors during replication) and/or external factors (vaccination, prior exposure to NAs, and NA genetic barriers). Residence in the southeastern geopolitical zone was associated with having an HBV variant . This is similar to other studies globally, reflecting geographical or regional significant differences in HBV variants within a country or continent. In Nigeria, more long-term therapeutic use of herbal antiviral agents has been reported in the SE . The cross-resistance of some of these agents may contribute to the development of HBV variants. Although high pre-treatment VL is documented to be associated with HBV variants , there was no significant association in our study. On account of immunity, HBV variants are expected to be associated with the extremes of age . The 55–59-year age group fits into this, but the 30–34-year age group does not. There may be other factors like coinfection, VL, genotype, vaccination status, and previous NA exposure at play here that require further investigation. HDV-HBV coinfection presents the most severe VH disease with faster progression and poorer prognosis compared with mono-infective VH. The HDV seroprevalence from this study was 7.34% using the antigenically distinct Cusabio ELISA kit that determined the HDV antibody. This brings the burden of HDV in Nigeria to about 1.4 million people considering the current population. Recent pockets of HDV prevalence studies in Nigeria were commonly conducted in health facilities. Such hospital-based studies have demonstrated varying prevalence ranging from 9 to 19% . However, our finding is similar to the population seroprevalence of HDV in West Africa (7.33%), but well above the global average of 4.5% . This is the first time a national prevalence of HDV has been determined in a house-to-house-based study in Nigeria. This implies that the contribution of HDV to the burden of hepatic disease is quite significant in Nigeria. Understanding the burden of HDV will provide essential information to enhance the surveillance and control of HDV infection in Nigeria. More studies to determine the circulating genotypes of HDV and to identify the risk factors for HDV infection and its genotype will be crucial in guiding HDV management in Nigeria. Recent WHO CHB new treatment guidelines recommend the treatment of CHB cases with (i) evidence of significant fibrosis, (ii) HBV DNA >2000 IU/mL and an ALT level above the upper limit of normal, (iii) the presence of coinfections (such as HIV, hepatitis D, or hepatitis C), and (iv) those with persistently abnormal ALT levels. However, practical application is limited due to the high price of the drugs. From our findings, the optimal therapeutic management of HBV in Nigeria should include the following. A clinical review of how the dominant circulating genotype E interacts with the currently approved NAs is advised; meanwhile, tenofovir should be the first line of medication in qualified patients. Baseline genotyping and RAVs assessment, though beneficial in the management of HBV, are costly. Interventions by the government and other stakeholders are necessary in order to subsidise HBV management. Evidence from this study suggests that the use of the current HBV (subtype A2) vaccine remains beneficial in Nigeria. Deployment or accelerated HBV control approaches including awareness creation, affordable, accessible investigations (especially genotyping), and targeted management in addition to current good clinical practices are crucial to VH elimination in Nigeria and the world as scheduled by the WHO, with a focus on the northcentral and the southeastern geopolitical zones. We recognise the following limitations. Those with known HIV status may have refused to participate in the original NAIIS study. Since HIV-positive individuals have a higher risk of HBV infection, there is a possibility that our study result may be underestimating the real HBV burden in Nigeria. Adding biomarker investigations would have complemented the outcome of this study but we worked with limited samples in the available timeframe. Also, conducting next-generation sequencing would provide more robust data in detecting novel (sub-)genotypes and variants since Sanger sequencing detects only one of the dominant subtypes . We hope to be able to carry this out in the future. This first nationwide, population-based HBV study in Nigeria identified HBV genotype E as the predominant circulating subtype, national HBV drug-resistant associated variants, immune escape variants, and HDV prevalences of 9.3, 0.4, and 7.34%, respectively. Sustained national and regional surveillance of HBV variants is crucial to understanding their trend, impacts on HBV vaccination, and management. Our study also demonstrated the considerable role of conducting baseline viral genomic investigations (routine baseline genotyping, DRAV testing, and VL testing) in addition to the usual biochemical workup for HBV management in Nigeria and the region. These will guide in enhancing a personalised approach to HBV infection treatment, limiting the incidence of treatment failure in a clime where coinfection and comorbidity are common. With a significant national HDV prevalence of 7.34%, HBV-positive patients should be screened for HDV. |
Neuropsychopharmacology renaissance in Japan: A new era after the crisis | 8f058a8c-b720-4762-a8bd-7a5e9bc47c35 | 11488593 | Pharmacology[mh] | |
Genomic Epidemiology of the Main SARS‐CoV‐2 Variants Circulating in Italy During the Omicron Era | 682628bf-357c-4afd-9731-738feb8577d7 | 11816846 | Biochemistry[mh] | Introduction COVID‐19 pandemic caused more than 665 million cases all over the world with more than 6,7 million of deaths by the end of 2022 ( https://www.worldometers.info/coronavirus/ ). The first genomes of SARS‐CoV‐2 were characterized and publicly shared already in January 2020 reaching by December 2022 the number of more than 15 millions genomes available for the scientific community ( https://gisaid.org/ ). This large publicly available data, and the development of efficient methods for phylogenetic and phylodynamic analyses, allowed to track the evolution of the viral genome and identify emerging variants providing important public health tools for the surveillance of SARS‐CoV‐2 during the pandemic . After the spillover event (or events) and the appearance of the first variant with the highest transmissibility (D614G) in 2020 , the virus circulated as a heterogeneous population of genomic sublineages all derived from the original lineages (called A and B, following the Pango classification). The Variants of Concern (VOCs), carrying an unusual number of mutations, especially in the Spike protein and conferring to the mutant an increased transmissibility, were described for the first time in December 2020 (VOC Alpha, Beta, Gamma followed by Delta and then Omicron) and spread all over the world, with a mechanism of variant replacement . At present, Omicron remains the dominant variant circulating globally, quite distantly related to previous VOCs since it carries the highest number of mutations ever found in other VOCs. Moreover, it resulted associated with increased infectivity and enhanced immunoevasive properties . Omicron was first identified in mid‐November 2021 in South Africa and was designated as VOC on November 26, 2021 ( https://www.who.int/news/item/28-11-2021 ) . However, retrospective analyses revealed that Omicron was present in Europe 10 days before its discovery in South Africa with no obvious transmission link between the two locations . Omicron comprises five distinct sublineages (BA.1‐5) that were discovered almost simultaneously, in November 2021, and each sublineage is different from the others as Alpha, Beta, Gamma, and Delta are far from each other . It has been hypothesized that BA.4 and BA.5 may have diverged via a recombination event, with a suggested breakpoint between the E and M genes . Epidemiological studies showed a global increase in the infection‐induced seroprevalence after the emergence of the Omicron variant in Europe . Thus, it is possible to identify a pre‐Omicron era, characterized by a low level of immunity in the population with the rise of variants with progressive increased transmissibility, and an Omicron era, characterized by the emergence of lineages with greater immunoevasive capacity selected by extensive natural and/or vaccine‐induced immunizaty . It is debated whether Omicron has a lower virulence, however, the herd immunity due to previous infections and vaccinations observed during Omicron diffusion might strongly influence hospitalization and morbidity . Convincingly, a recent WHO report showed evidence of reduced severity and lower mortality of the Omicron variant compared with the Delta variant after adjusting for the confounding effects of age, sex, ethnicity, prior infection, vaccination status, and comorbidities ( https://www.who.int/publications/i/item/9789240051829 ). Both Pfizer and Moderna introduced an updated booster vaccine targeting Omicron sublineages to obtain higher effectiveness . SARS‐CoV‐2 recombinants emerging during the different waves of COVID‐19 pandemic raised significant concerns, primarily due to their potential to accelerate immune evasion by means of antigenic shift. Among these recombinants, the first observed was named “Deltacron” , which originated in early 2022 from the recombination of Delta and Omicron BA.1 lineages, however, it exhibited limited spread. More recently, the newly identified XBB lineage, also called the Kraken variant , has gained considerable attention originating through the recombination of two highly diversified lineages, BJ.1 and BA.2.75.2, both arising from the Omicron BA.2 lineage. Remarkably, the XBB variants swiftly spread worldwide, infecting also subjects who had been vaccinated and/or with hybrid immunity. In September 2023, the new updated vaccine targeting Omicron XBB.1.5 became available . Aims of this work were to study the clinical characteristics of COVID‐19 patients and to reconstruct the genomic epidemiology and phylodynamic of the main SARS‐CoV‐2 Omicron lineages circulating in Italy in 2022. Materials and Methods 2.1 Sample Collection Between January 1 and December 31, 2022, the Italian Centers participating in the SCIRE (SARS‐CoV‐2 Italian Research Enterprise) collaborative group characterized a total of 8970 SARS‐CoV‐2 positive samples obtained from either hospitalized or asymptomatic subjects tested in screening programs. The demographic characteristics of patients, as well as information about COVID‐19 vaccination status, hospitalization and SARS‐CoV‐2 genotype, were collected at each center for surveillance or for research purposes. This study was conducted in accordance with the principles of the 1964 Declaration of Helsinki and approved by the Sacco Hospital ethics committee (protocol n. 47866, September 9, 2020). 2.2 Virus Characterization Variant assessment was performed by different methods: RT‐PCR variant specific screening assays ( n = 4640, 51.7%), spike sequencing ( n = 1164, 13%), and whole‐genome sequencing (WGS, n = 3166, 35.3%). Viral RNA extraction, RT‐PCR genotyping, amplification, and sequencing were obtained using different commercial kits or homemade procedures as previously described . The SARS‐CoV‐2 lineage and clade were assigned to all Spike or Whole Genome (WG) sequences using the Pangolin COVID‐19 Lineage Assigner v. 4.3 ( https://pangolin.cog-uk.io/ ) and Nextclade v. 2.14.1 ( https://clades.nextstrain.org/ ). Mutations were identified using Nextclade. 2.3 Statistical Analysis Statistical analyses were performed with the IBM SPSS Statistics version 29. Descriptive analyses of data are presented as a median and an interquartile range (IQR) when quantitative and as a proportion when qualitative. To compare normally distributed, nonnormally distributed continuous, and categorical variables, parametric tests ( t test and ANOVA), nonparametric tests (Mann–Whitney and Kruskal–Wallis), and the Pearson 2 test (or Fisher exact test, when necessary) were used, respectively. A p value < 0.05 was considered statistically significant. 2.4 SARS‐CoV‐2 Data Sets To study the major lineages of Omicron variant circulating during 2022, isolates of Omicron BA.1, BA.2, and BA.5 (BA.1, n = 268; BA.2, n = 677; BA.5, n = 713) were selected and aligned with other Italian sequences of the same lineage, available in GISAID ( https://gisaid.org ). Genomes were selected based on the following criteria: 10 whole genomes for each Italian region and sampling month, according with the circulation period of each subvariant, with a maximum of two sequences for region/week, excluding identical genomes and those with more than 5% of gaps. Three Italian data sets were set up: BA.1 (including a total of 880 isolates), BA.2 ( n = 1627), and BA.5 ( n = 1761) Omicron subvariants. The data set composition and regional distribution of Italian sequences are summarized in Tables and . To place the Italian sequences in the international contest, an additional data set was set up for each variant, selecting five genomes for each European and non‐European countries and sampling month. Identical strains or those with more than 5% of gaps were excluded (Table ). Alignment of multiple sequences was obtained using MAFFT ( https://mafft.cbrc.jp/alignment/server/ ) and the alignment was manually cropped using BioEdit v. 7.2.6.1 ( https://bioedit.software.informer.com/ ). at the same length (29 774 bp). The isolates included in the Omicron BA.1 data set dated between November 2021 and April 2022, the BA.2 subvariant isolates dated between January 2021 and December 2022, while the genomes included in the BA.5 subvariant data set had a date between April 2021 and December 2022. 2.5 Phylogenetic Analysis The statistically significant clusters (including more than three sequences) were identified in the International ML trees by Cluster Picker v.1.2.3 using 70% bootstrap support and a mean genetic distance of 0.1% as thresholds. Epidemiological characteristics of the identified clusters were further investigated using Cluster Matcher v. 1.2.3 which allows the identification of clusters meeting given criteria. Clusters were classified as mixed (M), containing both Italian and non‐Italian isolates in different proportions, pure Italian (IT), including only Italian genomes, or European (EU), containing only European genomes. The maximum likelihood trees of the three Italian data sets were estimated using IQ‐TREE v. 1.6.12 ( http://www.iqtree.org/ ) . The GTR + F + R3 (General time reversible + empirical base frequencies + three number of categories) model was used for BA.1 and BA.2 variants, while GTR + F + R6 models (General time reversible + empirical base frequencies + six number of categories) was used for BA.5. One thousand parametric bootstrap replicates were performed to support the nodes (≥ 60% bootstrap support). For Italian data sets, the statistically significant clusters (including more than three sequences) were identified in the ML tree by Cluster Picker v.1.2.3 using 60% bootstrap support and a mean genetic distance of 0.1% as thresholds. Preliminary maximum likelihood tree was constructed including all the variants' significant clusters. 2.6 Phylodynamic Analysis To characterize the epidemiological and evolutionary history of the different SARS‐CoV‐2 Omicron variants in Italy, only clusters including at least 10 sequences were considered for each Italian data set, by using the coalescent and the birth‐death models. Bayesian analysis was performed by BEAST v. 1.10.4 ( https://beast.community/ ) with the same substitution model and molecular clock employed for the previously described analyses . Evolutionary rates were estimated using a Log Normal prior (mean, M = 8E‐4; variance, S = 1.25) in real space using a strict clock and Bayesian Skygrid model, a nonparametric coalescent model that estimates the effective population size over time. MCMC (Markov chain Monte Carlo) analyses were run for 60 million generations and sampled every 3000. Convergence was assessed by estimating Effective Sampling Size (ESS) after applying a 10% burn‐in through Tracer v.1.7 software ( http://tree.bio.ed.ac.uk/software/tracer/ ) , accepting ESS of at least 200. The uncertainty of estimates was indicated with 95% highest prior density (HPD) intervals. The final tree was selected based on the maximum posterior probability (pp) value after performing a 10% burn‐in using Tree Annotator v.10.4 software (included in the BEAST package). Posterior probabilities greater than 0.7 were considered significant. Finally, all trees were visualized and edited in FigTree v. 1.4.4 ( http://tree.bio.ed.ac.uk/software/figtree/ ). The birth‐death skyline model implemented in Beast v. 2.7 was used to infer changes in the effective reproductive number ( R e ), and other epidemiological parameters such as the death/recovery rate ( δ ), the transmission rate ( λ ), the origin of the epidemic, and the sampling proportion ( ρ ) . Given that the samples were collected during a short period of time, a “birth‐death skyline serial” model was used. For the birth‐death analysis, one and two intervals and a lognormal before R e , with a mean (M) of 0.0 and a variance (S) of 1.8 were chosen, which allows the R e values to change between less than 1 and more than 7. A normal prior with M = 48.8 and S = 15 (IC95%: 24.0–73.4) was used for the rate of becoming uninfectious. These values are expressed as units per year and reflect the inverse of the time of infectiousness (5.3–19 days; mean, 7.5) according to the serial interval estimated by Li et al. Sampling probability ( ρ ) was estimated assuming a prior β ( α = 1.0 and β = 1500), estimated based on available genomes in the analyses (normalizing to 1) and numbers of COVID‐19 active cases at pick of the studied period. For all subvariants, origin of the epidemic was estimated using a lognormal prior with M = 0.1 and S = 0.3. The mean growth rate was calculated based on the birth and recovery rates ( r = λ − δ ), and the doubling time was estimated by the equation: doubling time = ln(2)/ r . Sample Collection Between January 1 and December 31, 2022, the Italian Centers participating in the SCIRE (SARS‐CoV‐2 Italian Research Enterprise) collaborative group characterized a total of 8970 SARS‐CoV‐2 positive samples obtained from either hospitalized or asymptomatic subjects tested in screening programs. The demographic characteristics of patients, as well as information about COVID‐19 vaccination status, hospitalization and SARS‐CoV‐2 genotype, were collected at each center for surveillance or for research purposes. This study was conducted in accordance with the principles of the 1964 Declaration of Helsinki and approved by the Sacco Hospital ethics committee (protocol n. 47866, September 9, 2020). Virus Characterization Variant assessment was performed by different methods: RT‐PCR variant specific screening assays ( n = 4640, 51.7%), spike sequencing ( n = 1164, 13%), and whole‐genome sequencing (WGS, n = 3166, 35.3%). Viral RNA extraction, RT‐PCR genotyping, amplification, and sequencing were obtained using different commercial kits or homemade procedures as previously described . The SARS‐CoV‐2 lineage and clade were assigned to all Spike or Whole Genome (WG) sequences using the Pangolin COVID‐19 Lineage Assigner v. 4.3 ( https://pangolin.cog-uk.io/ ) and Nextclade v. 2.14.1 ( https://clades.nextstrain.org/ ). Mutations were identified using Nextclade. Statistical Analysis Statistical analyses were performed with the IBM SPSS Statistics version 29. Descriptive analyses of data are presented as a median and an interquartile range (IQR) when quantitative and as a proportion when qualitative. To compare normally distributed, nonnormally distributed continuous, and categorical variables, parametric tests ( t test and ANOVA), nonparametric tests (Mann–Whitney and Kruskal–Wallis), and the Pearson 2 test (or Fisher exact test, when necessary) were used, respectively. A p value < 0.05 was considered statistically significant. SARS‐CoV‐2 Data Sets To study the major lineages of Omicron variant circulating during 2022, isolates of Omicron BA.1, BA.2, and BA.5 (BA.1, n = 268; BA.2, n = 677; BA.5, n = 713) were selected and aligned with other Italian sequences of the same lineage, available in GISAID ( https://gisaid.org ). Genomes were selected based on the following criteria: 10 whole genomes for each Italian region and sampling month, according with the circulation period of each subvariant, with a maximum of two sequences for region/week, excluding identical genomes and those with more than 5% of gaps. Three Italian data sets were set up: BA.1 (including a total of 880 isolates), BA.2 ( n = 1627), and BA.5 ( n = 1761) Omicron subvariants. The data set composition and regional distribution of Italian sequences are summarized in Tables and . To place the Italian sequences in the international contest, an additional data set was set up for each variant, selecting five genomes for each European and non‐European countries and sampling month. Identical strains or those with more than 5% of gaps were excluded (Table ). Alignment of multiple sequences was obtained using MAFFT ( https://mafft.cbrc.jp/alignment/server/ ) and the alignment was manually cropped using BioEdit v. 7.2.6.1 ( https://bioedit.software.informer.com/ ). at the same length (29 774 bp). The isolates included in the Omicron BA.1 data set dated between November 2021 and April 2022, the BA.2 subvariant isolates dated between January 2021 and December 2022, while the genomes included in the BA.5 subvariant data set had a date between April 2021 and December 2022. Phylogenetic Analysis The statistically significant clusters (including more than three sequences) were identified in the International ML trees by Cluster Picker v.1.2.3 using 70% bootstrap support and a mean genetic distance of 0.1% as thresholds. Epidemiological characteristics of the identified clusters were further investigated using Cluster Matcher v. 1.2.3 which allows the identification of clusters meeting given criteria. Clusters were classified as mixed (M), containing both Italian and non‐Italian isolates in different proportions, pure Italian (IT), including only Italian genomes, or European (EU), containing only European genomes. The maximum likelihood trees of the three Italian data sets were estimated using IQ‐TREE v. 1.6.12 ( http://www.iqtree.org/ ) . The GTR + F + R3 (General time reversible + empirical base frequencies + three number of categories) model was used for BA.1 and BA.2 variants, while GTR + F + R6 models (General time reversible + empirical base frequencies + six number of categories) was used for BA.5. One thousand parametric bootstrap replicates were performed to support the nodes (≥ 60% bootstrap support). For Italian data sets, the statistically significant clusters (including more than three sequences) were identified in the ML tree by Cluster Picker v.1.2.3 using 60% bootstrap support and a mean genetic distance of 0.1% as thresholds. Preliminary maximum likelihood tree was constructed including all the variants' significant clusters. Phylodynamic Analysis To characterize the epidemiological and evolutionary history of the different SARS‐CoV‐2 Omicron variants in Italy, only clusters including at least 10 sequences were considered for each Italian data set, by using the coalescent and the birth‐death models. Bayesian analysis was performed by BEAST v. 1.10.4 ( https://beast.community/ ) with the same substitution model and molecular clock employed for the previously described analyses . Evolutionary rates were estimated using a Log Normal prior (mean, M = 8E‐4; variance, S = 1.25) in real space using a strict clock and Bayesian Skygrid model, a nonparametric coalescent model that estimates the effective population size over time. MCMC (Markov chain Monte Carlo) analyses were run for 60 million generations and sampled every 3000. Convergence was assessed by estimating Effective Sampling Size (ESS) after applying a 10% burn‐in through Tracer v.1.7 software ( http://tree.bio.ed.ac.uk/software/tracer/ ) , accepting ESS of at least 200. The uncertainty of estimates was indicated with 95% highest prior density (HPD) intervals. The final tree was selected based on the maximum posterior probability (pp) value after performing a 10% burn‐in using Tree Annotator v.10.4 software (included in the BEAST package). Posterior probabilities greater than 0.7 were considered significant. Finally, all trees were visualized and edited in FigTree v. 1.4.4 ( http://tree.bio.ed.ac.uk/software/figtree/ ). The birth‐death skyline model implemented in Beast v. 2.7 was used to infer changes in the effective reproductive number ( R e ), and other epidemiological parameters such as the death/recovery rate ( δ ), the transmission rate ( λ ), the origin of the epidemic, and the sampling proportion ( ρ ) . Given that the samples were collected during a short period of time, a “birth‐death skyline serial” model was used. For the birth‐death analysis, one and two intervals and a lognormal before R e , with a mean (M) of 0.0 and a variance (S) of 1.8 were chosen, which allows the R e values to change between less than 1 and more than 7. A normal prior with M = 48.8 and S = 15 (IC95%: 24.0–73.4) was used for the rate of becoming uninfectious. These values are expressed as units per year and reflect the inverse of the time of infectiousness (5.3–19 days; mean, 7.5) according to the serial interval estimated by Li et al. Sampling probability ( ρ ) was estimated assuming a prior β ( α = 1.0 and β = 1500), estimated based on available genomes in the analyses (normalizing to 1) and numbers of COVID‐19 active cases at pick of the studied period. For all subvariants, origin of the epidemic was estimated using a lognormal prior with M = 0.1 and S = 0.3. The mean growth rate was calculated based on the birth and recovery rates ( r = λ − δ ), and the doubling time was estimated by the equation: doubling time = ln(2)/ r . Results 3.1 Population Characteristics Analyzed samples were collected from Italian centers located in Liguria ( n = 802), Lombardy ( n = 5368), Umbria ( n = 66), Marche ( n = 2506), and Lazio ( n = 228). Females accounted for 54% ( n = 4788/8867) and the median age was 58 years (IQR: 37–76) without any significant differences between sexes. Significant differences were observed in the median age over different months ( p < 0.001), with an increase in median age overtime (from 51 years in January to 73 years in December). Despite information of previous exposure to SARS‐CoV‐2 infection was available for a limited number of subjects ( n = 478), 54.8% ( n = 262) experienced a reinfection. Around one third of subjects had a known clinical status ( n = 3102); 61.5% presented mild infections ( n = 1908), followed by 31.7% of moderate/severe infections requiring hospitalization ( n = 984). Among hospitalized patients, 6.3% ( n = 62) required intensive care and 8 (0.8%) died. Hospitalized patients showed a higher median age compared with asymptomatic or mildly symptomatic subjects ( p < 0.001, 73 vs. 52 and 49, respectively). Only a minority of the subjects were asymptomatics (210, 6.8%). These data are summarized in Table . 3.2 COVID‐19 Vaccinated versus Nonvaccinated Among subjects with known COVID‐19 vaccination status ( n = 4179), 67.3% ( n = 2814) received at least one dose of vaccine. More than half of the studied subjects received three doses (53.4%, n = 1030/1930) of vaccine, only 3.1% received four doses ( n = 61) and 78.8% received BNT162b2 vaccine ( n = 719). The median time between the last dose of vaccine administered and infection was 6 months overall (IQR: 4–9). This value increased significantly ( p < .00001) over the study period from 4 months (IQR: 2–8) in January to 12 months (IQR: 10–12) in December. Considering the number of received doses, significantly ( p < .00001) longer times were observed among those who had received one (6 months, IQR: 1–11), two (7 months; IQR: 5–10) or three doses (7 months, IQR: 4–9) compared with those with four doses (4 months; IQR: 1–5). No differences were observed in the proportion of vaccinated or nonvaccinated subjects in the study period, however, the median age of vaccinated individuals was lower compared with that of nonvaccinated ones (57.2 vs. 60, p < 0.001). A significant larger proportion of unvaccinated subjects presented reinfection compared with vaccinated (53%, 79/149 vs. 25.1%, 45/179; p < 0.001). Significant differences in the distribution of clinical status were present with the highest proportion of nonhospitalized subjects in vaccinated compared with unvaccinated (75.3%, 892/1,184 vs. 60.9%, 297/488; p < 0.0001). The proportion of deaths was significantly higher in unvaccinated than in vaccinated (0.6%, 3/488 vs. 0.4%, 5/1,184; p < 0.0001). No significant differences were observed in the gender distribution between vaccinated and unvaccinated subjects. 3.3 Lineages and Clades The main observed variant in the studied cohort was Omicron (8740/8970, n = 97.4%) and its sublineages showing a prevalence of 44.6%, 26.8%, 1.8%, and 26.8% for BA.1 ( n = 3898), BA.2 ( n = 2338), BA.4 ( n = 160), and BA.5 ( n = 1654), respectively. The Delta variant was observed until August, when the last case was observed, and globally accounted for 1.8% ( n = 161). Recombinants represented 0.7% ( n = 61) of total sequences and included XC ( n = 39), XAZ ( n = 1), XBB ( n = 16), XBG ( n = 1), XBF ( n = 1), XQ ( n = 1), and XT ( n = 2). First cases of XBB recombinants were observed in November ( n = 10, 2.6%). BA.1 remained the dominant until March (90.3%, n = 2241; 91.2%, n = 869; and 57.1%, n = 628 in January, February, and March, respectively) and completely disappeared since November. From April (95.2%, 867/911) to June (48.6%, 232/477), BA.2 became prevalent and was then replaced by BA.5. BA.5 reached the highest prevalence in September (96.7%, 384/397) and then decreased to 44.1% (162/367) in December when BQ.1 and descendants prevailed (52.6%, n = 193). First case of BQ.1 was observed in September (Table ). Accordingly, the main clades included 21 K (39.7%, n = 3469), 21 L (25.4%, n = 2279), and 22B (22.6%, n = 2030) (Figure ). By considering clinical status between subjects infected with Delta versus Omicron variant, a significantly higher proportion of nonhospitalized subjects was observed in subjects infected by Omicron (68.4%, 2091/3056 vs. 58.7%, 27/46; p = 0.017) and a significant higher proportion of deaths was found in Delta patients (2.2%, 1/46 vs. 0.2%, 7/3,056; p = 0.017). Of note, considering vaccination status, significant higher proportions of hospitalization and deaths were present in vaccinated patients carrying Delta variant compared with vaccinated or unvaccinated subjects with Omicron (72%, 18/25 vs. 23.2%, 269/1159 and 38.8%, 185/477 for hospitalization and 4%, 1/25 versus 0.3%, 4/1159 and 0.6%, 3/477 for deaths, p = 0.02). Considering Delta versus Omicron sublineages, the highest proportions of hospitalization were observed in Delta and BA.5 compared with BA.1 and BA.2 (53.1%, 17/32 and 51.5%, 135/262 vs. 11.8%, 52/442 and 28.8%, 242/839; p < 0.0001), while the proportion of deaths was significantly higher in subjects affected by Delta compared with those by Omicron sublineages (3.1%, 1/32 vs. 1.4%, 6/442, 0 and 0.4%, 1/262; p < 0.0001). In accordance with the circulation period of the different variants, the median time from vaccination to infection was significantly ( p < .00001) longer for the BQ.1 variant (11 months; IQR: 9–12) and recombinant lineages (12, IQR: 11–12) than for the Delta (3; IQR: 2–6) and BA.1 variants (4; IQR: 2–7). 3.4 Mutation Analyses of the Italian Sequences Table shows the sublineage composition of Italian Omicron BA.1 data set. The comparison between genomes from Italy and the reference sequence showed 49 aminoacidic substitutions and 7 deletions present in at least 10% of isolates. More than 30 mutations were present in the spike protein. Over 90% of the sequences had characteristics mutations of this variant and its descendants (Table ). The V1187I mutation in ORF1a, characteristic of sublineages BA.1.17 and BA.1.17.2, was globally found in 32.4% ( n = 285) of genomes but was present in 90.5% (67/74) and 97.6% (204/209) of BA.1.17 and BA.1.17.2, respectively. The R346K mutation in the spike protein, found in 39.2% ( n = 345) of sequences, was present in 94.8% ( n = 275) of BA.1.1 genomes ( n = 290) and in almost all (88.4%, n = 61) BA.1.1.1 ( n = 69) and descendants isolates. The G446S mutation in the Spike protein, typical of the BA.1.1 and descending sublineages, was found in a total of 665 isolates (75.6%), of which 73.3% ( n = 545) of BA.1.1 and descendants ( n = 746). The A701V mutation in the Spike protein, present in 20.5% ( n = 180) of genomes, was found in 85.6% (179/209) of the sequences belonging to this sublineage BA.1.17.2. In addition, the totality of the sequences of sublineages BA.1.15 and descendants (17/17), had the additional mutation D343G in the protein N, distinctive of this sublineage. The sublineage composition of the sequences included in the Omicron BA.2 data set was shown in Table . In the BA.2 and descendants data set, only mutations/deletions typical of this lineage were found, as shown in Supporting Information (Table ). In the ORF3a region, the H78Y mutation, present in a total of 16.5% ( n = 268) of the isolates, was prevalent in the BA.2.9 sublineage isolates (88.5%, 234/265). In the ORF1a region C655R, A2909V and Q3966H mutations (observed in less than 5% in data set global) were identified in almost 100% of the isolates of sublineages BA.2.52.2 (33/33), BA.2.3 (44/44), and BA.2.22 (16/18), where these substitutions are characteristic. Similarly, S959P mutation in ORF1b, was present in 95.2% (20/21) of the BA.2.10 isolates. The L140F mutation in ORF3a, was found in almost all BA.2.3 and descendant sequences (97.7%, 42/43). In protein S, two mutations characteristics of the sublineage BA.2.12.1, L452Q and S704L, were identified in 94.5% (63/66) and 98.5% (65/66) of its isolates, respectively. Table shows the sublineage composition of Omicron BA.5 data set. A total of 50 mutations and 5 deletions were found in at least 10% of the sequences analyzed (Table ). These substitutions have been identified in more than 80% of the isolates, except for the T1050N mutation, in the ORF1b region, with a global prevalence of 20.8% ( n = 367) but which was present in almost all isolates BA.5.2, BA.5.2.2 and descendant sublineages, and mutation D16G in the ORF9b region; this substitution, present in almost 50% ( n = 844) of the isolates, was found in all BA.5.2 isolates ( n = 350) and in 97.6% (322/330) of BA.5.2.1 sequences. In protein S, in addition to mutations typical of this variant, 98.1% ( n = 1,721) of the sequences bore the mutation G142Y. Substitutions with a global frequency of less than 10% but characteristics of different sublineages have been identified in the ORF1a, ORF1b, S and N regions. In the ORF1a region, mutations S302F, Q556K, K3839R and T4161I were observed in all BA.5.1.23 ( n = 27), BA.5.3.1 ( n = 16), BA.5.1.10 ( n = 101), and BA.5.1.8 ( n = 37) sequences, respectively. 3.5 Phylogenetic Analysis of International Data Sets Maximum Likelihood analysis of the international data sets showed that the majority of whole genomes of BA.1, BA.2, and BA.5 (ranging from 72.5% to 87.6%) were scattered throughout the trees, while 12.4% (228/1837) of BA.1, 19.9% (649/3246) of BA.2, and 27.5% (885/3219) of BA.5 genomes formed significant clusters, from 3 to 17, 30 and 60 sequences (for BA.1, BA.2 and BA.5, respectively) and mainly localized at the external nodes of the trees. In detail, 46.2% (24/52) of BA.1 clusters included sequences exclusively from Italy, as well as 37.9% (53/140) of BA.2 clusters and 36.5% (69/189) of BA.5 clusters, while mixed clusters were 9.6% (5/52), 27.9% (39/140), and 49.7% (94/189), respectively. 3.6 Phylogenetic Analysis and Dating of Italian Clusters The phylogenetic analysis conducted on the Italian sequences of the subvariant Omicron BA.1 showed the presence of 30 clusters, characterized by more than three sequences (min 4–max 21), which included 24.3% ( n = 214) of total analyzed sequences ( n = 880); four (8.7%) clusters included more than 10 genomes. There was no change in the pattern of clustering based on the sampling area (northern, southern, central Italy, and islands). Analysis of the Omicron BA.2 subvariant showed the presence of 60 clusters (min–max: 4–30 sequences), which included 22.6% of the isolates analyzed (368/1627); 7 (6.3%) clusters included more than 10 genomes. No different clustering pattern was found based on the sampling area. The 26.5% ( n = 467) of isolates included in the BA.5 data set ( n = 1761) grouped into 68 clusters, of which 10 (7.4%) clusters included a number greater/equal to 10 genomes. Sequences from the islands clustered more frequently than those from northern, central, and southern Italy (52.3% vs. 37.6%, 35.6%, 37.2%; p < 0.05). Maximum Likelihood analysis conducted on isolates included in all BA.1, BA.2, and BA.5 clusters showed that these lineages formed three highly significant monophyletic groups (Table and Figure ). Preliminary analysis by root‐to‐tip regression revealed a linear relationship between genetic diversity and time (correlation coefficient = 0.81 and R 2 = 0.66) (Figure ). Given the limited number of BA.1 clusters containing more than 10 isolates, the Bayesian phylogenetic analysis was conducted on a data set that included all sequences forming clusters with at least four sequences ( n = 214). Bayesian analysis estimated a mean substitution rate of 4.84 × 10 ‐4 s/s/y (95%HPD: 3.76–5.98 × 10 ‐4 s/s/y) and showed that all sequences grouped within 12 statistically supported clusters (pp > 0.9) in the tree (Figure ). The tMRCA of each cluster was dated between September and November 2021 (95% HPD: June–December 2021) (Table ). These clusters contained an average of 17.8 genomes (minimum of 4 and maximum of 71) with a persistence between 2 and 7 months (Table ). Earlier clusters (dated September 2021) showed the larger size (20.5 vs. 6.5 isolates) and the longer persistence (7 vs. 4.5 months) than later clusters (dated October/November). Bayesian phylogenetic analysis was conducted on BA.2 data set that included all sequences included in the seven largest Italian clusters containing more than 10 sequences for a total of 111 genomes. The Bayesian analysis estimated a mean evolutionary rate of 3.99 × 10 ‐4 s/s/y (95%HPD: 2.70–5.33 × 10 ‐4 ). Clusters contained an average of 15.9 genomes (min–max: 10–30), dated between November 2021 and January 2022 (95%HPD: August 2021–February 2022) and a persistence between 4 and 8 months (Figure ; Table ) without any relationship between the clusters size and persistence. Bayesian analysis of the Omicron BA.5 variant was conducted on the 164 sequences included in the 10 clusters containing more than 10 sequences. The estimated evolutionary rate showed an average of 4.56 × 10 ‐4 s/s/y (95%HPD: 3.72 × 10 ‐4 –5.44 × 10 ‐4 ). Clusters' tMRCAs dated from October 2021 to May 2022 (95%HPD: July 2021–July 2022) (Figure ), but most of them dated in March and April 2022. Clusters contained an average of 16.4 genomes (min–max: 10–39) and showed a persistence of a mean 8.3 months (range: 5–11 months) (Table ). No relationship was observed between the clusters size and persistence. 3.7 Bayesian Phylodynamic Analysis The Bayesian phylodynamic analysis of the BA.1 Italian clusters, showed that the number of infections progressively grew since the origin of the epidemic (September 2021); a spike growth started in November 2021 reaching the plateau in January 2022 lasting until March 2022, when the effective number of infections started to decrease (Figure ). In agreement with this dynamic, the estimate of R e was close to the threshold 1 until December when the effective reproduction number reached 1.45, followed by a decline in January 2022 (when the number of infections reached the plateau) to the initial values (Figure ). In the case of BA.2, an exponential increase of the effective number of infections was observed only in January/February 2022 and the plateau was reached between March and April 2022, when an initial decline in the number of infections was observed, followed by a rebound during summer (Figure ). Similarly, the estimate of the R e has shown values around 1 since the beginning of the epidemic, but the peak (1.42) was reached between January and February 2022, returning to values around the unity in February–March showing a more pronounced reduction between May and July 2022 (Figure ). The curve showing the effective number of BA.5 infections exhibits two growth phases, with the initial phase in January 2022, being flatter, followed by a subsequent steeper increase starting from May 2022 and reaching a peak of cases around July. The decrease began in the second half of the same month of July or August, with a more pronounced decline starting from October 2022 (Figure ). Similarly, the estimate of the R e showed values above 1 from October 2021, although the highest values were observed from May 2022 (1.28) to July, when the estimates of the effective reproduction number dropped around 1, where they remained until the end of the study (Figure ). Population Characteristics Analyzed samples were collected from Italian centers located in Liguria ( n = 802), Lombardy ( n = 5368), Umbria ( n = 66), Marche ( n = 2506), and Lazio ( n = 228). Females accounted for 54% ( n = 4788/8867) and the median age was 58 years (IQR: 37–76) without any significant differences between sexes. Significant differences were observed in the median age over different months ( p < 0.001), with an increase in median age overtime (from 51 years in January to 73 years in December). Despite information of previous exposure to SARS‐CoV‐2 infection was available for a limited number of subjects ( n = 478), 54.8% ( n = 262) experienced a reinfection. Around one third of subjects had a known clinical status ( n = 3102); 61.5% presented mild infections ( n = 1908), followed by 31.7% of moderate/severe infections requiring hospitalization ( n = 984). Among hospitalized patients, 6.3% ( n = 62) required intensive care and 8 (0.8%) died. Hospitalized patients showed a higher median age compared with asymptomatic or mildly symptomatic subjects ( p < 0.001, 73 vs. 52 and 49, respectively). Only a minority of the subjects were asymptomatics (210, 6.8%). These data are summarized in Table . COVID‐19 Vaccinated versus Nonvaccinated Among subjects with known COVID‐19 vaccination status ( n = 4179), 67.3% ( n = 2814) received at least one dose of vaccine. More than half of the studied subjects received three doses (53.4%, n = 1030/1930) of vaccine, only 3.1% received four doses ( n = 61) and 78.8% received BNT162b2 vaccine ( n = 719). The median time between the last dose of vaccine administered and infection was 6 months overall (IQR: 4–9). This value increased significantly ( p < .00001) over the study period from 4 months (IQR: 2–8) in January to 12 months (IQR: 10–12) in December. Considering the number of received doses, significantly ( p < .00001) longer times were observed among those who had received one (6 months, IQR: 1–11), two (7 months; IQR: 5–10) or three doses (7 months, IQR: 4–9) compared with those with four doses (4 months; IQR: 1–5). No differences were observed in the proportion of vaccinated or nonvaccinated subjects in the study period, however, the median age of vaccinated individuals was lower compared with that of nonvaccinated ones (57.2 vs. 60, p < 0.001). A significant larger proportion of unvaccinated subjects presented reinfection compared with vaccinated (53%, 79/149 vs. 25.1%, 45/179; p < 0.001). Significant differences in the distribution of clinical status were present with the highest proportion of nonhospitalized subjects in vaccinated compared with unvaccinated (75.3%, 892/1,184 vs. 60.9%, 297/488; p < 0.0001). The proportion of deaths was significantly higher in unvaccinated than in vaccinated (0.6%, 3/488 vs. 0.4%, 5/1,184; p < 0.0001). No significant differences were observed in the gender distribution between vaccinated and unvaccinated subjects. Lineages and Clades The main observed variant in the studied cohort was Omicron (8740/8970, n = 97.4%) and its sublineages showing a prevalence of 44.6%, 26.8%, 1.8%, and 26.8% for BA.1 ( n = 3898), BA.2 ( n = 2338), BA.4 ( n = 160), and BA.5 ( n = 1654), respectively. The Delta variant was observed until August, when the last case was observed, and globally accounted for 1.8% ( n = 161). Recombinants represented 0.7% ( n = 61) of total sequences and included XC ( n = 39), XAZ ( n = 1), XBB ( n = 16), XBG ( n = 1), XBF ( n = 1), XQ ( n = 1), and XT ( n = 2). First cases of XBB recombinants were observed in November ( n = 10, 2.6%). BA.1 remained the dominant until March (90.3%, n = 2241; 91.2%, n = 869; and 57.1%, n = 628 in January, February, and March, respectively) and completely disappeared since November. From April (95.2%, 867/911) to June (48.6%, 232/477), BA.2 became prevalent and was then replaced by BA.5. BA.5 reached the highest prevalence in September (96.7%, 384/397) and then decreased to 44.1% (162/367) in December when BQ.1 and descendants prevailed (52.6%, n = 193). First case of BQ.1 was observed in September (Table ). Accordingly, the main clades included 21 K (39.7%, n = 3469), 21 L (25.4%, n = 2279), and 22B (22.6%, n = 2030) (Figure ). By considering clinical status between subjects infected with Delta versus Omicron variant, a significantly higher proportion of nonhospitalized subjects was observed in subjects infected by Omicron (68.4%, 2091/3056 vs. 58.7%, 27/46; p = 0.017) and a significant higher proportion of deaths was found in Delta patients (2.2%, 1/46 vs. 0.2%, 7/3,056; p = 0.017). Of note, considering vaccination status, significant higher proportions of hospitalization and deaths were present in vaccinated patients carrying Delta variant compared with vaccinated or unvaccinated subjects with Omicron (72%, 18/25 vs. 23.2%, 269/1159 and 38.8%, 185/477 for hospitalization and 4%, 1/25 versus 0.3%, 4/1159 and 0.6%, 3/477 for deaths, p = 0.02). Considering Delta versus Omicron sublineages, the highest proportions of hospitalization were observed in Delta and BA.5 compared with BA.1 and BA.2 (53.1%, 17/32 and 51.5%, 135/262 vs. 11.8%, 52/442 and 28.8%, 242/839; p < 0.0001), while the proportion of deaths was significantly higher in subjects affected by Delta compared with those by Omicron sublineages (3.1%, 1/32 vs. 1.4%, 6/442, 0 and 0.4%, 1/262; p < 0.0001). In accordance with the circulation period of the different variants, the median time from vaccination to infection was significantly ( p < .00001) longer for the BQ.1 variant (11 months; IQR: 9–12) and recombinant lineages (12, IQR: 11–12) than for the Delta (3; IQR: 2–6) and BA.1 variants (4; IQR: 2–7). Mutation Analyses of the Italian Sequences Table shows the sublineage composition of Italian Omicron BA.1 data set. The comparison between genomes from Italy and the reference sequence showed 49 aminoacidic substitutions and 7 deletions present in at least 10% of isolates. More than 30 mutations were present in the spike protein. Over 90% of the sequences had characteristics mutations of this variant and its descendants (Table ). The V1187I mutation in ORF1a, characteristic of sublineages BA.1.17 and BA.1.17.2, was globally found in 32.4% ( n = 285) of genomes but was present in 90.5% (67/74) and 97.6% (204/209) of BA.1.17 and BA.1.17.2, respectively. The R346K mutation in the spike protein, found in 39.2% ( n = 345) of sequences, was present in 94.8% ( n = 275) of BA.1.1 genomes ( n = 290) and in almost all (88.4%, n = 61) BA.1.1.1 ( n = 69) and descendants isolates. The G446S mutation in the Spike protein, typical of the BA.1.1 and descending sublineages, was found in a total of 665 isolates (75.6%), of which 73.3% ( n = 545) of BA.1.1 and descendants ( n = 746). The A701V mutation in the Spike protein, present in 20.5% ( n = 180) of genomes, was found in 85.6% (179/209) of the sequences belonging to this sublineage BA.1.17.2. In addition, the totality of the sequences of sublineages BA.1.15 and descendants (17/17), had the additional mutation D343G in the protein N, distinctive of this sublineage. The sublineage composition of the sequences included in the Omicron BA.2 data set was shown in Table . In the BA.2 and descendants data set, only mutations/deletions typical of this lineage were found, as shown in Supporting Information (Table ). In the ORF3a region, the H78Y mutation, present in a total of 16.5% ( n = 268) of the isolates, was prevalent in the BA.2.9 sublineage isolates (88.5%, 234/265). In the ORF1a region C655R, A2909V and Q3966H mutations (observed in less than 5% in data set global) were identified in almost 100% of the isolates of sublineages BA.2.52.2 (33/33), BA.2.3 (44/44), and BA.2.22 (16/18), where these substitutions are characteristic. Similarly, S959P mutation in ORF1b, was present in 95.2% (20/21) of the BA.2.10 isolates. The L140F mutation in ORF3a, was found in almost all BA.2.3 and descendant sequences (97.7%, 42/43). In protein S, two mutations characteristics of the sublineage BA.2.12.1, L452Q and S704L, were identified in 94.5% (63/66) and 98.5% (65/66) of its isolates, respectively. Table shows the sublineage composition of Omicron BA.5 data set. A total of 50 mutations and 5 deletions were found in at least 10% of the sequences analyzed (Table ). These substitutions have been identified in more than 80% of the isolates, except for the T1050N mutation, in the ORF1b region, with a global prevalence of 20.8% ( n = 367) but which was present in almost all isolates BA.5.2, BA.5.2.2 and descendant sublineages, and mutation D16G in the ORF9b region; this substitution, present in almost 50% ( n = 844) of the isolates, was found in all BA.5.2 isolates ( n = 350) and in 97.6% (322/330) of BA.5.2.1 sequences. In protein S, in addition to mutations typical of this variant, 98.1% ( n = 1,721) of the sequences bore the mutation G142Y. Substitutions with a global frequency of less than 10% but characteristics of different sublineages have been identified in the ORF1a, ORF1b, S and N regions. In the ORF1a region, mutations S302F, Q556K, K3839R and T4161I were observed in all BA.5.1.23 ( n = 27), BA.5.3.1 ( n = 16), BA.5.1.10 ( n = 101), and BA.5.1.8 ( n = 37) sequences, respectively. Phylogenetic Analysis of International Data Sets Maximum Likelihood analysis of the international data sets showed that the majority of whole genomes of BA.1, BA.2, and BA.5 (ranging from 72.5% to 87.6%) were scattered throughout the trees, while 12.4% (228/1837) of BA.1, 19.9% (649/3246) of BA.2, and 27.5% (885/3219) of BA.5 genomes formed significant clusters, from 3 to 17, 30 and 60 sequences (for BA.1, BA.2 and BA.5, respectively) and mainly localized at the external nodes of the trees. In detail, 46.2% (24/52) of BA.1 clusters included sequences exclusively from Italy, as well as 37.9% (53/140) of BA.2 clusters and 36.5% (69/189) of BA.5 clusters, while mixed clusters were 9.6% (5/52), 27.9% (39/140), and 49.7% (94/189), respectively. Phylogenetic Analysis and Dating of Italian Clusters The phylogenetic analysis conducted on the Italian sequences of the subvariant Omicron BA.1 showed the presence of 30 clusters, characterized by more than three sequences (min 4–max 21), which included 24.3% ( n = 214) of total analyzed sequences ( n = 880); four (8.7%) clusters included more than 10 genomes. There was no change in the pattern of clustering based on the sampling area (northern, southern, central Italy, and islands). Analysis of the Omicron BA.2 subvariant showed the presence of 60 clusters (min–max: 4–30 sequences), which included 22.6% of the isolates analyzed (368/1627); 7 (6.3%) clusters included more than 10 genomes. No different clustering pattern was found based on the sampling area. The 26.5% ( n = 467) of isolates included in the BA.5 data set ( n = 1761) grouped into 68 clusters, of which 10 (7.4%) clusters included a number greater/equal to 10 genomes. Sequences from the islands clustered more frequently than those from northern, central, and southern Italy (52.3% vs. 37.6%, 35.6%, 37.2%; p < 0.05). Maximum Likelihood analysis conducted on isolates included in all BA.1, BA.2, and BA.5 clusters showed that these lineages formed three highly significant monophyletic groups (Table and Figure ). Preliminary analysis by root‐to‐tip regression revealed a linear relationship between genetic diversity and time (correlation coefficient = 0.81 and R 2 = 0.66) (Figure ). Given the limited number of BA.1 clusters containing more than 10 isolates, the Bayesian phylogenetic analysis was conducted on a data set that included all sequences forming clusters with at least four sequences ( n = 214). Bayesian analysis estimated a mean substitution rate of 4.84 × 10 ‐4 s/s/y (95%HPD: 3.76–5.98 × 10 ‐4 s/s/y) and showed that all sequences grouped within 12 statistically supported clusters (pp > 0.9) in the tree (Figure ). The tMRCA of each cluster was dated between September and November 2021 (95% HPD: June–December 2021) (Table ). These clusters contained an average of 17.8 genomes (minimum of 4 and maximum of 71) with a persistence between 2 and 7 months (Table ). Earlier clusters (dated September 2021) showed the larger size (20.5 vs. 6.5 isolates) and the longer persistence (7 vs. 4.5 months) than later clusters (dated October/November). Bayesian phylogenetic analysis was conducted on BA.2 data set that included all sequences included in the seven largest Italian clusters containing more than 10 sequences for a total of 111 genomes. The Bayesian analysis estimated a mean evolutionary rate of 3.99 × 10 ‐4 s/s/y (95%HPD: 2.70–5.33 × 10 ‐4 ). Clusters contained an average of 15.9 genomes (min–max: 10–30), dated between November 2021 and January 2022 (95%HPD: August 2021–February 2022) and a persistence between 4 and 8 months (Figure ; Table ) without any relationship between the clusters size and persistence. Bayesian analysis of the Omicron BA.5 variant was conducted on the 164 sequences included in the 10 clusters containing more than 10 sequences. The estimated evolutionary rate showed an average of 4.56 × 10 ‐4 s/s/y (95%HPD: 3.72 × 10 ‐4 –5.44 × 10 ‐4 ). Clusters' tMRCAs dated from October 2021 to May 2022 (95%HPD: July 2021–July 2022) (Figure ), but most of them dated in March and April 2022. Clusters contained an average of 16.4 genomes (min–max: 10–39) and showed a persistence of a mean 8.3 months (range: 5–11 months) (Table ). No relationship was observed between the clusters size and persistence. Bayesian Phylodynamic Analysis The Bayesian phylodynamic analysis of the BA.1 Italian clusters, showed that the number of infections progressively grew since the origin of the epidemic (September 2021); a spike growth started in November 2021 reaching the plateau in January 2022 lasting until March 2022, when the effective number of infections started to decrease (Figure ). In agreement with this dynamic, the estimate of R e was close to the threshold 1 until December when the effective reproduction number reached 1.45, followed by a decline in January 2022 (when the number of infections reached the plateau) to the initial values (Figure ). In the case of BA.2, an exponential increase of the effective number of infections was observed only in January/February 2022 and the plateau was reached between March and April 2022, when an initial decline in the number of infections was observed, followed by a rebound during summer (Figure ). Similarly, the estimate of the R e has shown values around 1 since the beginning of the epidemic, but the peak (1.42) was reached between January and February 2022, returning to values around the unity in February–March showing a more pronounced reduction between May and July 2022 (Figure ). The curve showing the effective number of BA.5 infections exhibits two growth phases, with the initial phase in January 2022, being flatter, followed by a subsequent steeper increase starting from May 2022 and reaching a peak of cases around July. The decrease began in the second half of the same month of July or August, with a more pronounced decline starting from October 2022 (Figure ). Similarly, the estimate of the R e showed values above 1 from October 2021, although the highest values were observed from May 2022 (1.28) to July, when the estimates of the effective reproduction number dropped around 1, where they remained until the end of the study (Figure ). Discussion Since early 2022 the Omicron variant has rapidly spread worldwide, becoming up to now the dominant variant with its derived sublineages . The higher transmissibility, the lower neutralizing efficacy of antibodies stimulated by previous infections or vaccination, the less severe clinical spectrum, the shorter incubation period, and the higher replicative efficiency, made this variant very different from those that circulated previously. In addition, the widespread diffusion of vaccination leading to over 85% of the Italian population vaccinated with a complete cycle ( https://www.lombardianotizie.online/vaccinati-over-80/ ), and the progressive easing of containment measures up to their total elimination, radically changed the epidemiology of the infection leading to a distinction between a past “pre‐Omicron” and a current Omicron era . According to the study period, the Omicron variant was highly prevalent in this work, representing more than 97% of viral detections while the Delta variant was observed in less than 2% of the subjects up to August, when it disappeared similarly to what observed in the rest of the world. A similar replacement trend was also observed in the succession of Omicron sublineages overtime. Lineage BA.1 was prevalent until March 2022, when it was replaced by BA.2 which remained the dominant lineage until June, when BA.5 became prevalent until November. At the end of the study the lineage BQ.1, derived from BA.5, became the most frequent. While the BA.1 variant became extinct a few months after its spread, BA.2 and BA.5 variants continued (February 2024) to circulate with different derived sublineages and recombinant forms favored by the increased transmissibility . The circulation of recombinants started in 2022 with the co‐circulation of Delta and Omicron VOCs, however, their large spread matched with the identification of XBB recombinants derived from recombination between two lineages of BA.2, which were first identified only at the end of study period (November 2022). Due to the predominant enrollment of patients from clinical centers and related microbiology laboratories, only a small number of asymptomatic subjects were included. Vaccination coverage with at least one dose of anti‐SARS‐CoV‐2 vaccine was significantly lower in enrolled subjects compared with the national coverage. Despite this bias, the unvaccinated subjects more frequently required hospitalization compared with vaccinated (24.7% among vaccinated vs. 39.1% among unvaccinated), unvaccinated also experienced a doubled frequency of reinfections and a higher frequency of deaths, confirming previous data on the efficacy of COVID‐19 vaccines. Moreover, these data confirm that Omicron is less virulent than the Delta variant but also indicated, differently from previous reports , a lower lethality both in vaccinated and unvaccinated subjects. Despite the small number of individuals infected by Delta variant in the study, a relevant difference in the proportion of deaths was also observed comparing with different Omicron sublineages. A relevant factor possibly influencing these observations could be the changed criteria adopted for the admission of COVID‐19 patients during the study period by the clinical centers. As vaccination became more spread in the population, the COVID‐19 pressure on the healthcare system was alleviated allowing the structures to admit also less severe infections. Mitigation of prophylactic measures also favored the nosocomial circulation of the virus in patients and health workers. These phenomena are clearly testified by the decreasing age of the enrolled subjects throughout the course of the study. This kind of bias probably also applies to all other studies describing clinical differences between SARS‐CoV‐2 variants, given the impossibility to set‐up rigorous prospective studies. Moreover, although this work is the result of the collaboration of many clinical/diagnostic centers located throughout the country, some regions are less represented leading to a potential sampling bias . However, the study included more than 8000 samples collected during the year 2022 in five Italian regions accounting for more than 33% of the Italian population (19 million out of a total population of 58 million individuals in 2024); two regions comprising at least 72.5% of the population living in North‐Western (around 72 million out of 115 million inhabitants) and three in the central part of the Country, accounting for 68% (8 million out of 69 million, data from ISTAT: http://dati.istat.it/Index.aspx?DataSetCode=DCIS_POPRES1 ). Compared with previous variants, the Omicron variant displayed a high number of mutations, with an average of 50 substitutions throughout the genome, mainly in the spike protein. These characteristics are responsible for a higher binding affinity to the ACE2 receptor and greater immune escape from neutralizing and therapeutic monoclonal antibodies . This variant has rapidly further evolved giving rise to large array of multiple lineages and sublineages with specific mutational profiles. By analyzing the mutational profile of these sublineages, we found a high number of mutations, mainly located in the S gene, all identical to those previously described. The phylogenetic analysis of the international data sets showed only the presence of small clusters at the external nodes of the tree, including few isolates probably closely epidemiologically related, thus preventing the observation of larger significant transmission clusters, as reported in other study . This was due to the scanty, relatively rare, and dispersed sampling, along with the strategies adopted to reduce the magnitude of genomes introduced in the analysis. It is also likely that, as the spread rate of the variant exceeded its evolutionary rate (Omicron became prevalent worldwide within a couple of months) thanks to its escape to natural and vaccine‐induced immunity and to the lowering of restrictions, single sublineage did not have sufficient evolutionary pressure for being selected to form large clusters, but only small and fragmented groups sharing the same recent ancestor . Analyzing the subvariants within the international context, there was a tendency for Italian isolates to group in the tree in the same regions, even without forming distinct and significant clades. For this reason, the phylogenetic analysis was conducted considering only the national context in which we found a partial formation of clusters on a local basis, mainly in the case of the BA.1 and BA.2 lineages. Indeed, thanks to the neutral evolution phenomena, such as the “founding effect,” it was possible to identify significant clusters only at local (national) level, while in the international context, due to the high degree of evolutionary correlation among strains of a single variant (BA.1, BA.2, and BA.5), it is difficult to identify more closely related groups of sequences that share a recent common ancestor . The tMRCA for BA.5 suggests that this lineage would have been circulating throughout the period dominated by BA.1 and then BA.2 without any transmission advantage. According to literature data, maximum likelihood estimations suggest that BA.5 could have descended from BA.2 . For these subvariants, higher R e values were observed than those estimated for previous variants , confirming Omicron's enhanced transmissibility. Although the literature data indicate a higher transmissibility of BA.2 than BA.1 , the values we estimated were comparable. These estimates are in line with the official ones ( https://covid19.infn.it/ ), except for the peak in January 2022, corresponding to the simultaneous circulation of the Delta and Omicron variants. Although the mean R e value estimated at peak for BA.5 was lower than those estimated for BA.1 and BA.2, there was a persistence of values above 1 over time since the beginning of the epidemic, which would account for the peak of infected individuals observed in the 2022 wave ( https://covid19.infn.it/ ). Analyses show a good temporal correspondence between the trend in the number of infections estimated from the Skyline graph and the estimated R e by birth‐death Skyline. In conclusion, these data allow an accurate description of the epidemiological dynamics of Omicron sublineages in Italy over a period of great epidemiological changes in the COVID‐19 epidemic. SCIRE collaborative Group: Claudia Balotta, Mario Corbellino, Massimo Galli, Valentina Ricucci, Federica Stefanelli, Nadia Randazzo, Giada Garzillo, Massimo Clementi, Maurizio Zazzi, Lia Fiaschi, Massimo Andreoni, Arianna Miola, Valeria Ricci, Laura Li Puma, Luigi Ruggerone. Annalisa Bergna, Alessia Lai, Gianguglielmo Zehender conceived the project; Fabio Sagradi, Stefano Menzo, Nicasio Mancini, Bianca Bruzzone, Stefano Rusconi, Greta Marchegiani, Nicola Clementi, Daniela Francisci, Ilaria Vicenti, Silvia Ronchiadin, Carla della Ventura, Leonardo Lanfranchi, Sophie Testa, Sara Caucci, Carla Acciarri, Luca Carioti, Alessandro Occhionero, Federica Novazzi, Angelo Paolo Genoni, Francesca Drago Ferrante, Vanessa De Pace, Monica Ferraris, Matilde Ogliastro, Arianna Gabrieli, Massimo De Paschale, Giada Canavesi, Maria Concetta Bellocchi, Marco Iannetta, Loredana Sarmati, Francesca Ceccherini‐Silberstein, Agostino Riva, Spinello Antinori collected the samples and information; Alessia Lai, Harsel Djaya Mbissam performed statistical data analyses; Annalisa Bergna, Alessia Lai, Gianguglielmo Zehender performed phylogenetic analyses; Annalisa Bergna, Alessia Lai, Gianguglielmo Zehender interpreted the results; Fabio Sagradi, Bianca Bruzzone, Greta Marchegiani, Nicola Clementi, Ilaria Vicenti, Carla della Ventura, Leonardo Lanfranchi, Sara Caucci, Carla Acciarri, Luca Carioti, Federica Novazzi, Angelo Paolo Genoni, Francesca Drago Ferrante, Vanessa De Pace, Monica Ferraris, Matilde Ogliastro, Massimo De Paschale, Giada Canavesi, Maria Concetta Bellocchi contributed to the sequencing; Annalisa Bergna, Alessia Lai, Stefano Menzo, Gianguglielmo Zehender wrote the first draft of the manuscript. All authors read, revised and approved the final version of the manuscript. The authors declare no conflicts of interest. Supporting information. |
Use of a standardized diagnostic approach improves the prognostic information of histopathologic factors in pancreatic and periampullary adenocarcinoma | c610e1ae-250e-4c54-8a3c-b549ac59c266 | 3999361 | Pathology[mh] | Pathology guidelines that change the incidence of histopathology parameters are clinically relevant since the parameters carry prognostic information. Guidelines on gross examination and sectioning of pancreaticoduodenectomy (PD) specimens have changed during the last years, after the introduction of the Leeds pathology protocol (LEEPP) . This standardized procedure raised the incidence of involved margins (R1) and involved lymph nodes (N1), and also decreased pancreatic origin and increased distal bile duct origin compared to large series using non-standardized procedures . Proportions of tumour origin vary greatly between different series of operated periampullary adenocarcinomas and it is not known which proportions most accurately reflect the biology of the tumours, or are most clinically relevant. It is however evident that a meticulous pathology examination improves the quality of the pathology report for these cancer forms by producing a higher incidence of N1 and R1 . A high proportion of R1 also seems to correlate to a low relative incidence of pancreatic origin, suggesting that a more thorough examination decreases the relative incidence of pancreatic origin . So far, the reported increase of R1 and decrease in pancreatic origin in the LEEPP-series has been attributed to this particular slicing method. It is however not clear to what extent this change is due to the method or to the interest and dedication of the pathologist. Here, we present the results of a different standardized protocol (SP), in which the pathologist gains access to the full length of the common bile duct through a longitudinal opening via the posterior margin of the PD-specimen, and only standard size blocks are made. It has been stated that this method is inferior to the LEEPP, due to its limited value for assessing tumour origin and resection margins . This method has however not been studied in a standardized setting before.
Data collection and patient characteristics The study cohort is a retrospective consecutive series of 175 PD-specimens with primary adenocarcinomas surgically treated at the University hospitals of Lund and Malmö, Sweden, from January 1 2001 until December 31 2011. Data on survival were gathered from the Swedish National Civil Register. Follow-up started at the date of surgery and ended at death or at December 31 2013, whichever came first. Data on margin status was collected from the original pathology reports, as were data on age at surgery, date of surgery, sex, and whether the specimen was handled according to the SP or not. Data was also gathered on the origin of lymph nodes submitted in separate containers. After information was given on how and from where the surgeons harvested lymph nodes submitted in separate containers, positions 6, 8, 12, 13, 14 and 17 were classified as originating from the specimen, and other positions including 9 and 16 were classified as not originating from the specimen. Of the 175 PDs, 46 (26%) were examined and sectioned according to our SP by one pathologist (JE) and 129 (74%) were examined and sectioned by several pathologists according to personal choice (non-standardized protocol, NSP). Ethical permission was obtained from the Ethics Committee at Lund University. Sectioning of the specimens, standardized protocol This method is, by opening the PD-specimen along the bile duct, similar to one of the methods earlier described by the Royal College of Pathologists but performed in a standardized manner and without opening the pancreatic duct. The specimens were handled after fixation in formalin (Figure ). Margins were stained in different colours; one for the pancreatic transection margin, one for the margin towards the superior mesenteric vein (SMV), one for the margin towards the superior mesenteric artery (SMA), one for the anterior surface and one for the posterior margin. The specimens were accessed through a longitudinal opening of the common bile duct at the posterior margin, from the most proximal part of the bile duct through the papilla of Vater. In the same plane the section was deepened through the common bile duct and into the pancreatic parenchyme. This produced a book-like opening that visualized the whole length of the common bile duct, the ampulla and adjacent pancreatic parenchyme as well as parts of the posterior margin and parts of the SMV-margin. Several standard size blocks were sampled from the ampulla with adjacent duodenal mucosa, pancreatic parenchyme and anterior and posterior margins. The bile duct was sampled longitudinally, with adjacent pancreatic parenchyme, posterior margin and SMV-margin. Additional standard size blocks were sampled from the SMA-margin, from all visible or palpable lymph nodes in the specimen and from additional areas with possible tumour growth. En face sections were made from the pancreatic, bile duct, pyloric and duodenal transection margins. Standardized protocol vs non-standardized protocol Re-evaluations of slides All haematoxylin & eosin stained slides from all cases were revised by one pathologist (JE), blinded to the original report and outcome. Other stains were not revised or used for the assessment of any parameter. Data were gathered on tumour origin, size and grade, perineural invasion, lymphatic vessel and blood vessel invasion, invasion of peripancreatic fat, number of lymph nodes and involved lymph nodes found by the pathologist in the specimen, number of lymph nodes and involved lymph nodes harvested from the specimen by the surgeon and submitted in separate containers, number of lymph nodes and involved lymph nodes in separate containers originating from other areas, N-stage, T-stage and margin status. Decision on tumour origin was based on the anatomical centre of the tumour, with the aid of preinvasive precursor lesions or multifocality, if present. A tumour in the duodenal mucosa with intestinal morphology that involved the ampulla in the periphery was considered to be of duodenal origin. A similar tumour with the ampulla in the centre was considered to be of ampullary origin. A tumour along the bile duct that involved the ampulla was considered to be of bile duct origin if the ampulla was in the periphery of the tumour, but of ampullary origin if the ampulla was in the centre. Multifocal tumour growth or multifocal premalignant changes in the pancreatic parenchyme in the absence of evidence of other tumour origin was considered as a sign of pancreatic origin. In addition to tumour origin the distinction between intestinal morphology and pancreaticobiliary morphology was made for all ampullary carcinomas using morphological criteria . For the assessment of tumour grade, only the poorest degree of differentiation was recorded. Margin status was denoted as R1 if cancer was present less than 1 mm from any margin except for the duodenal serosa, as R0 if the shortest distance exceeded 1 mm, and as unknown (Rx) if any margin, except the duodenal serosa close to the cancer, was insufficiently sampled. If a margin was considered sufficiently sampled or not differed by the location of the tumour. In addition to pancreatic and distal bile duct transection margins, an ampullary carcinoma needed at least one standard size block showing the relation to the anterior surface, adjacent to the duodenal wall, two showing the relation to the posterior surface adjacent to the duodenal wall, one from the SMA-margin and one from the SMV-margin, in order to be considered sufficiently sampled regarding margins. Carcinomas of pancreatic or distal bile duct origin needed, in addition to pancreatic and distal bile duct transection margins, at least two blocks showing the relation to the posterior margin, one from the SMA-margin, one from the SMV-margin and one from the anterior margin. For duodenal origin, one block each from the posterior and anterior margins adjacent to the duodenal wall was considered sufficient. A case could be considered as R1 in an unspecified margin even if other margins were insufficiently sampled. For sampling of lymph nodes in the specimen, the full surface around the specimens was searched manually and also visually after sectioning in intervals of approximately 3 mm. Statistical analysis The Chi-square test and Fisher’s Exact test were used to analyse differences in the distribution of histopathological factors in relation to use of standardized vs non-standardized protocol, and according to tumour location. Kaplan-Meier analysis and log rank test were used to illustrate differences in 5-year overall survival (OS) in strata according to margin status. Cox regression models were used to calculate hazard ratios (HR) for the impact of histopathology parameters on 5-year OS, in univariable and multivariable analysis, adjusted for age, sex, tumour morphology, tumour size, tumour grade, T-stage, N-stage, margin status, perineural invasion, growth in peripancreatic fat, invasion of lymphatic vessels and invasion of blood vessels. Cases who died within 1 month from surgery (n = 2) or were lost to follow up (n = 1) were excluded from the survival analyses. All tests were two-sided and a p-value <0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics version 20.0 (SPSS Inc., Chicago, IL, USA).
The study cohort is a retrospective consecutive series of 175 PD-specimens with primary adenocarcinomas surgically treated at the University hospitals of Lund and Malmö, Sweden, from January 1 2001 until December 31 2011. Data on survival were gathered from the Swedish National Civil Register. Follow-up started at the date of surgery and ended at death or at December 31 2013, whichever came first. Data on margin status was collected from the original pathology reports, as were data on age at surgery, date of surgery, sex, and whether the specimen was handled according to the SP or not. Data was also gathered on the origin of lymph nodes submitted in separate containers. After information was given on how and from where the surgeons harvested lymph nodes submitted in separate containers, positions 6, 8, 12, 13, 14 and 17 were classified as originating from the specimen, and other positions including 9 and 16 were classified as not originating from the specimen. Of the 175 PDs, 46 (26%) were examined and sectioned according to our SP by one pathologist (JE) and 129 (74%) were examined and sectioned by several pathologists according to personal choice (non-standardized protocol, NSP). Ethical permission was obtained from the Ethics Committee at Lund University.
This method is, by opening the PD-specimen along the bile duct, similar to one of the methods earlier described by the Royal College of Pathologists but performed in a standardized manner and without opening the pancreatic duct. The specimens were handled after fixation in formalin (Figure ). Margins were stained in different colours; one for the pancreatic transection margin, one for the margin towards the superior mesenteric vein (SMV), one for the margin towards the superior mesenteric artery (SMA), one for the anterior surface and one for the posterior margin. The specimens were accessed through a longitudinal opening of the common bile duct at the posterior margin, from the most proximal part of the bile duct through the papilla of Vater. In the same plane the section was deepened through the common bile duct and into the pancreatic parenchyme. This produced a book-like opening that visualized the whole length of the common bile duct, the ampulla and adjacent pancreatic parenchyme as well as parts of the posterior margin and parts of the SMV-margin. Several standard size blocks were sampled from the ampulla with adjacent duodenal mucosa, pancreatic parenchyme and anterior and posterior margins. The bile duct was sampled longitudinally, with adjacent pancreatic parenchyme, posterior margin and SMV-margin. Additional standard size blocks were sampled from the SMA-margin, from all visible or palpable lymph nodes in the specimen and from additional areas with possible tumour growth. En face sections were made from the pancreatic, bile duct, pyloric and duodenal transection margins.
Re-evaluations of slides All haematoxylin & eosin stained slides from all cases were revised by one pathologist (JE), blinded to the original report and outcome. Other stains were not revised or used for the assessment of any parameter. Data were gathered on tumour origin, size and grade, perineural invasion, lymphatic vessel and blood vessel invasion, invasion of peripancreatic fat, number of lymph nodes and involved lymph nodes found by the pathologist in the specimen, number of lymph nodes and involved lymph nodes harvested from the specimen by the surgeon and submitted in separate containers, number of lymph nodes and involved lymph nodes in separate containers originating from other areas, N-stage, T-stage and margin status. Decision on tumour origin was based on the anatomical centre of the tumour, with the aid of preinvasive precursor lesions or multifocality, if present. A tumour in the duodenal mucosa with intestinal morphology that involved the ampulla in the periphery was considered to be of duodenal origin. A similar tumour with the ampulla in the centre was considered to be of ampullary origin. A tumour along the bile duct that involved the ampulla was considered to be of bile duct origin if the ampulla was in the periphery of the tumour, but of ampullary origin if the ampulla was in the centre. Multifocal tumour growth or multifocal premalignant changes in the pancreatic parenchyme in the absence of evidence of other tumour origin was considered as a sign of pancreatic origin. In addition to tumour origin the distinction between intestinal morphology and pancreaticobiliary morphology was made for all ampullary carcinomas using morphological criteria . For the assessment of tumour grade, only the poorest degree of differentiation was recorded. Margin status was denoted as R1 if cancer was present less than 1 mm from any margin except for the duodenal serosa, as R0 if the shortest distance exceeded 1 mm, and as unknown (Rx) if any margin, except the duodenal serosa close to the cancer, was insufficiently sampled. If a margin was considered sufficiently sampled or not differed by the location of the tumour. In addition to pancreatic and distal bile duct transection margins, an ampullary carcinoma needed at least one standard size block showing the relation to the anterior surface, adjacent to the duodenal wall, two showing the relation to the posterior surface adjacent to the duodenal wall, one from the SMA-margin and one from the SMV-margin, in order to be considered sufficiently sampled regarding margins. Carcinomas of pancreatic or distal bile duct origin needed, in addition to pancreatic and distal bile duct transection margins, at least two blocks showing the relation to the posterior margin, one from the SMA-margin, one from the SMV-margin and one from the anterior margin. For duodenal origin, one block each from the posterior and anterior margins adjacent to the duodenal wall was considered sufficient. A case could be considered as R1 in an unspecified margin even if other margins were insufficiently sampled. For sampling of lymph nodes in the specimen, the full surface around the specimens was searched manually and also visually after sectioning in intervals of approximately 3 mm. Statistical analysis The Chi-square test and Fisher’s Exact test were used to analyse differences in the distribution of histopathological factors in relation to use of standardized vs non-standardized protocol, and according to tumour location. Kaplan-Meier analysis and log rank test were used to illustrate differences in 5-year overall survival (OS) in strata according to margin status. Cox regression models were used to calculate hazard ratios (HR) for the impact of histopathology parameters on 5-year OS, in univariable and multivariable analysis, adjusted for age, sex, tumour morphology, tumour size, tumour grade, T-stage, N-stage, margin status, perineural invasion, growth in peripancreatic fat, invasion of lymphatic vessels and invasion of blood vessels. Cases who died within 1 month from surgery (n = 2) or were lost to follow up (n = 1) were excluded from the survival analyses. All tests were two-sided and a p-value <0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics version 20.0 (SPSS Inc., Chicago, IL, USA).
All haematoxylin & eosin stained slides from all cases were revised by one pathologist (JE), blinded to the original report and outcome. Other stains were not revised or used for the assessment of any parameter. Data were gathered on tumour origin, size and grade, perineural invasion, lymphatic vessel and blood vessel invasion, invasion of peripancreatic fat, number of lymph nodes and involved lymph nodes found by the pathologist in the specimen, number of lymph nodes and involved lymph nodes harvested from the specimen by the surgeon and submitted in separate containers, number of lymph nodes and involved lymph nodes in separate containers originating from other areas, N-stage, T-stage and margin status. Decision on tumour origin was based on the anatomical centre of the tumour, with the aid of preinvasive precursor lesions or multifocality, if present. A tumour in the duodenal mucosa with intestinal morphology that involved the ampulla in the periphery was considered to be of duodenal origin. A similar tumour with the ampulla in the centre was considered to be of ampullary origin. A tumour along the bile duct that involved the ampulla was considered to be of bile duct origin if the ampulla was in the periphery of the tumour, but of ampullary origin if the ampulla was in the centre. Multifocal tumour growth or multifocal premalignant changes in the pancreatic parenchyme in the absence of evidence of other tumour origin was considered as a sign of pancreatic origin. In addition to tumour origin the distinction between intestinal morphology and pancreaticobiliary morphology was made for all ampullary carcinomas using morphological criteria . For the assessment of tumour grade, only the poorest degree of differentiation was recorded. Margin status was denoted as R1 if cancer was present less than 1 mm from any margin except for the duodenal serosa, as R0 if the shortest distance exceeded 1 mm, and as unknown (Rx) if any margin, except the duodenal serosa close to the cancer, was insufficiently sampled. If a margin was considered sufficiently sampled or not differed by the location of the tumour. In addition to pancreatic and distal bile duct transection margins, an ampullary carcinoma needed at least one standard size block showing the relation to the anterior surface, adjacent to the duodenal wall, two showing the relation to the posterior surface adjacent to the duodenal wall, one from the SMA-margin and one from the SMV-margin, in order to be considered sufficiently sampled regarding margins. Carcinomas of pancreatic or distal bile duct origin needed, in addition to pancreatic and distal bile duct transection margins, at least two blocks showing the relation to the posterior margin, one from the SMA-margin, one from the SMV-margin and one from the anterior margin. For duodenal origin, one block each from the posterior and anterior margins adjacent to the duodenal wall was considered sufficient. A case could be considered as R1 in an unspecified margin even if other margins were insufficiently sampled. For sampling of lymph nodes in the specimen, the full surface around the specimens was searched manually and also visually after sectioning in intervals of approximately 3 mm.
The Chi-square test and Fisher’s Exact test were used to analyse differences in the distribution of histopathological factors in relation to use of standardized vs non-standardized protocol, and according to tumour location. Kaplan-Meier analysis and log rank test were used to illustrate differences in 5-year overall survival (OS) in strata according to margin status. Cox regression models were used to calculate hazard ratios (HR) for the impact of histopathology parameters on 5-year OS, in univariable and multivariable analysis, adjusted for age, sex, tumour morphology, tumour size, tumour grade, T-stage, N-stage, margin status, perineural invasion, growth in peripancreatic fat, invasion of lymphatic vessels and invasion of blood vessels. Cases who died within 1 month from surgery (n = 2) or were lost to follow up (n = 1) were excluded from the survival analyses. All tests were two-sided and a p-value <0.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS Statistics version 20.0 (SPSS Inc., Chicago, IL, USA).
The annual PD-rate increased during the study period, with 35 and 29 cases operated in 2010 and 2011, respectively, compared to a median of 13 per year (range 8–19) during 2001–2009. Forty-two of the 46 SP-cases were diagnosed during 2010 – 2011, which coincided with an increased number of lymph nodes sent for analysis in separate containers; median 1 (interquartile range, IQR 0 – 2) during 2001 – 2009 and median 7 (IQR 3.25 – 10) during 2010 – 2011. Median 5-year OS was 30.4 months in the full cohort of all 172 SP- and NSP-cases, 35.0 months in the SP-group and 29.7 months in the NSP-group. In the SP-group of 46 cases, 27 died during follow up and 19 were censored at December 31 2013. Out of the 129 NSP-cases, 3 were excluded from the survival analysis, but included in all other analyses. Of the remaining 126 cases, 88 died during follow up and 38 were censored at December 31 2013. Differences in the distribution of histopathological parameters between SP-cases and NSP-cases As shown in Table , there were several significant differences in the distribution of histopathological parameters between the re-evaluated NSP- and SP-materials. Tumour origin differed between the SP-group and the NSP-group (p = 0.040), with a higher proportion of distal bile duct origin (39% vs 21%) and a lower proportion of ampullary origin (26% vs 45%) in the former. There was no significant difference between the SP-group and the NSP-group regarding the number of lymph nodes found by the pathologist in the PD-specimens, but the number of lymph nodes harvested from the specimen by the surgeon, as well as the total number of lymph nodes originating from the PD-specimens, was significantly higher in the SP-group compared with the NSP-group (p < 0.001 for both). The number of involved lymph nodes in the PD-specimens was also significantly higher in the SP-group as compared with the NSP-group (p = 0.001), and the number of involved lymph nodes from the PD-specimens submitted in separate containers and total number of involved lymph nodes originating from the specimens differed significantly. The proportion of cases with involved lymph nodes (N1-N2) did not differ significantly between the SP-group and NSP-group. Since the increase in the number of lymph nodes harvested from the specimen by the surgeon occurred in 2009, a separate analysis on lymph node-variables was performed for the last 2.5 years of the study period (July 2009 – 2011). This revealed a significant difference between the SP-group (n = 44) and the NSP-group (n = 31) in the number of involved lymph nodes found in the PD-specimens by the pathologist (median 2.5 vs 1, p = 0.046). There were however no significant differences in the total number of lymph nodes from the specimen (median 16 vs 12, p = 0.601), fraction of cases with 10 or more lymph nodes (89% vs 74%, p = 0.128) or fraction of cases with involved lymph nodes (71% vs 65%, p = 0.622). As further shown in Table , there was a significantly larger proportion of R1 cases (p = 0.002), tumours larger than 20 mm (p = 0.008), perineural tumour growth (p = 0.035) and infiltration of peripancreatic fat (p = 0.002) in the SP-group compared with the NSP-group. In contrast, infiltration of blood vessels was more often found in the NSP-group (p = 0.004). We also examined the involvement of different resection margins by tumour type (Table ). Significant differences (R0 vs R1 and Rx) between the SP and non-SP groups were found at the posterior margin (p = 0.001), the SMA-margin (p < 0.001) and the SMV-margin (p < 0.001), and in tumours of distal bile duct origin (p = 0.006). Effect of re-evaluations of slides The distribution of histopathological characteristics in the total re-evaluated material, stratified by tumour origin, is shown in Table . In the original reports there were 14 NSP-cases without information on margin status. Re-evaluation of slides changed margin status for the NSP-group, increasing R1 from 45/115 to 60/129 and decreasing R0 from 70/115 to 12/129 (p < 0.001), and re-evaluations also rendered 56 NSP-cases with unknown margin status (Rx). Re-evaluation of slides rendered a non-significant increase of R1 in the SP-material, from 63% (29/46) to 76% (35/46) (p = 0.257). Re-evaluations revealed lymph node involvement in 20% (14/70) of NSP-cases that were N0 in the original report. This caused a non-significant change in fraction with involved lymph nodes in the NSP-group, from 46% (59/129) to 57% (73/129) (p = 0.105). Re-evaluations rendered no alterations in the fraction of involved lymph nodes in the SP-material. Overall survival in relation to margin status Kaplan-Meier analysis revealed a significantly prolonged five-year OS in the re-evaluated R0-group compared with the original report R0-group (p < 0.001) (Figure ). As further shown in Table , the unadjusted HR for R1 vs R0 in the original report was 1.6 (95% CI 1.1 - 2.4). In the re-evaluated material the unadjusted HR for R1 vs R0 was 3.3 (95% CI 1.5 - 7.0) and the unadjusted HR for Rx vs R0 was 2.3 (95% CI 1.0 - 5.2). Re-evaluated, but not originally reported, margin status remained an independent prognostic factor in adjusted analysis (HR 2.2, 95% CI 1.0 - 4.9 for R1 and Rx vs R0) (Table ). The unadjusted and adjusted HRs for re-evaluated histopathology parameters are shown in Table .
As shown in Table , there were several significant differences in the distribution of histopathological parameters between the re-evaluated NSP- and SP-materials. Tumour origin differed between the SP-group and the NSP-group (p = 0.040), with a higher proportion of distal bile duct origin (39% vs 21%) and a lower proportion of ampullary origin (26% vs 45%) in the former. There was no significant difference between the SP-group and the NSP-group regarding the number of lymph nodes found by the pathologist in the PD-specimens, but the number of lymph nodes harvested from the specimen by the surgeon, as well as the total number of lymph nodes originating from the PD-specimens, was significantly higher in the SP-group compared with the NSP-group (p < 0.001 for both). The number of involved lymph nodes in the PD-specimens was also significantly higher in the SP-group as compared with the NSP-group (p = 0.001), and the number of involved lymph nodes from the PD-specimens submitted in separate containers and total number of involved lymph nodes originating from the specimens differed significantly. The proportion of cases with involved lymph nodes (N1-N2) did not differ significantly between the SP-group and NSP-group. Since the increase in the number of lymph nodes harvested from the specimen by the surgeon occurred in 2009, a separate analysis on lymph node-variables was performed for the last 2.5 years of the study period (July 2009 – 2011). This revealed a significant difference between the SP-group (n = 44) and the NSP-group (n = 31) in the number of involved lymph nodes found in the PD-specimens by the pathologist (median 2.5 vs 1, p = 0.046). There were however no significant differences in the total number of lymph nodes from the specimen (median 16 vs 12, p = 0.601), fraction of cases with 10 or more lymph nodes (89% vs 74%, p = 0.128) or fraction of cases with involved lymph nodes (71% vs 65%, p = 0.622). As further shown in Table , there was a significantly larger proportion of R1 cases (p = 0.002), tumours larger than 20 mm (p = 0.008), perineural tumour growth (p = 0.035) and infiltration of peripancreatic fat (p = 0.002) in the SP-group compared with the NSP-group. In contrast, infiltration of blood vessels was more often found in the NSP-group (p = 0.004). We also examined the involvement of different resection margins by tumour type (Table ). Significant differences (R0 vs R1 and Rx) between the SP and non-SP groups were found at the posterior margin (p = 0.001), the SMA-margin (p < 0.001) and the SMV-margin (p < 0.001), and in tumours of distal bile duct origin (p = 0.006).
The distribution of histopathological characteristics in the total re-evaluated material, stratified by tumour origin, is shown in Table . In the original reports there were 14 NSP-cases without information on margin status. Re-evaluation of slides changed margin status for the NSP-group, increasing R1 from 45/115 to 60/129 and decreasing R0 from 70/115 to 12/129 (p < 0.001), and re-evaluations also rendered 56 NSP-cases with unknown margin status (Rx). Re-evaluation of slides rendered a non-significant increase of R1 in the SP-material, from 63% (29/46) to 76% (35/46) (p = 0.257). Re-evaluations revealed lymph node involvement in 20% (14/70) of NSP-cases that were N0 in the original report. This caused a non-significant change in fraction with involved lymph nodes in the NSP-group, from 46% (59/129) to 57% (73/129) (p = 0.105). Re-evaluations rendered no alterations in the fraction of involved lymph nodes in the SP-material.
Kaplan-Meier analysis revealed a significantly prolonged five-year OS in the re-evaluated R0-group compared with the original report R0-group (p < 0.001) (Figure ). As further shown in Table , the unadjusted HR for R1 vs R0 in the original report was 1.6 (95% CI 1.1 - 2.4). In the re-evaluated material the unadjusted HR for R1 vs R0 was 3.3 (95% CI 1.5 - 7.0) and the unadjusted HR for Rx vs R0 was 2.3 (95% CI 1.0 - 5.2). Re-evaluated, but not originally reported, margin status remained an independent prognostic factor in adjusted analysis (HR 2.2, 95% CI 1.0 - 4.9 for R1 and Rx vs R0) (Table ). The unadjusted and adjusted HRs for re-evaluated histopathology parameters are shown in Table .
This is, to our best knowledge, the first report on standardized longitudinal opening and slicing of the common bile duct in the handling of PD-specimens with primary adenocarcinoma. Our results confirm previous reports on standardized protocols in the pathology examination of operated periampullary adenocarcinomas by showing that a 1-mm cut-off in the assessment of margin status is relevant for overall survival, both in unadjusted analysis and after adjusting for other histopathology parameters. Microscopic re-evaluation of margin status revealed a larger proportion of involved margins than stated in the original reports. Thereby, the prognostic value of uninvolved margins was increased, regardless of other histopathology parameters. This suggests that a “guilty until proven innocent”-approach towards margins in pancreaticoduodenectomies gives more accurate prognostic information than the opposite approach. Moreover, survival in the large group of cases with unassessable margin status (Rx) differed significantly both from cases with uninvolved margins and from cases with involved margins, suggesting that it is not appropriate to classify these cases as R0. The more frequent finding of growth in peripancreatic fat and perineural tumour growth in SP-cases compared to NSP-cases may be an effect of more extensive sampling in the periphery of the tumour as well as along the bile duct and margins in SP-cases compared with NSP-cases. Tumour infiltration in blood vessels was more often found in NSP-cases than in SP-cases (29% vs 9%), which may be due to an unintended more thorough search for evaluable pathology parameters in SP-cases that had very little coverage on margins and lymph nodes. This model of explanation suggests that the proportion of cases with tumour infiltration in blood vessels in the NSP-group more accurately reflects the actual percentage of infiltration in blood vessels. As a cautionary remark, the possibility of a type I error, i.e. a false positive detection of significant differences between the NSP-group and the SP-group, should also be considered, since a large number of comparisons have been performed. A type II error, i.e. failure to detect the true incidence of involved blood vessels in the SP-group, is also possible due to the relatively small sample size in this group. Comparisons of the incidence of involved margins between our SP-material, excluding duodenal origin, and other standardized series show 78% R1 (32/41) in our SP-group compared with 59% (32/54) and 61% (51/83) in the LEEPP-series . The incidence of involved margins is often not comparable between SP-series and NSP-series, due to a 0-mm definition of margin involvement, or lack of definitions on margin involvement in NSP-series. The fraction of cases with involved lymph nodes is however comparable, showing that non-standardized series report involved lymph nodes in less than 60% of cases, compared to more than 70% in our SP-group and in the LEEPP-series. If such differences are coincidental or actually statistically significant, as well as their potential clinical significance, remains unknown. In the present study, we were able to demonstrate a significantly higher number of involved lymph nodes in the specimens in the SP-group compared with the NSP-group, despite a temporal association between an increased number of lymph nodes harvested from the specimens by the surgeons and the studied standardized protocol. In our material the differences in tumour origin between the SP-group and the NSP-group were significant. It is however not known if there are any clinically relevant differences between the tumour origins of standardized and non-standardized series. It has however previous been shown that the morphological distinction between intestinal and pancreatobiliary morphology has prognostic implications, not only in ampullary adenocarcinomas, but in all periampullary adenocarcinomas, regardless of tumour origin . Moreover, while differences in the expression of cytokeratins and mucins according to morphology have been observed in ampullary carcinomas , these differences seem to be less evident in series stratified solely by the anatomical centre of the ampullary adenocarcinomas . These findings suggest that morphological and molecular tumour characteristics have a greater prognostic impact than the appreciated tumour origin. Despite a very different approach to the specimen, the results on tumour origin, N-stage and margin status in our standardized group are similar to the results of the LEEPP-series and to a lesser degree similar to the results of two other variants on standardized protocols . Whether or not our standardized protocol was more time consuming or more demanding than the LEEPP, and thus inferior due to practical reasons, has however not been studied.
A 1-mm threshold for margin involvement is relevant for overall survival in operated periampullary adenocarcinomas, regardless of tumour origin and other histopathology parameters. Standardized protocols on sectioning of pancreaticoduodenectomy specimens seem to increase the yield of adverse prognostic histopathology parameters compared with non-standardized protocols. Standardizations in pancreatic pathology are needed to decrease unjustifiable variability in pathology reports, both for the sake of the treatment of individual patients and for the sake of future studies and clinical trials.
OS: Overall survival; HR: Hazard ratio; PD: Pancreaticoduodenectomy; LEEPP: Leeds pathology protocol; R1: Involved margins; Rx: Unknown margin status; R0: Uninvolved margins; N1-N2: Involved lymph nodes; SP: Standardized protocol; NSP: Non-standardized protocol; SMV: Superior mesenteric vein; SMA: Superior mesenteric artery; M: Median; IQR: Interquartile range; T-stage: Tumour stage; N-stage: Lymph node stage.
The authors declare that they have no competing interests.
JE conceived of the study, collected data, performed the statistical analyses and drafted the manuscript. KJ participated in the design of the study, statistical analyses and drafting of the manuscript. Both authors read and approved the final manuscript.
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Enhanced detection of distinct honeycomb-structured neuronal SMARCC2 cytobodies in Parkinson’s Disease via Cyclic Heat-Induced Epitope Retrieval (CHIER) | c0d44a30-6572-4d4d-ae60-5dd87eb39934 | 11651576 | Anatomy[mh] | Antigen retrieval is crucial in immunohistochemistry (IHC), particularly for formalin-fixed paraffin-embedded (FFPE) human brain sections. These tissues undergo extensive crosslinking during the fixation process, which masks antigenic sites and prevents effective antibody binding. Heat Induced Epitope Retrieval (HIER) is frequently used to reverse these crosslinks, improving the exposure of linear epitopes, especially in nuclear and cytoplasmic proteins . Hydrated heating during HIER is particularly effective for unmasking antigens hidden within tightly packed chromatin structures. For example, nuclear antigens such as p53 and Ki67 and cytoskeletal and membrane proteins often benefit from this technique. The HIER process likely disrupts formalin-induced protein cross-links and destabilises DNA, converting double-stranded DNA into single strands and enabling antibodies to access previously masked epitopes . Formic acid treatment is often employed in addition to HIER to improve aggregated protein detection . Cyclic Heat-Induced Epitope Retrieval (CHIER) builds upon the HIER method by incorporating repeated cycles of dry heating and cooling preceding the standard epitope retrieval procedure. CHIER is an additional antigen retrieval treatment whereby tissue sections undergo several cycles of timed heating and cooling on a hot plate. We hypothesised that it primarily benefits chromatin-associated and/or aggregated proteins like SMARCC2, whose antigenic sites are often buried within nucleic acid stretches. SWI/SNF Related, Matrix Associated, Actin Dependent Regulator of Chromatin Subfamily C Member 2 (SMARCC2), also known as Mammalian Chromatin Remodelling Complex BRG1-Associated Factor 170 (Baf170), is a core subunit of the SWI/SNF family chromatin remodelling complexes. The Switch/Sucrose Nonfermentable (SWI/SNF) complex plays a crucial role in chromatin remodelling and the regulation of transcription by recruiting transcription factors, coactivators, repressors, and histone modifiers . These multi-subunit, ATP-dependent molecular machines slide and evict nucleosomes . These elements are vital at various stages of neurogenesis in both postnatal and adult stages. When chromatin regulation is disrupted, it can lead to faults in epigenetic gene regulation and result in abnormal gene expression patterns. These irregularities also contribute to a variety of chronic pathologies, including neurodegenerative diseases like Parkinson’s Disease (PD) . When we apply CHIER for SMARCC2 antibody detection, we show that it enhances epitope retrieval, which is difficult to label with conventional methods. By implementing CHIER, we have successfully detected SMARCC2 in the nucleus and improved the detection of large SMARCC2 + cytoplasmic bodies called cytobodies in human brain tissue. We subsequently investigated the potential role of SMARCC2 further and found that SMARCC2 can translocate from the nucleus to the cytoplasm. Our results show that these cytobodies are increased in PD and potentially implicate SMARCC2 aggregation in the pathological process of PD. Human brain tissue Human post-mortem brain tissue was received from the Neurological Foundation Human Brain Bank at the Centre for Brain Research, University of Auckland, New Zealand. All brain tissue was donated with written informed consent from donors and their families. All protocols followed relevant guidelines and regulations approved by the University of Auckland Human Participants Ethics Committee (Ref: 011654–14/NTA/208). Brain tissue specimens was first accessed for research purposes on 27/05/2019. A neuropathologist assessed all cases used in this study. The neurologically normal cases ( n control = 22) had no clinical history of neurological abnormalities, and no other significant neuropathology was noted upon post-mortem examination. The mean age (± SD) of control cases was 70 ± 17, ranging from 35 to 98 years . The mean post-mortem delay (PMD) of neurologically normal control cases was 17 ± 7 hours with a range of 4–33 hours. All PD cases ( n = 22) had a clinical history of PD, and pathological features were consistent with PD pathology, as confirmed by a neuropathologist. Key neuropathological features were loss of pigment and pigmented cells in the substantia nigra and accumulation of LBs in the substantia nigra and other brain regions; many cases also had evidence of cortical LB disease. PD cases had a disease duration ranging from 1–25 years; the mean duration was 14 ± 7 years . The mean age of PD cases was 78 ± 8 and ranged from 60–91 years; the mean post-mortem delay was 11 ± 7 hours with a range of 2.25–25 hours. Formalin-fixed paraffin-embedded tissue processing and tissue microarray construction Upon receipt of the brain, the right hemisphere of each brain was fixed by perfusion of 15% formaldehyde in 0.1 M phosphate buffer through the cerebral arteries and subsequently dissected into anatomically significant blocks. 5 mm-thick cuts were sampled from each block for paraffin embedding. The brain tissue blocks were processed for paraffin embedding as previously described . A tissue microarray (TMA) was constructed using 2 mm paraffin-embedded formalin-fixed cores of PD (n = 22) and neurologically normal controls (n = 22) middle temporal gyrus (MTG) grey matter, as described previously . The MTG was selected due to its relatively homogeneous distribution of α-Synuclein (α-Syn) pathology and involvement during later disease stages. All paraffin blocks were sequentially sectioned using a rotary microtome (Leica Biosystems, RM2335) at a thickness of 7 μm. Sections were individually mounted onto Über plus charged microscope slides (IntstrumeC) using a 41°C-water bath (Leica Biosystems, H1210). Fluorescent immunohistochemistry 7 μm-thick sections from paraffin-embedded MTG blocks or tissue microarrays (TMA) were fluorescently stained as previously described . The detailed step-by-step standard protocol (10 mM tris-EDTA pH 9 heated to 121°C in a pressure cooker) can be found on protocols.io (DOI: dx.doi.org/10.17504/protocols.io.5qpvo3wdzv4o/v1 ). The primary antibodies used in this study (four SMARCC2/Baf170 antibodies: Mouse SMARCC2, PCRP-SMARCC2-1A3, Developmental Studies Hybridoma Bank, 1:100; Rabbit SMARCC2, Origene (AP06744U-N), 1:100; Rabbit Baf170, Abcam (ab71907),1:300; Ms Baf170, Santa Cruz Biotechnology (sc17838), 1:100; Rabbit α-synuclein-phospho S129, ab51253, Abcam, 1:3000; Guinea Pig Neun, ABN90, Millipore, 1:500; Guinea Pig p62, GP52-c, Progen, 1:500, Rat pTFP-43, BL829901, clone ID3, BioLegend, 1:3000). These antibodies have been extensively validated and used previously . Control sections where the primary antibody was omitted showed no immunoreactivity. The control experiments showed that the secondary antibodies displayed no cross-reactivity. Cyclic Heat-Induced Epitope Retrieval (CHIER) Epitope retrieval is paramount for the detection of proteins using immunohistochemistry. Cyclic Heat-Induced Epitope Retrieval (CHIER) is a novel cyclic heating technique developed in-house that enhances the detection of SMARCC2 compared to other standard antigen retrieval protocols. Four CHIER variations were included in the analysis. These variations include changes in temperature, incubation times and number of cycles. The antigen retrieval protocols were performed on sequential MTG sections. A detailed step-by-step CHIER protocol can be found on protocols.io (DOI: dx.doi.org/10.17504/protocols.io.kxygx3284g8j/v1 ). Image acquisition and quantification Whole-tissue images were acquired using an automated fluorescence microscope (Zeiss Axioimager Z2) equipped with a MetaSystems VSlide slide scanner (MetaSystems) and Colibri 7 light source, running Metafer 5 (v4.4.114) with a Plan-Apochromat 20x/0.8 NA dry objective lens. Images were stitched using the MetaCyte software. Sections stained for SMARCC2 were used for the quantification as described previously . The images were extracted from VSViewer, and the rips and fold were segmented out from each section on FIJI/ImageJ (V 2.14.0/1.54f) using the polygon selection tool. Following the segmentation, a precise measurement of the area was made. To obtain a background staining intensity measure for the SMARCC2 staining, a 50 μm × 50 μm square (area = 2500 μm 2 ) was placed over three different areas of background staining, and the grayscale pixel value was measured. The background measurements were averaged to give a mean background staining intensity value. The multipoint tool was used to determine the number of cells with SMARCC2 + cytobodies. To be counted, a cell needed a SMARCC2 + cytobody in a cell as delineated by NeuN labelling and be located close to the nucleus. If this criterion was satisfied, the single largest aggregate close to the nucleus was selected with the multipoint tool. Once all the apparent cytobodies were selected, the grayscale pixel value was measured for every selection point. To be considered a true aggregate, the grayscale pixel value for each selection point had to be higher than a predetermined threshold (45 grayscale points). To obtain total SMARCC2 + cytobody cell density values (cells/mm 2 ), the total number of SMARCC2 + cytobody cells counted for each case was then divided by the measured area. For tissue microarray core analysis, approximately 4mm 2 for each case was quantified. For the treatment comparison on MTG sections, approximately 4–4.5 mm 2 for each case was quantified. Two individuals (BF and BVD) counted while blinded to the case number and disease status. The diameters of cytobodies were measured using the straight line tool in ImageJ (NIH, Bethesda, MD). Measurements were performed on calibrated images. For each cytobody, the straight line tool was used to draw a line across the widest part of the cytobody, defining this as the diameter. Care was taken to position the line from one edge of the cytobody to the opposite edge without overshooting the boundary. Measurements were repeated across 120 cytobody samples from neurologically normal (n: 5) and PD cases (n: 5). Super-resolution images were acquired using an LSM 800 with an Airyscan confocal microscope (Zeiss) with a 63x/1.4 NA Plan Apochromat DIC M27 oil immersion objective lens and GaAsp-PMT detector. Images were acquired using the built-in Airyscan module and processed using the ZEN microscopy software (Zeiss). All images were acquired using optimal Nyquist sampling parameters, and those acquired in a Z-series used the optimal step size of 0.13 μm. Stimulated emission depletion (STED) images were acquired using an Abberior Facility STED microscope (60x UPLXAPO oil immersion lens, 1.42 NA) using ImSpector Lightbox software (Specim, v.16.3.13779). A 561-nm pulsed diode laser was used to excite Alexa Fluor 594. A pulsed 775-nm laser was used for STED imaging to deplete both fluorophores. The Dapi channel was not depleted. After scanning, the images were processed using the PureDenoise plugin for ImageJ (National Institutes of Health, USA v1.53f51). All deconvolution of STED images and 3D reconstruction of aggregates was performed using the Huygens Professional software package (Scientific Volume Imaging, Hilversum, The Netherlands) . Western blot Protein for western blot analysis was extracted using sample harvesting buffer (62.5 mM Tris-HCl pH 6.8, 2% SDS, 10% glycerol), subsequently denatured in NuPage LDS sample buffer (ThermoFisher Scientific; NP0007) at 85°C for 5 min and loaded into 4–12% Bis-Tris gels (ThermoFisher Scientific; NP0336BOX) to be resolved via SDS-PAGE, using a MOPS SDS running buffer (ThermoFisher Scientific; J62847-AP) with a dual colour Protein Ladder (BioRad; 1610374). Gels were transferred with NuPage transfer buffer (ThermoFisher Scientific; NP0006) onto methanol-activated PVDF membranes (Millipore, IPFL00005) for 1 h using a constant voltage of 20 V. Membranes were blocked for 1 h at room temperature in a 1:1 solution of Intercept® (TBS) Blocking Buffer (LI-COR, 927–60001) and TBS-T (TBS with 0.01% Tween 20). Primary antibodies (Mouse SMARCC2, PCRP-SMARCC2-1A3, Developmental Studies Hybridoma Bank, 1:100; Rabbit SMARCC2, Origene (AP06744U-N), 1:2500; Rabbit Baf170, Abcam (ab71907),1:300) were incubated overnight at 4°C in a blocking buffer. Membranes were washed in TBS-T (3 × 10 min) and incubated with secondary antibodies (diluted 1:10,000 in blocking buffer with 0.02% SDS) for 3 h at room temperature, protected from light. Membranes were washed in TBS-T (3 × 10 min), in TBS (10 min) and imaged using a BioRad ChemiDocTM MP Imaging System (Full uncropped Western blots: image). Statistical analysis Data visualisation and statistical hypothesis testing were performed using GraphPad Prism® Version 9.00. Normality testing was performed using the D’Agostino-Pearson normality test. Mann-Whitney test was used to compare groups. Correlations were determined using Spearman correlation. Statistical significance was set at p < 0.05. Final figure were composed using Adobe Photoshop CC (Adobe Systems Incorporated, v23.1). Statistical significance was set as p < 0.05. Human post-mortem brain tissue was received from the Neurological Foundation Human Brain Bank at the Centre for Brain Research, University of Auckland, New Zealand. All brain tissue was donated with written informed consent from donors and their families. All protocols followed relevant guidelines and regulations approved by the University of Auckland Human Participants Ethics Committee (Ref: 011654–14/NTA/208). Brain tissue specimens was first accessed for research purposes on 27/05/2019. A neuropathologist assessed all cases used in this study. The neurologically normal cases ( n control = 22) had no clinical history of neurological abnormalities, and no other significant neuropathology was noted upon post-mortem examination. The mean age (± SD) of control cases was 70 ± 17, ranging from 35 to 98 years . The mean post-mortem delay (PMD) of neurologically normal control cases was 17 ± 7 hours with a range of 4–33 hours. All PD cases ( n = 22) had a clinical history of PD, and pathological features were consistent with PD pathology, as confirmed by a neuropathologist. Key neuropathological features were loss of pigment and pigmented cells in the substantia nigra and accumulation of LBs in the substantia nigra and other brain regions; many cases also had evidence of cortical LB disease. PD cases had a disease duration ranging from 1–25 years; the mean duration was 14 ± 7 years . The mean age of PD cases was 78 ± 8 and ranged from 60–91 years; the mean post-mortem delay was 11 ± 7 hours with a range of 2.25–25 hours. Upon receipt of the brain, the right hemisphere of each brain was fixed by perfusion of 15% formaldehyde in 0.1 M phosphate buffer through the cerebral arteries and subsequently dissected into anatomically significant blocks. 5 mm-thick cuts were sampled from each block for paraffin embedding. The brain tissue blocks were processed for paraffin embedding as previously described . A tissue microarray (TMA) was constructed using 2 mm paraffin-embedded formalin-fixed cores of PD (n = 22) and neurologically normal controls (n = 22) middle temporal gyrus (MTG) grey matter, as described previously . The MTG was selected due to its relatively homogeneous distribution of α-Synuclein (α-Syn) pathology and involvement during later disease stages. All paraffin blocks were sequentially sectioned using a rotary microtome (Leica Biosystems, RM2335) at a thickness of 7 μm. Sections were individually mounted onto Über plus charged microscope slides (IntstrumeC) using a 41°C-water bath (Leica Biosystems, H1210). 7 μm-thick sections from paraffin-embedded MTG blocks or tissue microarrays (TMA) were fluorescently stained as previously described . The detailed step-by-step standard protocol (10 mM tris-EDTA pH 9 heated to 121°C in a pressure cooker) can be found on protocols.io (DOI: dx.doi.org/10.17504/protocols.io.5qpvo3wdzv4o/v1 ). The primary antibodies used in this study (four SMARCC2/Baf170 antibodies: Mouse SMARCC2, PCRP-SMARCC2-1A3, Developmental Studies Hybridoma Bank, 1:100; Rabbit SMARCC2, Origene (AP06744U-N), 1:100; Rabbit Baf170, Abcam (ab71907),1:300; Ms Baf170, Santa Cruz Biotechnology (sc17838), 1:100; Rabbit α-synuclein-phospho S129, ab51253, Abcam, 1:3000; Guinea Pig Neun, ABN90, Millipore, 1:500; Guinea Pig p62, GP52-c, Progen, 1:500, Rat pTFP-43, BL829901, clone ID3, BioLegend, 1:3000). These antibodies have been extensively validated and used previously . Control sections where the primary antibody was omitted showed no immunoreactivity. The control experiments showed that the secondary antibodies displayed no cross-reactivity. Epitope retrieval is paramount for the detection of proteins using immunohistochemistry. Cyclic Heat-Induced Epitope Retrieval (CHIER) is a novel cyclic heating technique developed in-house that enhances the detection of SMARCC2 compared to other standard antigen retrieval protocols. Four CHIER variations were included in the analysis. These variations include changes in temperature, incubation times and number of cycles. The antigen retrieval protocols were performed on sequential MTG sections. A detailed step-by-step CHIER protocol can be found on protocols.io (DOI: dx.doi.org/10.17504/protocols.io.kxygx3284g8j/v1 ). Whole-tissue images were acquired using an automated fluorescence microscope (Zeiss Axioimager Z2) equipped with a MetaSystems VSlide slide scanner (MetaSystems) and Colibri 7 light source, running Metafer 5 (v4.4.114) with a Plan-Apochromat 20x/0.8 NA dry objective lens. Images were stitched using the MetaCyte software. Sections stained for SMARCC2 were used for the quantification as described previously . The images were extracted from VSViewer, and the rips and fold were segmented out from each section on FIJI/ImageJ (V 2.14.0/1.54f) using the polygon selection tool. Following the segmentation, a precise measurement of the area was made. To obtain a background staining intensity measure for the SMARCC2 staining, a 50 μm × 50 μm square (area = 2500 μm 2 ) was placed over three different areas of background staining, and the grayscale pixel value was measured. The background measurements were averaged to give a mean background staining intensity value. The multipoint tool was used to determine the number of cells with SMARCC2 + cytobodies. To be counted, a cell needed a SMARCC2 + cytobody in a cell as delineated by NeuN labelling and be located close to the nucleus. If this criterion was satisfied, the single largest aggregate close to the nucleus was selected with the multipoint tool. Once all the apparent cytobodies were selected, the grayscale pixel value was measured for every selection point. To be considered a true aggregate, the grayscale pixel value for each selection point had to be higher than a predetermined threshold (45 grayscale points). To obtain total SMARCC2 + cytobody cell density values (cells/mm 2 ), the total number of SMARCC2 + cytobody cells counted for each case was then divided by the measured area. For tissue microarray core analysis, approximately 4mm 2 for each case was quantified. For the treatment comparison on MTG sections, approximately 4–4.5 mm 2 for each case was quantified. Two individuals (BF and BVD) counted while blinded to the case number and disease status. The diameters of cytobodies were measured using the straight line tool in ImageJ (NIH, Bethesda, MD). Measurements were performed on calibrated images. For each cytobody, the straight line tool was used to draw a line across the widest part of the cytobody, defining this as the diameter. Care was taken to position the line from one edge of the cytobody to the opposite edge without overshooting the boundary. Measurements were repeated across 120 cytobody samples from neurologically normal (n: 5) and PD cases (n: 5). Super-resolution images were acquired using an LSM 800 with an Airyscan confocal microscope (Zeiss) with a 63x/1.4 NA Plan Apochromat DIC M27 oil immersion objective lens and GaAsp-PMT detector. Images were acquired using the built-in Airyscan module and processed using the ZEN microscopy software (Zeiss). All images were acquired using optimal Nyquist sampling parameters, and those acquired in a Z-series used the optimal step size of 0.13 μm. Stimulated emission depletion (STED) images were acquired using an Abberior Facility STED microscope (60x UPLXAPO oil immersion lens, 1.42 NA) using ImSpector Lightbox software (Specim, v.16.3.13779). A 561-nm pulsed diode laser was used to excite Alexa Fluor 594. A pulsed 775-nm laser was used for STED imaging to deplete both fluorophores. The Dapi channel was not depleted. After scanning, the images were processed using the PureDenoise plugin for ImageJ (National Institutes of Health, USA v1.53f51). All deconvolution of STED images and 3D reconstruction of aggregates was performed using the Huygens Professional software package (Scientific Volume Imaging, Hilversum, The Netherlands) . Protein for western blot analysis was extracted using sample harvesting buffer (62.5 mM Tris-HCl pH 6.8, 2% SDS, 10% glycerol), subsequently denatured in NuPage LDS sample buffer (ThermoFisher Scientific; NP0007) at 85°C for 5 min and loaded into 4–12% Bis-Tris gels (ThermoFisher Scientific; NP0336BOX) to be resolved via SDS-PAGE, using a MOPS SDS running buffer (ThermoFisher Scientific; J62847-AP) with a dual colour Protein Ladder (BioRad; 1610374). Gels were transferred with NuPage transfer buffer (ThermoFisher Scientific; NP0006) onto methanol-activated PVDF membranes (Millipore, IPFL00005) for 1 h using a constant voltage of 20 V. Membranes were blocked for 1 h at room temperature in a 1:1 solution of Intercept® (TBS) Blocking Buffer (LI-COR, 927–60001) and TBS-T (TBS with 0.01% Tween 20). Primary antibodies (Mouse SMARCC2, PCRP-SMARCC2-1A3, Developmental Studies Hybridoma Bank, 1:100; Rabbit SMARCC2, Origene (AP06744U-N), 1:2500; Rabbit Baf170, Abcam (ab71907),1:300) were incubated overnight at 4°C in a blocking buffer. Membranes were washed in TBS-T (3 × 10 min) and incubated with secondary antibodies (diluted 1:10,000 in blocking buffer with 0.02% SDS) for 3 h at room temperature, protected from light. Membranes were washed in TBS-T (3 × 10 min), in TBS (10 min) and imaged using a BioRad ChemiDocTM MP Imaging System (Full uncropped Western blots: image). Data visualisation and statistical hypothesis testing were performed using GraphPad Prism® Version 9.00. Normality testing was performed using the D’Agostino-Pearson normality test. Mann-Whitney test was used to compare groups. Correlations were determined using Spearman correlation. Statistical significance was set at p < 0.05. Final figure were composed using Adobe Photoshop CC (Adobe Systems Incorporated, v23.1). Statistical significance was set as p < 0.05. SMARCC2 localisation in the middle temporal gyrus (MTG) grey matter We observed SMARCC2-1A3 labelling in the nucleus using our standard antigen retrieval protocol. This SMARCC2-1A3 labelling was punctate and present within NeuN + neurons. Spotty staining was observed in the cytoplasm (A). As expected, non-specific lipofuscin autofluorescence was also present in these neurons ( , indicated by *). In a subset of MTG neurons, intense SMARCC2-1A3 + labelling was observed in the cytoplasm. SMARCC2-1A3 labelling was present as a circular cytoplasmic body in these cells, which we named cytobodies. These SMARCC2 + cytobodies were found in neurologically normal and PD cases . If present, then most commonly, only one SMARCC2 + cytobody/cell was found. However, some cells contained between 1–4 SMARCC2 + cytobodies/cell. SMARCC2 + cytobodies were only found in neurons. Overall, the cellular SMARCC2-1A3 staining based on observations from all neurologically normal and PD cases could be categorised as (1) Nuclear punctate SMARCC2-1A3, (2) nuclear punctate SMARCC2-1A3 with a SMARCC2 + cytobody, (3) weak to no nuclear SMARCC2-1A3 with a SMARCC2 + cytobody or (4) no SMARCC2-1A3 labelling . The staining intensity of the SMARCC2 + cytobodies was higher than the nuclear punctate labelling. This large intensity difference resulted in an apparent lack of nuclear SMARCC2-1A3 labelling in some cells despite SMARCC2-1A3 labelling still being present, as demonstrated . Here, a typical neuron with nuclear punctate SMARCC2-1A3 labelling and a SMARCC2 + cytobody is imaged using two different integration times. is imaged using the parameters (normal integration) identical to , whereas imaging (short exposure) is optimised to avoid saturation of the SMARCC2 + cytobody. This short exposure still saturated SMARCC2 + cytobodies in other cases (e.g. PD105), where only neurons with SMARCC2 + cytobodies that lack nuclear SMARCC2-1A3 labelling were found . As part of this research, we tested additional antigen retrieval steps to our standard Tris-EDTA protocol to improve SMARCC2 labelling . Cyclic Heat-Induced Epitope Retrieval (CHIER) is a novel cyclic heating technique developed in-house using a sequence of heating and cooling tissue slides on a hot plate. We compared different CHIER variations to standard and standard + formic using tissue from PD cases. In the cases with high numbers of neurons with SMARCC2 + cytobodies, all antigen retrieval variations, including the standard antigen retrieval protocol, detected cytobodies. Acid treatment, commonly used to increase the labelling of aggregated proteins, did not improve SMARCC2 + cytobodies detection. The number of neurons with SMARCC2 + cytobodies was quantified for each variation. CHIER variation D ((5 min at 70° Celsius + 5 min at room temp) repeated six times) improved the SMARCC + staining significantly compared to all other antigen retrievals. CHIER D (13.4 ± 1.63) resulted in a three-fold increase in the number of neurons with SMARCC2 + cytobodies/mm 2 compared to the standard antigen retrieval (60 min hotplate at 60° Celsius with tris EDTA ph9 with Tween in the pressure cooker) (3.77 ± 0.60; Fig 1 in , ). We used our optimised antigen retrieval method (CHIER D) to quantify the neurons with SMARCC2 + cytobodies in MTG grey matter. We found an increase of neurons with SMARCC2 + cytobodies/mm 2 in PD (13.5 ± 12.2 in PD vs 5.3 ± 5.0 in neurologically normal cases, p = 0.014) . We subsequently correlated our counts with age at death, post-mortem delay, brain weight, years of PD onset and α-Syn load. No strong correlations or differences between sexes were found. Moderate correlations were present between neurons with SMARCC2 + cytobodies and age at death (r = 0.4346; p = 0.043), post-mortem delay (r = -0.5157; p = 0.014) and brain weight (r = -0.5302; p = 0.011) . Up to now, only nuclear SMARCC2 labelling has been described. Therefore, to cross-validate SMARCC2-1A3 labelling of SMARCC2 + cytobodies, we tested three additional SMARCC2/Baf170 antibodies targeting the central and C-terminal ends of SMARCC2 . SMARCC2 (APO06744PU-N) labelled nuclear puncta and cytobodies similarly to SMARCC2-1A3 ( , yellow and cyan arrows). SMARCC2 (ab71907) and Baf170 (sc17838) never labelled SMARCC2 + cytobodies as observed for SMARCC2-1A3 and SMARCC2 (APO06744PU-N) and only labelled nuclear puncta, some of which overlapped with SMARCC2-1A3 (white and red arrows; ). To investigate if truncated SMARCC2 and isoforms are present, protein extracts of the middle temporal gyrus (MTG) and primary pericyte cultures from MTG were analysed. Western blotting of the positive control containing full-length SMARCC2 protein (TP303774, Origene) with SMARCC2-1A3 showed a clear band at 150 kDa as expected and a faint band at 130 kDa. These bands overlap with the SMARCC2 (ab71907) bands observed at 150 and 130 kDa (High exposure image of 150 kDa region shown underneath entire blot; ). Two clear bands at 60 kDa and 25 kDa were observed in the MTG extracts with SMARCC2-1A3. In PD cases, the 60 kDa SMARCC2-1A3 band was less intense to absent, whereas in control cases, the 25 kDa SMARCC2-1A3 band was not consistently observed. SMARCC2 (ab71907) only detected a 150 kDa band in the MTG tissue . Western blotting with SMARCC2 (AP06744PU-N) detected two clear bands at 130 kDa and 25 kDa, with the 25 kDa band overlapping with the 25 kDa SMARCC2-1A3 band (High exposure image of 25 kDa region shown underneath entire blot; ). 3D architecture SMARCC2 + cytobodies CHIER is compatible with advanced fluorescent techniques with super-resolution imaging of the SMARCC2 + cytobodies, revealing a more complex structure resembling a honeycomb architecture. The staining observed in the SMARCC2 + cytobodies resembles a spherical structure with an intricate, lattice-like pattern akin to the internal framework of a cellular matrix. The average diameter of the SMARCC2 + cytobodies was 1.8 μm, ranging between 1 and 3.8 μm. Even though most SMARCC2 + cytobodies were single circular structures, some were more complex and consisted of multiple fused cytobodies Due to the similarities with aggregate pathology observed in other neurodegenerative diseases, we investigated potential interactions between SMARCC2 + cytobodies and α-Syn and p62. CHIER did not negatively affect the labelling staining of these antibodies. Overall, SMARCC2 + cytobodies did not co-localise with α-Syn pathology (labelled by pS129 α-Syn; ), although a rare example did make contact with an α-Syn aggregate . Furthermore, occasionally, p62 was found within SMARCC2 + cytobodies . We observed SMARCC2-1A3 labelling in the nucleus using our standard antigen retrieval protocol. This SMARCC2-1A3 labelling was punctate and present within NeuN + neurons. Spotty staining was observed in the cytoplasm (A). As expected, non-specific lipofuscin autofluorescence was also present in these neurons ( , indicated by *). In a subset of MTG neurons, intense SMARCC2-1A3 + labelling was observed in the cytoplasm. SMARCC2-1A3 labelling was present as a circular cytoplasmic body in these cells, which we named cytobodies. These SMARCC2 + cytobodies were found in neurologically normal and PD cases . If present, then most commonly, only one SMARCC2 + cytobody/cell was found. However, some cells contained between 1–4 SMARCC2 + cytobodies/cell. SMARCC2 + cytobodies were only found in neurons. Overall, the cellular SMARCC2-1A3 staining based on observations from all neurologically normal and PD cases could be categorised as (1) Nuclear punctate SMARCC2-1A3, (2) nuclear punctate SMARCC2-1A3 with a SMARCC2 + cytobody, (3) weak to no nuclear SMARCC2-1A3 with a SMARCC2 + cytobody or (4) no SMARCC2-1A3 labelling . The staining intensity of the SMARCC2 + cytobodies was higher than the nuclear punctate labelling. This large intensity difference resulted in an apparent lack of nuclear SMARCC2-1A3 labelling in some cells despite SMARCC2-1A3 labelling still being present, as demonstrated . Here, a typical neuron with nuclear punctate SMARCC2-1A3 labelling and a SMARCC2 + cytobody is imaged using two different integration times. is imaged using the parameters (normal integration) identical to , whereas imaging (short exposure) is optimised to avoid saturation of the SMARCC2 + cytobody. This short exposure still saturated SMARCC2 + cytobodies in other cases (e.g. PD105), where only neurons with SMARCC2 + cytobodies that lack nuclear SMARCC2-1A3 labelling were found . As part of this research, we tested additional antigen retrieval steps to our standard Tris-EDTA protocol to improve SMARCC2 labelling . Cyclic Heat-Induced Epitope Retrieval (CHIER) is a novel cyclic heating technique developed in-house using a sequence of heating and cooling tissue slides on a hot plate. We compared different CHIER variations to standard and standard + formic using tissue from PD cases. In the cases with high numbers of neurons with SMARCC2 + cytobodies, all antigen retrieval variations, including the standard antigen retrieval protocol, detected cytobodies. Acid treatment, commonly used to increase the labelling of aggregated proteins, did not improve SMARCC2 + cytobodies detection. The number of neurons with SMARCC2 + cytobodies was quantified for each variation. CHIER variation D ((5 min at 70° Celsius + 5 min at room temp) repeated six times) improved the SMARCC + staining significantly compared to all other antigen retrievals. CHIER D (13.4 ± 1.63) resulted in a three-fold increase in the number of neurons with SMARCC2 + cytobodies/mm 2 compared to the standard antigen retrieval (60 min hotplate at 60° Celsius with tris EDTA ph9 with Tween in the pressure cooker) (3.77 ± 0.60; Fig 1 in , ). We used our optimised antigen retrieval method (CHIER D) to quantify the neurons with SMARCC2 + cytobodies in MTG grey matter. We found an increase of neurons with SMARCC2 + cytobodies/mm 2 in PD (13.5 ± 12.2 in PD vs 5.3 ± 5.0 in neurologically normal cases, p = 0.014) . We subsequently correlated our counts with age at death, post-mortem delay, brain weight, years of PD onset and α-Syn load. No strong correlations or differences between sexes were found. Moderate correlations were present between neurons with SMARCC2 + cytobodies and age at death (r = 0.4346; p = 0.043), post-mortem delay (r = -0.5157; p = 0.014) and brain weight (r = -0.5302; p = 0.011) . Up to now, only nuclear SMARCC2 labelling has been described. Therefore, to cross-validate SMARCC2-1A3 labelling of SMARCC2 + cytobodies, we tested three additional SMARCC2/Baf170 antibodies targeting the central and C-terminal ends of SMARCC2 . SMARCC2 (APO06744PU-N) labelled nuclear puncta and cytobodies similarly to SMARCC2-1A3 ( , yellow and cyan arrows). SMARCC2 (ab71907) and Baf170 (sc17838) never labelled SMARCC2 + cytobodies as observed for SMARCC2-1A3 and SMARCC2 (APO06744PU-N) and only labelled nuclear puncta, some of which overlapped with SMARCC2-1A3 (white and red arrows; ). To investigate if truncated SMARCC2 and isoforms are present, protein extracts of the middle temporal gyrus (MTG) and primary pericyte cultures from MTG were analysed. Western blotting of the positive control containing full-length SMARCC2 protein (TP303774, Origene) with SMARCC2-1A3 showed a clear band at 150 kDa as expected and a faint band at 130 kDa. These bands overlap with the SMARCC2 (ab71907) bands observed at 150 and 130 kDa (High exposure image of 150 kDa region shown underneath entire blot; ). Two clear bands at 60 kDa and 25 kDa were observed in the MTG extracts with SMARCC2-1A3. In PD cases, the 60 kDa SMARCC2-1A3 band was less intense to absent, whereas in control cases, the 25 kDa SMARCC2-1A3 band was not consistently observed. SMARCC2 (ab71907) only detected a 150 kDa band in the MTG tissue . Western blotting with SMARCC2 (AP06744PU-N) detected two clear bands at 130 kDa and 25 kDa, with the 25 kDa band overlapping with the 25 kDa SMARCC2-1A3 band (High exposure image of 25 kDa region shown underneath entire blot; ). + cytobodies CHIER is compatible with advanced fluorescent techniques with super-resolution imaging of the SMARCC2 + cytobodies, revealing a more complex structure resembling a honeycomb architecture. The staining observed in the SMARCC2 + cytobodies resembles a spherical structure with an intricate, lattice-like pattern akin to the internal framework of a cellular matrix. The average diameter of the SMARCC2 + cytobodies was 1.8 μm, ranging between 1 and 3.8 μm. Even though most SMARCC2 + cytobodies were single circular structures, some were more complex and consisted of multiple fused cytobodies Due to the similarities with aggregate pathology observed in other neurodegenerative diseases, we investigated potential interactions between SMARCC2 + cytobodies and α-Syn and p62. CHIER did not negatively affect the labelling staining of these antibodies. Overall, SMARCC2 + cytobodies did not co-localise with α-Syn pathology (labelled by pS129 α-Syn; ), although a rare example did make contact with an α-Syn aggregate . Furthermore, occasionally, p62 was found within SMARCC2 + cytobodies . Our study enhanced the well-established Tris-EDTA antigen retrieval protocol by incorporating additional antigen retrieval steps. Notably, formic acid treatment, a technique often employed to improve aggregated protein detection, had little effect. Cyclic Heat-Induced Epitope Retrieval (CHIER), a novel technique we developed, increased the detection of SMARCC2 + cytobodies threefold. This method involves heating and cooling the tissue slides on a hot plate. CHIER variation D, which involves a cycle of 5 minutes at 70° Celsius followed by 5 minutes at room temperature, repeated six times, proved the most effective. In our hands, CHIER had no deleterious effects on other antibody detections (Neun, α-Syn pS129, pTDP43, Fig 2 in ) or Ulex Eurapaeus Lectin (endothelial marker, Fig 2 in ), nor did it negatively affect detection with super-resolution microscopy. This novel variation expands the repertoire of antigen retrieval options with CHIER, combining the antigen retrieval benefits of HIER and formic acid treatment. Emerging studies indicate dysfunction in chromatin remodelling processes in neurodegenerative disorders, including PD . α-Synuclein (overexpression disturbs the SWI/SNF complex . α-Syn is a key player in PD, and the abnormal accumulation of α-Syn aggregates is a pathological hallmark of PD (reviewed in ). However, the direct mechanism by which this occurs remains unknown. Our study found limited evidence of direct interaction between SMARCC2 + cytobodies and α-Syn (p-S129) labelled aggregates. To our knowledge, the presence of SMARCC2 + cytobodies in neurons or any other cell type has not been studied. By applying CHIER, we could accurately quantify the amount of SMARCC2 + cytobodies in MTG. By doing so, we observed nuclear and cytoplasmic SMARCC2 with a significant increase of neurons with SMARCC2 + cytobodies in PD. The staining observed in the SMARCC2 + cytobodies resembles a complex spherical structure with an intricate, lattice-like pattern akin to the internal framework of a cellular matrix. This distinctive configuration resembling honeycomb candy suggests a complex and organised arrangement indicative of specific biological processes or structural functionalities in the cellular environment. The lattice-like pattern of the SMARCC2 + antibodies implies that other proteins are likely interacting with SMARCC2. The presence of p62 in some of the SMARCC2 + cytobodies indicates that these cytobodies are partially destined to be degraded by autophagy. In this aspect, SMARCC2 resembles the translocation from the nucleus to the cytoplasm seen for TDP-43 protein. In ALS, TDP-43 undergoes cytoplasmic mislocalisation and aggregation, along with a myriad of post-translational modifications such as phosphorylation, ubiquitination, and truncation, altering its structure and function . Although this comparison is purely speculative, as this manuscript did not investigate phosphorylation or ubiquitination, it does warrant further investigation into why SMARCC2 + cytobodies are increased in PD. Previous studies identified the crucial and multifaceted role of SMARCC2 in SWI/SNF complexes. Even though SWI/SNF complexes contain the same core proteins (SMARCC1, SMARCC2, SMARCD1), numerous variable subunits provide each complex with a distinct identity that modulates its function . It is likely that through this mechanism of variable subunits in SWI/SNF complexes, SMARCC2-mediated gene regulation is altered . Combined with the known SMARCC2 isoforms and/or SMARCC2 truncational variants, this could explain why only a partial overlap was observed for the nuclear puncta detected with the four SMARC2/Baf170 antibodies . The C-terminus SMARCC2/Baf170 antibodies did not label the SMARCC2 cytobodies, whereas the antibodies detecting the central part of the proteins did. This differential immunolabeling combined with the identification of lower molecular weight SMARCC2 bands (60 and 25kDa; ) suggests that the SMARCC2 + cytobodies found in neurons contain a short isoform or a truncated SMARCC2, being 25 or 60 kDa in size. It is important to highlight that SMARCC2-1A3 targets the SWIRM domain, which interacts directly with DNA, mediating specific protein-protein interactions to assemble chromatin-protein complexes . Our data does not preclude the presence of truncated SMARCC2 from the nucleus, which still contains the SWIRM domain, but does add to the complex role of SMARCC2 in chromatin regulation and neurodegenerative diseases such as PD. Cyclic Heat-Induced Epitope Retrieval (CHIER) is a new antigen retrieval protocol that can significantly improve the detection of hard-to-detect epitopes. Using CHIER, we observed a notable increase in SMARCC2-positive cytoplasmic bodies within neurons of the MTG in PD, a phenomenon not previously reported in PD research. This novel finding warrants further investigation to elucidate the origins, associated interacting proteins, and potential implications of truncated SMARCC2 accumulation in these cytoplasmic bodies to better understand their role in PD. Additionally, CHIER does not compromise the antigenicity of other antibodies, supporting its broader application in multiplex fluorescent immunohistochemistry and super-resolution imaging, with the potential for improving the detection of other chromatin-binding or aggregated proteins. S1 Appendix Fluorescent labelling standard antigen retrieval compared to CHIER. (PDF) S1 Raw image Uncropped Western blots. (PDF) S1 Video 3D render of SMARCC2 + cytobody in neuron shown in A. Labelling in this video was performed using CHIER protocol D. (AVI) S2 Video 3D render of SMARCC2 + cytobody in neuron shown in C. SMARCC2+ (yellow), NeuN (cyan), Hoechst (blue). Labelling in this video was performed using CHIER protocol D. (AVI) S1 File (PDF) |
Knowledge and attitudes on implementing cardiovascular pharmacogenomic testing | ab190280-5bce-408f-a874-38eb5a6f145a | 10903329 | Pharmacology[mh] | As pharmacogenomic research continues to advance, an increasing number of clinically actionable gene‐drug pairs are being discovered. Whereas there are hundreds of reported gene‐drug associations with variable levels of evidence, 97% of people in the United States tested with a targeted, clinical 12‐gene pharmacogenomic panel carry at least one actionable variant. The utility of these variants includes increasing accuracy in drug dosing and selection as well as reducing adverse drug events and improving treatment efficacy. , , Many studies have focused on understanding provider knowledge and comfort with implementing clinical pharmacogenomic testing. Researchers have explored both primary care providers (PCPs), , as well as specialists, such as oncologists, neurologists, and cardiologists, who prescribe medications that may be impacted by pharmacogenomic test results , to better understand the current state of provider knowledge and attitudes on pharmacogenomics, and ultimately guide clinical implementation. To clinically implement pharmacogenomic testing, providers need sufficient education and familiarity with genetic‐guided medication management to facilitate appropriate test ordering. However, many healthcare providers report little to no knowledge of pharmacogenomics, having never received formal education on the topic. In previous studies, only 10–13% of pediatricians, PCPs, cardiologists, and psychiatrists reported being familiar with pharmacogenomics. With such limited physician knowledge, it is not surprising that the number of physicians who report ordering pharmacogenomic testing is also low. Across specialties, studies found that only up to 20% of respondents had previously ordered a pharmacogenomic test during the last year, of which a larger percentage of specialists had ordered a pharmacogenomic test (15.2% cardiologists, 18.3% dermatologists, and 19.5% neurologists) compared to PCPs (11.7%). Of the PCPs who reported ordering a pharmacogenomic test in a nationwide survey, 29% reported receiving pharmacogenomic education, whereas the same survey administered to cardiologists revealed that 55% of test adopters reported receiving pharmacogenomic education. These similar trends in education levels are consistent across studies, which have found that provider education on pharmacogenomics is broadly lacking. However, Unertl et al. found that cardiologists could reference specific primary sources or continuing education by which they learned about pharmacogenomics even if they had not received formal training, whereas other specialists or PCPs could not reference such specific sources of information. A common challenge with genetic testing is that non‐genetics providers are not adequately educated on ordering, interpreting, or communicating genetic test results. Qualitative interviews illustrate provider concerns, such as lack of knowledge, inability to interpret results, and lack of ability to translate test results into clinical management. , Providers also frequently raised concerns about whose responsibility it is to order the test and communicate results to the patient, as well as the long‐term responsibility for actionable results. The goal of implementing pharmacogenomics is to utilize results to guide drug dosage and selection, yet only 26% of PCPs report confidence in using pharmacogenomics in prescribing decisions. Commonly cited barriers to clinical implementation of pharmacogenomic testing include the lack of provider knowledge and education, as well as ambiguity on the scope of interpretation and who is responsible for the test results over the course of patient care. Across disease domains with established clinically actionable gene‐drug pairs (e.g., psychiatry, oncology, neurology, and cardiology), cardiologists generally report higher levels of knowledge, exposure, and ordering patterns. , Most cardiologists were able to correctly identify clopidogrel (86.4%) and warfarin (64.4%) as commonly prescribed cardiovascular medications that elicit variable responses due to genetic variability, whereas only 43.3% and 21.7% of psychiatrists correctly identified carbamazepine and atomoxetine, respectively, as psychiatric medications that elicit variable responses due to genetic variability. Cardiologists have previously reported confidence in their knowledge of pharmacogenomics, whereas PCPs and pharmacists report an overall lack of education and knowledge. In another study, cardiologists were able to correctly answer objective cardiovascular pharmacogenomic knowledge questions (e.g., which cardiovascular medications elicit variable responses to genetic variation ), supporting their self‐reported familiarity with pharmacogenomic testing. Previous studies have focused predominantly on PCPs or a mixture of specialists and their knowledge and comfort with pharmacogenomics. However, cardiology providers commonly prescribe medications with clinically actionable pharmacogenomic evidence, which makes them a unique and important population to measure perspectives on implementing pharmacogenomic testing. Additionally, there are many subspecialties within cardiology that may report different exposure and awareness of pharmacogenomics, but this has not previously been studied. Most studies have evaluated pharmacogenomics more generally across specialties but have not assessed provider opinions on pre‐emptive pharmacogenomic testing and/or panel‐based testing, which have important implications on test turnaround time and medication management, respectively. Whereas pharmacogenomic early adopters and expert medical groups have avoided these challenges by selecting commonly prescribed medications to pre‐emptively screen all patients, this strategy has proven challenging to implement universally due to a fragmented US healthcare system, resource constraints, and other reasons outlined above. , Building on previously reported pharmacogenomic awareness and ordering patterns among cardiologists compared to other providers, our study aims to specifically evaluate cardiology providers' knowledge and attitudes toward the implementation of pharmacogenomics into their practice. In this assessment, we aim to better understand which clinical providers feel prepared to implement pharmacogenomic‐guided prescribing and uncover barriers that may affect panel‐based testing and clinical implementation. AND METHODS Study design and survey An online, anonymous 28‐question survey was developed and sent to cardiology providers across the state of California. Recruitment was limited to providers in the state of California to focus on the recruitment of providers from a variety of practice settings, professions, and subspecialties. The Institutional Review Board of the Stanford School of Medicine determined this project was exempt. Survey responses were collected from December 2021 to February 2022. The survey was developed by a multidisciplinary team and included multiple choice questions that assessed demographics; objective knowledge questions on clopidogrel (Plavix) and CYP2C19 ; provider experience ordering genetic and pharmacogenomic testing; familiarity and comfort with panel‐based pharmacogenomic testing and return of results; provider utilized pharmacogenomic resources (e.g., the Pharmacogenomics Knowledge Base [PharmGKB] and the Clinical Pharmacogenetics Implementation Consortium [CPIC]); and perceived barriers to implementing clinical pharmacogenomic testing (Supplementary Material ). Provider knowledge and attitude questions on genetics and pharmacogenomics were adapted from previously reported surveys. , , , Likert scale responses were used to assess reported knowledge and familiarity with pharmacogenomic testing and comfort with interpreting and returning pharmacogenomic test results. Open‐ended questions were included throughout to allow providers to indicate what testing they previously ordered and to allow for general comments on implementing pharmacogenomic testing. The survey was distributed via Qualtrics (version December 2021). Subjects Subjects were eligible to participate in the study if they were clinical cardiology providers currently practicing in the state of California. Clinical cardiology providers were defined as cardiologists (MD), genetic counselors (MS), nurse/nurse practitioners (RN, NP, or similar), physician assistants (MS), and/or pharmacists (PharmD). Recruitment emails containing a link to the online survey were deployed through four email listservs: Northern California Coalition of Genetic Counselors, Southern California Genetic Counselors, California Pharmacists Association, and the California Society of Health‐System Pharmacists. Recruitment emails containing a link to the online survey were also distributed to cardiology fellowship directors at institutions, including Stanford University, the University of California Los Angeles, Kaiser Permanente, and the University of California San Francisco. Additionally, recruitment flyers that included a QR code to the online survey were distributed to selected cardiology providers at Stanford Health Care, including the Stanford Center for Inherited Cardiovascular Disease and Stanford Cardiology Faculty. Additional study participants were recruited by posting about the survey on Twitter through the personal accounts of the authors and those of PharmGKB and CPIC. Data analysis Survey responses were summarized using descriptive statistics, including means, medians, and frequencies. Chi‐Square or Fisher's exact tests were used as appropriate to assess associations among provider knowledge, comfort, and ordering preferences. Likert scale survey responses were dichotomized to compare those who selected “strongly disagree” and “disagree” to those who selected “agree” and “strongly agree,” as we were interested more broadly in comparing these two groups, as well as to increase the sample size in each group to allow for these comparisons. Univariable analyses were conducted to determine which covariates should be included in the regression model. Logistic regression was performed to assess predictors of interest in pharmacogenomic testing and familiarity with pharmacogenomics. All statistical analyses were performed using R Statistics software. An online, anonymous 28‐question survey was developed and sent to cardiology providers across the state of California. Recruitment was limited to providers in the state of California to focus on the recruitment of providers from a variety of practice settings, professions, and subspecialties. The Institutional Review Board of the Stanford School of Medicine determined this project was exempt. Survey responses were collected from December 2021 to February 2022. The survey was developed by a multidisciplinary team and included multiple choice questions that assessed demographics; objective knowledge questions on clopidogrel (Plavix) and CYP2C19 ; provider experience ordering genetic and pharmacogenomic testing; familiarity and comfort with panel‐based pharmacogenomic testing and return of results; provider utilized pharmacogenomic resources (e.g., the Pharmacogenomics Knowledge Base [PharmGKB] and the Clinical Pharmacogenetics Implementation Consortium [CPIC]); and perceived barriers to implementing clinical pharmacogenomic testing (Supplementary Material ). Provider knowledge and attitude questions on genetics and pharmacogenomics were adapted from previously reported surveys. , , , Likert scale responses were used to assess reported knowledge and familiarity with pharmacogenomic testing and comfort with interpreting and returning pharmacogenomic test results. Open‐ended questions were included throughout to allow providers to indicate what testing they previously ordered and to allow for general comments on implementing pharmacogenomic testing. The survey was distributed via Qualtrics (version December 2021). Subjects were eligible to participate in the study if they were clinical cardiology providers currently practicing in the state of California. Clinical cardiology providers were defined as cardiologists (MD), genetic counselors (MS), nurse/nurse practitioners (RN, NP, or similar), physician assistants (MS), and/or pharmacists (PharmD). Recruitment emails containing a link to the online survey were deployed through four email listservs: Northern California Coalition of Genetic Counselors, Southern California Genetic Counselors, California Pharmacists Association, and the California Society of Health‐System Pharmacists. Recruitment emails containing a link to the online survey were also distributed to cardiology fellowship directors at institutions, including Stanford University, the University of California Los Angeles, Kaiser Permanente, and the University of California San Francisco. Additionally, recruitment flyers that included a QR code to the online survey were distributed to selected cardiology providers at Stanford Health Care, including the Stanford Center for Inherited Cardiovascular Disease and Stanford Cardiology Faculty. Additional study participants were recruited by posting about the survey on Twitter through the personal accounts of the authors and those of PharmGKB and CPIC. Survey responses were summarized using descriptive statistics, including means, medians, and frequencies. Chi‐Square or Fisher's exact tests were used as appropriate to assess associations among provider knowledge, comfort, and ordering preferences. Likert scale survey responses were dichotomized to compare those who selected “strongly disagree” and “disagree” to those who selected “agree” and “strongly agree,” as we were interested more broadly in comparing these two groups, as well as to increase the sample size in each group to allow for these comparisons. Univariable analyses were conducted to determine which covariates should be included in the regression model. Logistic regression was performed to assess predictors of interest in pharmacogenomic testing and familiarity with pharmacogenomics. All statistical analyses were performed using R Statistics software. Subject demographics A total of 61 providers completed the survey across all recruitment venues (Table ); however, given the diversity of distribution channels used for this survey (see Materials and Methods ), it was not possible to determine an exact number of potential subjects that had the opportunity to participate. As such, only an estimate can be provided, which was likely in the range of ~700–1000 subjects. Pharmacists (45.9%, 19/61) and physicians (31.2%, 28/61) accounted for the majority of respondents, with genetic counselors (14.8%, 9/61) and nurses (8.2%, 5/61) comprising the remaining respondents. Experience levels varied widely, with similar numbers of respondents in each experience group. The median number of years of experience was 10 years (interquartile range: 4–17). A wide range of practice settings and specialties were reported. Cardiology providers practicing within academic medical centers accounted for 31% (19/61) of respondents, with the remaining 69% (42/61) practicing in settings, such as outpatient clinics (23%, 14/61), hospitals (20%, 12/61), healthcare systems (12%, 7/61), private practice (5%, 3/61), health maintenance organizations (5%, 3/61), and community pharmacies (5%; 3/61). Most respondents did not provide specialized cardiovascular or genetics services (66%, 40/61) and reported practicing in general cardiology, retail or community pharmacy, or other specialties of medicine (i.e., internal medicine, pediatrics, etc.). The remaining 34% (21/61) worked in advanced heart failure, electrophysiology, interventional cardiology, congenital heart disease, and inherited heart disease. Approximately 50% (29/60) reported involvement in research as a part of their current position. Familiarity and knowledge of pharmacogenomics Most respondents reported receiving varying levels of genetics education (94%, 150/159); however, only 52% (26/50) reported confidence that their genetics education prepared them well to order pharmacogenomic testing (Figure ). Over 90% (54/59) indicated that they had previously heard of the term “pharmacogenomics” prior to taking the survey (Figure ). When asked to indicate the level of familiarity with the field of pharmacogenomics, 66% (39/59) of respondents reported being “somewhat,” “very,” or “extremely familiar,” with genetic counselors being most likely to be familiar with pharmacogenomics ( p < 0.001). All genetic counselors surveyed reported familiarity with pharmacogenomics (9/9, 100%), most pharmacists (19/27, 70%) and physicians (11/18, 61%) reported familiarity, whereas no nurses reported familiarity with pharmacogenomics (0/5, 0%). Pharmacists were slightly more likely (odds ratio [OR]: 2.37, 95% confidence interval [CI]: 1.08, 5.76) to be familiar with pharmacogenomics when compared only to physicians. To assess provider knowledge of pharmacogenomics, an objective assessment was included that asked which metabolizer status is associated with diminished effectiveness of the antiplatelet agent clopidogrel. Of 59 respondents, 22 (37%) correctly identified that the US Food and Drug Administration‐approved drug label for clopidogrel includes a black box warning that CYP2C19 poor metabolizers may experience diminished drug effectiveness (Figure ). Of note, pharmacists identified the correct CYP2C19 metabolizer status more often than other providers (15/22 correct responses, 68%). Experience and comfort with pharmacogenomics Only nine of 59 (15%) respondents had previously ordered, or participated in ordering, a clinical pharmacogenomic test compared to 31 of 59 (52%) of respondents who had previously ordered any clinical genetic test. Of the nine respondents who had previously ordered a pharmacogenomic test, four (44%) were pharmacists, three (33%) were physicians, and the remaining two (22%) were a nurse and a genetic counselor, and most (6/9, 67%) had ordered fewer than 10 in the past 6 months. When asked how easy they found it to interpret the reported test results, only two of nine (22%) indicated it to be easy. To characterize how providers anticipated utilizing pharmacogenomic testing in the future, respondents were asked if they anticipated ordering a pharmacogenomic test in the next 6 months. No respondents indicated that they planned to order a pharmacogenomic test in the next 6 months, and 32% (16/50) were “unsure.” When the time constraint was removed, ~36% (21/59) of respondents indicated that they were “likely” or “very likely” to order a clinical pharmacogenomic test in the future (Figure ). Physicians and pharmacists were most likely to indicate that they would likely order a clinical pharmacogenomic test in the future. Those with confidence in their genetics education were significantly more likely to order a pharmacogenomic test in the future (OR: 4.91, 95% CI: 1.46–19). Over half (34/57) of respondents indicated that they were uncomfortable with the logistics of ordering a clinical pharmacogenomic test (Figure ). Pharmacists reported comfort with test ordering logistics more often than physicians, genetic counselors, and nurses. However, over half (29/57) of respondents indicated that they were comfortable communicating pharmacogenomic test results to patients. When asked what factors would increase comfort communicating results to patients, pharmacogenomics education (20%, 38/195), information about drug selection and dosage on reports (18%, 36/195), and consultation with a PharmD (18%,36/195) were the most cited factors (Figure ). Additional clinical support was commonly cited as a factor that would increase comfort, either by a pharmacist (16%, 32/195) or a genetic counselor (10%, 20/195). Report preferences Respondents were asked to select their preferences for what information they would like to receive on pharmacogenomic test reports. When ordering a single gene pharmacogenomic test, 60% (34/57) wanted to receive information on all potentially impacted medications compared to 33% (19/57) who were only interested to learn about all potentially impacted cardiovascular medications (Figure ). Of note, only 7% (4/57) of respondents wanted to limit their pharmacogenomic test result to only the medication that initiated the test order. Respondents were asked to indicate their pharmacogenomic report preferences under two clinical scenarios. When asked if they would be interested in a pharmacogenomic panel test that included additional genes and all potentially impacted medications if they were considering a single gene pharmacogenomic test, 84% (48/57) of respondents indicated that they would be interested (Figure ). Moreover, 89% (50/56) also indicated that they would be interested in including relevant cardiovascular pharmacogenomic content as a part of a clinical diagnostic panel test that they would order for an inherited cardiovascular disease (Figure ). Clinical implementation All respondents, regardless of past pharmacogenomic testing experience, were asked to identify sources of clinical support and resources that they currently have available and could utilize when ordering and/or interpreting pharmacogenomic tests (Figure ). Notably, 22% (19/87) indicated that they do not currently have access to any clinical support or resources. For those who did report access to clinical resources, the common sources of support were access to pharmacists (29%, 25/87) and genetic counselors (18%, 16/87). When asked about barriers to implementing clinical pharmacogenomic testing (Figure ), a lack of insurance reimbursement for testing was the most commonly cited barrier (21%, 31/154). Other common barriers included: lack of confidence in how results would be integrated (19%, 28/154), lack of clinical support (18%, 28/154), lack of opportunities for education (15%), and lack of perceived benefit/clinical utility (15%, 22/154). In addition, 12% (18/154) of respondents cited concerns for their personal responsibility in documenting and communicating pharmacogenomic results to other providers. Information about current resources utilized to learn more about pharmacogenomics was also measured (Figure ). Although 18% (18/99) of respondents indicated that they do not currently use any resources to learn more about pharmacogenomics, most cited the use of primary literature (26%, 26/99) and colleagues (15%, 15/99) to learn more about pharmacogenomics. Only 14% (14/99) and 11% (11/99) reported using online resources, such as PharmGKB and CPIC, respectively. A total of 61 providers completed the survey across all recruitment venues (Table ); however, given the diversity of distribution channels used for this survey (see Materials and Methods ), it was not possible to determine an exact number of potential subjects that had the opportunity to participate. As such, only an estimate can be provided, which was likely in the range of ~700–1000 subjects. Pharmacists (45.9%, 19/61) and physicians (31.2%, 28/61) accounted for the majority of respondents, with genetic counselors (14.8%, 9/61) and nurses (8.2%, 5/61) comprising the remaining respondents. Experience levels varied widely, with similar numbers of respondents in each experience group. The median number of years of experience was 10 years (interquartile range: 4–17). A wide range of practice settings and specialties were reported. Cardiology providers practicing within academic medical centers accounted for 31% (19/61) of respondents, with the remaining 69% (42/61) practicing in settings, such as outpatient clinics (23%, 14/61), hospitals (20%, 12/61), healthcare systems (12%, 7/61), private practice (5%, 3/61), health maintenance organizations (5%, 3/61), and community pharmacies (5%; 3/61). Most respondents did not provide specialized cardiovascular or genetics services (66%, 40/61) and reported practicing in general cardiology, retail or community pharmacy, or other specialties of medicine (i.e., internal medicine, pediatrics, etc.). The remaining 34% (21/61) worked in advanced heart failure, electrophysiology, interventional cardiology, congenital heart disease, and inherited heart disease. Approximately 50% (29/60) reported involvement in research as a part of their current position. Most respondents reported receiving varying levels of genetics education (94%, 150/159); however, only 52% (26/50) reported confidence that their genetics education prepared them well to order pharmacogenomic testing (Figure ). Over 90% (54/59) indicated that they had previously heard of the term “pharmacogenomics” prior to taking the survey (Figure ). When asked to indicate the level of familiarity with the field of pharmacogenomics, 66% (39/59) of respondents reported being “somewhat,” “very,” or “extremely familiar,” with genetic counselors being most likely to be familiar with pharmacogenomics ( p < 0.001). All genetic counselors surveyed reported familiarity with pharmacogenomics (9/9, 100%), most pharmacists (19/27, 70%) and physicians (11/18, 61%) reported familiarity, whereas no nurses reported familiarity with pharmacogenomics (0/5, 0%). Pharmacists were slightly more likely (odds ratio [OR]: 2.37, 95% confidence interval [CI]: 1.08, 5.76) to be familiar with pharmacogenomics when compared only to physicians. To assess provider knowledge of pharmacogenomics, an objective assessment was included that asked which metabolizer status is associated with diminished effectiveness of the antiplatelet agent clopidogrel. Of 59 respondents, 22 (37%) correctly identified that the US Food and Drug Administration‐approved drug label for clopidogrel includes a black box warning that CYP2C19 poor metabolizers may experience diminished drug effectiveness (Figure ). Of note, pharmacists identified the correct CYP2C19 metabolizer status more often than other providers (15/22 correct responses, 68%). Only nine of 59 (15%) respondents had previously ordered, or participated in ordering, a clinical pharmacogenomic test compared to 31 of 59 (52%) of respondents who had previously ordered any clinical genetic test. Of the nine respondents who had previously ordered a pharmacogenomic test, four (44%) were pharmacists, three (33%) were physicians, and the remaining two (22%) were a nurse and a genetic counselor, and most (6/9, 67%) had ordered fewer than 10 in the past 6 months. When asked how easy they found it to interpret the reported test results, only two of nine (22%) indicated it to be easy. To characterize how providers anticipated utilizing pharmacogenomic testing in the future, respondents were asked if they anticipated ordering a pharmacogenomic test in the next 6 months. No respondents indicated that they planned to order a pharmacogenomic test in the next 6 months, and 32% (16/50) were “unsure.” When the time constraint was removed, ~36% (21/59) of respondents indicated that they were “likely” or “very likely” to order a clinical pharmacogenomic test in the future (Figure ). Physicians and pharmacists were most likely to indicate that they would likely order a clinical pharmacogenomic test in the future. Those with confidence in their genetics education were significantly more likely to order a pharmacogenomic test in the future (OR: 4.91, 95% CI: 1.46–19). Over half (34/57) of respondents indicated that they were uncomfortable with the logistics of ordering a clinical pharmacogenomic test (Figure ). Pharmacists reported comfort with test ordering logistics more often than physicians, genetic counselors, and nurses. However, over half (29/57) of respondents indicated that they were comfortable communicating pharmacogenomic test results to patients. When asked what factors would increase comfort communicating results to patients, pharmacogenomics education (20%, 38/195), information about drug selection and dosage on reports (18%, 36/195), and consultation with a PharmD (18%,36/195) were the most cited factors (Figure ). Additional clinical support was commonly cited as a factor that would increase comfort, either by a pharmacist (16%, 32/195) or a genetic counselor (10%, 20/195). Respondents were asked to select their preferences for what information they would like to receive on pharmacogenomic test reports. When ordering a single gene pharmacogenomic test, 60% (34/57) wanted to receive information on all potentially impacted medications compared to 33% (19/57) who were only interested to learn about all potentially impacted cardiovascular medications (Figure ). Of note, only 7% (4/57) of respondents wanted to limit their pharmacogenomic test result to only the medication that initiated the test order. Respondents were asked to indicate their pharmacogenomic report preferences under two clinical scenarios. When asked if they would be interested in a pharmacogenomic panel test that included additional genes and all potentially impacted medications if they were considering a single gene pharmacogenomic test, 84% (48/57) of respondents indicated that they would be interested (Figure ). Moreover, 89% (50/56) also indicated that they would be interested in including relevant cardiovascular pharmacogenomic content as a part of a clinical diagnostic panel test that they would order for an inherited cardiovascular disease (Figure ). All respondents, regardless of past pharmacogenomic testing experience, were asked to identify sources of clinical support and resources that they currently have available and could utilize when ordering and/or interpreting pharmacogenomic tests (Figure ). Notably, 22% (19/87) indicated that they do not currently have access to any clinical support or resources. For those who did report access to clinical resources, the common sources of support were access to pharmacists (29%, 25/87) and genetic counselors (18%, 16/87). When asked about barriers to implementing clinical pharmacogenomic testing (Figure ), a lack of insurance reimbursement for testing was the most commonly cited barrier (21%, 31/154). Other common barriers included: lack of confidence in how results would be integrated (19%, 28/154), lack of clinical support (18%, 28/154), lack of opportunities for education (15%), and lack of perceived benefit/clinical utility (15%, 22/154). In addition, 12% (18/154) of respondents cited concerns for their personal responsibility in documenting and communicating pharmacogenomic results to other providers. Information about current resources utilized to learn more about pharmacogenomics was also measured (Figure ). Although 18% (18/99) of respondents indicated that they do not currently use any resources to learn more about pharmacogenomics, most cited the use of primary literature (26%, 26/99) and colleagues (15%, 15/99) to learn more about pharmacogenomics. Only 14% (14/99) and 11% (11/99) reported using online resources, such as PharmGKB and CPIC, respectively. Whereas cardiovascular medications comprise a growing proportion of the clinically actionable gene‐drug pairs, most cardiologists are not utilizing this information to guide their clinical practice. However, previous studies , have found that cardiovascular providers have higher levels of knowledge of pharmacogenomics and order pharmacogenomic testing more frequently than other clinicians, presenting an opportunity to bridge an implementation gap. Given the paucity of literature on clinical implementation barriers, panel‐based testing, and reporting preferences among cardiology providers, we aimed to assess these important areas to inform the increasing number of clinical institutions that are considering implementing pharmacogenomics into their cardiovascular services. Cardiology providers in this study reported high levels of familiarity with pharmacogenomics, despite only half of respondents reporting that they felt their genetics education prepared them well to order pharmacogenomic testing, which was generally higher than previously reported among PCPs and other specialists. , However, this level of familiarity with pharmacogenomics has increased in recent years, which could be due to the fact that 50% of respondents had 5 or fewer years of experience and training programs are integrating pharmacogenomics education into their curriculum more frequently. , This contrasts with previous studies, which reported that only 26% of PCPs had confidence in using pharmacogenomic information into prescribing decisions. Interestingly, this high level of self‐reported familiarity was contradicted by the fact that only 33% of respondents correctly identified CYP2C19 poor metabolizers as having a diminished response to clopidogrel. Previous studies have shown that up to 86% of cardiologists correctly identify this gene‐drug association. Lower levels of knowledge of this gene‐drug pair in our study could be due to our study allowing respondents to select “unsure” as a response to this question and including providers other than prescribing physicians, such as nurses and genetic counselors; however, pharmacists identified the correct metabolizer status more often than physicians. These data demonstrate that familiarity with pharmacogenomics among all cardiovascular clinical providers is not isolated to cardiologists, and familiarity with pharmacogenomics may not always translate to real‐world understanding. Only 15% of respondents reported experience ordering a clinical pharmacogenomic test, which was highly consistent with previous research despite this being assessed almost a decade ago. Therefore, there has not been a significant increase in uptake of pharmacogenomic testing in the past 8 years despite increased and ongoing efforts in translational research, education, and the availability of published pharmacogenomic‐guided prescribing recommendations. Although few providers have reported ordering a clinical pharmacogenomics test in the past, 36% of respondents indicated that they are “likely” or “very likely” to order a clinical pharmacogenomics test in the future. This suggests that there could be an increase in pharmacogenomic test ordering in the future, with half of the respondents reporting that they are comfortable discussing pharmacogenomic test results with their patients. As there has not been a consensus in previous research about which providers might be responsible for pharmacogenomic testing and result communication, this suggests that clinical implementation may be most successful among specialists who are confident in their ability to counsel patients on this type of testing. There was extensive interest in pre‐emptive pharmacogenomic testing among the respondents, with the majority showing interest in a pharmacogenomic panel that included all potentially impacted medications regardless of indication for the test. However, providers have previously cited concerns regarding their responsibility to disseminate and manage pharmacogenomic results, which was similarly cited by 12% of our respondents as a reason for not having ordered a pharmacogenomic test in the past. Despite this concern, the strong provider interest in pharmacogenomic panels including all impacted medications could indicate that their preference for expanded testing outweighs this concern, possibly due to their perceived utility in pre‐emptive panel‐based pharmacogenomic testing. Although few respondents having ordered a pharmacogenomic test, 52% had previously ordered a clinical genetic test for one of their patients. Indications for these diagnostic genetic tests included familial hypercholesterolemia, cardiomyopathies, arrhythmias, and other cardiovascular related and non‐cardiovascular related disorders (i.e., inherited kidney diseases and cancer). Many of the commercially available pharmacogenomic tests include medications used to treat these diseases (i.e., statins to treat familial hypercholesterolemia) as well as other cardiovascular medications commonly prescribed in the general population (i.e., warfarin, clopidogrel, and statins). , , Of note, ~90% of survey respondents were interested in including cardiovascular pharmacogenomic content when ordering a clinical diagnostic panel for inherited cardiovascular diseases. This could facilitate a potential area for pharmacogenomic testing implementation, as providers who are already communicating the results from the diagnostic genetic test to their patients could also include an efficient discussion of the pharmacogenomic results during those visits. Regardless of whether respondents had experience ordering pharmacogenomic tests, there were several perceived barriers to clinical implementation, most of which can be addressed by education. The most frequently reported reasons for not ordering a pharmacogenomic test in the past were that providers were uncertain about the clinical value of the test (25%) and did not think it was applicable for their patients (17%), which is consistent with previous studies in which providers have cited a perceived lack of evidence for the clinical utility of testing. It is estimated that 90–99% of the population in the United States carries at least one actionable variant in a well‐established pharmacogenomic gene. , , Educating providers on these general population studies alongside the well‐characterized gene‐drug associations in medicine could minimize this implementation barrier. Resources, such as PharmGKB and CPIC, catalog these gene‐drug associations and publish peer‐reviewed guidelines for pharmacogenomic‐guided medication management. Only a small proportion of survey respondents were aware of these resources and cited using them to learn more about pharmacogenomics, whereas 18% of respondents indicated that they do not currently use any resources to learn more about pharmacogenomics. This is consistent with past surveys, which reported ~15% of respondents have not consulted any resources to learn more about pharmacogenomics. Respondents highlighted that education about pharmacogenomics and information on drug selection or dosage would increase their comfort communicating pharmacogenomic test results to patients. This information is accessible by PharmGKB and CPIC; therefore, wide integration of these two resources into clinical practice could serve to improve provider knowledge on the clinical utility of implementing pharmacogenomic testing. The second most common reason that providers cited for not having ordered a pharmacogenomic test was that they did not know what test to order. This is consistent with most of the respondents' self‐reported lack of comfort with the logistics of ordering pharmacogenomic tests. Despite this, they reported high levels of comfort communicating results with patients. This highlights an area for targeted education about the process of test ordering, as the limiting factor does not seem to be education on pharmacogenomics in general, but rather knowledge of laboratories and the testing workflows that are available. One possible model for implementation that could minimize this barrier is the utilization of panel‐based testing which can reduce the provider‐burden of identifying single‐gene tests. This likely would be of interest to healthcare providers as the majority (84%) of our respondents would be interested in a pharmacogenomics panel. Other cited barriers to clinical implementation were insurance reimbursement, lack of confidence in how results would be integrated, and lack of clinical support within practice. This demonstrates additional needs of clinicians and how pharmacogenomics education could be targeted to support clinical implementation. As more medical schools, genetic counseling programs, pharmacy schools, and other clinician training programs integrate pharmacogenomics into their curricula, , it is likely that awareness and education on pharmacogenomics will improve over time. However, across provider types, respondents who underwent training more recently did not have significantly higher levels of self‐reported familiarity with pharmacogenomics or answer the knowledge assessment question correctly more often. This could indicate that the education currently provided in these training programs is not adequately targeting the needs of clinicians in practice. Limitations of this study include a modest sample size, which did not equally represent all included provider types. For instance, pharmacists were over‐represented and there may be other relevant cardiology provider types (e.g., physician assistants) that were not included. Another limitation of our study was that survey recruitment was limited to providers in the state of California; however, this may not be generalizable to all cardiology providers in the United States or in other countries. Moreover, with a participation rate of less than 10%, it is important to note that sampling bias could have been introduced by participating providers who are more interested in pharmacogenomics. Future research could focus on assessing cardiology providers across the United States to understand if there are any regional differences in pharmacogenomics education or experience. Additionally, future studies could examine larger cohorts of providers who have experience ordering pharmacogenomic tests and which educational topics (i.e., logistics, navigating insurance, clinical utility, and report interpretation) were most predictive of ordering patterns and/or the most in need of additional training. In conclusion, this study builds off the previously reported literature around provider opinions on the field of pharmacogenomics by focusing on the current knowledge and attitudes on implementing clinical pharmacogenomic testing across a diverse range of cardiology providers, including their perspectives on panel‐based testing and reporting preferences. Taken together, these novel results indicate that cardiology providers currently have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they have high levels of interest in implementing panel‐based pharmacogenomic testing with broad reporting of potentially impacted medications, and pairing pharmacogenomics with other genetic tests, such as diagnostic panels for cardiovascular diseases. Cardiovascular providers also have a high level of confidence and comfort with communicating pharmacogenomic test results to their patients. Importantly, this study also identifies critical educational needs for cardiology providers that would likely result in facilitating future clinical implementation programs, including the opportunity to measure the effectiveness of educational interventions using this and/or other published provider surveys on implementing pharmacogenomics. C.R., M.C., M.E.G., K.M., T.E.K., E.A., H.N., M.T.W., and S.A.S. wrote the manuscript. C.R., M.C., M.E.G., K.M., T.E.K., E.A., M.T.W., and S.A.S. designed the research. C.R. performed the research. C.R., H.N., and S.A.S. analyzed data. This study was supported by Stanford University School of Medicine, Department of Genetics, Stanford, CA. M.E.G. is currently employed by and has equity interest in Color Health; the remaining authors declared no competing interests with this work. Data S1. |
Role of the cGAS-STING pathway in radiotherapy for non-small cell lung cancer | 5048d16a-d132-4d8e-a826-0684d58a682c | 10478265 | Internal Medicine[mh] | Lung cancer is one of the most common cancers and the leading cause of cancer-related deaths worldwide . Among the common lung cancer types 85% of clinical cases are non-small cell lung cancer (NSCLC) ,which has a low overall cure rate and survival rate . Radiotherapy (RT), as a traditional treatment, is applied to more than 50% of patients with malignant tumors, and its principle of action is to directly cause fatal DNA damage in irradiated cells, or indirectly induce DNA damage by producing reactive oxygen species . RT induces DNA damage, resulting in the formation of micronuclei containing chromatin and dsDNA in the cytosol, and the nuclear envelope of micronuclei is easily ruptured due to the lack of a stable nuclear lamina, exposing dsDNA to the cytoplasm and becoming the trigger point of the innate immune response, exerting anti-tumor effects . Radiation therapy plays an important role in the treatment of non-small cell lung cancer, and inevitable lung tissue will be irradiated at a certain dose during the treatment, causing different degrees of radiation-induced lung injury, with an incidence of about 5–20%, and reducing the local control rate of the tumor to a certain extent, becoming an important limiting factor in the dose of radiotherapy . Cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS)/interferon stimulating factors (STING) signaling pathway, as an important part of the innate immune system, plays an important role in maintaining the homeostasis of the body. Blocking the cGAS-STING pathway inhibited inflammatory response and reduced tissue damage, while activating the cGAS-STING pathway promoted antiviral and anti-tumor effects. Understanding the regulatory mechanism of cGAS-STING pathway links can use existing drugs or new drugs developed to intervene in the cGAS-STING pathway and provide new ideas and methods for the treatment of clinically relevant diseases. The purpose of this review is to discuss the immune activation mechanism of cGAS-STING in lung cancer radiotherapy and the mechanism of lung injury and to discuss new therapeutic methods.
The cGAS-STING signaling pathway is an important cytosolic DNA sensing pathway in vivo, which induces the expression of type I IFNs and affects the immune response of the body, and plays an important role in regulating pathogen infection, tumor immunity,and autoimmune diseases. cGAS has a highly conserved nucleotidyltransferase domain and can detect double-strands DNA (dsDNA) released into the cytosol. The Binding of cGAS and dsDNA is length-dependent and independent of DNA sequences . dsDNA binds to cGAS as a dimer in a 2:2 manner, causing a conformational change in the active site of cGAS , which in turn promotes ATP and GTP synthesis of the second messenger cyclic guanylin acid-adenylate (cGAMP) . Synthetic cGAMP binds to STING molecules localized as homodimers on the ER , resulting in conformational changes in STING to form STING tetramers and higher-order oligomers. This conformational change induces activation of STING, which shifts to a more closed conformation and translocates to the Golgi through the ER-Golgi intermediate compartment . Structural studies have shown that two cysteine residues on STING protein are palmitoylated in the Golgi apparatus and recruit and activate TANK binding kinase-1 (TBK1) in the Golgi apparatus . Activation of TBK1 in turn transphosphorylates the C-terminal domain of STING, thereby recruiting interferon regulatory factor 3 (IRF3) . Phosphorylated IRF3 dimerizes and translocates into the nucleus to activate transcription of genes encoding type I IFNs 1 7. STING can also simultaneously activate IκB kinases (IKK) to mediate the transcription of interleukin-6 (IL-6), tumor necrosis factor (TNF), and inflammatory cytokines such as type I IFN activated by nuclear factor kappa-B (NF-κB) . It plays an immunoregulatory role and affects the body’s viral defense, inflammation, and cancer treatment.(Fig. ).
DNA, as the blueprint of life, is regulated by DNA damage response or DNA damage repair system (DDR) to ensure the integrity of the genome. When DNA is damaged, the DDR pathway causes cell cycle arrest and repairs DNA, ensuring that cell cycle cycles occur orderly; however, when damage cannot be effectively repaired, cells enter senescence; if DNA is severely damaged, it directly leads to apoptosis . Radiotherapy (RT) is used as a traditional treatment in more than 50% of patients with malignant tumors, and its principle of action is to directly cause fatal DNA damage in irradiated cells, or indirectly induce DNA damage by producing reactive oxygen species ; its types of induced DNA damage include base mutations, single-strand breaks (SSBs), and double-strand breaks (DSBs) . Radiation induction regulates the tumor microenvironment and promotes the recruitment and infiltration of immune cells. Radiation therapy (RT) can cause DNA damage in tumor cells , leading to chromosomal instability (CIN). CIN is a characteristic feature of cancer and it will induce micronuclei formation .Human mtDNA’s nucleotide sequence was discovered in 1981 to be a 16 569 bp double-stranded circular molecule that codes for 37 genes that can express a number of important proteins involved in oxidative phosphorylation and essential for cellular energy metabolism . The permeability of the inner and outer mitochondrial membranes varies when cancer cells experience oxidative stress and mitochondrial malfunction, and mitochondrial DNA can exit the mitochondrial outer membrane into the cytosol by mitochondrial membrane permeability transition holes or BAX/BAK-dependent permeabilization of the outer mitochondrial membrane. Inflammation is brought on by mtDNA translocation into the cytoplasm, cGAS recognition and binding, and subsequent activation of downstream immune pathways . In a model of cisplatin-induced acute kidney injury, cisplatin caused mtDNA leakage into the cytoplasm through the mitochondrial outer membrane BAX/BAK pore, activated the cGAS-STING signaling pathway, and resulted in inflammation and acute kidney injury. By inhibiting STING, however, the cisplatin-induced renal inflammation could be reduced . dsDNA from micronuclei as well as DNA damage induction will be recognized by the cytoplasmic DNA sensor cGAS, thereby activating the cGAS-STING signaling pathway, shaping innate immunity in a type I IFN-dependent manner, promoting adaptive immune responses, and thus effectively anti-tumor . Cancer cells are irradiated and exposed to tumor-specific antigens, which make them visible for immune surveillance and promote the activation of cytotoxic T cells. In the absence of STING in the host, the amount of IFN-β induced in the tumor decreased after irradiation. Consistent with the immunogenicity of IFNs, the radiation effect was attenuated in STING deficient mice compared with controls, indicating that STING dependent cytosolic DNA sensing plays a critical role in the radiation effect in vivo. Generally, tumor cells escape immune response through the inactivation of the STING signaling pathway. When the cGAS-STING signaling pathway in tumor cells is activated, it induces expression of cytokines such as IL-6, TNF, and type I IFN, leading to tumor cell death or apoptosis, releases dsDNA, and other tumor-derived antigens, activates dendritic cells (DCs), and then initiates anti-tumor immunity. In the tumor microenvironment, tumor-derived DNA can be taken up by DCs through unknown mechanisms, further triggering stronger adaptive anti-tumor immune response . Tumor cells enhanced cross-antigen presentation by DCs after irradiation, whereas DCs lacking STING was unable to cross-infect primary CD + 8 T cells . Compared with irradiation alone, cGAMP combined with irradiation effectively reduced tumor burden in vivo, indicating that cGAMP treatment enhanced radiotherapy efficacy. DNA produced by tumor cells after radiotherapy promotes the anti-tumor effect of radiotherapy by triggering the cGAS/STING pathway to enhance T cell responses in mice to induce anticancer immunity in a STINE-dependent manner . However, whether radiotherapy can induce cGAS-STING mediated anti-tumor effect is related to the applied radiation dose, too high dose will affect the survival of immune cells in the tumor microenvironment, but also up-regulate the negative regulators of the DNA sensing pathway, inhibit cGAS-STING pathway activation, and then promote immunosuppression, while lower dose can effectively activate the cGAS/STING pathway. Vanpouille-Box et al. found that Trex1 is a DNA exonuclease that acts as an upstream regulator of RT-driven anti-tumor immunity, and the DNA exonuclease Trex1 is produced in different cancer cells after irradiation at doses of 12 to 18 Gy, mainly by degrading cytosolic DNA, resulting in a decrease in dsDNA, a ligand required to activate cGAS/STING, and inhibiting anti-tumor immune effects .Repeated irradiation at doses that do not induce Trex1 promotes IFN-β production, thereby recruiting and activating Batf3-dependent DCs. This effect is essential for priming of CD + 8 T cells that mediate systemic tumor rejection. Radiotherapy leads to dsDNA accumulation in cancer cells when Trex1 is not activated type I IFNs are activated through the cGAS/STING pathway, downstream recruitment of DCs, and activation of CD + 8 T cells or anti-PD-1 antibodies to initiate tumor rejection. In tumors treated with irradiation doses exceeding the Trex1 induction threshold, clearance of dsDNA from cancer cell sol hinders IFN-β release in cancer cells, resulting in a reduced recruitment of DCs and insufficient activation of CD + 8 T cells leading to diminished local tumor regression . Jason J. found unfavorable local tumor response was linked to overexpression of the DNase III (TREX1) exonuclease .RT acts as an inducer of antitumor immune responses, in part, depending on the type I IFN secretion caused by activation of the cGAS/STING signaling pathway and the interaction between immune cells. Exosomes are membrane microvesicles that range in size from 30 to 100 nm and are released by all types of cells. They offer a highly developed method of local and distant intercellular communication . Julie M showed that irradiated mouse breast cancer cells (RT-TEX) create tumor-derived exosomes (TEX) that transmit dsDNA to DCs and cause them to upregulate costimulatory molecules and STING-dependent IFN-I activation .Therefore, exploring the molecular mechanisms affecting the activation of this pathway will provide new targets for enhancing RT-induced anti-tumor immunity.(Fig. ).
Radiation therapy is one of the important treatment methods for thoracic malignant tumors. During the treatment, inevitable lung tissues will be irradiated with a certain dose , which causes different degrees of radiation-induced lung injury, with early manifestations of radiation pneumonitis and radiation-induced pulmonary fibrosis, thus making it difficult for the chest irradiation dose routinely used in clinical practice to reach the dose required for radical resection of tumors, and it is also difficult to further improve the local tumor control rate in patients with thoracic tumors, especially inoperable non-small cell lung cancer. Radiation-induced lung injury occurs in 13–37% of patients receiving radiotherapy for lung cancer , and with the substantial progress in the technology level and equipment of radiotherapy in recent years, the incidence of R ILI, although decreasing, is still higher than 15% , and the mortality rate is as high as 4% . It is an important dose-limiting factor in thoracic radiotherapy and affects the quality of life of patients. High doses of ionizing radiation are well-known to cause DNA double-strand breaks . DNA damage leads to oxidative stress, vascular damage, and inflammation. Pneumonia develops within hours or days of high-dose irradiation and is associated with increased capillary permeability and accumulation of inflammatory cells in the lung . The recruited inflammatory cells secrete profibrotic cytokines to activate resident fibroblasts, ultimately leading to excessive collagen production and deposition in the interstitial space of the lung. Some major signaling pathways have been identified that are associated with the amplification of inflammatory cytokine cascades, with NF-κB playing an important role in the regulation of gene expression of various inflammatory cytokines . NF-κB is an important transcription factor widely present in eukaryotic cells, which can participate in the transcriptional regulation of a variety of genes and is closely related to important physiological and pathological processes such as immune response, inflammatory response, as well as cell proliferation, differentiation, and apoptosis . NF -κB binds to its inhibitor protein IκB at rest and is inactive . When cells are stimulated by external stimuli, such as oxidative stress, infection, or physicochemical stimuli, they can activate the transcriptional activity of NF-κB and promote the acidification and degradation of IκB, thereby releasing NF-κB into the nucleus and binding to the κB site of the target gene, rapidly inducing target gene transcription and up-regulating the expression of various biomacromolecules, including inflammatory cytokines, chemokines, and apoptosis-related factors. Among them, inflammatory factors such as TNF -α and I L-1β can also up-regulate NF-κB transcriptional activity, thus forming positive feedback and continuously expanding the stimulation signal .The continuous expression and accumulation of these inflammatory factors can cause damage to tissue cells. Studies have shown that nuclear factor-κB inflammation-related pathways and cytokines mainly mediate inflammatory responses such as tumor necrosis factor TNF -α, interleukin − 1, and interleukin − 6 play an important role in the initiation and promotion of radiation-induced lung injury. NF-κB is continuously activated throughout radiation-induced lung injury, which may be one of the causes of persistent chronic inflammation . NF-κB is a major switch that regulates the body’s inflammatory response. When the body is irradiated, intracellular DNA damages and activates the cGAS/STING pathway, phosphorylates NF-κB to inhibit protein kinase, so that NF-κB inhibitory protein IκB is ubiquitinated and degraded, thus activating NF-κB into the nucleus to initiate the release of a variety of inflammatory factors. Activation of inflammatory factors in the lung stimulates the phenotypic transformation of lung epithelial cells into intercellular cells, producing large amounts of extracellular matrix proteins that accumulate and deposit in the pulmonary interstitium and promote the formation of pulmonary fibrosis . Therefore, reducing lung fibrosis and lung inflammation effectively protects against RILI. Because NF-κB factor is a heterodimer composed of two peptides, p 50 and p65, and only the C -terminus of p 65 protein contains a transcriptional activation region that can act directly on targeted genes to activate transcription, changes in NF-κB activity can currently be evaluated by detecting the expression of p 65. Related studies have shown that 3,3 ′-diindolylmethane (DIM) can inhibit the NF-κB pathway, and in mouse models, DIM can effectively ameliorate RILI-induced pulmonary fibrosis and lung inflammation while reducing the number of inflammatory cells in BALF as shown by H E staining HE staining and Masson staining . Savita et al. showed that Quercetin-3-Rutinoside provides radioprotection to the lung by regulating NF-κB/TGF-β1 signaling, scavenging free radicals, preventing perivascular invasion, and prolonging the inflammatory cascade, which may otherwise lead to chronic radiation fibrosis. Inhibition of the cGAS/STING/NF-κB pathway is therefore a potential target for the treatment of radiation-induced lung injury.
Immune checkpoint inhibitors mainly include PD-1/PD-L1 antibody and CTLA-4 antibody. Theoretically, ICI therapy can re-edit the tumor immune microenvironment to induce tumor regression, and the activity of PD-1/PD-L1 immune checkpoint inhibitors varies in different cancers, and many studies have demonstrated that they confer resistance in multiple cancer types. The effectiveness of immune checkpoint inhibitors depends on innate antitumor immunity, particularly the production of tumor antigens and tumor-specific cytotoxic T cells (CTLs). However, most cancer patients remain unresponsive to checkpoint inhibitor therapy, most of which are due to their inability to mount sufficient antitumor immunity. Numerous studies have shown weak responses to multiple immune checkpoints in STING null mice, including PD-1, PD-L1, CTLA4, and CD47 . STING activators are ideal sensitizers for enhancing anti-PD-1/PD-L1 therapy, and STING agonists can significantly enhance cytotoxic T cell infiltration in tumor cells . Immune checkpoints negatively regulate T cells in the immune system, and immune checkpoint blockade therapy has shown good efficacy in tumors, while the STING signaling pathway is essential for the anti-tumor effect of immune checkpoint blockade therapy in mice. In wild-type mouse melanoma models, intramuscular injection of cGAMP away from the tumor site significantly enhanced the therapeutic effect of immune checkpoint blockade, and the combination of cGAMP and PD-L1 antibody effectively inhibited tumor growth in B16 melanoma mice45. When cGAS, STING is absent, responses to immunotherapies such as immunosuppressive molecule blockade are weak, and the combination of STING agonists and PD-1 blockers shows stronger antitumor efficacy, and when combined, tumor models that do not respond well to immune checkpoint blockade become sensitized . Radiotherapy has gained broad public consensus as an adjuvant to activate immune responses. Jason R. Baird et al. demonstrated synergistic local and distant tumor control when radiation therapy was combined with a novel STING ligand in a mouse model of pancreatic cancer . Radiation therapy can act synergistically with PD-1 inhibitors to enhance their respective antitumor activity, particularly in patients with advanced tumors . NF-κB control plays a crucial role in immune-inflammatory responses, tumorigenesis, and development/radioresistance. Inhibition of the canonical NF-κB pathway has been shown to attenuate radiation efficacy, whereas non-canonical NF-κB deficiency promotes radiation-induced antitumor immunity . Mechanistic studies have shown that non-canonical NF-κB signaling in dendritic cell DCs is associated with activation of the DNA-reception-mediated STING pathway . It has been shown that modulation of type I interferons by application of the NF-κB2 competitive inhibitor S N52 facilitated the therapeutic effect of IR, but tumors receiving combination therapy were not completely eliminated. Sustained IFN-I signaling induces immunosuppressive mechanisms, including PD-L1 expression on DCs and other myeloid cells and PD-1 expression on T cells, which leads to CD8 + T cell depletion . Tumor-bearing mice were treated with anti-PD-L1 agents following SN52 and IR treatment. PD-L1 blockade enhanced the therapeutic effect of the SN52 + IR combination and led to tumor rejection. To investigate whether this combined treatment could generate long-lasting protective T cell immunity, tumor-free mice were rechallenged with high-dose MC38 tumor cells on the contralateral side. A few weeks later, no palpable tumors were detected in treated mice. These findings reveal that combining IR with manipulation of the STING-IFN pathway and immune checkpoint inhibition can better activate innate immunity and reduce immunosuppression, and may provide a novel approach for the treatment of tumors, that is, inhibition of non-canonical NF-kB plus antiPD-L1 antibody drugs .
Activation of the cGAS-STING pathway in lung cancer radiotherapy has shown great antitumor potential by promoting the secretion of type I IFNs, significantly increasing the infiltration of CD + 8 T cells and effectively stimulating anti-tumor immune responses in the body. When exosomes deliver dsDNA from radiation-damaged cancer cells to DCs, type I interferon (IFN-I) is activated via the cGAS/STING pathway.RT-TEX serve as transmitters of the molecular alterations that occurred in radioactively treated cancer cells. Adjuvants that activated DCs and might trigger protective antitumor T-cell responses were conveyed by RT-TEX together with tumor antigens.When the STING signaling pathway is used for anti-tumor therapy, therapeutic window and toxic side effects should be considered, and excessive activation of the pathway is associated with the occurrence of related injuries. Although the combination of radiation and immunotherapy has proven effective in preclinical studies, the future application of this combination remains challenging. Optimization of radiation dose and time and identification of potential biomarkers can further enhance the effectiveness of this unique combination, and a better understanding of how the cGAS/STING pathway mediates anti-tumor effects will contribute to the use of STING agonists in cancer therapy and design better treatment regimens.
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Combining Cortical Voltage Imaging and Hippocampal Electrophysiology for Investigating Global, Multi-Timescale Activity Interactions in the Brain | 00c6a29e-f4a5-462f-b5ba-dee2f39737fd | 9224488 | Physiology[mh] | Hippocampal–cortical interactions have been widely studied with the aim of understanding their role in supporting memory . Yet, most studies have focused on the interplay between the hippocampus and selected cortical areas with major anatomical connections to the hippocampus, such as the entorhinal or the medial prefrontal cortex . Less is known about the interrelation between hippocampal activity and activity phenomena spanning large portions of cortical space . Cortex-wide activity is classically studied with imaging techniques that rely on indirect correlates of neural activity, such as the blood-oxygen-level-dependent (BOLD) or intracellular calcium signals, whereas most of our knowledge of the hippocampus comes from microelectrode recordings . While classical imaging methods allow for excellent spatial coverage, they suffer from limited spatial resolution. Microelectrode techniques, on the other hand, provide recordings with excellent temporal resolution but limited spatial information . In particular, conventional widefield imaging using genetically encoded calcium indicators (GECIs) presents a significant temporal discrepancy in activity when compared with electrophysiology, due to the distinct nature of the recorded signals . Cortical widefield voltage imaging using genetically encoded voltage indicators (GEVIs) in head-fixed mice provides a large-scale view on cortical activity with both high spatial and high temporal resolution, and it can be combined with electrode-based electrophysiology . Here we describe the combination of cortical voltage imaging with hippocampal electrode recordings to simultaneously monitor activity both from the cortex and the hippocampus during rest and traditional behavioral tasks. Specifically, we give examples of how this combination can contribute to questions focused on sensory-hippocampal integration and hippocampal–cortical interaction.
2.1. Simultaneous Cortical Voltage Imaging with Hippocampal Electrophysiology To investigate the interactions between the hippocampus and the cortex, here we used cortex-wide voltage imaging in combination with electrophysiological recording using a silicon probe in the hippocampal CA1 . We used transgenic mice that express the transgene for chimeric VSFP Butterfly Y/R (chiVSFP Butterfly) under the tetO promoter. Crossing with CaMK2A-tTA mice resulted in chiVSFP Butterfly expression in neocortical and hippocampal pyramidal neurons . By replacing a segment of the Ciona intestinalis voltage sensing domain by a homologous portion of the fast activating and deactivating Kv3.1 potassium channel, chiVSFP Butterfly was developed from earlier VSFPs . This modification accelerated the GEVI response dynamics, with chiVSFP Butterfly readily following membrane voltage oscillations at frequencies up to at least 200 Hz. In contrast to monochromatic GEVIs, chiVSFP Butterfly reports membrane voltage changes in two fluorescence bands with opposite fluorescence changes. This allows for ratiometric measurements that facilitate correction for hemodynamic and pH-related confounds inherent to monochromatic (single-wavelength) GEVI imaging . First, we recorded two vital states, in vivo (in resting state) and ex vivo (following terminal euthanasia) from the same mouse to compare the signal-to-noise ratio. As expected, in the ex vivo condition, the neocortex did not show any activity, whereas in the living brain spontaneous fluctuations were observed in the neocortex ( A). As was also expected, the probabilistic distribution of cortical transients in the in vivo state adheres to the power law, whereas that of the ex vivo state is reflective of noise. Similarly, in the in vivo state, in the hippocampal electrophysiological recordings that were synchronized to cortical voltage imaging, spontaneous sharp-wave ripple (SWR) events can be observed in the hippocampal pyramidal layer which accompanies the cortical transients ( A). In the ex vivo state, there is an absence of hippocampal activity, as expected. The impact of movements in the active behavioral state causes a strong modulation in the cortex-wide neural activity . In the rodent hippocampus, the theta frequency band (5–10 Hz) is a hallmark of active states such as walking, running and sniffing. In line with previous studies , we found that cortical activity in multiple brain areas increased during bouts of treadmill running. Interestingly, in coexistence with hippocampal theta, cortical activity, mostly in the primary motor cortex (M1), seems to be more tightly related to running ( C). When correlating hippocampal theta power with the cortical activity, we also found M1 activity preceding episodes of increased hippocampal theta oscillation ( D). 2.2. Layer-Specific Hippocampal Signal during Integrative Visual Information Process In rodents, eye movements have also been linked to spatial navigation processes . Visual information is crucial for spatial navigation, where instantaneous visual input constantly updates egocentric and allocentric spatial information, and gaze direction is a vital input to that computation. Here, we show that stimulus-evoked voltage activity spreads from the visual cortex to higher cortical areas such as the retrosplenial, cingulate and parietal cortices ( A,B). Additionally, we show that combining eye-tracking with hippocampal probe recordings allows the investigation of hippocampal layer-specific activity associated with eye saccade movements ( C). Interestingly, we specifically observed an emergence of gamma-band activity in the stratum lacunosum moleculare following the saccade movement. Additionally, this modulation seems to be different across layers, which suggests that the saccade movement of the eye associates with local circuits within the hippocampus. Finally, when correlating gamma-band activity in the stratum lacunosum moleculare with the imaged cortical activity, we observed a correlation between a set of medial to lateral areas (parietal, primary and secondary lateral visual cortices; primary auditory cortex) that precedes medium gamma oscillation in the hippocampal CA1 ( D). During episodes of medium gamma oscillations, this correlation seems to be centered on more medial areas (primary and secondary motor, sensory and retrosplenial cortices), which may be related to the locomotion of the animal. 2.3. Hippocampal Neuronal Interrelation with Cortical Modules The hippocampus has several efferent and afferent projections connecting with different brain regions including the cortex, and hippocampal-cortical communication is crucial for processes like archiving memory traces from short-term cortical representations into long-term hippocampal storage . Combining cortical voltage imaging with hippocampal silicon probe recordings thus provides a unique opportunity for studying this connection in vivo. Here, we used 16-channel silicon probes to detect hippocampal CA1 activity ( A) in awake, head-fixed animals that have been implanted with a transcranial window for cortical voltage imaging. We detected multiple neurons with distinct waveforms ( B). Next, we computed spike-triggered averages of the neocortical activity associated with hippocampal neuron spiking activity, and observed different cortical maps associated with the firing activity from different neurons from the CA1 pyramidal layer ( C). Here, we demonstrate that this combined approach offers the potential to examine hippocampal-cortical associations in detail. 2.4. Cortical Microstimulation and Hippocampal Electrophysiology Next, we demonstrate the technical feasibility of observing both cortical voltage activity and hippocampal electrophysiological activity in response to cortical microstimulation in vivo. To this end, we electrically stimulated the retrosplenial (RS) and somato-sensory (SS) cortices individually with varying stimulation intensities (20, 50, 100 and 200 µA), and monitored how these two cortical structures interact with both the rest of the cortical hemisphere and with hippocampal oscillations at different frequencies in a resting-state mouse ( A). Following RS or SS stimulations at 200 µA, we observed a stimulated area displaying an instantaneous burst of activity followed by a spreading hyperpolarization lasting for about one second in the cortical imaging data ( B). Looking at stimulation effects on the hippocampal spectral activity at different intensities (20, 50, 100 and 200 µA), we found that RS stimulation (suppression) caused an interference on the hippocampal LFP (mostly at frequencies between 5 and 40 Hz) ( C). This hippocampal oscillatory interference is proportional to the size of the current (and consequently RS suppression) induced in the RS area ( D). Conversely, SS stimulation did not show significant differences in the hippocampal LFP (repeated-measures ANOVA; N = 50 stimuli for each condition). Combining cortical imaging, cortical microstimulations and hippocampal LFP, our observations suggest that a causal relationship may exist between the retrosplenial cortex and hippocampal CA1, but further investigation is needed to establish if this is due to cortical inputs into the hippocampus, or due to antidromic activation and the suppression of hippocampal afferents in the retrosplenial cortex.
To investigate the interactions between the hippocampus and the cortex, here we used cortex-wide voltage imaging in combination with electrophysiological recording using a silicon probe in the hippocampal CA1 . We used transgenic mice that express the transgene for chimeric VSFP Butterfly Y/R (chiVSFP Butterfly) under the tetO promoter. Crossing with CaMK2A-tTA mice resulted in chiVSFP Butterfly expression in neocortical and hippocampal pyramidal neurons . By replacing a segment of the Ciona intestinalis voltage sensing domain by a homologous portion of the fast activating and deactivating Kv3.1 potassium channel, chiVSFP Butterfly was developed from earlier VSFPs . This modification accelerated the GEVI response dynamics, with chiVSFP Butterfly readily following membrane voltage oscillations at frequencies up to at least 200 Hz. In contrast to monochromatic GEVIs, chiVSFP Butterfly reports membrane voltage changes in two fluorescence bands with opposite fluorescence changes. This allows for ratiometric measurements that facilitate correction for hemodynamic and pH-related confounds inherent to monochromatic (single-wavelength) GEVI imaging . First, we recorded two vital states, in vivo (in resting state) and ex vivo (following terminal euthanasia) from the same mouse to compare the signal-to-noise ratio. As expected, in the ex vivo condition, the neocortex did not show any activity, whereas in the living brain spontaneous fluctuations were observed in the neocortex ( A). As was also expected, the probabilistic distribution of cortical transients in the in vivo state adheres to the power law, whereas that of the ex vivo state is reflective of noise. Similarly, in the in vivo state, in the hippocampal electrophysiological recordings that were synchronized to cortical voltage imaging, spontaneous sharp-wave ripple (SWR) events can be observed in the hippocampal pyramidal layer which accompanies the cortical transients ( A). In the ex vivo state, there is an absence of hippocampal activity, as expected. The impact of movements in the active behavioral state causes a strong modulation in the cortex-wide neural activity . In the rodent hippocampus, the theta frequency band (5–10 Hz) is a hallmark of active states such as walking, running and sniffing. In line with previous studies , we found that cortical activity in multiple brain areas increased during bouts of treadmill running. Interestingly, in coexistence with hippocampal theta, cortical activity, mostly in the primary motor cortex (M1), seems to be more tightly related to running ( C). When correlating hippocampal theta power with the cortical activity, we also found M1 activity preceding episodes of increased hippocampal theta oscillation ( D).
In rodents, eye movements have also been linked to spatial navigation processes . Visual information is crucial for spatial navigation, where instantaneous visual input constantly updates egocentric and allocentric spatial information, and gaze direction is a vital input to that computation. Here, we show that stimulus-evoked voltage activity spreads from the visual cortex to higher cortical areas such as the retrosplenial, cingulate and parietal cortices ( A,B). Additionally, we show that combining eye-tracking with hippocampal probe recordings allows the investigation of hippocampal layer-specific activity associated with eye saccade movements ( C). Interestingly, we specifically observed an emergence of gamma-band activity in the stratum lacunosum moleculare following the saccade movement. Additionally, this modulation seems to be different across layers, which suggests that the saccade movement of the eye associates with local circuits within the hippocampus. Finally, when correlating gamma-band activity in the stratum lacunosum moleculare with the imaged cortical activity, we observed a correlation between a set of medial to lateral areas (parietal, primary and secondary lateral visual cortices; primary auditory cortex) that precedes medium gamma oscillation in the hippocampal CA1 ( D). During episodes of medium gamma oscillations, this correlation seems to be centered on more medial areas (primary and secondary motor, sensory and retrosplenial cortices), which may be related to the locomotion of the animal.
The hippocampus has several efferent and afferent projections connecting with different brain regions including the cortex, and hippocampal-cortical communication is crucial for processes like archiving memory traces from short-term cortical representations into long-term hippocampal storage . Combining cortical voltage imaging with hippocampal silicon probe recordings thus provides a unique opportunity for studying this connection in vivo. Here, we used 16-channel silicon probes to detect hippocampal CA1 activity ( A) in awake, head-fixed animals that have been implanted with a transcranial window for cortical voltage imaging. We detected multiple neurons with distinct waveforms ( B). Next, we computed spike-triggered averages of the neocortical activity associated with hippocampal neuron spiking activity, and observed different cortical maps associated with the firing activity from different neurons from the CA1 pyramidal layer ( C). Here, we demonstrate that this combined approach offers the potential to examine hippocampal-cortical associations in detail.
Next, we demonstrate the technical feasibility of observing both cortical voltage activity and hippocampal electrophysiological activity in response to cortical microstimulation in vivo. To this end, we electrically stimulated the retrosplenial (RS) and somato-sensory (SS) cortices individually with varying stimulation intensities (20, 50, 100 and 200 µA), and monitored how these two cortical structures interact with both the rest of the cortical hemisphere and with hippocampal oscillations at different frequencies in a resting-state mouse ( A). Following RS or SS stimulations at 200 µA, we observed a stimulated area displaying an instantaneous burst of activity followed by a spreading hyperpolarization lasting for about one second in the cortical imaging data ( B). Looking at stimulation effects on the hippocampal spectral activity at different intensities (20, 50, 100 and 200 µA), we found that RS stimulation (suppression) caused an interference on the hippocampal LFP (mostly at frequencies between 5 and 40 Hz) ( C). This hippocampal oscillatory interference is proportional to the size of the current (and consequently RS suppression) induced in the RS area ( D). Conversely, SS stimulation did not show significant differences in the hippocampal LFP (repeated-measures ANOVA; N = 50 stimuli for each condition). Combining cortical imaging, cortical microstimulations and hippocampal LFP, our observations suggest that a causal relationship may exist between the retrosplenial cortex and hippocampal CA1, but further investigation is needed to establish if this is due to cortical inputs into the hippocampus, or due to antidromic activation and the suppression of hippocampal afferents in the retrosplenial cortex.
A common caveat of many system-level studies is the assumption that specific cognitive responses only involve specific brain areas. This is because in vivo recordings are commonly designed to target only a few areas, leaving the contributions of the rest of the brain aside. Here, we advocate that widefield voltage imaging can be a valuable approach for observing multiple cortical areas simultaneously in awake, behaving animals. Compared to indicators of other brain activity proxies, such as calcium and glutamate, voltage activity has a faster temporal resolution, similar to that of electrophysiology, which allows causal analysis in combination with electrophysiological data. It is important to emphasize that the combination of electrophysiology with cortical voltage imaging is flexible and may be adapted to different scientific questions. Here, we demonstrated the feasibility of combining cortical voltage imaging with hippocampal electrophysiology to start yielding new insights into the hippocampal –cortical relationship associated with visual processing. Visual information plays an important role in spatial navigation . Particularly, identifying landmarks and borders are processes that are needed for spatial cognition and require information from primary visual areas to reach higher areas in the brain’s organizational hierarchy such as the hippocampus in the brain, where a cognitive representation of the environment may be generated. Nevertheless, how visual signals modulate spatial representations in the hippocampus and how information propagates to the hippocampus is still unknown. To investigate this, we advocate that widefield cortical voltage recordings may provide important details on the visual integration mechanism . Towards this goal, we show here that the activity from the visual cortex propagates to other higher cortical areas that are interconnected, such as the hippocampus, retrosplenial, cingulate and parietal cortices . Additionally, we observed that saccadic movement relates mostly to medium gamma in the stratum lacunosum moleculare. Correlating this hippocampal gamma activity with cortical activity, we found that activity in a set of cortical areas (among those areas the visual cortex) precedes the medium gamma in the hippocampus. Thus, with our combination of techniques we could demonstrate a novel interaction between eye–hippocampus–cortex in the awake state. Hierarchically, the hippocampus is seen as an important central area for the memory process. It is composed of several efferent and afferent projections scattered throughout the brain, among them the cortex. The classic hypothesis that the hippocampus retains short-term memories and indexes them to the cortex for long-term memory highlights the importance of hippocampal–cortical communication . Prior to this process, a short-term memory emerges from the encoding of sensory information and its adaptation to the hippocampus. In this sense, the spike modulation resulting from the hippocampal–cortical interaction can address this computation. Here, we showed that activity in the hippocampus can have different temporal and spatial dynamics to cortical activity. On a broad neocortical level, the reactivation of memory has previously been observed . Together with our result, we can speculate that information about hippocampal events such as replays or the formation of cell assembles are transmitted to specific cortical circuits. We also demonstrated a combination between cortical voltage activity and hippocampal LFP during microstimulations of the retrosplenial or somatosensory cortex. Our results show that gamma oscillation in the hippocampus is suppressed by the inhibition caused specifically in the retrosplenial cortex by the stimulation, and that this suppression is correlated with the intensity of the current in the retrosplenial cortex. Previously, we reported that retrosplenial cortex activity interacts with gamma oscillation in CA1 during sleep, and that this interaction has a temporal relationship from the cortex to the hippocampus . This, together with our result here, indicates that retrosplenial-CA1 communication has a direct influence on the hippocampal LFP. In conclusion, the hippocampal–cortical relationship is recognized in neuroscience for playing a fundamental part in the memory consolidation mechanism. Despite this, the study of basic interactions between these two structures presents functional gaps, which in part is due to technical limitations. In the upcoming years, cortical wide-field voltage imaging may contribute to the understanding of hierarchical neocortical processes in different behavioral states. Combined with hippocampal LFP, this approach has the potential to clarify the fundamental circuitry of cognitive processes such as memory consolidation.
4.1. Animals We used CaMK2A-tTA;tetO-chiVSFP transgenic mice (3 to 6 months and weighing 25–35 g) . This line of transgenic mouse expresses a GEVI specifically in pyramidal neurons across all cortical layers. Macroscopic epifluorescence imaging restricts the optical access to the superficial cortex . Animals were housed under a 12 h light/dark cycle with ad libitum water and food access. 4.2. Surgical Procedure for Combining Wide-Field Imaging with Hippocampal Electrophysiology To record cortical optical voltage imaging in combination with hippocampal electrophysiology (N = 4 mice), we performed a surgical procedure to expose the scalp and chronically implant a 16-channel linear probe (Atlas Neuroengineering, Belgium, 50 μm spacing between recording sites) into the hippocampus. For surgeries, animals were anaesthetized and placed in a stereotaxic frame with a nasal mask delivering isoflurane at 0.5–1.5%. During the entire surgery, the body temperature was maintained by a heat-pad under the body around 37 °C and the breathing rate at 0.5–1 Hz. Then, 2% lidocaine (50 μL) was injected subcutaneously at the incision zone. We successively exposed a wide area of the scalp ( A), and thinned the skull of the entire right hemisphere with a surgical drill in order to remove the skull capillaries to reduce light scattering. Additionally, two screws were implanted into the skull of the left hemisphere to improve the mechanical stability of the head-plate; a third screw was also implanted in the superficial region of the cerebellum in the same hemisphere to be used as a ground and reference. For hippocampal electrophysiology recording, a 16-channel linear probe (Atlas Neuroengineering, Belgium, 50 μm spacing between recording sites) was chronically implanted into the right hemisphere (ipsilateral of the imaged cortex) ( B). The probe was initially placed in +2.4 mm ML and −4.3 mm AP at a 60-degree angle, and then lowered and fixed at ~2.2 mm depth. Finally, the head-plate was carefully placed and fixed onto the skull with acrylic cement. 4.3. Combining Wide-Field Voltage Imaging with Hippocampal Electrophysiology We performed synchronized cortical voltage imaging and hippocampal LFP recording from the mice after post-operative recovery. The optical configuration for voltage imaging is as previously described, using a widefield dual-emission macroscope ( C,D) . Fluorescence excitation was provided by high-power halogen lamps (Brain Vision, Moritex), and we simultaneously measured both mKate2 (GEVI FRET acceptor) and mCitrine (GEVI FRET donor) epifluorescence emissions using two synchronized sCMOS PCO edge 4.2 cameras in combination with Leica PlanAPO1.0 and Leica PlanAPO1.6 lenses. The optics used were: mCitrine excitation 500/24 and emission FF01-542/27, mKate2 emission BLP01-594R-25 with beam splitters 515LP and 580LP (all Semrock). Image series were acquired from the right cortical hemisphere at 50 Hz frame rate with 375 × 213 pixel resolution (~60 pixel/mm) and 12 bit sampling depth, in blocks of 10 min. To compute the optically measured voltage activity, a gain-equalized ratio (ΔR/R) between the mCitrine–mKate2 fluorescence emission was calculated (R = mCitrine/mKate2), then normalized as ΔR/R = (R(t) − Rmean)/Rmean ; Rmean was the session-averaged ratio. We isolated and subtracted the heartbeat frequency components in addition to a high pass filter >0.5 Hz to remove residual hemodynamic signals . To quantify the cortical voltage fluctuations, we detected the activity transients using a similar approach to that reported by Scott et al. , where the global state represented by the active states of each pixel has to cross a certain threshold defined as the mean of the total activated frames. Synchronized to the cortical voltage imaging, local field potential (LFP) from the hippocampal CA1 was acquired using a 16-channel headstage (Intan Technologies, RHD2132, Los Angeles, CA, USA) and an Open Ephys system. The raw signal was recorded with 0.1–7500 Hz filtering and sampled at 20 kHz, and then down-sampled to 1 kHz for analysis. We used kilosort 2.0 for spike sorting. Theta power was computed from the envelope of the filtered LFP signal between 5–10 Hz. 4.4. Visual Stimulus Presentation Visual stimuli were presented on a monitor positioned 10 cm from the left eye of the mouse. We presented 50 gratings at 45 degrees during 1 s with random intervals between 1 and 2 s. 4.5. Eye-Tracking and Pupil Detection To detect the saccade movements of the eye of the mouse during recording, we used a fixed camera (Basler aca1920-150 um, objective with f = 20 mm) directed to the face of the head-fixed mouse with an infrared illumination, and acquired images at 20 Hz. We then used DeepLabCut to label the pupil size detected in each behavioral imaging frame. From the high-movements of the circle centroid in the pupil, we obtained saccade times by the thresholding eye speed from the resultant vector of the movements of the eyes. This method has been previously described . 4.6. Cortical Microstimulation with Combined Cortical Voltage Imaging and Hippocampal Electrophysiology For cortical microstimulations, we used a bundle of two tungsten electrodes (50 μm diameter) that were staggered to create a vertical distance of ~250 μm between the tips. The implant surgical procedure is as described above, with the addition of a chronic implantation of two stimulation electrode bundles into the retrosplenial (RS) and somato-sensory (SS) cortex before the head-bar fixation. For RS implantation, we first performed a small craniotomy on the right hemisphere of the skull at coordinates +0.5 mm (ML) and −2.5 mm (AP), and implanted the bundle electrode in +0.5 mm (DV) and at 45 degrees tilt towards the midline (outside of the visual field of the camera for the cortical imaging). Then we performed a small craniotomy on the right hemisphere at coordinates +3 mm (ML) and +1 mm (AP) above the SS cortex. The bundle electrode in this case was also implanted +0.5 mm (DV), but angled at 30 degrees tilt towards the lateral side of the brain. After 10 days of post-operative recovery, awake animals were placed into the recording setup for cortical stimulation in combination with cortical voltage imaging and hippocampal electrophysiology. We used an Arduino UNO to send 50 square pulses of 10 milliseconds, with inter-stimulus interval randomized between 1.5–2.5 s, controlling a stimulus isolator (World Precision A365), which was also connected to Open Ephys for the synchronization. Stimulation was provided at intensities of 20, 50, 100 and 200 µA.
We used CaMK2A-tTA;tetO-chiVSFP transgenic mice (3 to 6 months and weighing 25–35 g) . This line of transgenic mouse expresses a GEVI specifically in pyramidal neurons across all cortical layers. Macroscopic epifluorescence imaging restricts the optical access to the superficial cortex . Animals were housed under a 12 h light/dark cycle with ad libitum water and food access.
To record cortical optical voltage imaging in combination with hippocampal electrophysiology (N = 4 mice), we performed a surgical procedure to expose the scalp and chronically implant a 16-channel linear probe (Atlas Neuroengineering, Belgium, 50 μm spacing between recording sites) into the hippocampus. For surgeries, animals were anaesthetized and placed in a stereotaxic frame with a nasal mask delivering isoflurane at 0.5–1.5%. During the entire surgery, the body temperature was maintained by a heat-pad under the body around 37 °C and the breathing rate at 0.5–1 Hz. Then, 2% lidocaine (50 μL) was injected subcutaneously at the incision zone. We successively exposed a wide area of the scalp ( A), and thinned the skull of the entire right hemisphere with a surgical drill in order to remove the skull capillaries to reduce light scattering. Additionally, two screws were implanted into the skull of the left hemisphere to improve the mechanical stability of the head-plate; a third screw was also implanted in the superficial region of the cerebellum in the same hemisphere to be used as a ground and reference. For hippocampal electrophysiology recording, a 16-channel linear probe (Atlas Neuroengineering, Belgium, 50 μm spacing between recording sites) was chronically implanted into the right hemisphere (ipsilateral of the imaged cortex) ( B). The probe was initially placed in +2.4 mm ML and −4.3 mm AP at a 60-degree angle, and then lowered and fixed at ~2.2 mm depth. Finally, the head-plate was carefully placed and fixed onto the skull with acrylic cement.
We performed synchronized cortical voltage imaging and hippocampal LFP recording from the mice after post-operative recovery. The optical configuration for voltage imaging is as previously described, using a widefield dual-emission macroscope ( C,D) . Fluorescence excitation was provided by high-power halogen lamps (Brain Vision, Moritex), and we simultaneously measured both mKate2 (GEVI FRET acceptor) and mCitrine (GEVI FRET donor) epifluorescence emissions using two synchronized sCMOS PCO edge 4.2 cameras in combination with Leica PlanAPO1.0 and Leica PlanAPO1.6 lenses. The optics used were: mCitrine excitation 500/24 and emission FF01-542/27, mKate2 emission BLP01-594R-25 with beam splitters 515LP and 580LP (all Semrock). Image series were acquired from the right cortical hemisphere at 50 Hz frame rate with 375 × 213 pixel resolution (~60 pixel/mm) and 12 bit sampling depth, in blocks of 10 min. To compute the optically measured voltage activity, a gain-equalized ratio (ΔR/R) between the mCitrine–mKate2 fluorescence emission was calculated (R = mCitrine/mKate2), then normalized as ΔR/R = (R(t) − Rmean)/Rmean ; Rmean was the session-averaged ratio. We isolated and subtracted the heartbeat frequency components in addition to a high pass filter >0.5 Hz to remove residual hemodynamic signals . To quantify the cortical voltage fluctuations, we detected the activity transients using a similar approach to that reported by Scott et al. , where the global state represented by the active states of each pixel has to cross a certain threshold defined as the mean of the total activated frames. Synchronized to the cortical voltage imaging, local field potential (LFP) from the hippocampal CA1 was acquired using a 16-channel headstage (Intan Technologies, RHD2132, Los Angeles, CA, USA) and an Open Ephys system. The raw signal was recorded with 0.1–7500 Hz filtering and sampled at 20 kHz, and then down-sampled to 1 kHz for analysis. We used kilosort 2.0 for spike sorting. Theta power was computed from the envelope of the filtered LFP signal between 5–10 Hz.
Visual stimuli were presented on a monitor positioned 10 cm from the left eye of the mouse. We presented 50 gratings at 45 degrees during 1 s with random intervals between 1 and 2 s.
To detect the saccade movements of the eye of the mouse during recording, we used a fixed camera (Basler aca1920-150 um, objective with f = 20 mm) directed to the face of the head-fixed mouse with an infrared illumination, and acquired images at 20 Hz. We then used DeepLabCut to label the pupil size detected in each behavioral imaging frame. From the high-movements of the circle centroid in the pupil, we obtained saccade times by the thresholding eye speed from the resultant vector of the movements of the eyes. This method has been previously described .
For cortical microstimulations, we used a bundle of two tungsten electrodes (50 μm diameter) that were staggered to create a vertical distance of ~250 μm between the tips. The implant surgical procedure is as described above, with the addition of a chronic implantation of two stimulation electrode bundles into the retrosplenial (RS) and somato-sensory (SS) cortex before the head-bar fixation. For RS implantation, we first performed a small craniotomy on the right hemisphere of the skull at coordinates +0.5 mm (ML) and −2.5 mm (AP), and implanted the bundle electrode in +0.5 mm (DV) and at 45 degrees tilt towards the midline (outside of the visual field of the camera for the cortical imaging). Then we performed a small craniotomy on the right hemisphere at coordinates +3 mm (ML) and +1 mm (AP) above the SS cortex. The bundle electrode in this case was also implanted +0.5 mm (DV), but angled at 30 degrees tilt towards the lateral side of the brain. After 10 days of post-operative recovery, awake animals were placed into the recording setup for cortical stimulation in combination with cortical voltage imaging and hippocampal electrophysiology. We used an Arduino UNO to send 50 square pulses of 10 milliseconds, with inter-stimulus interval randomized between 1.5–2.5 s, controlling a stimulus isolator (World Precision A365), which was also connected to Open Ephys for the synchronization. Stimulation was provided at intensities of 20, 50, 100 and 200 µA.
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Competency-based cardiac imaging for patient-centred care. A statement of the European Society of Cardiology (ESC). With the contribution of the European Association of Cardiovascular Imaging (EACVI), and the support of the Association of Cardiovascular Nursing & Allied Professions (ACNAP), the Association for Acute CardioVascular Care (ACVC), the European Association of Preventive Cardiology (EAPC), the European Association of Percutaneous Cardiovascular Interventions (EAPCI), the European Heart Rhythm Association (EHRA), and the Heart Failure Association (HFA) of the ESC | 57abd644-6640-4aeb-ba42-9e19c77c0417 | 10610731 | Internal Medicine[mh] | Non-invasive and invasive imaging of the heart is central to diagnosis, risk assessment, therapeutic decision-making, medical and invasive therapies, prognosis, and long-term monitoring in Cardiology. Cardiac imaging is thus central in striving for precision medicine, the essence of which is the provision of individualized care to each and every patient. Examples of such imaging performed by cardiologists include: (i) invasive coronary angiography and cardiac computed tomography (CCT); (ii) cardiovascular magnetic resonance (CMR); (iii) echocardiography; (iv) nuclear cardiology; and (v) advanced invasive imaging (optical coherence tomography and intracardiac echocardiography). For all these imaging modalities we highlight the importance of an in-depth understanding of cardiovascular pathology, complex physiology, and the consequences of imaging findings in the management of cardiovascular health and disease.
Imaging is a core competency of all cardiologists, with echocardiography and coronary angiography (both invasive and non-invasive) an important aspect of training and firmly embedded in mainstream cardiology practice. In the core cardiology curriculum applicable to all cardiologists, the European Association of Cardiovascular Imaging (EACVI) was integral to the development of all imaging capabilities and standards which are used to train cardiologists who are then formally assessed by the European Examination in Core Cardiology. Cardiologists consider disease process, pathology, and management options rather than purely the individual imaging modality, placing them in a unique position to select the most appropriate imaging test for each specific clinical scenario, taking patient preference into account.
Accurate, efficient, and effective cardiac imaging requires not only intricate knowledge of imaging modalities, and the adaptations that are required to optimize imaging protocols to the physiological condition of each individual patient, but also of the rapidly changing field of cardiovascular medicine. For decades, cardiologists have independently performed invasive and non-invasive imaging modalities from ultrasound (transthoracic and transoesophageal echocardiography) to x-ray-based angiography (invasive cardiac and coronary angiography and intervention), which has significantly contributed to the improved management of cardiovascular diseases and outcomes. Cardiologists are uniquely placed to naturally integrate into their clinical practice computed tomography (CT) and CMR which complement their existing anatomical (invasive angiography) and functional (echocardiography) imaging tests. Translational research in cardiac imaging leading to a paradigm shift in cardiovascular clinical practice has been driven predominantly by cardiologists including roles in image interpretation and quality control in core labs, and participation in commercial trials. Examples of investigator-led research relevant to chronic coronary syndromes include the ISCHEMIA trial, the SCOT-HEART trial, the MR-INFORM trial, and the DISCHARGE trial. The results of these trials have transformed cardiovascular medicine practice within the last years. The portfolio of up-to-date clinical practice guidelines and clinical consensus statements for the diagnosis and management of cardiovascular disease published by the European Society of Cardiology (ESC) and EACVI are used by millions of practitioners worldwide. These documents, written by cardiovascular practitioners for cardiovascular practitioners, include recommendations on which cardiac imaging modality to choose, what to expect from the report, and how to act on relevant findings. Cardiologists are fully trained and competent to produce information for patients undergoing the examination and preparation involved, to supervise patients’ preparation on the day of the test, and to consent patients to the test (including stress tests and CMR in patients with cardiac devices). Imaging cardiologists are trained in image acquisition, image post-processing and reconstruction, and image interpretation. Thanks to their in-depth knowledge of cardiovascular physiology and pathology, cardiologists are uniquely positioned to produce a clinically meaningful cardiac imaging report with adequate description and interpretation of the findings that the referring physician (cardiologists in most cases) can act upon. Cardiologists reporting imaging are also well-positioned to provide clinical advice on further additional testing (e.g. genetic testing or myocardial biopsy) or initiation of therapy (such as revascularization or cardiac device implantation). Similarly, the treatment of patients with structural heart disease continues to expand cardiology practice. Structural heart interventions depend on imaging which is central to pre-, peri-, and post-procedural management to balance procedural risk and appropriate patient selection. Importantly, imaging and imaging results must often be immediately available (e.g. in the context of complications) or are integrated into the procedure itself. Without this in-depth knowledge of the fast-changing field of cardiovascular medicine, even expert cardiac imagers would not provide the highest quality services. The core principles of competency are effectiveness, efficiency, equity, patient-centredness, safety, and timeliness ( Table ). They apply to all imaging modalities. They need to be adapted to each individual patient to be safe and effective, with particular attention to patient heart rate and rhythm in order to be safe, which is key for the delivery of value-based cardiac imaging. Examples include exercise or pharmacologically induced stress imaging (echocardiography, CMR, nuclear cardiology, CT perfusion), ensuring low radiation exposure and high image quality using beta-blockers for CCT, emergency indications for cardiac imaging, such as suspected pulmonary embolism, aortic dissection, acute and severe mitral valve regurgitation after myocardial infarction. Cardiologists can also capitalize on their intricate knowledge and experience in cardiovascular pharmacology, from the prescription and administration of beta-blockers, vasodilator stress agents, including indication and contraindications on the use of these drugs during cardiac imaging tests, as well as extensive experience in advanced life support in case of cardiac and respiratory arrest, thus significantly improving patients’ safety. Many cardiology imaging services and the imaging training offered are dependent on cardiologists and have been developed by cardiologists, either in conjunction with other specialties (such as radiology) or as stand-alone departments. The demand for cardiac imaging is increasing ( Figure ) and in many countries, there is a need to train more individuals to provide high-quality cardiac imaging services to meet this demand. The combination of imaging and cardiology expertise is essential not only for the optimal application of imaging tests but also for the appropriate interpretation of cardiac imaging findings. Echocardiography is the most frequently performed cardiac imaging test ( Table ) and is firmly embedded within cardiology services independent of service size, scope (hospitals for secondary, tertiary, or quaternary care), and setting (inpatient/outpatient). Furthermore, this makes echocardiography practical in many settings such as rapid assessment of response to treatments, screening of family members, and general assessment of the patients’ overall cardiological condition. Cardiology is both central and integral to cardiac imaging, and while collaboration with cardiac radiologists and nuclear cardiology physicians can be useful and is encouraged, it is not essential as long as the required expertise is covered by the imaging cardiologist, which is often the case ( Table ). Many highly successful Cardiology-led departments have been established with reputations for national and international excellence. Where services are conjoint between experts, there is evidence that this both enhances the quality of care and leads to rapid service growth, such as that seen in CCT in the United States of America.
To define the scope of practice of clinicians across non-invasive cardiac imaging modalities there is a series of complementary and integrated curricula and syllabi developed by the EACVI for advanced training in each specific modality. Commencing in 2003 with a single examination for transthoracic echocardiography, the EACVI certification programme now encompasses all four imaging modalities with seven dedicated certification programmes (three for echocardiography, two for CMR, one for CCT, and one for nuclear cardiology). There has been a steady, consistent year-on-year increase in uptake of these programmes with currently over 1000 candidates annually ( Figure ). Each certification programme has a specific examination which has evolved over time. From handwritten examinations which were manually marked and graded, these examinations now use a multiple-choice format with well-documented methodology for standard setting and determination of pass marks and pass rates. The examination delivery method has also evolved to a computer-based examination with remote proctoring allowing candidates to take these examinations from any location. This has increased the numbers of candidates but critically maintains examination security. This also maintains consistency with the ESC core cardiology examination with increasing numbers of candidates ( Figure ). It includes a published blueprint, weighting the key components of the curriculum for the examination, question writing and standard-setting groups, and consistent methodology for pass mark determination. The full examination cycle for each of the EACVI examinations replicates the process used for the ESC European Examination in Core Cardiology. With several modalities, there are different levels of certification. The basic level of education is established in level I and focuses on the clinical indications and basic knowledge of the technique and appropriate use following the guidelines of each cardiovascular disease. Level I courses at conferences or local initiatives are secured through central endorsement by the EACVI/ESC and supported throughout Europe and beyond. Also, EACVI has provided a certified online level I course for each of the four modalities since 2022. The advanced levels of certification, levels II and III, further elaborate on theoretical knowledge, but also largely consist of practical education. Level II emphasizes competency to acquire images (including technical considerations), interpret these images, and provide a structured report of salient findings. It is defined as the minimum standard to report independently ( Figure ). Level III requires a wider and more in-depth understanding of the modality including publications and evidence of training others ( Figure ). It also includes other aspects of delivering a full cardiac imaging service. Important parts of the full service include data handling and secure storage, patient safety (particularly for CMR, CCT, and nuclear cardiology), and liaison with the multi-professional team (such as the ability to present cases at a multidisciplinary meeting). This is furthermore true in the acute and emergency setting where collaboration with critical care and emergency medicine colleagues is common practice. The volume of reported cases required is also higher. In line with evolving trends, online case repositories or cases reviewed during didactic teaching can also be submitted in part as evidence recognizing a move to more online education. In case there is no certified professional in the trainees’ hospital, remote teaching is arranged to supervise the expansion of knowledge and competence. To implement standardization in education and to provide valuable official output for practitioners, scientists, policymakers, and the public, EACVI also publishes several official documents each year, including recommendation papers, consensus statements, and position statements, which follow a thorough methodology and an extensive review process. While a patient-centred approach leads to the creation of multi-modality imaging recommendations, focus is also given to each distinct modality governed by the EACVI.
At all levels, the need to integrate imaging is central to the entire programme of certification. This is not simply ensuring the optimal use of limited resources for cardiac diagnostic testing but also relates to the training of future cardiologists, integration with colleagues across the multi-professional team, and the focus on patient-centred care. The use of cardiac pathology to drive the overall shape and construction of each curriculum ensures consistency with the core cardiology curriculum (as opposed to a more modality-centred curriculum) and allows a trainee seamlessly to build on the core knowledge in each modality already attained. It facilitates concomitant training in multiple modalities, stressing the use of pathophysiology and disease processes to determine the optimal use of investigations and avoiding layered, multiple, and duplicate testing. Integration of cardiac imaging in the overall investigation and management of patients maintains the most patient-focused care. In more complex cases this approach cements the role of case discussion across the multi-professional team at clinical case conferences or multidisciplinary team meetings. To further recognize the role of integrated multi-modality imaging the ESC is supporting a shift towards multi-modality imaging congresses with EACVI 2023 being the first such multi-modality congress. In May 2023 EACVI launched a multi-modality certification and continues this trend. Though initially, this will simply recognize an individual certified in two complementary imaging modalities this will evolve further in the future with the ever-increasing emphasis on disease and patient-focused care placing the emphasis on the imaging specialist with an in-depth understanding of all imaging modalities but a high level of expertise in two or more of them.
A recent report by the European Society of Cardiovascular Radiology and European Society of Radiology on the status and vision of cardiac radiology in Europe emphasizes the need to increase cardiac imaging expertise and capacity amongst radiologists. This report, however, fails to acknowledge the integral nature of cardiologists in cardiac imaging. We strongly disagree with the implied perspective that radiology alone is critical and always required for cardiac imaging and thus we do not endorse the content of this report. Furthermore, as already stated, there are multiple world-renowned imaging departments that are wholly Cardiology led, directed, and managed from inception and which continue to deliver cutting-edge clinical services, training, and academic outputs. Cardiac imaging has evolved to become central to cardiovascular disease management and imaging investigations are frequently amongst the first investigations requested by clinicians. The central and expanding role of cardiac imaging to identify and risk stratify pathology and guide treatment will continue to evolve and develop in the coming years. Using a clearly defined competency framework these cardiac imaging standards equip cardiologists with the necessary expertise but can apply equally to all medical specialists, irrespective of previous experience, training, and specialty. Finally, and importantly, the ultimate voice is that of our patient. In discussion with patients and the leadership of the ESC Patient Forum, we captured key statements related to cardiac imaging ( Table ). Patients assign little importance to which modality or which speciality (cardiology, radiology, nuclear medicine, and critical care) provides the investigations. Patients just want to receive the best care possible. In the future, this will become more important as we use imaging to directly guide treatment and therapeutic decision making.
Human experts and cardiac imaging competency will continue to be indispensable in the future, despite a fast-changing landscape impacting cardiac imaging with innovations in digital health and artificial intelligence (AI). First, the development and iterative improvement of AI solutions in cardiac imaging using supervised learning requires expert image annotations. Second, human expert assessment of AI-enabled cardiac image segmentations will require competency. Undoubtedly, we will see many changes in cardiac imaging through digital innovation, but human competency will work hand in hand with AI-enabled solutions to provide better care to patients.
Imaging is integral to Cardiology. There is a major demand to increase capacity in expert cardiac imaging services and the frameworks devised, developed, and implemented by the ESC and EACVI equip cardiologists to provide these services. EACVI promotes collaborative approaches to cardiac imaging between specialties where possible and desired. The main mission of EACVI is to promote and spread the appropriate use of cardiac imaging throughout all member countries. A professional barrier created around ‘specialty-based’ rather than ‘competence-based’ delivery of cardiac services (in particular for CCT and CMR) has been one of the major limiting factors for the wider use of fundamental diagnostic tests in many countries. To foster the efficient and effective use of cardiac imaging in modern cardiology, in some countries, legislation governing who can deliver imaging may need to be revisited. EACVI and the ESC support a competency-based cardiac imaging service delivery that will assure availability and optimal quality for the benefit of our patients ( Table and ).
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Effect of holmium laser prostatectomy on surgical outcomes of primary bladder neck obstruction | dd9aacb6-b64e-46c4-8dcc-122ee3f6f1cc | 11837319 | Surgical Procedures, Operative[mh] | Benign prostatic hyperplasia (BPH) is the most common cause of lower urinary tract symptoms (LUTS) in older men . However, other causes of LUTS exist, including overactive bladder, urethral stricture, prostatitis, urinary tract infection, and neurogenic bladder dysfunction . Primary bladder neck obstruction (PBNO) causes LUTS without BPH . This condition is considerably rare and not fully understood by urologists . To date, literature on the natural course, etiology, and presentation of PBNO is limited . PBNO has not been properly established as a disease entity, leading to a significant number of misdiagnoses in clinical practice . The clinical presentation of PBNO includes various symptoms such as voiding, storage, and pelvic pain and discomfort . Videourodynamic study (VUDS) was considered the gold standard diagnosis for PBNO . However, challenges, such as radiation exposure and high costs associated with performing VUDS to diagnose PBNO in clinical practice, exist . Alpha-blockers are the first-line treatment for PBNO . Surgical treatment mainly involves transurethral incision of the bladder neck . However, to our knowledge, no studies are available on surgical treatment for PBNO using a holmium laser. Since 2018, we have diagnosed PBNO using cystourethroscopy and treated it with a holmium laser prostatectomy. This study aimed to evaluate the efficacy and safety of holmium laser prostatectomy in patients diagnosed with PBNO compared to those diagnosed with BPH. Patients This study included patients who underwent holmium laser prostatectomy or holmium laser enucleation of the prostate for PBNO and BPH at the Seoul National University Hospital between January 2018 and August 2022. Patients in both groups were managed following the same clinical protocol. This study was approved by the Institutional Review Board (IRB) of Seoul National University Hospital. (IRB No.0810-027-260, IRB NO.2407-103-1553). The inclusion criteria for the PBNO were as follows: Patients aged ≥ 50 y who presented with moderate to severe LUTS who visited the urology outpatient clinic; patients with typical cystourethroscopic findings for PBNO; and patients with a total prostate volume < 40 mL assessed by transrectal ultrasound (TRUS) imaging. The sagittal view on TRUS showed bladder neck elevation in most patients with PBNO (Fig. B). We defined typical cystourethroscopic findings for PBNO as follows: High bladder neck when viewed horizontally from the verumontanum (Fig. < link rid="fig1”> A- ); the finding of annular narrowing of the bladder neck opening (Figs. A and ); isolated median lobe hypertrophy (median bar) was excluded. These findings were obtained using 30° rigid cystourethroscopy (Karl Storz Hopkins) in a lithotomy position. The inclusion criterion for the BPH group was patients aged ≥ 50 y, with clinical diagnosis of BPH. The exclusion criteria for the PBNO and BPH groups were the presence of genitourinary cancer, history of surgery, urethral stricture, urinary tract infection (UTI), interstitial cystitis, and neurogenic bladder dysfunction. Patients with minimal neuropathy, which was determined to have a negligible or minimal impact on LUTS by medical history and physical examination, were included in this study. This study included patients who underwent holmium laser prostatectomy or holmium laser enucleation of the prostate for PBNO and BPH at the Seoul National University Hospital between January 2018 and August 2022. Patients in both groups were managed following the same clinical protocol. This study was approved by the Institutional Review Board (IRB) of Seoul National University Hospital. (IRB No.0810-027-260, IRB NO.2407-103-1553). The inclusion criteria for the PBNO were as follows: Patients aged ≥ 50 y who presented with moderate to severe LUTS who visited the urology outpatient clinic; patients with typical cystourethroscopic findings for PBNO; and patients with a total prostate volume < 40 mL assessed by transrectal ultrasound (TRUS) imaging. The sagittal view on TRUS showed bladder neck elevation in most patients with PBNO (Fig. B). We defined typical cystourethroscopic findings for PBNO as follows: High bladder neck when viewed horizontally from the verumontanum (Fig. < link rid="fig1”> A- ); the finding of annular narrowing of the bladder neck opening (Figs. A and ); isolated median lobe hypertrophy (median bar) was excluded. These findings were obtained using 30° rigid cystourethroscopy (Karl Storz Hopkins) in a lithotomy position. The inclusion criterion for the BPH group was patients aged ≥ 50 y, with clinical diagnosis of BPH. The exclusion criteria for the PBNO and BPH groups were the presence of genitourinary cancer, history of surgery, urethral stricture, urinary tract infection (UTI), interstitial cystitis, and neurogenic bladder dysfunction. Patients with minimal neuropathy, which was determined to have a negligible or minimal impact on LUTS by medical history and physical examination, were included in this study. The diagnostic workup included a physical examination, including digital rectal examination, assessment of symptoms using the International Prostate Symptom Score (IPSS) and Overactive Bladder Symptom Score (OABSS), urinalysis, and urine culture to exclude UTI, TRUS to measure prostate volume, uroflowmetry with ultrasound measurement of post-void residual urine volume and prostate-specific antigen (PSA) test. In cases where nodules were palpable on DRE or elevated PSA levels clinically indicated suspicion of prostate cancer, a TRUS-guided prostate biopsy was performed. After confirming a negative result for prostate cancer in the pathological report, surgery was performed on different dates. A urodynamic study (UDS) was performed on all patients . The bladder contractility index (BCI) was defined as PdetQmax + 5Qmax . We defined patients with a BCI < 100 as having detrusor underactivity (DUA) and those with a BCI of ≥ 100 as having non-DUA . The surgical outcomes included operative time, enucleation time, morcellation time, and extracted prostate volume. Perioperative outcomes included the duration of Foley catheterization, length of hospital stay after surgery, and surgical pathology. The IPSS, OABSS, and uroflowmetry data were measured at 2 weeks, 3 mo, and 6 mo postoperatively. Patient-reported subjective satisfaction with the surgical outcomes was assessed 6 mo postoperatively . Postoperative complications were evaluated at 2 weeks, 3 mo, and 6 mo using the Clavien-Dindo classification. The patient was placed in the lithotomy position under spinal or general anesthesia. The Ho: YAG laser (VersaPulse PowerSuite 100 W, Lumenis Pulse™ 120 H, Yokneam, Israel) was set to 80 W (2 J, 40 Hz). The three-lobe technique is primarily used when a clear surgical plane for enucleation is identified . The median lobe was first enucleated. Initial incisions were made on both sides of the verumontanum to identify the capsular plane. The surgical plane of capsule is characterized by circular fibers running in the transverse direction. Longitudinal incisions were made at the 5 o’clock and 7 o’clock positions of the bladder neck, connecting with the previous incisions. Transverse incision was made immediately above the verumontanum to enucleate the median lobe. Resection of both lateral lobe was performed for cases in which the surgical plane in the lateral lobes was not identifiable during enucleation. Resection of each lateral lobe was then started distally at the verumontanum, and the lower limit was defined with incisions on both sides of the initial incision at the verumontanum. A prostatic mucosal incision was performed at the 1 and 11 o’clock positions over the entire length of the prostate to define the margin of the lateral lobe resection. The lobe was then released, starting distally, until only a 12 o’clock mucosal bridge remained at the bladder neck . After meticulous bleeding control in the prostatic fossa, morcellation was performed using a 26-Fr nephroscope and a tissue morcellator (Versacut™, Lumenis). A 22-Fr 3-way Foley catheter was placed under continuous irrigation and removed on the first postoperative day. The patients were discharged typically on the first day after surgery. Statistical analysis All variables were expressed as mean ± standard deviation. Propensity matching was performed when a significant difference was observed in the sample size between the BPH and PBNO groups. For the comparison of clinical parameters between the two groups, paired t-tests were used for continuous variables and chi-square tests for categorical variables. Within each group, changes in postoperative functional outcomes were compared using paired t-tests and chi-squared tests for continuous and categorical variables, respectively. Statistical significance was set at p < 0.05. All variables were expressed as mean ± standard deviation. Propensity matching was performed when a significant difference was observed in the sample size between the BPH and PBNO groups. For the comparison of clinical parameters between the two groups, paired t-tests were used for continuous variables and chi-square tests for categorical variables. Within each group, changes in postoperative functional outcomes were compared using paired t-tests and chi-squared tests for continuous and categorical variables, respectively. Statistical significance was set at p < 0.05. Patient demographics and operative and perioperative outcomes Twenty-eight patients with PBNO and 447 with BPH were identified (Table ) (Fig. ). The mean age of the PBNO group was 67.9 (± 6.5) y, and the mean total prostate volume was 32.0 (± 8.8) mL. No significant differences were observed in the baseline total IPSS and OABSS between the PBNO and BPH groups ( p = 0.47, p = 0.38). On preoperative UDS, detrusor underactivity was significantly more prevalent in the PBNO group (78.6%) than in the BPH group (57.5%) ( p < 0.01). The total operation time was shorter in the PBNO group [26.7 (± 9.5) min] than in the BPH group [61.4 (± 32.0) min] ( p < 0.01). The Bladder Outlet Obstruction Index in the BPH group and the PBNO group was 38.4 (± 15.9) and 30.7 (± 15.9), respectively, showing no significant difference ( p = 0.16). Twenty-eight patients with PBNO and 447 with BPH were identified (Table ) (Fig. ). The mean age of the PBNO group was 67.9 (± 6.5) y, and the mean total prostate volume was 32.0 (± 8.8) mL. No significant differences were observed in the baseline total IPSS and OABSS between the PBNO and BPH groups ( p = 0.47, p = 0.38). On preoperative UDS, detrusor underactivity was significantly more prevalent in the PBNO group (78.6%) than in the BPH group (57.5%) ( p < 0.01). The total operation time was shorter in the PBNO group [26.7 (± 9.5) min] than in the BPH group [61.4 (± 32.0) min] ( p < 0.01). The Bladder Outlet Obstruction Index in the BPH group and the PBNO group was 38.4 (± 15.9) and 30.7 (± 15.9), respectively, showing no significant difference ( p = 0.16). The postoperative functional outcomes and results of the three self-administered questionnaires for the PBNO and BPH groups are presented in Table and Fig. . The total IPSS significantly improved at 2 weeks postoperatively compared to the preoperative values in both the PBNO and BPH groups ( p < 0.01), whereas no significant differences were observed in the OABSS between the preoperative and 2-week postoperative assessments ( p = 0.27, p = 0.32). The PBNO and BPH groups showed significant improvements in total IPSS, OABSS, and Qmax at 3 and 6 mo postoperatively compared with preoperative values ( p < 0.01). However, the PBNO group exhibited less improvement in the IPSS voiding score and maximum flow rate (Qmax) at 3 and 6 mo postoperatively than the BPH group ( p < 0.01). Additionally, at 6 mo postoperatively, the total IPSS was higher in the PBNO group [10.5 (± 7.9)] than in the BPH group [6.0 (± 4.7)] ( p = 0.07). No significant differences were observed in OABSS at 6 mo postoperatively between the PBNO group [3.4 (± 2.3)] and the BPH group [3.3 (± 2.5)] ( p = 0.81). At 6 mo postoperatively, the proportion of patients in the BPH group who responded positively to the satisfaction with treatment question (STQ) was higher than that in the PBNO group; however, this difference was not statistically significant (STQ: 60.7% vs. 92.2%, p = 0.087). Similarly, a higher proportion of patients in the BPH group showed a positive response to the overall response assessment (ORA) and the willingness to undergo surgery question (WSQ) compared to the PBNO group; however, there were no statistical differences [ORA: 82.1% vs. 94.0%, p = 0.566; WSQ: 53.6% vs. 88.4%, p = 0.093]. The PBNO group showed one case of recatheterization at 2 weeks postoperatively ( n = 1, 3.5%) (Table ). None of the patients required a blood transfusion or transurethral coagulation. During the follow-up period of up to 6 months postoperatively, there were no complications of bladder neck contracture or urethral stricture in both groups. PBNO is characterized by the bladder neck not opening sufficiently during urination, leading to obstructed urinary flow without any anatomical obstruction, such as benign prostate enlargement or urethral stenosis . There is no universal agreement or diagnosis for PBNO. Traditionally, diagnosis is achieved by coupling the outcomes of UDS with radiographic visualization of the bladder neck area (Fig. C) . The urodynamic outcome is characterized by outlet obstruction accompanied by a reduction in Qmax (10–15 mL/s; normal value > 18 mL/s), high-pressure detrusor contractility, and increased intravesical pressure . Nitti et al. categorized PBNO into the following three distinct types: (1) classic high-pressure, low-flow voiding; (2) normal-pressure, low-flow voiding with narrowing of the bladder neck; and (3) delayed opening of the bladder neck. These three classifications indicate vesical neck dysfunction, resulting in functional obstruction . Other previous studies have characterized the urodynamic outcomes of PBNO. However, no universally accepted definition of the video-UDS for PBNO exists. Furthermore, video-UDS is limited by its low availability, high cost, and radiation exposure . Girolamo et al. attempted to diagnose PBNO using MR voiding cystourethrography to overcome the limitations of the video-UDS . MR voiding cystourethrography offers advantages such as reduced radiation exposure and elimination of the need for cannulation maneuvers of the urethra . However, a limitation of MR voiding cystourethrography is that the diagnostic tool is unfamiliar to urologists and requires a specialist. In contrast, cystourethroscopy has advantages over video-UDS regarding accessibility and cost, and it is more familiar to urologists. In this study, PBNO was diagnosed when the bladder neck was not visible when viewed horizontally from the verumontanum using rigid cystourethroscopy (Fig. < link rid="fig1”> A- ). The bladder neck opening shows annular narrowing (Figs. A and ). Using the criteria for diagnosing PBNO with cystourethroscopy, as outlined in this study, could help urologists to diagnose PBNO in their clinical practice. To our knowledge, only three studies have reported transurethral incision (TUI) for PBNO. Kochakarn et al. performed a unilateral TUI of the bladder neck in patients with PBNO ( n = 35) . Follow-up was conducted for up to 1 y postoperatively, and their retrospective analysis showed that the IPSS and Qmax significantly improved. Yang et al. conducted a prospective study ( n = 33) after TUI of the bladder neck, with preservation of the supramontanal tissue . IPSS and Qmax significantly improved 2 y postoperatively. Mattioli et al. performed a retrospective analysis ( n = 196) of TUI using a thulium laser. The IPSS and Qmax significantly improved 1 y postoperatively . The authors’ study was followed up for 6 mo postoperatively. The total IPSS score and Qmax improved compared to those before surgery and were similar to those in the postoperative outcomes of previous studies . We performed a holmium laser prostatectomy on patients with PBNO; to our knowledge, this is the first study using this surgical method. Holmium laser prostatectomy was performed instead of TUI because of the possibility of recurrence. According to the authors’ previous surgical experience of performing a TUI of the bladder neck in patients diagnosed with PBNO, the functional outcome improved postoperatively; however, symptoms of obstruction recurred during long-term follow-up. On cystourethroscopy, the bladder neck remained in the form of an isolated median lobe because of the previous incision. Accordingly, a secondary prostatectomy was performed to remove the enlarged median lobe. No recurrence of symptoms occurred thereafter. Based on our experience with these cases, we have been performing a holmium laser prostatectomy rather than TUI of the bladder neck in patients with PBNO since 2018. No previous studies have compared the results of surgical treatment for PBNO with those for BPH. In this study, the PBNO group showed less improvement in the IPSS voiding score [5.5 (± 4.8) vs. 2.0 (± 3.4)] and Qmax [14.8 (± 5.6) mL/s vs. 23.6 (± 5.6) mL/s] at 6 mo after surgery compared to the BPH group. In the subjective satisfaction survey 6 mo postoperatively, the PBNO group showed lower satisfaction than the BPH group, although the difference was not statistically significant. The difference in the results of the objective and subjective indicators after surgery between the PBNO and BPH groups was attributed to the fact that the ratio of the DUA among the UDS parameters of the PBNO and BPH groups performed before surgery was higher in the PBNO group (78.6%) than in the BPH group (57.5%). The underlying mechanisms responsible for the observed increased prevalence of preoperative DUA in the PBNO group compared to the BPH group remain unclear, necessitating further investigation. The advantages of this study are as follows: First, unlike previous studies, we compared and analyzed the postoperative outcomes in the PBNO and BPH groups. Second, the two patient groups were registry-based prospective cohorts that included patients who underwent diagnosis and treatment according to the same clinical protocol. This study had some limitations. First, mid-term follow-up was performed until 6 mo postoperatively, and long-term follow-up was not possible. Second, the number of cases in the PBNO group ( n = 28) was relatively small compared with that in the BPH group. Third, preoperative and postoperative sexual function was not assessed, which requires investigation in future studies. Holmium laser prostatectomy was effective and safe for patients with PBNO with elevated subjective patient satisfaction. Below is the link to the electronic supplementary material. Supplementary Material 1 |
Comparison of two statistical indicators in communicating epidemiological results to the population: a randomized study in a high environmental risk area of Italy | a99c55e0-0203-4bcf-bccb-4c9b811745ac | 6560769 | Health Communication[mh] | Risk communication is an important but difficult task, which poses numerous challenges for scientists, health practitioners and policy makers. Research has investigated how risk and benefit judgement in different fields may differ between experts and lay people , however this discrepancy does not necessarily imply lay people’s higher tendency to misunderstanding or misperceptions . Indeed, it may reflect different perspectives and judgements as a result of several factors influencing the risk evaluation process, including personal attitudes, general knowledge on the subject, media portrayals of hazards and risks, public perceptions, social roles and networks . The formatting of the information seems to be an important factor in risk communication. Several studies have investigated how the use of alternative numerical and/or graphical formats to express risks and benefits related to a medical diagnosis or a treatment may influence patient’s decisions, confidence on such decision or level of concern, and two recent systematic reviews have concluded that different formats seem to have an impact on perceived magnitude of the risks . Sensitivity to result format seems to be an important aspect to consider also in the context of public health issues at the population level. This becomes even more important in the context of “community based participatory research” paradigms that call for a collaborative process in which the communities are involved to “co-create knowledge” . In environmental epidemiology, no previous study has compared the use of different statistical formats in communicating results to the general population, despite, especially in environmental emergency contexts, communication plays a crucial role. Hence, with the present paper we aim at investigating whether the degree of concern expressed by residents of a high-risk area about epidemiological results on cancer mortality in the same area is influenced by the statistical indicator used to communicate such results . In particular, we report the results of a randomized study conducted on a sample of residents in the city of Livorno (159,431 inhabitants - western coast of Tuscany), which, together with the neighboring municipality of Collesalvetti (16,791 inhabitants), is classified as a high-risk environmental site, according to the Seveso Directive , due to the presence of a large commercial harbor and several petrochemical plants producing dangerous pollutants . According to what frequently done in similar studies performed in clinical context , the randomized study compared a relative risk indicator with an absolute risk indicator, when used to communicate results about the health profile of the population in the area of interest (see ).
Participants A sample of 579 residents aged between 18 and 80, stratified by gender, age (18–30, 30–40, 40–50, 50–60, 60–70, over 70) and urban district (5 urban districts), was randomly extracted from the municipality records of Livorno. The sample size was established accounting for feasibility and statistical considerations (see Additional file ). Then, subjects within each stratum were randomly assigned to one of 3 trained interviewers. Within each stratum defined on age, gender, district and interviewer, subjects were randomized to one of the different indicators under comparison. Interviews were collected from October 2012 to March 2013. Of the initial sample of 579 inhabitants, 340 responded to the questionnaire (59%). The response rate was similar for males and females, and lower in young people (18–25) and over 75 than in the other age groups. The urban district 5, in the South of the city, was characterized by the lowest response rate. The study was performed within a project funded by the Istituto Toscano Tumori and approved by the local ethics committee on September 2010. Indicators under comparison Depending on the randomization arm, the burden of mortality attributable to" living in Livorno-Collesalvetti" was expressed through one of the following two indicators: 1) the percent excess of risk (% excess) of death in Livorno-Collesalvetti in respect to Tuscany: [12pt]{minimal}
$$ \%0.5em excess=100 (O-E)/E=100 ( SMR-1) $$ % excess = 100 ∗ O − E / E = 100 ∗ SMR − 1 where O was the observed number of deaths from a specific cause in the area during the period of interest, E was the corresponding expected number of deaths, calculated according to the regional rates by age, gender and deprivation level, and SMR was the standardized mortality ratio, calculated as the ratio O/E; 2) the time needed to harm (TNH), i.e. the number of days one has to wait for, on average, to observe 1 death in excess in Livorno, taking Tuscany as the reference: [12pt]{minimal}
$$ TNH=N/(O (1-1/ SMR)) $$ TNH = N / O ∗ 1 − 1 / SMR where N is the total follow up duration, in days. While the percent excess represents a relative measure of excess mortality, the proposed TNH is an absolute measure of excess mortality. This indicator is similar to the Number Needed to Harm (NNH), which is conventionally used to express risks associated with a treatment and refers to the number of individuals receiving the treatment needed to have an additional adverse event. As for NNH, the smaller the TNH, the higher is the impact. Quantifying impacts in terms of time needed to observe an event is quite usual in communicating epidemiological results and examples can be found also in clinical context (, https://www.theguardian.com/society/2016/jan/20/older-person-dying-winter-fuel-poverty , ) With the aim to provide sufficient information for deriving the absolute excess of mortality in both arms, we always accompanied the percent excess with the total number of deaths observed in the study area. Questionnaires Questionnaires development started from a preliminary draft, which was assessed on a small sample of residents through the cognitive interviewing technique . For simplicity, we will refer to the version of the questionnaire where the burden of mortality was expressed in terms of % excess as % excess-questionnaire, and to the version where the burden was expressed in terms of TNH as TNH-questionnaire. Under both experimental conditions, participants had to rate their degree of concern about mortality from cancer in Livorno in respect to the regional average on a scale from 1 to 10 (item R3). Then, results regarding mortality from three different types of cancer (sexual glands cancer, thyroid cancer, lung cancer) among women were presented, and participants were asked which one was the most and the least alarming option (item R4). The formulation of questions R3 and R4 differed under the two experimental conditions (Table ). For example, in Livorno during the reference period there were 620 deaths from cancer, corresponding to a SMR equal to 104.5%. This result was expressed in terms of a 4.5% excess in mortality from cancer in the % excess-questionnaire (coupled with the total number of deaths from cancer), and in terms of one extra death from cancer every 13 days in the TNH-questionnaire, in both cases taking the mortality level in the region as reference. It is worth noticing that the enrolled subjects were expected not to be more familiar with one of the two indicators than with the other, because no information campaign was been conducted before the randomized experiment. The questionnaires contained also items assessing baseline attitude towards risk (question R1), baseline risk perception (question R2), numerical skills and socio-demographic data. While risk attitude and perception were measured at the beginning of the interview, before the questions involving the two indicators, numerical skill and socio-demographic data were collected at the end of the interview. Baseline risk attitude and perception were measured by items concerning the health/safety domain drawn from the Original 40-Item Domain-Specific Risk-Taking (DOSPERT) Scale 2002 (see Additional file ) . Numerical skills were measured through three open questions concerning probability, derived from Schwartz et al. (1997) (Additional file ). Outcomes In this paper, we analysed the following outcome variables: Degree of concern about mortality from cancer measured on a scale from 1 to 10 from question R3. Proportion of subjects who expressed a degree of concern larger than 5 in question R3. Rank associated to the concern about mortality from each of the three causes compared in question R4: from 1 (the most worrisome option) to 3 (the least worrisome option). We a priori selected 5 as the cut-off for the degree of concern about mortality from cancer because it was the intermediate value of the scale. However, a sensitivity analysis was conducted changing the threshold used for the definition of the binary variable. Statistical analysis We analysed data using an Inverse Probability of Treatment Weighting (IPTW) approach based on propensity score (PS). This method attempts to weight individuals according to PS in order to create a ‘pseudo-population’ where baseline covariates are balanced between groups . IPTW not only removes possible sources of residual confounding, but also allows us to account for data correlation introduced by stratified randomization. In addition, it may bring to efficiency gain as compared with the regression-based approach, if uncertainty around PS estimates is taken into account . We implemented the IPTW approach using the command teffects ipw in Stata 13.1 . In our study, PS was defined as the conditional probability of being assigned to TNH-questionnaire, given the subject’s baseline characteristics. We estimated PS by specifying a logistic model for the questionnaire assignment given the following explanatory variables: age (18–34, 35–64, 65 and over), gender, urban district, interviewer, educational attainment (intermediate school diploma or lower, high school diploma, university degree), numerical skills (at least one right answer over three, no right answer; see Additional file ), smoking status (current smoker, former smoker, no smoker), employment status (employed, retired, not employed), general risk attitude and risk perception, respectively measured as mean values of the 8 items of questions R1 and R2 (see Additional file ). The analyses were conducted excluding the subjects with missing values on the outcome: 9 participants for question R3 (2.6%) and 8 participants for question R4 (2.3%). In order to deal with missing values in the baseline characteristics, for each incomplete explanatory variable, we included in the PS an indicator of missing entry . Relaying on the fact that PS is a balancing score (i.e., conditionally on PS, the distribution of the measured covariates is similar between groups), we evaluated the appropriateness of our PS model by comparing, for each covariate, the between groups standardized mean differences calculated before and after adjustment . We also checked for the overlap of the PS distributions under % excess and TNH, and we removed from the analysis the units not included in the common support. The relative effect of the two risk indicators was measured in terms of mean differences when degree of concern or ranks were considered, and in terms of proportion differences when considering R3 (“degree of concern for cancer mortality”) as a binary variable (high vs low concern). Stratified analyses were performed by educational achievement (intermediate school diploma; high school diploma or higher) and numerical skills (at least one right answer over three, no right answer; see Additional file ). In reporting the results for question R4 (“which result is the most concerning and which one is the least concerning to you”), we draw descriptive cumulative rankograms and we calculated the crude and the adjusted Surfaces Under the Cumulative Rank curve (SUCRA) . It is worth noticing that, despite of the fact that the distribution of the degree of concern for cancer mortality was skewed (see the next section), we focused on the mean difference between groups, in order to enhance the interpretation of the result. However, in a sensitivity analysis based on quantile regression, we performed also a comparison between groups at different quantile of the score (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7), adjusting for the same variables included in the propensity score model.
A sample of 579 residents aged between 18 and 80, stratified by gender, age (18–30, 30–40, 40–50, 50–60, 60–70, over 70) and urban district (5 urban districts), was randomly extracted from the municipality records of Livorno. The sample size was established accounting for feasibility and statistical considerations (see Additional file ). Then, subjects within each stratum were randomly assigned to one of 3 trained interviewers. Within each stratum defined on age, gender, district and interviewer, subjects were randomized to one of the different indicators under comparison. Interviews were collected from October 2012 to March 2013. Of the initial sample of 579 inhabitants, 340 responded to the questionnaire (59%). The response rate was similar for males and females, and lower in young people (18–25) and over 75 than in the other age groups. The urban district 5, in the South of the city, was characterized by the lowest response rate. The study was performed within a project funded by the Istituto Toscano Tumori and approved by the local ethics committee on September 2010.
Depending on the randomization arm, the burden of mortality attributable to" living in Livorno-Collesalvetti" was expressed through one of the following two indicators: 1) the percent excess of risk (% excess) of death in Livorno-Collesalvetti in respect to Tuscany: [12pt]{minimal}
$$ \%0.5em excess=100 (O-E)/E=100 ( SMR-1) $$ % excess = 100 ∗ O − E / E = 100 ∗ SMR − 1 where O was the observed number of deaths from a specific cause in the area during the period of interest, E was the corresponding expected number of deaths, calculated according to the regional rates by age, gender and deprivation level, and SMR was the standardized mortality ratio, calculated as the ratio O/E; 2) the time needed to harm (TNH), i.e. the number of days one has to wait for, on average, to observe 1 death in excess in Livorno, taking Tuscany as the reference: [12pt]{minimal}
$$ TNH=N/(O (1-1/ SMR)) $$ TNH = N / O ∗ 1 − 1 / SMR where N is the total follow up duration, in days. While the percent excess represents a relative measure of excess mortality, the proposed TNH is an absolute measure of excess mortality. This indicator is similar to the Number Needed to Harm (NNH), which is conventionally used to express risks associated with a treatment and refers to the number of individuals receiving the treatment needed to have an additional adverse event. As for NNH, the smaller the TNH, the higher is the impact. Quantifying impacts in terms of time needed to observe an event is quite usual in communicating epidemiological results and examples can be found also in clinical context (, https://www.theguardian.com/society/2016/jan/20/older-person-dying-winter-fuel-poverty , ) With the aim to provide sufficient information for deriving the absolute excess of mortality in both arms, we always accompanied the percent excess with the total number of deaths observed in the study area.
Questionnaires development started from a preliminary draft, which was assessed on a small sample of residents through the cognitive interviewing technique . For simplicity, we will refer to the version of the questionnaire where the burden of mortality was expressed in terms of % excess as % excess-questionnaire, and to the version where the burden was expressed in terms of TNH as TNH-questionnaire. Under both experimental conditions, participants had to rate their degree of concern about mortality from cancer in Livorno in respect to the regional average on a scale from 1 to 10 (item R3). Then, results regarding mortality from three different types of cancer (sexual glands cancer, thyroid cancer, lung cancer) among women were presented, and participants were asked which one was the most and the least alarming option (item R4). The formulation of questions R3 and R4 differed under the two experimental conditions (Table ). For example, in Livorno during the reference period there were 620 deaths from cancer, corresponding to a SMR equal to 104.5%. This result was expressed in terms of a 4.5% excess in mortality from cancer in the % excess-questionnaire (coupled with the total number of deaths from cancer), and in terms of one extra death from cancer every 13 days in the TNH-questionnaire, in both cases taking the mortality level in the region as reference. It is worth noticing that the enrolled subjects were expected not to be more familiar with one of the two indicators than with the other, because no information campaign was been conducted before the randomized experiment. The questionnaires contained also items assessing baseline attitude towards risk (question R1), baseline risk perception (question R2), numerical skills and socio-demographic data. While risk attitude and perception were measured at the beginning of the interview, before the questions involving the two indicators, numerical skill and socio-demographic data were collected at the end of the interview. Baseline risk attitude and perception were measured by items concerning the health/safety domain drawn from the Original 40-Item Domain-Specific Risk-Taking (DOSPERT) Scale 2002 (see Additional file ) . Numerical skills were measured through three open questions concerning probability, derived from Schwartz et al. (1997) (Additional file ).
In this paper, we analysed the following outcome variables: Degree of concern about mortality from cancer measured on a scale from 1 to 10 from question R3. Proportion of subjects who expressed a degree of concern larger than 5 in question R3. Rank associated to the concern about mortality from each of the three causes compared in question R4: from 1 (the most worrisome option) to 3 (the least worrisome option). We a priori selected 5 as the cut-off for the degree of concern about mortality from cancer because it was the intermediate value of the scale. However, a sensitivity analysis was conducted changing the threshold used for the definition of the binary variable.
We analysed data using an Inverse Probability of Treatment Weighting (IPTW) approach based on propensity score (PS). This method attempts to weight individuals according to PS in order to create a ‘pseudo-population’ where baseline covariates are balanced between groups . IPTW not only removes possible sources of residual confounding, but also allows us to account for data correlation introduced by stratified randomization. In addition, it may bring to efficiency gain as compared with the regression-based approach, if uncertainty around PS estimates is taken into account . We implemented the IPTW approach using the command teffects ipw in Stata 13.1 . In our study, PS was defined as the conditional probability of being assigned to TNH-questionnaire, given the subject’s baseline characteristics. We estimated PS by specifying a logistic model for the questionnaire assignment given the following explanatory variables: age (18–34, 35–64, 65 and over), gender, urban district, interviewer, educational attainment (intermediate school diploma or lower, high school diploma, university degree), numerical skills (at least one right answer over three, no right answer; see Additional file ), smoking status (current smoker, former smoker, no smoker), employment status (employed, retired, not employed), general risk attitude and risk perception, respectively measured as mean values of the 8 items of questions R1 and R2 (see Additional file ). The analyses were conducted excluding the subjects with missing values on the outcome: 9 participants for question R3 (2.6%) and 8 participants for question R4 (2.3%). In order to deal with missing values in the baseline characteristics, for each incomplete explanatory variable, we included in the PS an indicator of missing entry . Relaying on the fact that PS is a balancing score (i.e., conditionally on PS, the distribution of the measured covariates is similar between groups), we evaluated the appropriateness of our PS model by comparing, for each covariate, the between groups standardized mean differences calculated before and after adjustment . We also checked for the overlap of the PS distributions under % excess and TNH, and we removed from the analysis the units not included in the common support. The relative effect of the two risk indicators was measured in terms of mean differences when degree of concern or ranks were considered, and in terms of proportion differences when considering R3 (“degree of concern for cancer mortality”) as a binary variable (high vs low concern). Stratified analyses were performed by educational achievement (intermediate school diploma; high school diploma or higher) and numerical skills (at least one right answer over three, no right answer; see Additional file ). In reporting the results for question R4 (“which result is the most concerning and which one is the least concerning to you”), we draw descriptive cumulative rankograms and we calculated the crude and the adjusted Surfaces Under the Cumulative Rank curve (SUCRA) . It is worth noticing that, despite of the fact that the distribution of the degree of concern for cancer mortality was skewed (see the next section), we focused on the mean difference between groups, in order to enhance the interpretation of the result. However, in a sensitivity analysis based on quantile regression, we performed also a comparison between groups at different quantile of the score (0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7), adjusting for the same variables included in the propensity score model.
The main characteristics of the 340 respondents, including socio-demographic variables and other covariates included in the PS model, are reported in Additional file : Table A1. The average degree of concern about overall cancer mortality (question R3) was high, equal to 8.30 (on a 1–10 scale), with standard deviation equal to 1.92. Around 91% of sample expressed a degree of concern higher than 5 (see Additional file : Figure A1). Notably, 8 and 10 modalities of question R3 received an unexpected amount of preference in respect to 9. Regarding question R4 (“which result is the most concerning and which one is the least concerning to you”), most of respondents declared to be particularly concerned about lung cancer mortality (62.9%), while thyroid cancer was selected as the item causing the lowest concern by 48.8% of the interviewees. Weighting using propensity score improved covariates balance, in particular for interviewer indicator and risk attitude (see Additional file : Figure A2). Few units were excluded from the analysis in order to guarantee overlapping between the PS distributions under % excess and under TNH. Tables and report the estimated effect of TNH-questionnaire versus % excess-questionnaire on each outcome variable (Average Causal Effect, ACE) and the weighted mean of the outcome, had all individuals been assigned to the % excess-questionnaire, considered here the control condition. As reported in Table , when epidemiological results were expressed in terms of TNH, the average concern about cancer mortality due to “living in Livorno” increased by 0.31 units ( p = 0.128), on a 1 to 10 scale, being the potential outcome mean under % excess equal to 8.15. Correspondently, the percentage of subjects declaring a concern larger than 5 increased by 6% ( p = 0.051) under TNH, being the percentage under % excess equal to 88%. The sensitivity analysis based on quantile regression provided results consistent with the estimated mean difference of 0.31 units arising from the main analysis (see Additional file : Figure A3). Analogously, using different cut-offs for the degree of concern (from 2 to 4 and from 6 to 9), the estimated probability of scores above the threshold still remained larger under TNH than under % excess, although the uncertainty of the results increased with higher cut-offs, reflecting the fact that, by increasing the cut-off, the probability of scores above the threshold progressively approached 50% (see Additional file : Figure A4). Figure reports the cumulative rankograms for the three causes of deaths compared in question R4 (“which result is the most concerning and which one is the least concerning to you”), under % excess and TNH. The cumulative rankogram for a specific cause of death represents the probabilities that that cause is classified among the k most worrisome ones, where k ranges from one to three. For each cumulative rankogram, we calculated also the surface under it, so-called SUCRA, which can be used to define a hierarchy among the three causes of deaths, with larger SUCRA values indicating higher degree of concern . While judgement about lung cancer mortality, classified as the most worrisome item, was similar under the two indicators (SUCRA = 0.748 and 0.765 under % excess and TNH, respectively), a certain difference was observed for thyroid cancer and sexual glands cancer. The adjusted analyses confirmed these descriptive results (Table ). No significant change in rank was observed for lung cancer mortality, while, compared with % excess, TNH caused sexual glands cancer mortality to be rated as more severe (difference between average ranks = − 0.13; p = 0.093) and thyroid gland cancer mortality to be rated as less worrisome (difference between average ranks = 0.19; p = 0.021). The adjusted SUCRA values, obtained as a simple transformation of the average ranks arising from IPTW regressions, were very similar to the unadjusted ones (Table ). Among people with high school diploma or higher, the probability of expressing degree of concern greater than 5 increased by 9.1% ( p = 0.020) under TNH, taking % excess as reference (Table ). Among people with intermediate school diploma there was no evidence of a difference between the two indicators. In the subgroup with higher mathematical skills, the probability of declaring a degree of concern greater than 5 increased by 7.5% ( p = 0.033) under TNH, taking % excess as reference. Among people with low mathematical skills, the same ACE estimate was negative and affected by large variability (Table ). As shown in Fig. , the ranks assigned to the three causes of deaths in question R4 by the respondents with intermediate school diploma or lower mathematical skills did not depend on the statistical indicator used. On the contrary, an effect of the indicator was found among the respondents with higher educational level or higher mathematical skills, limited to the ranks assigned to sexual gland cancer and thyroid cancer (for details see Additional file ).
In clinical context, several studies compared the use of alternative indicators of relative risk and absolute risk in communication to patients . This is the first study that tries to make something similar in the field of environmental epidemiology, with a randomized experiment in an area at high environmental risk. A sample of citizens was informed about epidemiological results derived from scientific work conducted on their own area. We focused on the individual degree of concern induced by communicating epidemiological results using two alternative risk indicators; investigating the level of understanding of the numerical messages by the respondents was out of the aims of our study. We found that judgments about local risks for population health were influenced by how these risks were communicated. Specifically, a measure similar to the Number Needed to Harm, which we called Time Needed to Harm, appeared to cause slightly greater concern in citizens than % excess risk, when the overall result concerning mortality from different types of cancer was communicated. Expressing the impact in terms of TNH led people to rank mortality from sexual glands cancer as slightly more alarming and mortality from thyroid gland cancer as slightly less alarming, as compared with expressing the same results in terms of % excess. On the contrary, no change was evident for the relative judgment about lung cancer, which was ranked as the most worrisome disease under both the experimental conditions. This result may be due to a complex mixture of factors that go beyond the numbers communicated, including role of health information campaigns and people’s knowledge, experience and personal view about severity and curability of the three diseases, and about factors than can cause them. Educational level and numeracy influenced health risk evaluation, confirming evidence reported elsewhere . In particular, the observed differences between indicators were larger when the subject had higher education or better numerical skills. A possible explanation of this result is that people with higher education level/mathematical skills tend to pay more attention to numbers, as compared with people with lower educational level/mathematical skills. On the contrary, the latter group may be more influenced by other factors, for example personal experiences and views. The role of individual experience in assigning scores or ranking diseases had emerged as relevant also during the cognitive interviews conducted to build the questionnaires: people tended to consider as more worrisome those diseases that they experienced directly or indirectly during their life, and the responses were sometimes influenced by the personal knowledge on the environmental pollution in the city and its relationship with specific diseases . For this reason, even if investigating the role of individual experience of the interviewees with the diseases mentioned in the questionnaire was out of our aim, we introduced in the final questionnaires a close-ended question to investigate the possible reasons of the response to R4 (“which result is the most concerning and which one is the least concerning to you”) . Only 32% of the 340 respondents declared to have replied on the basis of the numerical data presented, while the remaining 68% declared to have replied on the basis of personal knowledge or experience about the illness (37%) or on the basis of personal knowledge about pollutants released in the study area (31%). Study limitations In this research, the non-response rate was around 41%. This is in line with the rate of non-response in Italian surveys, which ranges between 20 and 50% . In our study, non-response was probably due to the difficulty in contacting potential participants using the municipality registry and in doing interviews at home (change of address, difficulty to find people at work or at school). Another plausible reason was the complexity of the questionnaires and the sensitive research topic (health status of the resident population) . Even the lack of trust in institutions may have induced people to avoid participation, but this aspect was not addressed in this study. As a consequence of the large non-response rate, the respondents might represent a selected subgroup of the original sample, with possible impact on the generalizability of the results in the presence of an interaction effect between type of indicator and factors related to the non-response. However, because of the randomized nature of the experiment, it is likely that this selection did not bring to biased effect estimates. A second limitation concerns the outcome that we measured. In fact, due to the complex and multidimensional nature of risk perception, we focused only on a specific aspect of this construct, that is the degree of concern of the respondents . Similarly, this study does not to provide an exhaustive comparison among alternative numerical formats, being % excess and TNH only two of the possible indicators to be used for communicating epidemiological results. From a statistical point of view, the comparison between the two indicators was made complex by the fact that the distribution of the outcome variable measuring the degree of concern of the respondents was strongly asymmetric. We performed several sensitivity analyses, which confirmed the robustness of our result, but for future investigations a revision of the response scale should be considered. Finally, the literature reports a variety of sociocultural, economic and psychological factors being crucial in modelling judgements and decisions . Detecting these factors is important to facilitate public health communication and promote equal access to information across society. In the present study, we conducted only subgroup analyses according to educational level and numeracy. Future studies aimed at elucidating the role of these factors may benefit from a more extensive assessment of the individual characteristics.
In this research, the non-response rate was around 41%. This is in line with the rate of non-response in Italian surveys, which ranges between 20 and 50% . In our study, non-response was probably due to the difficulty in contacting potential participants using the municipality registry and in doing interviews at home (change of address, difficulty to find people at work or at school). Another plausible reason was the complexity of the questionnaires and the sensitive research topic (health status of the resident population) . Even the lack of trust in institutions may have induced people to avoid participation, but this aspect was not addressed in this study. As a consequence of the large non-response rate, the respondents might represent a selected subgroup of the original sample, with possible impact on the generalizability of the results in the presence of an interaction effect between type of indicator and factors related to the non-response. However, because of the randomized nature of the experiment, it is likely that this selection did not bring to biased effect estimates. A second limitation concerns the outcome that we measured. In fact, due to the complex and multidimensional nature of risk perception, we focused only on a specific aspect of this construct, that is the degree of concern of the respondents . Similarly, this study does not to provide an exhaustive comparison among alternative numerical formats, being % excess and TNH only two of the possible indicators to be used for communicating epidemiological results. From a statistical point of view, the comparison between the two indicators was made complex by the fact that the distribution of the outcome variable measuring the degree of concern of the respondents was strongly asymmetric. We performed several sensitivity analyses, which confirmed the robustness of our result, but for future investigations a revision of the response scale should be considered. Finally, the literature reports a variety of sociocultural, economic and psychological factors being crucial in modelling judgements and decisions . Detecting these factors is important to facilitate public health communication and promote equal access to information across society. In the present study, we conducted only subgroup analyses according to educational level and numeracy. Future studies aimed at elucidating the role of these factors may benefit from a more extensive assessment of the individual characteristics.
Our experiment shows that communicating epidemiological results to the population is not a neutral task. In fact, the degree of concern induced by the presentation of results about community health, as well as the ranking of concern when comparing the results on different diseases, may depend on the risk indicator used. Additionally, we found that the impact of using different numerical formats may vary according to individual characteristics, such as education level or mathematical skill. In particular, people having higher education level/mathematical skills seem to be more influenced by the numerical formats of the message than people with lower education level/mathematical skills, who tend to express the same degree of concern independently from the statistical indicator used in communication. This likely originates from a different ability of the message to reach different individuals: the higher the actual or perceived ability to understand numbers, the more attention is given to the numerical content of the message; the lower the actual or perceived ability to understand numbers, the higher is the role of the a priori knowledge in interpreting the message. This result supports the idea that ignoring such factors, that may hamper or facilitate communication of health risks, can lead to unequal information and, as a consequence, unequal protection/prevention across society . Therefore, communication strategies shared by different actors are needed, which account for the heterogeneity of the population to whom the message is addressed.
Additional file 1: Sample size determination. (PDF 42 kb) Additional file 2: Questions R1 and R2. Description of questions R1 and R2 on risk attitude and perception. (PDF 15 kb) Additional file 3: Question on numerical skills. Description of the question on numerical skills. (PDF 33 kb) Additional file 4: Table A1. Description of the sample: socio-demographic characteristics, smoking habit, numerical skills, baseline risk perception and baseline attitude toward risk. (PDF 41 kb) Additional file 5: Figure A1. Histogram of the degree of concern of the respondents from question R3. (PDF 11 kb) Additional file 6: Figure A2. Standardized differences between the two experimental groups for each covariate included in the Propensity Score model, before and after adjustment through Inverse Probability of Treatment Weighting. (PDF 38 kb) Additional file 7: Figure A3. Degree of concern for cancer mortality: estimated differences between TNH and % excess at the quantiles of the outcome distribution ( p = 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7), and corresponding 95% confidence intervals (question R3). (PDF 43 kb) Additional file 8: Figure A4. Degree of concern for cancer mortality: estimated differences between the probabilities of a degree of concern larger than the cut-off under TNH and under % excess (cut-off = 2, 3, …, 9), with the corresponding 95% confidence intervals (question R3). (PDF 43 kb) Additional file 9: Table A2. Ranking sexual gland cancer, thyroid cancer and lung cancer mortalities according to the degree of concern (from 1: high concern, to 3: low concern). Causal effect of expressing the results in terms of TNH versus % excess (question R4), by education level and mathematical skills. (PDF 18 kb)
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"Those who died are the ones that are cured". Walking the political tightrope of Nodding Syndrome in northern Uganda: Emerging challenges for research and policy | e8f1cbcd-e934-4f1d-9e13-7509f4473d3c | 6605670 | Health Communication[mh] | Nodding Syndrome (NS), a severely debilitating neurological syndrome mainly affecting children, is considered a “political” issue in Uganda, unlike other affected areas such as Tanzania . This “politicization” of NS is the result of a long history of ethnic divisions , which are tied up with political power struggles and the civil war that was ongoing at the start of the epidemic . Around 1998, when the war between the Lord’s Resistance Army (LRA) and the current government was at its peak, more than half of the population in northern Uganda was living in internally displaced persons camps . This was when the NS epidemic erupted in Kitgum and neighbouring districts of Northern Uganda. The peak of the epidemic occurred in 2008 , two years after the Lord’s Resistance Army signed a truce with the Sudanese and Ugandan governments. People had just returned to their villages from IDP camps and were in the process of rebuilding their livelihoods after 10 years. NS is characterized by repetitive head nodding, often followed by other types of seizures, developmental retardation and growth faltering with the onset occurring in children aged 5–15 years . The case definition of NS categorized as suspected, probable and confirmed cases, was agreed on at an international scientific meeting organized in Kampala by WHO in 2012. It is based on major criteria such as repetitive involuntary dropping of the head in a previously normal person and onset between 3 to 18 years in combination with one minor criteria such as other neurological abnormalities, temporal and spatial clustering, seizure being triggered by food or cold weather, stunting, delayed physical development and psychiatric symptoms (WHO 2012). As studies are producing more knowledge the case definition continues to be debated and modified. Symptoms of head nodding were first reported over 50 years ago in Southern Tanzania , and later in Liberia , South Sudan and Uganda . There is still however, no clear biomarker for NS and the cause remains unknown despite a consistent epidemiological association with onchocerciasis, a parasitic infection transmitted by the blackfly . On-going research is exploring whether NS could be an auto-immune reaction to Onchocerca volvulus (OV) , the parasite causing river blindness or an OV- induced neuro-inflammatory disorder or a post-measles brain disorder triggered by malnutrition or an autism spectrum disorder . Another recent study suggests that NS in Uganda is a neurodegenerative disease . Based on the spatial and temporal clustering of NS along with other epilepsies, some researchers are also speculating whether NS is just one type of epilepsy, occurring within a spectrum of epilepsies, observed exclusively in onchocerciasis-endemic areas to the extent that it has been proposed to move the focus from NS to ‘onchocerciasis-associated epilepsy’ . This putative link increases the relevance of onchocerciasis control for prevention and control of NS. While NS appears to be a form of epilepsy for which the cause remains unclear and the classification using the current case definition has proven to be problematic in the field-context and without highly sophisticated equipment, for this manuscript we refer to NS as a specific form of epilepsy that has an epidemiological association to onchocerciasis. The NS cases presented in the results are simply self-reported cases. The cases were not examined by a medical doctor for study and have not been cross-checked with patient data. Onchocerciasis control programs in Northern Uganda began in 1994 but several years of civil conflict in the north have caused disruptions to these initiatives in the area . However, since 2012, ivermectin (IVM) has been distributed bi-annually and rivers are treated with larvicides, to prevent onchocerciasis and other parasitic diseases in Northern Uganda . Uganda has successfully eliminated onchocerciasis in all but two regions, one of which is the Madi-Mid North focus in Northern Uganda. The Mid-North focus includes Amuru, Gulu, Kitgum, Lamwo, Nwoya, Oyam, and Pader districts , where we also find NS. Since 2012, anti-epileptic medication is offered to NS patients free of charge among NS patients along with psychosocial care and nutritional supplements in government health centres and hospitals and by some non-governmental organisations (NGOs) . While such symptomatic treatment of NS is not curative, it has been shown to help suppress seizures . NS also negatively affects families socially and economically. Affected children need close monitoring in order to prevent them from running away or having serious accidents like falling into fire or drowning. Due to this, caretakers have to stay at home and are either unable to cultivate as much or are forced to tie children to trees in order to keep them safe . Social isolation of the affected children is also common because community members believe NS is communicable . This article presents the socio-political context of NS health interventions; in particular, how and why NS has been “politicised” in Uganda; how this “politicization” has affected research, and its dissemination and the implications this has for disease control. The insights presented will be critical for reducing resistance to research, interventions, treatment uptake and dissemination, which is necessary for the prevention and control of NS and onchocerciasis in Northern Uganda.
Study site and population Ethnographic research was carried out in Northern Uganda between 2015 and 2017, primarily in Kitgum district and partly in Gulu district. These districts were selected purposively on the basis of their having NS affected and non-affected villages. In addition, the research team was introduced to these districts during the second NS conference held in Gulu and thus leveraged on linkages with district officials and Hope4Humans to focus the study in the two districts. Extending the study to other districts like Pader and Lamwo with similar ethnic composition as the study areas was not feasible. However, focusing on the two districts enabled us to visit the research subjects repeatedly over the three-year period (2015–2017) which facilitated gaining community trust and an in-depth understanding of the context and beliefs around NS. The recent history of Northern Uganda, and our field sites, was dominated by the war between the Lord’s Resistance Army (LRA) and the government of Uganda, which lasted from 1987 to 2006. The forced displacement of much of the population into IDP camps took place from 1996–2007 where people were subjected to violence and governmental surveillance . Prior to the LRA war, Northern Uganda had endured over three decades of civil conflict, which enhanced the already existing North-South divide between the Acholi and Langi ethnic groups of the North and the Bantu in the South . Political distrust and suspicion about perceived neglect by the current government towards the Acholi people is a recurrent sentiment that has prevailed through all three epidemics–Ebola, HIV and now NS. President Museveni came to power by overthrowing an Acholi leader, General Tito Okello Lutwa in 1986. As a counterinsurgency, the LRA war against president Museveni and his National Resistance Army began a year later, mainly in response to alleged atrocities by the NRA against the Acholi who had feared retribution by the new government . These feelings have been reinforced by the level of economic investment, governmental and non-governmental development initiatives, social services and business-opportunities available in the south of the country as compared to the substantially less developed northern region . When responding to disease outbreaks in Northern Uganda it is crucial to keep this historical political context in mind. In 2015, a study retrospectively reported that the first case of NS was seen in Western Uganda in 1994 , however, it was only after media uproar in 2012 that NS attracted national attention through a campaign of the opposition party highlighting the perceived neglect of healthcare in the North . Consequent parliamentary debates about the outbreak of a previously unknown ‘disease’ named “Nodding Syndrome” drove governmental and non-governmental organisations (NGOs) to provide services and resources for NS control . These consisted of free of charge provision of anti-epileptic drugs (AED) for the management of seizures, along with nutritional supplements as well as behavioural and physical therapy at 17 government health facilities in the affected region . However, the resources provision for the NS response have been inadequate for different reasons. Between 2012 and 2017, NS outreach services and comprehensive in-patient care for severely affected children were also provided by a US funded NGO, Hope for Humans in Gulu district. In late 2017 the NGO had to close down after several failed efforts of finding a sustainable stream of funding or governmental support. This closure led to renewed accusations and media reports of the government’s and ministry of health’s failure to prioritize and protect Acholi children. After much political debate the new government committed to improved NS service provision in Northern Uganda. There has been a cyclical trend of political propaganda, where the Acholi in the north, both politicians and civilians, have criticized the ruling government of inadequate support, which has driven governmental interventions for NS in the region. The NS epidemic affected an already impoverished region of the country, exacerbating the economic burden on caretakers and the community . The region is still one of the most impoverished regions of the country. While 85% of Uganda’s poor were reported to live in the Northern and Eastern regions of the country in 2013, the Northern region accounted for more than half . The villages we visited in Gulu and Kitgum districts, survived mainly on subsistence farming. Droughts and el niño rains periodically affected the food production and inhabitants faced severe food shortages. Village inhabitants were mostly of the Acholi ethnic group, who had lived in the area for several generations but were displaced from their homes during the LRA war, when they lived in IDP camps . Sampling Contrasting villages with high prevalence (more than 6%) and low prevalence (about 1%) of epilepsy/Nodding syndrome were purposefully selected. Prevalence was calculated based on the 2012 data provided by the ministry of health for all villages in the Kitgum district, and from the Hope4Humans estimates and the local health centre for Gulu district. The study began with an exploratory phase, where data was collected from two high prevalence (Akoyo and Ajan) and one low prevalence (Dino) village in Gulu district, and from three villages in Kitgum district. Health officials at the district hospital which had a ward that handled epilepsy and nodding syndrome cases were interviewed. The main phase of data collection focused on Kitgum district as we were able to find 10 contrasting villages within two sub-counties, Akwang and Amida, which made it relevant for our study. Villages selected in Kitgum district are listed in . All villages were classified as hyper-endemic for onchocerciasis. Participant recruitment was carried out through a mixed-sampling approach, including both theoretical (based on emergent findings) and snowball sampling techniques (relying on one sampled person to contact the next person in the sample) in order to have maximum variation and representativeness in the sample. We purposefully selected varying social groups based on age; gender; persons directly affected/unaffected by NS/Epilepsy; occupation and livelihood regardless of local hierarchy or locally perceived expertise as shown in . Data collection An ethnographic approach, triangulating participant observations, in-depth interviews, focus group discussions, was chosen because it allows in-depth descriptions of disease perceptions and the detection of unforeseen and unknown variables that are hard to measure quantitatively . Additionally, text analysis of media reports was used to deepen the contextualization of the political environment and cross-check emerging themes. Data collection centred around emergent themes such as perceptions of epilepsy and the experiences of those affected, access to and perceptions of public, private and traditional health facilities in general and specifically for NS/epilepsy, health seeking behaviour, religious practices, daily activities and livelihoods. Participant observation was used to acquire an understanding of the local context. The researchers participated in daily activities in the community and the home setting, observed and participated in events in their usual context, while having informal conversations with a variety of community members. This method was used to cross-check the validity of information obtained in semi-structured interviews by establishing rapport and building trust with community members to reduce response bias. Repeated visits were made to the selected villages over the course of two years. Brief notes were taken during informal interviews if appropriate, otherwise the conversations were written down in detail afterwards. 94 in-depth interviews were conducted at participants’ homes in private or in places where the respondent felt at ease. Most in-depth interviews took an hour and were audio recorded with consent and conducted in the local language, Acholi. If the respondent did not wish to be audio recorded, detailed hand-written notes were taken. Later, all recordings were transcribed verbatim in Acholi and translated in English by trained field assistants. 13 formal focus group discussions were conducted (12 in Kitgum and 1 in Gulu) mostly at village centres, at market places or outside people’s homes when people were gathered together to socialise or for an event or they were organised by the village leaders in advance. Group discussions were used for different purposes: i.e., to get a quick picture of the village activities, livelihoods and facilities available like health centres, schools, traditional healers, water access points, and with village elders to get a better idea of how things might or might not have changed in contrast to the past, with the same gender to understand social norms, gender roles and disease perceptions. Some group discussions were audio recorded with consent while some were documented with hand written notes. All discussions were conducted in the local language, Acholi. Like IDIs, all recordings were transcribed verbatim in Acholi and translated to English by trained field assistants. Articles in media were monitored from 2015–2017 by using ‘google alerts’ service, i.e. a notification tool offered by Google based on set keywords, for the keywords ‘nodding disease’ and ‘nodding syndrome’ respectively. Most articles came from online English newspapers of Uganda, like “The observer”, “The monitor”, “Daily monitor” and “Acholi times” and occasionally there were some from “Huffington post” and scientific journals. Earlier articles dating back to 2012 were searched for through a google search. All articles were used to assess what was being presented in the media and analysed comparatively with emerging themes from the field. Data analysis Data analysis was retroductive (combining inductive analysis of field data and theory from existing anthropological literature) and was carried out concurrently with data collection. Relevant categories for analysis were identified combining data from participant observation, interviews and group discussions. Through the analysis process, data were constantly subjected to theoretical perspectives so as to ensure theoretical triangulation and to embed the findings in existing literature. We used concepts of uncertainty and meaning making coupled with sense making of epilepsy as elaborated by Susan Whyte . We also looked at fear and distrust and its role in the creation of rumours , also in conjunction with other epidemics that occurred in the same area to conceptualise the unique socio-political context , annihilation anxieties of minority and marginalised populations . Data were imported, managed and analysed using NVivo 12 Qualitative Data Analysis software (QSR International Pty Ltd. Cardigan UK). Ethical considerations The study was reviewed and approved by the Institutional Review Board of the Institute of Tropical Medicine in Antwerp (IRB/AB/ac/036 Ref: 983/14); the Makerere University School of Medicine’s Research Ethics Committee (REC REF 2015–079) and the Uganda National Council for Science and Technology (REF: SS 3845). Oral consent was obtained from all participants and preferred, since the act of signing one’s name when providing information can be a reason for mistrust, particularly among illiterate populations, which can significantly reduce the quality of the data (Refer to justification of oral consent attached). Oral consent was documented by the interviewer on a separate paper form. Interviewers followed the European Guidelines for FP7 projects and the guidelines of the American Anthropological Association. Children who are able to give assent to participate in research were asked to provide assent in addition to the consent of the legally authorized representative. Young people aged 16–18 with sufficient understanding were asked their full consent to participate in research independently of their parents and guardians. If a potential respondent was cognitively impaired, a close family member was asked for consent to ask questions pertinent to the potential respondent. Confidentiality was maintained by storing all data on a password protected computer and not transcribing names of respondents. Findings from the study will be disseminated in the form of scientific manuscripts which will be shared with the Makerere University School of Medicine’s Research Ethics Committee and the Uganda National Council for Science and Technology and the Ministry of Health.
Ethnographic research was carried out in Northern Uganda between 2015 and 2017, primarily in Kitgum district and partly in Gulu district. These districts were selected purposively on the basis of their having NS affected and non-affected villages. In addition, the research team was introduced to these districts during the second NS conference held in Gulu and thus leveraged on linkages with district officials and Hope4Humans to focus the study in the two districts. Extending the study to other districts like Pader and Lamwo with similar ethnic composition as the study areas was not feasible. However, focusing on the two districts enabled us to visit the research subjects repeatedly over the three-year period (2015–2017) which facilitated gaining community trust and an in-depth understanding of the context and beliefs around NS. The recent history of Northern Uganda, and our field sites, was dominated by the war between the Lord’s Resistance Army (LRA) and the government of Uganda, which lasted from 1987 to 2006. The forced displacement of much of the population into IDP camps took place from 1996–2007 where people were subjected to violence and governmental surveillance . Prior to the LRA war, Northern Uganda had endured over three decades of civil conflict, which enhanced the already existing North-South divide between the Acholi and Langi ethnic groups of the North and the Bantu in the South . Political distrust and suspicion about perceived neglect by the current government towards the Acholi people is a recurrent sentiment that has prevailed through all three epidemics–Ebola, HIV and now NS. President Museveni came to power by overthrowing an Acholi leader, General Tito Okello Lutwa in 1986. As a counterinsurgency, the LRA war against president Museveni and his National Resistance Army began a year later, mainly in response to alleged atrocities by the NRA against the Acholi who had feared retribution by the new government . These feelings have been reinforced by the level of economic investment, governmental and non-governmental development initiatives, social services and business-opportunities available in the south of the country as compared to the substantially less developed northern region . When responding to disease outbreaks in Northern Uganda it is crucial to keep this historical political context in mind. In 2015, a study retrospectively reported that the first case of NS was seen in Western Uganda in 1994 , however, it was only after media uproar in 2012 that NS attracted national attention through a campaign of the opposition party highlighting the perceived neglect of healthcare in the North . Consequent parliamentary debates about the outbreak of a previously unknown ‘disease’ named “Nodding Syndrome” drove governmental and non-governmental organisations (NGOs) to provide services and resources for NS control . These consisted of free of charge provision of anti-epileptic drugs (AED) for the management of seizures, along with nutritional supplements as well as behavioural and physical therapy at 17 government health facilities in the affected region . However, the resources provision for the NS response have been inadequate for different reasons. Between 2012 and 2017, NS outreach services and comprehensive in-patient care for severely affected children were also provided by a US funded NGO, Hope for Humans in Gulu district. In late 2017 the NGO had to close down after several failed efforts of finding a sustainable stream of funding or governmental support. This closure led to renewed accusations and media reports of the government’s and ministry of health’s failure to prioritize and protect Acholi children. After much political debate the new government committed to improved NS service provision in Northern Uganda. There has been a cyclical trend of political propaganda, where the Acholi in the north, both politicians and civilians, have criticized the ruling government of inadequate support, which has driven governmental interventions for NS in the region. The NS epidemic affected an already impoverished region of the country, exacerbating the economic burden on caretakers and the community . The region is still one of the most impoverished regions of the country. While 85% of Uganda’s poor were reported to live in the Northern and Eastern regions of the country in 2013, the Northern region accounted for more than half . The villages we visited in Gulu and Kitgum districts, survived mainly on subsistence farming. Droughts and el niño rains periodically affected the food production and inhabitants faced severe food shortages. Village inhabitants were mostly of the Acholi ethnic group, who had lived in the area for several generations but were displaced from their homes during the LRA war, when they lived in IDP camps .
Contrasting villages with high prevalence (more than 6%) and low prevalence (about 1%) of epilepsy/Nodding syndrome were purposefully selected. Prevalence was calculated based on the 2012 data provided by the ministry of health for all villages in the Kitgum district, and from the Hope4Humans estimates and the local health centre for Gulu district. The study began with an exploratory phase, where data was collected from two high prevalence (Akoyo and Ajan) and one low prevalence (Dino) village in Gulu district, and from three villages in Kitgum district. Health officials at the district hospital which had a ward that handled epilepsy and nodding syndrome cases were interviewed. The main phase of data collection focused on Kitgum district as we were able to find 10 contrasting villages within two sub-counties, Akwang and Amida, which made it relevant for our study. Villages selected in Kitgum district are listed in . All villages were classified as hyper-endemic for onchocerciasis. Participant recruitment was carried out through a mixed-sampling approach, including both theoretical (based on emergent findings) and snowball sampling techniques (relying on one sampled person to contact the next person in the sample) in order to have maximum variation and representativeness in the sample. We purposefully selected varying social groups based on age; gender; persons directly affected/unaffected by NS/Epilepsy; occupation and livelihood regardless of local hierarchy or locally perceived expertise as shown in .
An ethnographic approach, triangulating participant observations, in-depth interviews, focus group discussions, was chosen because it allows in-depth descriptions of disease perceptions and the detection of unforeseen and unknown variables that are hard to measure quantitatively . Additionally, text analysis of media reports was used to deepen the contextualization of the political environment and cross-check emerging themes. Data collection centred around emergent themes such as perceptions of epilepsy and the experiences of those affected, access to and perceptions of public, private and traditional health facilities in general and specifically for NS/epilepsy, health seeking behaviour, religious practices, daily activities and livelihoods. Participant observation was used to acquire an understanding of the local context. The researchers participated in daily activities in the community and the home setting, observed and participated in events in their usual context, while having informal conversations with a variety of community members. This method was used to cross-check the validity of information obtained in semi-structured interviews by establishing rapport and building trust with community members to reduce response bias. Repeated visits were made to the selected villages over the course of two years. Brief notes were taken during informal interviews if appropriate, otherwise the conversations were written down in detail afterwards. 94 in-depth interviews were conducted at participants’ homes in private or in places where the respondent felt at ease. Most in-depth interviews took an hour and were audio recorded with consent and conducted in the local language, Acholi. If the respondent did not wish to be audio recorded, detailed hand-written notes were taken. Later, all recordings were transcribed verbatim in Acholi and translated in English by trained field assistants. 13 formal focus group discussions were conducted (12 in Kitgum and 1 in Gulu) mostly at village centres, at market places or outside people’s homes when people were gathered together to socialise or for an event or they were organised by the village leaders in advance. Group discussions were used for different purposes: i.e., to get a quick picture of the village activities, livelihoods and facilities available like health centres, schools, traditional healers, water access points, and with village elders to get a better idea of how things might or might not have changed in contrast to the past, with the same gender to understand social norms, gender roles and disease perceptions. Some group discussions were audio recorded with consent while some were documented with hand written notes. All discussions were conducted in the local language, Acholi. Like IDIs, all recordings were transcribed verbatim in Acholi and translated to English by trained field assistants. Articles in media were monitored from 2015–2017 by using ‘google alerts’ service, i.e. a notification tool offered by Google based on set keywords, for the keywords ‘nodding disease’ and ‘nodding syndrome’ respectively. Most articles came from online English newspapers of Uganda, like “The observer”, “The monitor”, “Daily monitor” and “Acholi times” and occasionally there were some from “Huffington post” and scientific journals. Earlier articles dating back to 2012 were searched for through a google search. All articles were used to assess what was being presented in the media and analysed comparatively with emerging themes from the field.
Data analysis was retroductive (combining inductive analysis of field data and theory from existing anthropological literature) and was carried out concurrently with data collection. Relevant categories for analysis were identified combining data from participant observation, interviews and group discussions. Through the analysis process, data were constantly subjected to theoretical perspectives so as to ensure theoretical triangulation and to embed the findings in existing literature. We used concepts of uncertainty and meaning making coupled with sense making of epilepsy as elaborated by Susan Whyte . We also looked at fear and distrust and its role in the creation of rumours , also in conjunction with other epidemics that occurred in the same area to conceptualise the unique socio-political context , annihilation anxieties of minority and marginalised populations . Data were imported, managed and analysed using NVivo 12 Qualitative Data Analysis software (QSR International Pty Ltd. Cardigan UK).
The study was reviewed and approved by the Institutional Review Board of the Institute of Tropical Medicine in Antwerp (IRB/AB/ac/036 Ref: 983/14); the Makerere University School of Medicine’s Research Ethics Committee (REC REF 2015–079) and the Uganda National Council for Science and Technology (REF: SS 3845). Oral consent was obtained from all participants and preferred, since the act of signing one’s name when providing information can be a reason for mistrust, particularly among illiterate populations, which can significantly reduce the quality of the data (Refer to justification of oral consent attached). Oral consent was documented by the interviewer on a separate paper form. Interviewers followed the European Guidelines for FP7 projects and the guidelines of the American Anthropological Association. Children who are able to give assent to participate in research were asked to provide assent in addition to the consent of the legally authorized representative. Young people aged 16–18 with sufficient understanding were asked their full consent to participate in research independently of their parents and guardians. If a potential respondent was cognitively impaired, a close family member was asked for consent to ask questions pertinent to the potential respondent. Confidentiality was maintained by storing all data on a password protected computer and not transcribing names of respondents. Findings from the study will be disseminated in the form of scientific manuscripts which will be shared with the Makerere University School of Medicine’s Research Ethics Committee and the Uganda National Council for Science and Technology and the Ministry of Health.
Making sense of a ‘new’ disease in a politically contested, war-torn area Given the timing of the NS epidemic, community members linked the aetiology of NS to the LRA war in several ways. The most commonly perceived cause was poisoning either through the pollution of air and water with gunpowder during the war or by toxins in the food distributed at IDP camps. The second most commonly stated cause was that the spirits of the deceased during the war were angry for not getting a respectful burial and so were taking revenge on their children by inflicting this disease on them. Illness interpretations also included perceptions related to the epidemic occurrence of the disease outbreak. Crowding was seen to have enhanced the spread of the disease, ‘ like measles , through the air ’ due to the high concentration of people in the camps. The perceived epidemic nature of NS also led to some not believing that it was a form of epilepsy, an illness well known to them as illustrated in the following quote: “ You researchers say this is epilepsy , but we know epilepsy … we used to have it before but it was only one or two persons in the entire village who were affected… but this is different . This came during the war , and this affects entire villages . This is not epilepsy , this is because of the war . (…) Why is it that the villages where most atrocities took place , are also the villages that have the most people affected (by NS) ? ” ( IDI , father of NS victim ). Some associated NS with changes in political power, as illustrated at the funeral of an NS victim: “ During Obote’s first regime , there was a disease called ‘two nailon’ [gonorrhoea] . Later he was over thrown by Amin and this sickness disappeared … When Obote came back to power again , there came HIV/AIDS and this continued in Museveni’s regime . And in Museveni’s government there comes this sickness , this strange disease called nodding syndrome .” (Sermon of a middle-aged Acholi Catholic priest) Many respondents had also heard about the blackfly as a potential cause from researchers and health officials. However, few agreed with this possibility. Many were not convinced as they logically reasoned that blackflies had always been around while NS was something new that had started occurring during the war. Some resented and distrusted the government and suspected they were the reason for this illness. This distrust was due to the perceived lack of response to the NS outbreak until 2012—almost 15 years after the first cases were noticed, and approximately six years after the war had ended. The government response was perceived as having been initiated after the political propaganda around the disease began circulating through the media attention. Besides the growing sense of suspicion towards the government, conveys the sentiment that governmental authorities did not want affected locals to say that NS existed and was increasing. This resentment explains the second uproar in the media in 2018, after the closing of the NGO, Hope for Humans. Hope for Humans was requesting governmental funds and encouraging the government to take over the responsibility. When this request was refused the NGO was unsustainable and closed down. It was evident that people felt that the government and the MoH were not acknowledging the severity of the problem. The media reported that there was an angry backlash from the northern political representatives when the MoH suggested that there were no more new cases of NS while their people strongly asserted that there were in fact new cases. While the MoH may not be wrong to say that there were no new cases of NS according to case definitions, community members still perceived all epilepsies that occurred during or after the war to be NS and thus thought that the MoH was covering up facts and dismissing the problems people in the north were facing. Box 1. Delayed response and political propaganda driving initial response A middle-aged male village health worker, Orach, lamented about the first three cases seen in 1998. He said when they first noticed this strange disease, he took the children to the health centre in Kitgum which referred them to the hospital whose fees they could not afford, and so no action was taken. A few years later, his own son also got NS and he actively tried everything to get care. He said that it was only in 2012, after the Kitgum district’s parliamentarian from the opposition party voiced people’s suffering that they were taken to Kampala, the capital city, for treatment. In an informal conversation, the parliamentarian explained that she highlighted the current leadership’s neglect of the children in the north and mobilised a bus full of 24 patients and parents to be taken to the main referral hospital in the capital city. She notified the president and the hospital staff that these children were on their way to be examined and that the children of the north should not be neglected. Orach was one of the parents on this bus with his son. Another parent, Atim, who was also on the bus explained that while on the way, the bus was intercepted by police and they were detained for two days without a reason. The police then escorted the parents and the 24 affected children to the hospital. At the hospital, the president met them and the media was there taking photographs of their children with the president. They were provided with meals and accommodation for the rest of their stay. This made parents suspicious once again and they wondered why the police were involved. “ We asked ourselves , ‘what is the government trying to hide ? ’ ” … After treatment at the referral hospital, Orach said that the children showed improvement. However, once they returned to their home villages, they could not be fed in the same way and the children’s condition deteriorated. A year later, his son died reportedly due to uncontrolled, repetitive seizures. He said that researchers took a sample of his deceased son’s brain for testing but he had not heard back from them three years later (2015). In 2017, when we met him again, he expressed distrust in the governmental system. He said, “ In the district here , (Kitgum) they don’t want us to say that such a disease exists or that it is increasing” . The political propaganda that drove the initial response to the outbreak influenced how NS became a tool for power both for politicians and for people in the community gaining resources through the epidemic. shows that when these services were abruptly stopped, feelings of resentment and distrust towards the government were reinforced. Box 2. Inconsistent interventions and suspicion A psychiatric nurse at the government hospital in Gulu, who was part of the initial interventions to address NS explained that after the political and media attention that NS received, outreach programs and clinics were established in 2012 by the government. There were severe food shortages at the time generally as people were slowly recovering from the war, and households with affected children were struggling even more. To cater for this, the government introduced a program according to which the households of the affected children were supplied with food along with the treatment for seizures free of charge. She said, “ NS is highly politicized so the community thinks that it is beneficial to have a child with NS . As people and the government are providing food , clothes , and money to these families , the Ministry of Health’s focus is on identifying Nodding properly because many people were claiming to have NS (when they did not have NS) . When this programme proved unsustainable , the government suddenly stopped providing food to NS families . There was no proper way of weaning them off ”. Consequently, the affected parents felt that “ the government does not care about us ”. However, some still had a different view of the government. While most community members were disheartened by the prospects of NS and felt angered, frustrated and neglected by the government, some believed that researchers coming to the area were government agents who were not trying to find a remedy for NS. Consequences for health interventions The perceived link between NS, the war, forced displacement to government-protected camps, in addition to the overwhelming burden of caretaking under extreme poverty, the social inequality and ethnic tensions all enhanced distrust of the government. These factors directly created barriers to NS service delivery in terms of limiting care available in the private sector, increased distrust and reluctance to accept treatment and prevention for onchocerciasis , all relevant for managing NS . Some non-governmental health facilities, for example, the local Catholic missionary St. Joseph’s hospital in Kitgum, prefered not to treat NS patients due to the political nature of the disease. Reportedly, during the initial period when NS was getting political and media attention, the missionary hospital hosted a researcher who independently observed NS without informing them. After visiting one of the affected villages by himself, news reached the authorities and police tracked him down for questioning. The foreigner was reportedly arrested and deported for not following proper protocol and hospital employees were questioned. Whatever the veracity of the details of this and similar stories, it has led to sensitivity around accepting NS patients as illustrated by the following quote: “ We care for epileptic patients in this facility but for NS patients , we always refer them to Kitgum Government Hospital because NS has ‘political affiliations’ , and we are faith-based so we don’t want to mix politics and religion .” ( IDI , hospital staff ) What is interesting however, is how NS is distinguished from other epilepsies at hospitals, where NS and epilepsy were considered two separate medical conditions, whereas people in the community, perceived all epilepsies that occurred during or after the war as NS. Additionally, news of incidents like this spread through the community quickly and like any story travelling through the grapevine, it lost or enhanced some details allowing differing interpretations to arise. Some became suspicious of secrecy they observed or by the hidden agendas of researchers, the government or both. Despite the distrust of the government, most NS affected families still sought care in government facilities. While this behavior was seemingly counterintuitive, there were two main reasons for people to do so. Firstly, people were desperate for a cure as the burden of this disease was immense. Besides biomedical treatments, desperation had driven people to seek additional treatment options, including an array of traditional remedies through herbalists, spiritual healers and religious healers. This desperation was illustrated by a father who lost his son to NS. He expressed emphatically, “ Those who died are the ones that are cured ” implying that death among children with NS was often perceived as better than the continued suffering and disease-related hopelessness associated with NS within the context of poverty. Anti-epileptic drugs, when available, helped suppress symptoms for most patients and when the perceived benefit from them was greater than the cost, they continued to take the medication. A positive aspect of the biomedical health interventions in the area was that they were run and staffed by locals of the same ethnic group. So, while the community did not trust the government at large, they did trust the health professionals employed on a personal level. However, we also encountered a situation where one individual who had grown up in one of the villages there and came from a modest background, later was perceived as arrogant and driven by financial pursuits by community members after becoming successful. This individual was often used for sensitization by the MoH/government, which backfired as people did not trust in him despite their shared background and family history. While exploring community perceptions towards MDA and the distribution of Ivermectin, a drug distributed to treat and prevent onchocerciasis, the general impression was that more people were taking IVM now as compared to when it was first introduced. In addition to continuous sensitization, the research showed that people got a sense that the medication helped relieve symptoms and there was a better understanding of the side effects and why they occurred. However, some were still refusing to take the medication. In addition to common fears of side-effects, one reason for refusing up-take was that they did not trust the purpose of the medication. Some households perceived it to be a government strategy to reduce the population in the region. The village health worker who distributes IVM said, “ People argue that yes , this government seems to be having a plan to finish off the people of northern Uganda . Why is it that they are bringing these drugs here and not to his (current leader , Museveni’s) village ?” (IDI, female, ivermectin distributor) Consequences for research activities Due to the spatial and temporal clustering of NS, most studies have been conducted in a limited number of villages since the war ended. The village of Tumangu, for example, in Kitgum district is one of the most popular sites for research because it has had a high number of cases according to health officials. Certain studies reportedly took body samples of children with NS, including blood, skin snips, urine samples, and brains for autopsies. Some children were also reported to have been taken to the U.S.A. for further research. For community members, all this research, perceived as invasive, has not produced concrete results on the aetiology of the disease, which leads to feelings of anxiety, research fatigue and suspicions around the motives of the foreign researchers. The reported lack of dissemination of results lead to bits and pieces of information being shared in the form of gossip and rumours. People further perceived the lack of dissemination as purposefully withheld information and reinforced the belief that foreign researchers were simply using their children’s body parts for profits. Complaints were present across all study villages without exception i.e. researchers came, took information and never returned with results. This has led to research fatigue, distrust and desperation about finding a cure or answer. “ I wonder if researchers are just making money with our children’s samples ”. (IDI, mother of NS child) As a consequence of the lack of dissemination in addition to the absence of concrete results, people stated their intention to refuse co-operation in further research. Suspicions about the government’s supposed ill-intentions towards the Acholi were increasing, limited dissemination further reinforced their suspicions of researchers and the government purposefully withholding information to cover up their involvement. illustrates how research results were being disseminated as gossip, which created an opportunity for rumours to be spread and alternative interpretations to be mooted. Similarly, inadequately planned dissemination as depicted in , proved futile and created even more confusion and distrust in the community. Box 3. Ambiguity and rumours regarding research results lead to suspicions towards foreigners At the funeral of one of the girls who had suffered from NS, a local political official who was seemingly very passionate about safeguarding her community, addressed the congregation saying “ Many Americans have conducted research on this disease and around August or September this year (2015) some Americans who did tests and check-ups on these children came back and said that they found some kind of blisters in the children’s brains . So , we think that this is some kind of planned sickness that whites make to get profit .” She also added that the district officials did not like her and the village health worker because they spoke the truth about this disease. When we looked more into these rumours regarding ‘blisters’ in the brain, a person from the ministry of health explained that it was true that some crystal-like formations had been seen in the brain autopsies of NS children, however there was an ongoing debate amongst the scientific community about whether these crystals were simply an artefact of long and poor storage of samples and questioned whether they were linked to the cause or aetiology of the disease as there had been reported delays in the samples being shipped to the Unites States. Due to the uncertainty about cause of these crystal-like formations, nothing could be reasonably disseminated to the people in the affected communities. The challenge here was that partial knowledge was being disseminated by unqualified members of the community thereby adding to the suspicions and distrust. Box 4. Poor preparedness before dissemination The lack of community engagement, but also the pre-mature dissemination of research findings among community members can generate rumours, confusion, frustration and research fatigue, as well as widening the knowledge gap. This was seen at the 2 nd international conference on NS in Gulu, held in July 2015. Many clinicians, neurologists and researchers had heard complaints about the lack of dissemination, and so during one field visit to Tumangu village during the conference, where several parents of affected children were gathered, scientists spontaneously decided to address the community and share results. Dissemination in this way was unplanned, and epidemiological and medical vocabulary that would not make sense to a lay person was used, for example, “a case-control study showed an association to onchocerciasis”. A local health professional spontaneously attempted to translate the scientists’ message into Acholi. This ‘dissemination’ was followed by a slew of questions from parents and carers of those affected who were seemingly confused whether it was the blackfly causing the illness or not and what they should do to cure their children. In 2017, the community distrust was also expressed when we asked about a planned dissemination by the MoH, which took place in December 2016. An aggregate of all research findings was reportedly compiled and village leaders were invited to attend. One village leader who attended the dissemination stated, “ Yes , last year (2016) a dissemination meeting was held in Pader (district) by people from the ministry for both Lango and Acholi sub region . They invited us and I went but we don’t believe those findings . I wasn’t very interested because I think that meeting was meant for making money for Christmas since Christmas was just around the corner . They told us this (NS) was happening because of the blackfly but we don’t believe them because blackflies have always been here; so why didn’t this condition come up then ? I think NS is happening because of the war because the places heavily affected are places where most killings happened . And why is it only in Northern Uganda and not in Western (where the current leader comes from) ?”
Given the timing of the NS epidemic, community members linked the aetiology of NS to the LRA war in several ways. The most commonly perceived cause was poisoning either through the pollution of air and water with gunpowder during the war or by toxins in the food distributed at IDP camps. The second most commonly stated cause was that the spirits of the deceased during the war were angry for not getting a respectful burial and so were taking revenge on their children by inflicting this disease on them. Illness interpretations also included perceptions related to the epidemic occurrence of the disease outbreak. Crowding was seen to have enhanced the spread of the disease, ‘ like measles , through the air ’ due to the high concentration of people in the camps. The perceived epidemic nature of NS also led to some not believing that it was a form of epilepsy, an illness well known to them as illustrated in the following quote: “ You researchers say this is epilepsy , but we know epilepsy … we used to have it before but it was only one or two persons in the entire village who were affected… but this is different . This came during the war , and this affects entire villages . This is not epilepsy , this is because of the war . (…) Why is it that the villages where most atrocities took place , are also the villages that have the most people affected (by NS) ? ” ( IDI , father of NS victim ). Some associated NS with changes in political power, as illustrated at the funeral of an NS victim: “ During Obote’s first regime , there was a disease called ‘two nailon’ [gonorrhoea] . Later he was over thrown by Amin and this sickness disappeared … When Obote came back to power again , there came HIV/AIDS and this continued in Museveni’s regime . And in Museveni’s government there comes this sickness , this strange disease called nodding syndrome .” (Sermon of a middle-aged Acholi Catholic priest) Many respondents had also heard about the blackfly as a potential cause from researchers and health officials. However, few agreed with this possibility. Many were not convinced as they logically reasoned that blackflies had always been around while NS was something new that had started occurring during the war. Some resented and distrusted the government and suspected they were the reason for this illness. This distrust was due to the perceived lack of response to the NS outbreak until 2012—almost 15 years after the first cases were noticed, and approximately six years after the war had ended. The government response was perceived as having been initiated after the political propaganda around the disease began circulating through the media attention. Besides the growing sense of suspicion towards the government, conveys the sentiment that governmental authorities did not want affected locals to say that NS existed and was increasing. This resentment explains the second uproar in the media in 2018, after the closing of the NGO, Hope for Humans. Hope for Humans was requesting governmental funds and encouraging the government to take over the responsibility. When this request was refused the NGO was unsustainable and closed down. It was evident that people felt that the government and the MoH were not acknowledging the severity of the problem. The media reported that there was an angry backlash from the northern political representatives when the MoH suggested that there were no more new cases of NS while their people strongly asserted that there were in fact new cases. While the MoH may not be wrong to say that there were no new cases of NS according to case definitions, community members still perceived all epilepsies that occurred during or after the war to be NS and thus thought that the MoH was covering up facts and dismissing the problems people in the north were facing. Box 1. Delayed response and political propaganda driving initial response A middle-aged male village health worker, Orach, lamented about the first three cases seen in 1998. He said when they first noticed this strange disease, he took the children to the health centre in Kitgum which referred them to the hospital whose fees they could not afford, and so no action was taken. A few years later, his own son also got NS and he actively tried everything to get care. He said that it was only in 2012, after the Kitgum district’s parliamentarian from the opposition party voiced people’s suffering that they were taken to Kampala, the capital city, for treatment. In an informal conversation, the parliamentarian explained that she highlighted the current leadership’s neglect of the children in the north and mobilised a bus full of 24 patients and parents to be taken to the main referral hospital in the capital city. She notified the president and the hospital staff that these children were on their way to be examined and that the children of the north should not be neglected. Orach was one of the parents on this bus with his son. Another parent, Atim, who was also on the bus explained that while on the way, the bus was intercepted by police and they were detained for two days without a reason. The police then escorted the parents and the 24 affected children to the hospital. At the hospital, the president met them and the media was there taking photographs of their children with the president. They were provided with meals and accommodation for the rest of their stay. This made parents suspicious once again and they wondered why the police were involved. “ We asked ourselves , ‘what is the government trying to hide ? ’ ” … After treatment at the referral hospital, Orach said that the children showed improvement. However, once they returned to their home villages, they could not be fed in the same way and the children’s condition deteriorated. A year later, his son died reportedly due to uncontrolled, repetitive seizures. He said that researchers took a sample of his deceased son’s brain for testing but he had not heard back from them three years later (2015). In 2017, when we met him again, he expressed distrust in the governmental system. He said, “ In the district here , (Kitgum) they don’t want us to say that such a disease exists or that it is increasing” . The political propaganda that drove the initial response to the outbreak influenced how NS became a tool for power both for politicians and for people in the community gaining resources through the epidemic. shows that when these services were abruptly stopped, feelings of resentment and distrust towards the government were reinforced. Box 2. Inconsistent interventions and suspicion A psychiatric nurse at the government hospital in Gulu, who was part of the initial interventions to address NS explained that after the political and media attention that NS received, outreach programs and clinics were established in 2012 by the government. There were severe food shortages at the time generally as people were slowly recovering from the war, and households with affected children were struggling even more. To cater for this, the government introduced a program according to which the households of the affected children were supplied with food along with the treatment for seizures free of charge. She said, “ NS is highly politicized so the community thinks that it is beneficial to have a child with NS . As people and the government are providing food , clothes , and money to these families , the Ministry of Health’s focus is on identifying Nodding properly because many people were claiming to have NS (when they did not have NS) . When this programme proved unsustainable , the government suddenly stopped providing food to NS families . There was no proper way of weaning them off ”. Consequently, the affected parents felt that “ the government does not care about us ”. However, some still had a different view of the government. While most community members were disheartened by the prospects of NS and felt angered, frustrated and neglected by the government, some believed that researchers coming to the area were government agents who were not trying to find a remedy for NS.
Delayed response and political propaganda driving initial response A middle-aged male village health worker, Orach, lamented about the first three cases seen in 1998. He said when they first noticed this strange disease, he took the children to the health centre in Kitgum which referred them to the hospital whose fees they could not afford, and so no action was taken. A few years later, his own son also got NS and he actively tried everything to get care. He said that it was only in 2012, after the Kitgum district’s parliamentarian from the opposition party voiced people’s suffering that they were taken to Kampala, the capital city, for treatment. In an informal conversation, the parliamentarian explained that she highlighted the current leadership’s neglect of the children in the north and mobilised a bus full of 24 patients and parents to be taken to the main referral hospital in the capital city. She notified the president and the hospital staff that these children were on their way to be examined and that the children of the north should not be neglected. Orach was one of the parents on this bus with his son. Another parent, Atim, who was also on the bus explained that while on the way, the bus was intercepted by police and they were detained for two days without a reason. The police then escorted the parents and the 24 affected children to the hospital. At the hospital, the president met them and the media was there taking photographs of their children with the president. They were provided with meals and accommodation for the rest of their stay. This made parents suspicious once again and they wondered why the police were involved. “ We asked ourselves , ‘what is the government trying to hide ? ’ ” … After treatment at the referral hospital, Orach said that the children showed improvement. However, once they returned to their home villages, they could not be fed in the same way and the children’s condition deteriorated. A year later, his son died reportedly due to uncontrolled, repetitive seizures. He said that researchers took a sample of his deceased son’s brain for testing but he had not heard back from them three years later (2015). In 2017, when we met him again, he expressed distrust in the governmental system. He said, “ In the district here , (Kitgum) they don’t want us to say that such a disease exists or that it is increasing” .
Inconsistent interventions and suspicion A psychiatric nurse at the government hospital in Gulu, who was part of the initial interventions to address NS explained that after the political and media attention that NS received, outreach programs and clinics were established in 2012 by the government. There were severe food shortages at the time generally as people were slowly recovering from the war, and households with affected children were struggling even more. To cater for this, the government introduced a program according to which the households of the affected children were supplied with food along with the treatment for seizures free of charge. She said, “ NS is highly politicized so the community thinks that it is beneficial to have a child with NS . As people and the government are providing food , clothes , and money to these families , the Ministry of Health’s focus is on identifying Nodding properly because many people were claiming to have NS (when they did not have NS) . When this programme proved unsustainable , the government suddenly stopped providing food to NS families . There was no proper way of weaning them off ”. Consequently, the affected parents felt that “ the government does not care about us ”.
The perceived link between NS, the war, forced displacement to government-protected camps, in addition to the overwhelming burden of caretaking under extreme poverty, the social inequality and ethnic tensions all enhanced distrust of the government. These factors directly created barriers to NS service delivery in terms of limiting care available in the private sector, increased distrust and reluctance to accept treatment and prevention for onchocerciasis , all relevant for managing NS . Some non-governmental health facilities, for example, the local Catholic missionary St. Joseph’s hospital in Kitgum, prefered not to treat NS patients due to the political nature of the disease. Reportedly, during the initial period when NS was getting political and media attention, the missionary hospital hosted a researcher who independently observed NS without informing them. After visiting one of the affected villages by himself, news reached the authorities and police tracked him down for questioning. The foreigner was reportedly arrested and deported for not following proper protocol and hospital employees were questioned. Whatever the veracity of the details of this and similar stories, it has led to sensitivity around accepting NS patients as illustrated by the following quote: “ We care for epileptic patients in this facility but for NS patients , we always refer them to Kitgum Government Hospital because NS has ‘political affiliations’ , and we are faith-based so we don’t want to mix politics and religion .” ( IDI , hospital staff ) What is interesting however, is how NS is distinguished from other epilepsies at hospitals, where NS and epilepsy were considered two separate medical conditions, whereas people in the community, perceived all epilepsies that occurred during or after the war as NS. Additionally, news of incidents like this spread through the community quickly and like any story travelling through the grapevine, it lost or enhanced some details allowing differing interpretations to arise. Some became suspicious of secrecy they observed or by the hidden agendas of researchers, the government or both. Despite the distrust of the government, most NS affected families still sought care in government facilities. While this behavior was seemingly counterintuitive, there were two main reasons for people to do so. Firstly, people were desperate for a cure as the burden of this disease was immense. Besides biomedical treatments, desperation had driven people to seek additional treatment options, including an array of traditional remedies through herbalists, spiritual healers and religious healers. This desperation was illustrated by a father who lost his son to NS. He expressed emphatically, “ Those who died are the ones that are cured ” implying that death among children with NS was often perceived as better than the continued suffering and disease-related hopelessness associated with NS within the context of poverty. Anti-epileptic drugs, when available, helped suppress symptoms for most patients and when the perceived benefit from them was greater than the cost, they continued to take the medication. A positive aspect of the biomedical health interventions in the area was that they were run and staffed by locals of the same ethnic group. So, while the community did not trust the government at large, they did trust the health professionals employed on a personal level. However, we also encountered a situation where one individual who had grown up in one of the villages there and came from a modest background, later was perceived as arrogant and driven by financial pursuits by community members after becoming successful. This individual was often used for sensitization by the MoH/government, which backfired as people did not trust in him despite their shared background and family history. While exploring community perceptions towards MDA and the distribution of Ivermectin, a drug distributed to treat and prevent onchocerciasis, the general impression was that more people were taking IVM now as compared to when it was first introduced. In addition to continuous sensitization, the research showed that people got a sense that the medication helped relieve symptoms and there was a better understanding of the side effects and why they occurred. However, some were still refusing to take the medication. In addition to common fears of side-effects, one reason for refusing up-take was that they did not trust the purpose of the medication. Some households perceived it to be a government strategy to reduce the population in the region. The village health worker who distributes IVM said, “ People argue that yes , this government seems to be having a plan to finish off the people of northern Uganda . Why is it that they are bringing these drugs here and not to his (current leader , Museveni’s) village ?” (IDI, female, ivermectin distributor)
Due to the spatial and temporal clustering of NS, most studies have been conducted in a limited number of villages since the war ended. The village of Tumangu, for example, in Kitgum district is one of the most popular sites for research because it has had a high number of cases according to health officials. Certain studies reportedly took body samples of children with NS, including blood, skin snips, urine samples, and brains for autopsies. Some children were also reported to have been taken to the U.S.A. for further research. For community members, all this research, perceived as invasive, has not produced concrete results on the aetiology of the disease, which leads to feelings of anxiety, research fatigue and suspicions around the motives of the foreign researchers. The reported lack of dissemination of results lead to bits and pieces of information being shared in the form of gossip and rumours. People further perceived the lack of dissemination as purposefully withheld information and reinforced the belief that foreign researchers were simply using their children’s body parts for profits. Complaints were present across all study villages without exception i.e. researchers came, took information and never returned with results. This has led to research fatigue, distrust and desperation about finding a cure or answer. “ I wonder if researchers are just making money with our children’s samples ”. (IDI, mother of NS child) As a consequence of the lack of dissemination in addition to the absence of concrete results, people stated their intention to refuse co-operation in further research. Suspicions about the government’s supposed ill-intentions towards the Acholi were increasing, limited dissemination further reinforced their suspicions of researchers and the government purposefully withholding information to cover up their involvement. illustrates how research results were being disseminated as gossip, which created an opportunity for rumours to be spread and alternative interpretations to be mooted. Similarly, inadequately planned dissemination as depicted in , proved futile and created even more confusion and distrust in the community. Box 3. Ambiguity and rumours regarding research results lead to suspicions towards foreigners At the funeral of one of the girls who had suffered from NS, a local political official who was seemingly very passionate about safeguarding her community, addressed the congregation saying “ Many Americans have conducted research on this disease and around August or September this year (2015) some Americans who did tests and check-ups on these children came back and said that they found some kind of blisters in the children’s brains . So , we think that this is some kind of planned sickness that whites make to get profit .” She also added that the district officials did not like her and the village health worker because they spoke the truth about this disease. When we looked more into these rumours regarding ‘blisters’ in the brain, a person from the ministry of health explained that it was true that some crystal-like formations had been seen in the brain autopsies of NS children, however there was an ongoing debate amongst the scientific community about whether these crystals were simply an artefact of long and poor storage of samples and questioned whether they were linked to the cause or aetiology of the disease as there had been reported delays in the samples being shipped to the Unites States. Due to the uncertainty about cause of these crystal-like formations, nothing could be reasonably disseminated to the people in the affected communities. The challenge here was that partial knowledge was being disseminated by unqualified members of the community thereby adding to the suspicions and distrust. Box 4. Poor preparedness before dissemination The lack of community engagement, but also the pre-mature dissemination of research findings among community members can generate rumours, confusion, frustration and research fatigue, as well as widening the knowledge gap. This was seen at the 2 nd international conference on NS in Gulu, held in July 2015. Many clinicians, neurologists and researchers had heard complaints about the lack of dissemination, and so during one field visit to Tumangu village during the conference, where several parents of affected children were gathered, scientists spontaneously decided to address the community and share results. Dissemination in this way was unplanned, and epidemiological and medical vocabulary that would not make sense to a lay person was used, for example, “a case-control study showed an association to onchocerciasis”. A local health professional spontaneously attempted to translate the scientists’ message into Acholi. This ‘dissemination’ was followed by a slew of questions from parents and carers of those affected who were seemingly confused whether it was the blackfly causing the illness or not and what they should do to cure their children. In 2017, the community distrust was also expressed when we asked about a planned dissemination by the MoH, which took place in December 2016. An aggregate of all research findings was reportedly compiled and village leaders were invited to attend. One village leader who attended the dissemination stated, “ Yes , last year (2016) a dissemination meeting was held in Pader (district) by people from the ministry for both Lango and Acholi sub region . They invited us and I went but we don’t believe those findings . I wasn’t very interested because I think that meeting was meant for making money for Christmas since Christmas was just around the corner . They told us this (NS) was happening because of the blackfly but we don’t believe them because blackflies have always been here; so why didn’t this condition come up then ? I think NS is happening because of the war because the places heavily affected are places where most killings happened . And why is it only in Northern Uganda and not in Western (where the current leader comes from) ?”
Ambiguity and rumours regarding research results lead to suspicions towards foreigners At the funeral of one of the girls who had suffered from NS, a local political official who was seemingly very passionate about safeguarding her community, addressed the congregation saying “ Many Americans have conducted research on this disease and around August or September this year (2015) some Americans who did tests and check-ups on these children came back and said that they found some kind of blisters in the children’s brains . So , we think that this is some kind of planned sickness that whites make to get profit .” She also added that the district officials did not like her and the village health worker because they spoke the truth about this disease. When we looked more into these rumours regarding ‘blisters’ in the brain, a person from the ministry of health explained that it was true that some crystal-like formations had been seen in the brain autopsies of NS children, however there was an ongoing debate amongst the scientific community about whether these crystals were simply an artefact of long and poor storage of samples and questioned whether they were linked to the cause or aetiology of the disease as there had been reported delays in the samples being shipped to the Unites States. Due to the uncertainty about cause of these crystal-like formations, nothing could be reasonably disseminated to the people in the affected communities. The challenge here was that partial knowledge was being disseminated by unqualified members of the community thereby adding to the suspicions and distrust.
The lack of community engagement, but also the pre-mature dissemination of research findings among community members can generate rumours, confusion, frustration and research fatigue, as well as widening the knowledge gap. This was seen at the 2 nd international conference on NS in Gulu, held in July 2015. Many clinicians, neurologists and researchers had heard complaints about the lack of dissemination, and so during one field visit to Tumangu village during the conference, where several parents of affected children were gathered, scientists spontaneously decided to address the community and share results. Dissemination in this way was unplanned, and epidemiological and medical vocabulary that would not make sense to a lay person was used, for example, “a case-control study showed an association to onchocerciasis”. A local health professional spontaneously attempted to translate the scientists’ message into Acholi. This ‘dissemination’ was followed by a slew of questions from parents and carers of those affected who were seemingly confused whether it was the blackfly causing the illness or not and what they should do to cure their children. In 2017, the community distrust was also expressed when we asked about a planned dissemination by the MoH, which took place in December 2016. An aggregate of all research findings was reportedly compiled and village leaders were invited to attend. One village leader who attended the dissemination stated, “ Yes , last year (2016) a dissemination meeting was held in Pader (district) by people from the ministry for both Lango and Acholi sub region . They invited us and I went but we don’t believe those findings . I wasn’t very interested because I think that meeting was meant for making money for Christmas since Christmas was just around the corner . They told us this (NS) was happening because of the blackfly but we don’t believe them because blackflies have always been here; so why didn’t this condition come up then ? I think NS is happening because of the war because the places heavily affected are places where most killings happened . And why is it only in Northern Uganda and not in Western (where the current leader comes from) ?”
Nodding Syndrome prevention and treatment in Northern Uganda have become central to the country’s political agenda . While disease control, as such, always has a political dimension, the multiple levels of ‘ambiguity’ of Nodding Syndrome has direct implications for further research and the control of this disease. Disease conceptions for NS, similar to epilepsy, are not fixed but constantly created and recreated from particular perspectives . The unknown aetiology of NS creates an opportunity for different avenues for reasoning and rationalising for community members, health workers and researchers alike. Among the Acholi in Northern Uganda this has contributed to distrust in government interventions and research projects alike, giving rise to rumours of secrecy and hidden agendas of the government against the Acholi people. This contributes to a challenging situation: if the government does not intervene, it is seen as neglect; and when it does, people are suspicious of the aid and the motives behind it. The war and perceptions of neglect and powerlessness have led to annihilation anxieties among the Acholi, which is a common phenomenon in authoritarian socio-political contexts . As with NS, other epidemics have reflected these regional and ethnic tensions. During the Ebola Virus Disease (EVD) epidemic in 2000, also occurring during the LRA war, the Acholi attributed the first case to the government intentionally planting the disease in order to harm them. This was reportedly done by the government when an infected corpse of a deceased Acholi soldier was sent to his family in the north, despite the government’s awareness about the Acholi tradition of washing and preparing the corpse for burial . The Acholi believed that the government knew that touching the corpse would spread the disease but they sent the corpse to them anyway. These suspicions and fears were confirmed when the president did not express remorse for the Acholi lives lost from EVD . Similarly, the HIV epidemic amongst the Acholi was also explained as an intentional effort by the government to spread the disease. Both men and women were reportedly raped by infected government soldiers from other regions in order to spread the disease . The NS epidemic, similarly, coincided with the LRA war against the ruling government. Government response to the outbreak was slow and when it finally occurred it was driven, and continues to be driven, by politicians and made part of the political agenda. The Acholi’s suspicions of the government and its prevention, treatment and research interventions are further fed by their sense of desperation and poverty and limited economic progress. Enduring decades of war, Northern Ugandans have shown resilience but the trauma from it has been embodied as distrust towards the national leadership and so a defensive stance towards initiatives made by the government is taken. The consequences of structural violence, political economy and poverty as embodied in ill-health and trauma are described in several texts . The added fear of being victimised is overshadowed with hopelessness . Another contribution to this distrust is the perceived lack of proper dissemination of research results. The ambiguity around aetiology, delayed dissemination, inconclusive results and lack of a cure for the disease, despite years of research and invasive collection of body samples, contributes to make dissemination a real challenge. The other challenge regarding dissemination is that research findings take time to analyse and may be published years after the data was collected. Research findings are generally published a few years after the data collection was conducted and by the time results are published most project funds have been spent and the research projects have ended. Such delays due to the structure of research projects and their funding are extremely problematic. It is crucial for funds to be kept for the dissemination of the research among locally affected populations at the end of the study—ethical committees and the Ministry of Health should make this an obligation. The general distrust of government motives can also lead people to dismiss all health interventions, including mass drug administration of IVM. This has not posed as a problem for onchocerciasis control yet, as Uganda has had a very strong vector control program since 2012 where breeding sites of blackflies in rivers have regularly been treated with larvicides , thus reducing blackfly populations that transmit the OV parasite. Adam Hendy, an entomologist who worked in the area from 2014 to 2016 also confirmed that blackfly populations were very low. However, if for some reason, blackfly populations increase and onchocerciasis control is dependent solely on IVM distribution, this can become a public health problem in Northern Uganda. Feelings of distrust were not limited to the government, but also directed towards foreigners, researchers, and Euro-Americans. The notion that foreigners came to Africa to harvest body parts for profit has been another long-standing belief, similar to rumours of blood stealing in Sub Saharan Africa . One example of such beliefs was documented during the EVD epidemic when individuals were taken to isolation units for treatment. The treatment units were isolated with tarp fences, preventing relatives from visiting or seeing patients inside the unit. If the patients died, medical safety protocol required that the bodies were instantly placed in a corpse bag and shifted to a burial ground near the airport. The protocol for such emergencies did not foresee for the family to be notified, nor were they allowed to see the body, which fed rumours . Inadequate community engagement in the protocol was experienced as secrecy from the perspective of the locals, amplifying feelings of suspicion towards international response teams . While NS control in Northern Uganda is complex and multi-layered, a consistent, continuous and clear response by the government and researchers would contribute to limiting the ambiguity surrounding NS and its interpretations. The government’s response has been inconsistent and driven by media attention and political propaganda to maintain political control and economic power. Top-down approaches to research with minimal community engagement and dissemination gives rise to more rumours and misinformation , which has exacerbated the mistrust and set up frameworks for the failure of future interventions in Northern Uganda. Government support needs to be comprehensive and consistent for trust to be built up again. This data has shown how crucial it is for the government and for international agencies to take into consideration the cultural context of locals and perceptions regarding the causes of NS. Lack of continuous information and engagement will fuel distrust. To intervene effectively, at least some of the ambiguity and uncertainty must be overcome. The first step would be to engage the community actively throughout the different stages of research.
Conducting an ethnographic study over a three-year period and use of multiple qualitative methods of data collection facilitated an in-depth exploration of NS, context, interventions and gaps in relation to community engagement in research and programming including how these fit within the politically sensitive Northern Uganda. Our findings should be interpreted in view of the following limitations: The qualitative nature of the study does not facilitate quantification of community perceptions and practices. However, use of multiple methods of data collection helped to triangulate our findings. The study covered only two districts that were affected by war, thus applicability of our findings to other areas especially those not affected by war may be limited. Additionally, it is possible that people from Kitgum district have politicized Nodding Syndrome more than other districts as the parliamentarian who first brought the attention in the media in 2012 about Nodding Syndrome came from and represented Kitgum district. Additionally, to strengthen the understanding of how politicization affects health interventions in particular communities, it would have been valuable to conduct fieldwork in another onchocerciasis-endemic area of Uganda where a different ethnic group was in majority and where they were not subjected to war and civil conflict, e.g. Masindi district in Western Uganda as comparison. However, inclusion of highly affected and less affected areas in this study increases possibilities for generalizability of our findings. Conclusion and recommendations Given the ambiguity around NS, and the political context in Northern Uganda, moving forward NS requires the building of trust, the de-politicization of response, and more clarity and transparency. Trust can be built by engaging the community and making them active participants in every stage of the intervention, be it research, service delivery for treatment and prevention, and sensitisation. In addition, community participatory implementation and research methodologies should be used that include continuous community involvement and feedback loops to address rumours and feelings of resentment. This is best achieved through the extended involvement of the community including day-to-day interactions with implementation staff. By creating continuous feedback loops, the sharing of information and engaging in active dialogue, ambiguities around treatment, prevention and the intention of the research will be reduced. Dissemination must be planned. Well-prepared sessions on interim research findings must be conducted at regular intervals despite inconclusive results. This could be a requirement from the Ugandan Ethics Committees and the national Council for Science and Technology for every research, particularly on NS.
Given the ambiguity around NS, and the political context in Northern Uganda, moving forward NS requires the building of trust, the de-politicization of response, and more clarity and transparency. Trust can be built by engaging the community and making them active participants in every stage of the intervention, be it research, service delivery for treatment and prevention, and sensitisation. In addition, community participatory implementation and research methodologies should be used that include continuous community involvement and feedback loops to address rumours and feelings of resentment. This is best achieved through the extended involvement of the community including day-to-day interactions with implementation staff. By creating continuous feedback loops, the sharing of information and engaging in active dialogue, ambiguities around treatment, prevention and the intention of the research will be reduced. Dissemination must be planned. Well-prepared sessions on interim research findings must be conducted at regular intervals despite inconclusive results. This could be a requirement from the Ugandan Ethics Committees and the national Council for Science and Technology for every research, particularly on NS.
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Acupressure versus NSAID for relief of orthodontic pain | 94fe232f-12d7-416b-be09-a2234cff18de | 11753302 | Dentistry[mh] | Almost all orthodontic patients experience some kind of pain at some point during their treatment. The prevalence of pain was found to range from 70–95%. It was considered one of the most common negative side effects of orthodontic treatment and a major concern for patients and clinicians as it could inversely affect the patients’ compliance or may dissuade them from continuing treatment . Pain could be elicited by many aspects of treatment: insertion of separators, use of leveling archwires or later on of heavy rectangular archwires, functional appliances, diverse active auxiliary components, or at the end by the debonding process . From previous studies, it seems that all these measures were associated with pain . The most common method to control pain is the use of analgesics and anti-inflammatory drugs , which, however, may interfere with the rate of tooth movement . Acupressure—sometimes called acupuncture without needles—is a nonpharmacological treatment method used in traditional Chinese medicine. It is a mechanical method of pain control that has been investigated in different medical and dental conditions . The mechanism is to apply gentle manual pressure to specific trigger points on the body to relieve pain. These trigger points called acupressure points or acupoints are thought to work by enhancing normal blood flow or by stimulating the release of serotonin and endorphins responsible for counteracting the sensation of pain . The goal of delivering painless orthodontic treatment has motivated research to examine new methods for pain relief. If effective in reducing orthodontic pain, acupressure would be a noninvasive, safe method that could be repeatedly practiced by children and adults as long as it is applied correctly. Therefore, this research aimed to compare the nonpharmacological intervention acupressure and a pharmacological intervention with the nonsteroidal anti-inflammatory drug (NSAID) ibuprofen (400 mg; Kahira Pharm. & Chem. Ind. Co., under license from Abbott Laboratories, Shobra, El Sahel, Egypt) with a control group on pain experienced by patients during the period of orthodontic teeth separation using elastomeric rings (Dentsply Raintree Essix, Sarasota, FL, USA). Study design, setting, and sample size calculation A single-centered three parallel arms, longitudinal, prospective, randomized controlled clinical trial was conducted to reveal the effects of acupressure or the NSAID ibuprofen for relief of pain from orthodontic elastomeric separators. For assessing the power of the study, G*Power software (Heinrich-Heine-Universität Düsseldorf, Germany) was used to find the accepting type I statistical error of 5% and apply 2‑tailed statistical tests. Based on Hsieh et al. , the sample size was 15 participants per trial group. To avoid and counteract possible dropouts of participants for any reason, the group size was increased to 25 participants per group . Thus, a total of 75 patients were needed for the study to have a group ratio of 1:1:1 (drug intervention 25, acupressure 25, and controls 25). Nine participants were dropped from the trial, whereby 5 participants did not practice the acupressure approach correctly, 2 did not show up again, and the other 2 forgot to complete the sheets. Eligibility criteria Age ranged from 12–25 years. Furthermore, they had to present with healthy gingival tissue, no allergy to any analgesics, no history of any asthmatic steroid medication, or any other systemic diseases related to the kidney, liver, or heart. Exclusion criteria Patients were not considered for the trial if there was previous orthodontic treatment, recent use of analgesics, any contraindications to NSAIDs, previous acupressure experience, inflamed gingival tissue, pregnancy, spacing between teeth, interproximal caries, or retained deciduous teeth. Participants A total of 101 patients from the Department of Orthodontics, Faculty of Dentistry at Mansoura University who were enrolled for orthodontic treatment were screened to be included in the study. The planning and presentation of the study were guided by the Consolidated Standards of Reporting Trials (CONSORT) 2010 flow chart . Approval for this randomized controlled trial was obtained from the ethical committee of the Faculty of Dentistry at Mansoura University (code: 05051217). Consent was obtained from the participants/parents before their recruitment in the trial, in a verbal and written manner. The examination and determination of eligibility criteria of each participant were performed by one examiner under the supervision of the trial coordinator. After applying the inclusion and exclusion criteria, 75 participants were randomly assigned to one of three groups to ensure that the size of the groups were similar. The participants of the same group practiced the same method of pain relief after the insertion of separators and until the next visit 7 days later. The CONSORT flow diagram is shown in Fig. . At the start of orthodontic treatment, all participants received Duraseps elastic separators (Dentsply) in preparation to place bands on all four first molars. Separators were placed using placement pliers. The separator was stretched and guided in a slow controlled motion between the first molar and the neighboring tooth mesially and distally until the separator passed the contact area. Randomization and concealment Central randomization was performed, and participant recruitment was done by phone. The random allocation sequence was concealed in an envelope and held centrally. Participants were randomly assigned to three different groups and blinding was done using the SNOSE (sequentially numbered opaque sealed envelopes) technique. Each advice sheet was tightly sealed in one of the opaque envelopes identical in color, size, and weight prepared for that purpose. After shuffling, the participants’ names were replaced by codes on the envelopes and then stored with the trial coordinator, who was responsible for the randomization process and opening of the envelopes after finishing the trial. Intervention The first intervention group was the NSAID group. The participants were instructed to read and apply the instructions of the advice sheet, dictating the use of ibuprofen (Kahira Pharm. & Chem. Ind. Co., under license from: Abbott Laboratories) 400 mg with up to 4 doses in the first 24 h after the insertion of the separators for controlling the orthodontic pain (1 pill every 6 h). The toxicity of this dose is far below the established toxicity level, which is 3500 mg . The second intervention group was the acupressure group. The participants received an advice sheet with instructions to practice acupressure by applying pressure to a defined acupressure point on the back of the hand to control orthodontic pain as often as needed for the first 24 h only after insertion of the separators. The point LI4 for facial pain control is located between the thumb and index digits of the hand at the center between the first and second metacarpal bones. The point was explained to the participants with the help of a drawing (Fig. ). The third group was the control group; no specific pain relief intervention following separator placement was performed. All the participants were instructed that an extra dose of analgesic should not be needed; however, if extreme pain sensation was felt after doing the pain-relieving approach, either ibuprofen or acupressure, a supplementary dose of paracetamol could be taken 4 h after from the previous pain-relieving approach performed to avoid overlapping of the two analgesic effects, or a minimum of 4 h from the insertion of the separators for the control group to be sure that the pain had not reduced yet. All the advice sheets had a blank field to include the supplementary medication type, dose taken, and time. The participants taking the rescue dose were considered drop-out participants. All participants were guided to immediately call by phone or come to the orthodontic department in case any adverse reactions developed. Outcome All the information needed for the participants was given to them using advice sheets written in Arabic. To ensure that the advice sheet instructions could be easily understood by the participants, a pilot study with 10 participants was carried out per group. The participants were asked to log the intensity of the pain that they experienced after the insertion of the separators using a pain diary and a visual analog scale (VAS) . The pain diary covered the timepoints: 4 h after insertion, after eating (10 h), after sleeping (18 h), after 24 h, and after 7 days. The rationale for this schedule was based on the onset of the analgesic action and the drug half-life times plus the short onset of time for acupressure known from the previous studies. The length of the visual analog scale was 10 cm but without intermediate digits, to avoid choosing a random number by the participant and to give the participant the chance to correctly indicate how severe the pain was on a solid straight line . The VAS score was determined by measuring in millimeters from the beginning left of the line to the vertical line that the participant marked on the horizontal straight line of the scale (Fig. ). After the advice sheet and the questionnaires were completed, the examiners made all measurements to the approximation of 0.5 mm with a ruler made of stainless steel. Inter- and intrareliability tests were performed to ensure that reliable results were obtained. Statistical analyses Data were analyzed using SPSS® software version 22 (IBM, Armonk, NY, USA). Interpersonal and intrapersonal reliability were tested using Cronbach’s alpha with a correlation coefficient > 0.80 to assess the reliability of the data. The normality of data distribution was tested using the Shapiro–Wilk test. As the data were parametric and normally distributed, it was described as mean ± standard deviation [SD]. A graphic presentation of data was performed using clustered bars and error bar charts. The analysis of variance (ANOVA) test was used to compare VAS between measurement times with the group as an independent factor. The Bonferroni test was used for multiple comparisons if significant differences were detected. A probability value of less than 0.05 was set for statistical significance. A single-centered three parallel arms, longitudinal, prospective, randomized controlled clinical trial was conducted to reveal the effects of acupressure or the NSAID ibuprofen for relief of pain from orthodontic elastomeric separators. For assessing the power of the study, G*Power software (Heinrich-Heine-Universität Düsseldorf, Germany) was used to find the accepting type I statistical error of 5% and apply 2‑tailed statistical tests. Based on Hsieh et al. , the sample size was 15 participants per trial group. To avoid and counteract possible dropouts of participants for any reason, the group size was increased to 25 participants per group . Thus, a total of 75 patients were needed for the study to have a group ratio of 1:1:1 (drug intervention 25, acupressure 25, and controls 25). Nine participants were dropped from the trial, whereby 5 participants did not practice the acupressure approach correctly, 2 did not show up again, and the other 2 forgot to complete the sheets. Age ranged from 12–25 years. Furthermore, they had to present with healthy gingival tissue, no allergy to any analgesics, no history of any asthmatic steroid medication, or any other systemic diseases related to the kidney, liver, or heart. Patients were not considered for the trial if there was previous orthodontic treatment, recent use of analgesics, any contraindications to NSAIDs, previous acupressure experience, inflamed gingival tissue, pregnancy, spacing between teeth, interproximal caries, or retained deciduous teeth. A total of 101 patients from the Department of Orthodontics, Faculty of Dentistry at Mansoura University who were enrolled for orthodontic treatment were screened to be included in the study. The planning and presentation of the study were guided by the Consolidated Standards of Reporting Trials (CONSORT) 2010 flow chart . Approval for this randomized controlled trial was obtained from the ethical committee of the Faculty of Dentistry at Mansoura University (code: 05051217). Consent was obtained from the participants/parents before their recruitment in the trial, in a verbal and written manner. The examination and determination of eligibility criteria of each participant were performed by one examiner under the supervision of the trial coordinator. After applying the inclusion and exclusion criteria, 75 participants were randomly assigned to one of three groups to ensure that the size of the groups were similar. The participants of the same group practiced the same method of pain relief after the insertion of separators and until the next visit 7 days later. The CONSORT flow diagram is shown in Fig. . At the start of orthodontic treatment, all participants received Duraseps elastic separators (Dentsply) in preparation to place bands on all four first molars. Separators were placed using placement pliers. The separator was stretched and guided in a slow controlled motion between the first molar and the neighboring tooth mesially and distally until the separator passed the contact area. Central randomization was performed, and participant recruitment was done by phone. The random allocation sequence was concealed in an envelope and held centrally. Participants were randomly assigned to three different groups and blinding was done using the SNOSE (sequentially numbered opaque sealed envelopes) technique. Each advice sheet was tightly sealed in one of the opaque envelopes identical in color, size, and weight prepared for that purpose. After shuffling, the participants’ names were replaced by codes on the envelopes and then stored with the trial coordinator, who was responsible for the randomization process and opening of the envelopes after finishing the trial. The first intervention group was the NSAID group. The participants were instructed to read and apply the instructions of the advice sheet, dictating the use of ibuprofen (Kahira Pharm. & Chem. Ind. Co., under license from: Abbott Laboratories) 400 mg with up to 4 doses in the first 24 h after the insertion of the separators for controlling the orthodontic pain (1 pill every 6 h). The toxicity of this dose is far below the established toxicity level, which is 3500 mg . The second intervention group was the acupressure group. The participants received an advice sheet with instructions to practice acupressure by applying pressure to a defined acupressure point on the back of the hand to control orthodontic pain as often as needed for the first 24 h only after insertion of the separators. The point LI4 for facial pain control is located between the thumb and index digits of the hand at the center between the first and second metacarpal bones. The point was explained to the participants with the help of a drawing (Fig. ). The third group was the control group; no specific pain relief intervention following separator placement was performed. All the participants were instructed that an extra dose of analgesic should not be needed; however, if extreme pain sensation was felt after doing the pain-relieving approach, either ibuprofen or acupressure, a supplementary dose of paracetamol could be taken 4 h after from the previous pain-relieving approach performed to avoid overlapping of the two analgesic effects, or a minimum of 4 h from the insertion of the separators for the control group to be sure that the pain had not reduced yet. All the advice sheets had a blank field to include the supplementary medication type, dose taken, and time. The participants taking the rescue dose were considered drop-out participants. All participants were guided to immediately call by phone or come to the orthodontic department in case any adverse reactions developed. All the information needed for the participants was given to them using advice sheets written in Arabic. To ensure that the advice sheet instructions could be easily understood by the participants, a pilot study with 10 participants was carried out per group. The participants were asked to log the intensity of the pain that they experienced after the insertion of the separators using a pain diary and a visual analog scale (VAS) . The pain diary covered the timepoints: 4 h after insertion, after eating (10 h), after sleeping (18 h), after 24 h, and after 7 days. The rationale for this schedule was based on the onset of the analgesic action and the drug half-life times plus the short onset of time for acupressure known from the previous studies. The length of the visual analog scale was 10 cm but without intermediate digits, to avoid choosing a random number by the participant and to give the participant the chance to correctly indicate how severe the pain was on a solid straight line . The VAS score was determined by measuring in millimeters from the beginning left of the line to the vertical line that the participant marked on the horizontal straight line of the scale (Fig. ). After the advice sheet and the questionnaires were completed, the examiners made all measurements to the approximation of 0.5 mm with a ruler made of stainless steel. Inter- and intrareliability tests were performed to ensure that reliable results were obtained. Data were analyzed using SPSS® software version 22 (IBM, Armonk, NY, USA). Interpersonal and intrapersonal reliability were tested using Cronbach’s alpha with a correlation coefficient > 0.80 to assess the reliability of the data. The normality of data distribution was tested using the Shapiro–Wilk test. As the data were parametric and normally distributed, it was described as mean ± standard deviation [SD]. A graphic presentation of data was performed using clustered bars and error bar charts. The analysis of variance (ANOVA) test was used to compare VAS between measurement times with the group as an independent factor. The Bonferroni test was used for multiple comparisons if significant differences were detected. A probability value of less than 0.05 was set for statistical significance. The results were considered reliable as the interpersonal and intrapersonal correlation coefficients were > 0.80. All measurements were parametric and normally distributed (Shapiro–Wilk test, p value > 0.05). For all measurement times, the highest pain was recorded in the control group. For the ibuprofen and the acupressure groups, no significant difference in pain was noted after 4 h, 18 h, and 1 week and these two groups recorded significantly lower pain than the control group. However, after 10 h, no significant difference in pain between the control and acupressure groups was noted, while the ibuprofen group showed significantly lower pain than these two groups at this timepoint (Table and Fig. ). For the acupressure group, the highest pain was noted at 10 h, followed by 4 h (with no significant difference between these times); pain then progressively decreased with time at 18 h and 24 h (with no significant difference between these times). The lowest pain was noted after 1 week. For the control and the ibuprofen groups, the highest pain was noted after 4 h, and then the pain progressively decreased over time at subsequent measurement times (at 10 h and 18 h there was no difference, while pain continued to decrease at 24 h) with the lowest pain being noted after 1 week. Comparisons between the observation times for each group are presented in Table and Fig. . Placement of elastic separators commonly results in pain . Thus, controlling pain is important as it supports the success of orthodontic treatment. This study aimed to reveal whether acupressure is as effective as ibuprofen medication for relieving orthodontic pain after the insertion of separators. Numerous previous studies on pain control showed no correlation between pain and patient’s sex, likewise in the present study, no sex correlation was found and the sexes were combined for the data analysis . Acupressure, a nonpharmacological pain-relieving approach, is becoming globally known and usable because this approach is seen as an effective, yet very conservative approach in comparison with the conventional use of pharmacological drugs. On the other hand, recently available evidence is largely inconclusive. In the present study, a clear pattern was seen for the onset of pain in the three groups: the pain reached its highest level after 4 h and then started to decrease progressively. Ngan et al. used a visual analog scale to evaluate the level of perception of discomfort by orthodontic patients after the insertion of separators and found a significant increase in pain after separator insertion at 4 h and 24 h. The course of decline in pain perception is considered to be an indication of a decrease of pain by time and/or the loss of separator elasticity. In the control group and also in the ibuprofen group, there was no significant difference in pain perception at 10 h and 18 h, even though the pain level in the ibuprofen group was less, indicating superior analgesic activity compared with the control group . In the acupressure group, there was no significant difference in pain perception at 4 h and 10 h and also at 18 h and 24 h, indicating a significant decrease in pain perception at the 10 h timepoint. This could be attributed to the patients developing increasing skills in performing the acupressure technique and becoming confident with its effectiveness and, thus, performing it more effectively and regularly. In the present study, the control group recorded the highest pain level among the three groups at all timepoints except after 10 h or during eating where the pain perception was not different between this group and the acupressure group. The acupressure group showed a nonsignificantly higher pain perception than the control group. This may partly explain the dropouts in the current study. Drop-outs in the control group mainly occurred because of intolerable pain sensation or the participants’ decision to stop orthodontic treatment from the beginning. The acupressure dropouts occurred when a participant did not fulfill the advice sheet properly (was not able to practice the maneuver correctly or was not compliant with doing the acupressure at all), so was excluded from the study. It is highly recommended to test the participant’s understanding of the acupressure technique and application before advising the participant to use it for relieving orthodontic pain. Acupressure and ibuprofen groups recorded significantly lower pain perception than the control group at 4 h, 18 h, and 1 week because the participants were instructed to perform acupressure at any time and an indefinite number of times. Thus, participants were under the umbrella of pain-relieving approaches all day long during the first 24 h. However, after 10 h or during eating, the ibuprofen group showed significantly lower pain perception than the other two groups. In the acupressure group, this could be attributed to the nature of the acupressure technique requiring frequent application. Patients at this early time may have not yet have found the appropriate rate for them to do the acupressure. Between the ibuprofen and the acupressure groups after 4 h, 18 h, 24 h, and 1 week, no significant difference in pain perception was noted. This could be considered a promising result confirming the effectiveness of the acupressure approach for orthodontic pain relief with a similar effect to that of ibuprofen especially at the time of the peak of pain that occurred 4 h after insertion of the separators. In the present study design, there were 4 doses of ibuprofen, once every 6 h, unlike other studies where participants received medication after 3 or 4 h after insertion of the separators. In summary, acupressure could be an important alternative analgesic for pain induced by orthodontic elastic separators. Further studies are recommended to study its effect on orthodontic pain induced by other procedures and to find out the appropriate rate of application. Orthodontic pain resulting from the insertion of elastomeric separators reached a peak after 4 h, then decreased reaching the minimum at the end of the first week. There was no significant difference in pain perception between participants using ibuprofen or acupressure at the time of the peak of pain (after 4 h), after 18 h, after 24 h, and after 1 week. Both the ibuprofen and the acupressure groups recorded significantly lower pain than the control group at most of the timepoints which supports the analgesic effect of the acupressure approach. Further studies evaluating the long-term effect of acupressure and its analgesic effect for other orthodontic treatment procedures are recommended. |
COVID-19: Impacts and Implications for Pediatric Practice | 2c8b018b-e3e6-4912-8f18-9559810da514 | 7346792 | Pediatrics[mh] | To obtain continuing education credit: 1. Read the article carefully. 2. Read each question and determine the correct answer. 3. Visit PedsCE SM , ce.napnap.org, to complete the online Posttest and evaluation. 4. You must receive 70% correct responses to receive the certificate. 5. Tests will be accepted until December 31, 2021.
1. Distinguish risk factors for coronavirus disease 2019 (COVID-19)–related morbidity and mortality and identify modes of transmission. 2. Appraise appropriate COVID-19 testing parameters and procedures for children. 3. Compare pediatric clinical presentation to adults with COVID-19 infection and recommend appropriate treatment measures. 4. State appropriate infection-control measures to reduce transmission. 5. Describe measures to reduce the risk of infection spread, mitigate adverse health effects in high-risk children, and to promote general health through preventive care. Posttest Questions Contact hours: 0.75 (CE offering is not eligible for Pharmacology) Passing score: 70% This continuing education activity is administered by the National Association of Pediatric Nurse Practitioners (NAPNAP) as an Agency providing continuing education credit. Individuals who complete this program and earn a 70% or higher score on the Posttest will be awarded 0.75 contact hours. Earn FREE CE Contact Hours Online Contact Hours for this online activity are FREE for NAPNAP Members. Nonmembers will be charged a fee of $10 to receive contact hours for this online activity through PedsCE SM . Payment can be made by credit card through PedsCE SM . 1. To take the Posttest for this article and earn contact hours, please go to PedsCE SM at ce.napnap.org . 2. In the Course Catalog, search for the name of the CE article. 3. If you already have an account with PedsCE SM , log in using your username and password. If you are a NAPNAP member, log in with your username and password. If you are a first-time user and NAPNAP nonmember, click on “New Customer? Click Here.” 4. Once you have successfully passed the Posttest and completed the evaluation form, you will be able to print out your certificate immediately.
The coronavirus disease 2019 (COVID-19) is caused by a novel Betacoronavirus strain in the severe acute respiratory syndrome family and is also referred to as severe acute respiratory syndrome coronavirus 2. COVID-19 is a zoonotic, enveloped, and single-stranded ribonucleic acid (RNA) virus that can quickly mutate and recombine, creating novel virus strains that spread from animals to humans. There are four strains of coronavirus circulating in humans, all thought to originate in bats. COVID-19 was first reported in Wuhan, China, with controversial reports on the nature of its origin. Coronaviruses are known for causing severe respiratory distress and respiratory failure, along with coagulopathies, multisystem organ failure, and death . The timeline (see ) of the COVID-19 outbreak is astonishing, as China first reported a cluster of cases of pneumonia in Wuhan on December 31, 2019. Just a month later, the World Health Organization declared a public health emergency of international concern and, by March 11th, assessed the crisis as a global pandemic . Response in the United States evolved rapidly as President Trump declared a state of national emergency under the Stafford Act on March 13th. Six days later, California became the first state to issue a statewide stay-at-home order. The following week, the U.S. National Guard was activated in all 50 states. By the end of March, New York City emerged as the epicenter in the United States, and by the end of April, the United States reported more than 1 million cases, the highest number in the world . With global response encompassing social, political, organizational, and economic realms, world leaders are struggling to keep pace with the rapid changes. Challenges within the global health care system and the health care profession itself include rationing supplies and services within health care systems, many of which were stretched to the brink before this latest viral outbreak . Considering the urgency of the situation, shortcuts on research are occurring to accelerate outbreak response and inconsistencies are loudly and publicly debated. Social media and lurid reporting bolster feelings of mistrust and panic buying while burgeoning conspiracy theories commandeer national dialogue. This is a time in history to prioritize global health and thoughtful pandemic preparedness. Pediatric Nurse Practitioners are ideally situated to be a trusted source of accurate health information for children. This continuing education article summarizes the latest evidence-based information on the rapidly developing coronavirus pandemic, equipping PNPs for clinical preparation and response. Declaration of a public health emergency has directed the entire health care system to initiate population-based triage, the management of massive numbers of individuals seeking care. Tasks in this strategy include providing crisis leadership, sustaining organizational response, and achieving disease containment. Triage-based categories include addressing susceptible, exposed, infectious, removed, and/or vaccinated populations, usually through an incident command system. Goals are divided into two phases (see ). Phase 1 addresses broad generic interventions based on best public health practices, whereas phase 2 management decisions are surge-dependent and specific to the five aforementioned triage categories .
Children are a population who have been spared the significant burden of severe illness. To date, two studies ( n = 2,143 and n = 171) have described similar COVID-19 findings in pediatric patients. Boys are more commonly affected than girls, and most children were either asymptomatic or mildly symptomatic. Children aged younger than 3 years and those with congenital heart disease seem to be disproportionately impacted . Social determinants of health are emerging as a predictor of health disparity in COVID-19, many of which impact pediatric populations. Essential workers are less likely to be able to work from home and financially tolerate furlough. Persons with crowded housing, inconsistent access to care, chronic conditions, and high-stress levels impacting immune function are more susceptible to adverse outcomes as are those who experience racial or ethnic prejudice and/or discrimination . People of color, particularly African Americans, experience more serious COVID-19-related morbidity and mortality. Although African Americans make up 13% of the U.S. population, they account for approximately 30% of deaths, and up to 75% of COVID-19-related deaths in Chicago. Asian Americans show similar disparity at 18% of the U.S. population and 23% of COVID-19 deaths . Other populations at significant risk include older adults (> 65 years of age), persons with underlying medical conditions (e.g., asthma, cardiovascular disease, kidney disease), persons with immunocompromise, persons with severe obesity (body mass index > 40), persons with diabetes, persons undergoing dialysis, and persons residing in long-term care or nursing homes . Care must be taken to ensure the equitable, transparent provision of services during this pandemic.
COVID-19 is thought to spread mainly from person-to-person, primarily through close contact and droplet exposure from distances of 6 ft or less . Children carry the COVID-19 virus in the upper respiratory tract, making it easier to spread in childcare centers, schools, and homes, in which pediatric respiratory hygiene is inconsistent and problematic . R 0 (pronounced R-naught) is the average number of secondary cases attributable to an index case. In other words, it is the average number of persons someone with COVID-19 is predicted to infect. R 0 estimates for COVID-19 range from 2.0 to 5.7. Experts project 82% of the population needs immunity (antibody-induced or vaccine acquired) to stop transmission and achieve herd immunity . Early analysis suggests active public health surveillance, contact tracing, quarantine implementation, and coordinated social distancing efforts are critical in stopping the spread of COVID-19 . As of June 25, 2020, there were no confirmed cases of COVID-19 intrauterine transmission, although there were concerns over possible correlation to miscarriage, intrauterine growth restriction, and preterm delivery . However, in the weeks following this report, there is growing evidence maternal-fetal transmission is occurring . Unlike earlier outbreaks of severe acute respiratory syndrome, COVID-19 yields fewer maternal mortalities . COVID-19 outcomes of pregnant women are similar to women who are not pregnant, including the need for intensive care. As of May 1st, seven maternal deaths have been reported . There is currently no evidence to suggest COVID-19 transmission is foodborne, although early reports indicate the virus can live up to 24 hr on cardboard and paper (i.e., food packaging containers) and up to 3 days on harder surfaces . Current advice to reduce transmission associated with grocery shopping or take-out food includes handwashing before and after handling food packaging, removing packaging before eating, limiting trips to the grocery store, and ensuring food preparers (including grocers and restaurants) are complying with health guidance such as wearing masks and screening workers for illness . There are no reports of domestic pets as vectors, although one tiger at a New York City zoo tested positive . If persons are ill with known or suspected COVID-19, it is wise to self-isolate from pets if possible. To lower the risk of transmission, dogs should be walked on a leash, keeping a 6-ft distance from other people and animals. Crowds should be avoided, and pet owners should not allow strangers to pet their animals. If a pet shows signs of illness, the veterinarian should be called for further instruction as opposed to arriving unannounced at an animal clinic .
Pediatric health care providers have always demonstrated expertise in promoting general holistic health, and now that task is more critical than ever as persons with preexisting medical conditions are disproportionately affected by adverse outcomes from COVID-19. offers strategies for targeted health interventions to optimize health and mitigate potential serious and life-threatening outcomes associated with COVID-19 infections. Nonpharmaceutical interventions (NPIs) are actions, apart from immunization and medication administration, that people and communities can take to help slow the spread of illness. The goals of NPIs are to prevent and/or minimize morbidity and mortality while minimizing social disruption and economic effects. Timing is crucial to ensure NPIs are applied with the least restrictive measures which provide the greatest public health benefit . The challenge of NPIS is that evidence of efficacy is always retrospective. Evidence concerning NPIS implemented to mitigate the spread of COVID-19 in the United States is to date, inconclusive, although early analysis conducted by is promising (see ). Social distancing (e.g., maintaining a physical distance in public at a minimum of 6 ft from persons not living together in the same household) has emerged as a critical NPI to slow the spread of COVID-19 . Families can be equipped by health care providers who emphasize the importance of promoting adherence. Role modeling from parents and other adults in the home is an effective way to encourage children to adhere to public health guidelines. Parents should emphasize personal responsibility, especially with adolescents, by establishing clear expectations and firm guidelines with instruction, including ways in which a lack of personal responsibility can adversely impact the lives of others. Families should also consider postponing visits to see older family members or grandparents and consider the use of technology to maintain emotional and relational connections . On April 3, 2020, the Centers for Disease Control and Prevention (CDC) departed from previously issued guidance with a broad recommendation for anyone aged over 2 years to wear face masks or coverings while in public. This guidance does not replace recommendations for social distancing or personal hygiene measures to control the spread of COVID-19 . Persons excluded from mask usage include babies aged less than 2 years, and persons who have trouble breathing, are incapacitated, or are unable to remove a mask without assistance. Mask use is more effective in protecting others from the spread of viral pathogens than protecting the wearer from infection. Ideal fabrics for do-it-yourself masks include denim, canvas, and paper towels, with scarves as a last resort. Layering adds potential protection but also can decrease the ability to breathe easily . In general, surgical masks and N95 respirators should be reserved for health care workers and other first responders. In health care settings, N95 masks should be reserved for high-risk aerosolizing procedures such as intubation and endotracheal suction and high-risk health care workers, including those with a history of asthma. The use of expired N95 masks may be acceptable in some circumstances. Fit-testing and seal-check are recommended for all N95 mask use, expired or not . The straps and bridge of the nose are usually the first areas to break down and should be visually inspected before use. To preserve masks and maximize usage, longer usage is preferred over reuse. A face shield used over a mask is preferred and may help extend the life of the mask . Lack of adequate personal protective equipment (PPE) has been a widely publicized and broadly discussed concern of health care providers, first responders, and essential workers. Ideal PPE when caring for a patient with known or suspected COVID-19 infection includes: a new N95 mask, gown, medical-grade gloves, and eye covers and/or a face shield . Proper donning and doffing of PPE are essential to prevent viral spread. Institutions should take care to implement protocols and training to equip personnel adequately. Hand hygiene should be performed before and after removal, and masks should be removed by the straps and handled with gloves. If PPE is limited or not available in a health care setting, usage should be reserved for high-risk persons (e.g., persons aged > 60 years, with chronic medical conditions, or pregnant) or those performing high-risk aerosolizing procedures such as intubation, endotracheal suction, or cardiopulmonary resuscitation. Limiting visitors in the health care setting can be a measure to reduce PPE usage . The CDC has issued guidelines for reuse of surgical gloves, masks, and other PPE should new items not be available. Homemade PPE should be used as a last resort. The CDC has a PPE burn rate calculator tool available online to help estimate usage and ordering needs for health care settings . Frontline personnel and essential workers are concerned about COVID-19 transmission to family members and household contacts. Self-quarantine should be considered, particularly if there are persons in the home at a high risk for adverse outcomes from COVID-19 . Several hotel chains are offering free lodging to frontline personnel, and many other community efforts include the donation of vacation homes or recreational vehicle use. If self-isolation is not possible, a separate room and bathroom are ideal if available for symptomatic persons, with delivery of meals using disposable plates and utensils. Frontline workers should remove all clothing and shower at their place of employment if possible. Alternatively, stripping clothing in the garage or designated entry spot of the home while placing soiled clothing in a garbage bag for laundering is preferred. Shoes should be removed and placed in a plastic bin at the home entrance. Cleaning soles of shoes with bleach is not recommended, as it may increase the risk of exposure. Frontline workers should regularly self-monitor for symptoms, including temperature, and promptly report any potential signs of illness . Evidence is still emerging on the efficacy of these efforts, but early results point to handwashing, disinfecting carefully, avoiding sharing rooms and surfaces, managing home deliveries with caution, and ensuring adequate ventilation as most efficacious. Health care providers can help families plan for modifications of behavior and factors in the home environment with assistance in problem-solving to overcome barriers . In addition to consideration in the home setting, careful attention should be given to measures within the health care setting to minimize the risk of nosocomial infection (see ).
The gold standard of diagnosis for COVID-19 remains the reverse transcriptase-polymerase chain reaction (RT-PCR) using a nasopharyngeal swab, which demonstrates greater reliability over salivary or oropharyngeal specimen analysis . RT-PCR positivity is estimated to persist approximately 3 weeks beyond the onset of illness, indicating only the detection of viral RNA and not necessarily viable transmittable virus . At the end of May 2020, the United States is performing approximately 150,000 tests per day, with a daily goal of 500,000. Nationally, the positivity rate is around 20%, whereas Germany is reporting 6% and South Korea 3%. Positivity rates of more than 10% indicate less than ideal conditions and inadequate testing . Currently, there are approximately 70 assays commercially available with wide variability in length of testing and significant supply chain issues affecting the availability of cotton swabs, reagents, and other items necessary to complete testing. As rapid point-of-care tests emerge on the market (currently there are three), they arrive with a disadvantage of threats of inconsistency in reporting, creating more challenges with contact tracing. Currently, sensitivity and specificity vary widely and need further investigation . In clinical cases with a high index of suspicion and an initial negative nasopharyngeal RT-PCR, repeat testing should be pursued . Testing of children is variable by region related to state and county guidelines, testing availability and accessibility, and community prevalence. Time estimations of RT-PCR positivity and seroconversion are still unknown in children because largely adult populations have been studied to date. Some concern has emerged after reports of persistent polymerase chain reaction in stool specimens, suggesting possible implications for high-risk caregivers of children who need assistance with elimination needs . Serology testing for COVID-19 antibodies is rapidly emerging to explore individual immunity as well as the use of convalescent plasma in therapy for persons with active infection. The Food and Drug Administration (FDA) issued rapidly changing guidance on antibody testing, initially waiving the need to apply for an emergency use authorization but later requiring application within 10 days of appearance on the commercial market. If the test does not meet FDA standards, testing must be suspended . Experts advocate for a thoughtful, deliberate approach to ensure the utmost standards of scientific rigor and safety to guide high-stakes policy decisions . Barriers to testing are influenced by social determinants of health. Although the federal government passed legislation to cover the cost of COVID-19 testing, the cost of care associated with the diagnostic test may not be covered. Locations of testing centers should be accessible to the community, and drive-through testing centers should make accommodations for those who do not have a car . Testing times should provide flexibility in consideration of employment hours of essential workers. Efforts should be made to eliminate racial or ethnic discrimination while providing reassurance and anticipatory guidance to counter the fear of stigma resulting from a positive test. Many primary care systems are severely impaired, and many overwhelmed emergency centers may turn patients away. There is much work to be done to ensure equitable access for all to COVID-19 related care .
It appears children present with similar symptoms described in adults with active COVID-19 infection, although most are either asymptomatic or mildly symptomatic. In late April 2020, the CDC added six symptoms now believed to be associated with COVID-19, including chills, shivering, muscle aches, headache, sore throat, and a loss of taste and/or smell . These were added to previously identified symptoms of fever (91%–100%), cough (43%–80%), and rhinitis (33%–60%); 50%–80% of reported cases reported an ill family contact and 30% reported nosocomial contact . Although much has been discussed in the media concerning gastrointestinal symptoms as a pediatric presentation, the reported study referenced had five subjects, leaving much to be discovered . Emerging characteristics of serology and radiologic findings are listed in . Recent developments include concern about what is being called “COVID-toes.” Initially, dermatologists had concern for children with preexisting skin conditions, particularly those taking biologics or immunomodulators, who might be at increased risk for COVID-19-associated morbidity and mortality. Anecdotal reports were channeled to a registry development with the Global Rheumatology Alliance, in which more organized reports of pernio-like lesions on the toes began to coalesce. These lesions are characteristic of chilblains but without any cold exposure. Children report a burning sensation, pain, and/or tenderness lasting approximately 2 weeks. There is no correlation currently between dermatologic manifestation and severity of illness . As skin eruptions are common with viral illnesses of childhood, it is important to reassure parents COVID-toes seem to be an uncommon occurrence and to seek care with any health concerns . Concerned providers may report possible cases to http://www.aad.org/covidregistry . In addition, of concern are reports of a Kawasaki-like syndrome (referred to by the CDC as a multisystem inflammatory syndrome in children [MIS-C]) in 15 children aged 2–15 years hospitalized in New York City . Although none of these children have died related to MIS-C, five have required ventilator support, and six have died of other COVID-19 complications. Reports of MIS-C in Europe include 20 cases in Italy, 20 in Paris, and 12 in Britain . Some children appear to have signs of initial recovery, followed by a secondary inflammatory response. Clinical implications include increased vigilance of potential manifestations of systemic vasculitis with appropriate clinical assessment and public health reporting for COVID-19 . Parents can be reassured MIS-C still appears quite rare as a complication, and in and of itself, is not contagious . Other vascular complications include higher than previously indicated coagulopathies, possibly initiated by a cytokine storm. Retrospective autopsy findings suggest mortality related to undiagnosed deep vein thrombosis. Further exploration is needed to investigate the molecular mechanism, incidence, and clinical implications of these findings .
The National Institutes of Health published the first COVID-19 Treatment Guidelines in May of 2020. There are some special considerations for pediatric populations, but most of the guidance includes statements iterating that insufficient data exists for or against the use of pharmacological therapies to treat COVID-19 infections in children . Treatment mainly consists of supportive care with the provision of sufficient fluid and calorie intake, along with oxygen supplementation and airway support. Most cases appear to be mild and can be treated at home following clinician determination of minor illness with appropriate anticipatory guidance and evaluation of available resources. Vitamin D supplementation may play a role in reducing the risk of COVID-19 infections, but there is insufficient evidence to support a universal recommendation for children . Children who are ill enough to require hospitalization need observation for the progression of respiratory distress, multisystem organ failure, and development of secondary nosocomial infections . Other COVID-19 pharmacological treatment explorations include monoclonal antibodies, protease inhibitors, and RNA synthesis inhibitors . In particular, chloroquine has been widely publicized and publicly debated. Emerging recommendations include prioritizing available supply for rigorous, scientific clinical trials, preventing treatment interruptions for those on chloroquine for chronic rheumatic diseases, and provision of clear messages with transparent and accurate interpretation of available data concerning COVID-19 treatment . If a child has a laboratory-confirmed or clinically suspected case of COVID-19, isolation should be initiated. Discontinuing isolation can be test-based with two or more negative tests (with emergency use authorization approval from the FDA) more than 24 hr apart and meeting requirements for symptom-based strategy. If testing is not available, isolation may be discontinued solely with a symptom-based strategy after a minimum of 10 days from the onset of symptoms and more than 3 days from recovery (defined as a minimum of 72 hr afebrile without antipyretics and improvement in respiratory symptoms ).
The world is waiting with bated breath for a COVID-19 vaccine. With more than 100 potential vaccines in development, safety, and scientific rigor in the process will need to take the highest priority . Many approaches are being studied, including live-attenuated, inactivated, subunit, recombinant, viral vector, and deoxyribonucleic acid vaccines . Vaccine development is a process that customarily takes over 20 years, but for COVID-19, it is being attempted in 12–18 months. Comparatively, other vaccines for children have gone through rigorous clinical trials with more than 70,000 subjects studied over 4 years or more, a difficult bar to clear in these conditions. In biologics, the process is the product, and it is essential the process is the same for every dose . On May 4, 2020, the National Institute of Allergy and Infectious Disease announced the Human Epidemiology and Response to severe acute respiratory syndrome coronavirus 2 study. More than 6,000 children in 2,000 families currently enrolled in National Institutes of Health-funded pediatric research in 11 cities will participate in the effort to provide answers as to why most children with acute COVID-19 infection are not seriously ill. Families will be studied remotely with caregiver collection of specimens. Questions to be addressed include (1) do infection rates differ in children with asthma?, (2) how many children infected with COVID-19 develop symptoms?, and (3) are children resistant to COVID-19 infection? . Primary care access has been severely disrupted by restrictions implemented to prevent COVID-19 transmission. Challenges include limited PPE, limited availability of COVID-19 tests, patient workflow disruptions with closed waiting rooms and drive-through services, dramatic patient census drops and revenue shortfalls, and parental fears resulting in hesitance to present for care. In addition, rapid changes in telehealth in the last 2 months have exceeded changes made in the last two decades, with many practices quickly adapting from little-to-no telehealth to most services being delivered remotely . Long-term health impacts and outcomes remain to be seen.
Many pediatric nurse practitioners (PNPs) have been called upon to care for young adults, converting inpatient critical care units to house persons aged into their 30s . In times of emergency, this may be necessary. The National Association of Pediatric Nurse Practitioners (NAPNAP) asserted this is appropriate in certain circumstances but clarified certain conditions for consideration including (1) individual state nurse practice acts should be consulted and followed, (2) the PNP has education and training to give appropriate care to the assigned patient, (3) safe harbor protections are in place to protect the PNP from being forced to accept unsafe assignment, and (4) care will transition to an adult provider as soon as possible . Early estimates suggest measles vaccination rates have fallen by up to 60% since the onset of the COVID-19 pandemic . PNPs play an important role in promoting vaccination by encouraging and equipping families to stay on schedule to avoid vaccine-preventable illness . NAPNAP recommends innovative solutions to provide safe opportunities to keep vaccination schedules on time including (1) separating well and sick visit hours, (2) staggering appointment times, (3) closing waiting rooms, (4) reminding families about upcoming vaccines, (5) using every patient encounter as an opportunity to administer vaccines, and (6) administering as many simultaneous vaccines as possible . Schools are struggling to adapt rapidly, making high-stakes decisions with the little information available. The American Academy of Pediatrics issued guidance regarding return to school to shape conversations around holistic health and equity . Specific guidance provided includes overarching principles of flexibility to respond to quickly changing information in individual communities, advocacy for vulnerable and disadvantaged children, equity in school inclusion, and policies to support the overall health of children, their families, and their communities . NAPNAP also released a statement urging leaders and policymakers to prioritize planning and funding efforts to allow children to return to school safely as soon as possible. The impact of widespread school closures means millions of children are left without a safety net for critical support services, increasing widening disparity gaps, enhancing the potential for online exploitation of children, and growing concerns over the rise of mental health distress following prolonged isolation as well as distress emerging from rising tensions surrounding discrimination, racism, and prejudice . The world has changed in the weeks after the rapid spread of COVID-19 on a scale similar to that after the September 11 attacks. This pandemic is likely to change society in several ways, with long-term implications still largely unknown. Professional experts in science, medicine, nursing, economics, business, journalism, and others are offering professional opinions of their expectations of world changes and paradigm shifts . PNPs play a critical role in navigating significant amounts of changing information to help equip families to keep their children healthy and safe in these uncertain times. Important considerations for children include sharing everyday preventive health behaviors; promoting physical activity; maintaining social connections; watching for signs of stress, anxiety, and depression; and promoting adequate support systems issued a statement concerning child health and wellness during COVID-19. Recommendations for families include (1) supporting children as they ask questions about the pandemic, (2) close monitoring of child health and well-being with prompt contact of primary health care providers if changes are noticed, and (3) continuing to seek care in-person or using telehealth to maintain well visits and immunization schedules while receiving anticipatory guidance and necessary screenings. Recommendations for providers include (1) increasing the use of telehealth and telemedicine, (2) designing office experiences to support social distancing in a developmentally appropriate way, (3) increasing access to hand sanitation, (4) providing masks as indicated, (5) ensuring PPE is available for all staff, (6) advocating for mental health awareness and connection to resources, (7) referring families to credible sources of health information, (8) reminding families to present for well care, and (9) considering participation in research efforts. PNPs will need to continue to be active learners, adaptive and flexible while serving as trusted sources of information for families with children who concerned about immediate and long-term impacts and implications of COVID-19.
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Factors associated with stellate ganglion block success in recurrent ventricular arrhythmias | 641f5445-20f7-4f2b-88ae-f99eeafd62ab | 11769651 | Surgical Procedures, Operative[mh] | Ventricular tachycardia (VT) and ventricular fibrillation (VF) are life‐threatening conditions that are often challenging to treat. One potential target for the acute treatment of VT/VF is suppression of the sympathetic nervous system, since autonomic tone contributes to the initiation of ventricular arrythmias. An emerging treatment option is percutaneous stellate ganglion block (SGB) which temporarily reduces efferent sympathetic outflow to the myocardium, thereby reducing ventricular arrythmia burden. , SGB can be a safe and useful treatment for the acute suppression of refractory VT/VF , ; however, there is little research on the predictors of its success. We sought to examine differences in SGB effectiveness by patient and procedural characteristics, including aetiology of cardiomyopathy, type of arrhythmia, laterality of block, and the use of inotropes and mechanical support. In addition, we attempted to identify predictors of successful SGB at 24 h in a large multicentre registry.
Patient registry The registry included patients at Duke University Medical Center (Durham, USA) and Institute of Clinical and Experimental Medicine (IKEM) in Prague, CZ who were ≥18 years old and underwent SGB for treatment of refractory VT/VF between 2016 and 2022. This study utilizes the same registry as a recent investigation of SGB success and safety. Refractory VT/VF was defined as 3 or more episodes of the ventricular arrythmia requiring treatment within the 24 h prior to SGB. The VT/VF was considered refractory to treatment based on the clinical judgement of the primary team once the patient failed a combination of antiarrythmics, beta‐blockade, intubation/sedation, and/or ablation. There were no pre‐specified interventions that all patients required to be eligible for SGB. SGB was performed at bedside with ultrasound guidance by an anaesthesiologist or cardiologist. Technical details and safety considerations of SGB have been previously reported. This study was approved by both the Duke University and IKEM institutional review boards. Procedure details SGB was performed at bedside with ultrasound by an anaesthesiologist or cardiologist. Cardiologists were always present for SGB; however, at IKEM, the procedure was primarily conducted by cardiology while at Duke it was primarily conducted by anaesthesia. Technical and safety details can be found in previous review data. Once the injection needle was next to the stellate ganglion, 8–12 mL of local anaesthetic was then injected. Bilateral SGB was always attempted unless the patient was awake and not protected by intubation from bilateral recurrent laryngeal nerve paresis, or if a central line was in place that prevented the block. For unilateral SGB the left side was always given preference. If bilateral SGB was performed, both sides were done within 1 h. For repeat injections, if the initial procedure was unilateral, a unilateral SGB on the same side was attempted if bilateral block was still not feasible. If the initial block was bilateral, the repeat SGB was also bilateral. Clinical data Data were collected from telemetry, cardiac implanted electronic devices, the electronic medical record and SGB procedural notes. Variables collected included age, sex, ethnicity, co‐morbidities, cardiac implantable electronic devices (CIED) status, VT/VF type and morphology, presence of mechanical circulatory support, inotrope use, cardiogenic shock, catheter ablation procedure (prior to SGB), antiarrhythmic use, beta blocker use and dose, left ventricular ejection fraction, and serum creatinine. Regarding morphology of arrythmia, data were captured via CIED and telemetry, and patients were categorized into two groups, monomorphic/polymorphic VT and VF. In the course of their electrical storm, if patients exhibited both VT and VF, they were categorized as VF for the purpose of statistical analysis. Co‐morbidities examined included the aetiology of cardiomyopathy, atrial fibrillation, and acute myocardial infarction. Procedural characteristics included anaesthetic used (lidocaine, bupivacaine, and ropivacaine), laterality (left‐sided, right‐sided, or bilateral) and repeat injections. Primary outcomes The primary outcome of the initial analysis of this database was the change in VT/VF burden and defibrillations before and after SGB. This manuscript expands on the initial analysis by examining a new primary outcome of absence of VT/VF at 24 h post SGB. This was defined as zero episodes of ventricular arrythmia in the period 24 h after SGB. The secondary outcomes of interest were VT/VF event rates and shocks before and after SGB. VT/VF events before and after SGB were ascertained via manual review of continuous telemetry recordings or device interrogation for patients with CIED. A VT/VF episode was defined as an episode lasting greater than 30 s or an episode that required treatment with a shock. Both implantable cardioverter defibrillator (ICD) and external shocks were counted as shocks for the analysis. Statistical analysis First, non‐parametric tests (Mann–Whitney U test) were used to compare the number of VT/VF episodes, and recorded number of shocks between cohorts at 24 and 48 h pre and post SGB. These analyses were utilized to compare outcomes based on cardiomyopathy aetiology, arrhythmia aetiology, laterality of SGB, presence of inotropes, and presence of MCS. Additionally, repeat injection rates and in‐hospital mortality were examined using chi‐squared tests. In the next portion of the analysis, binary logistic regression was used to examine variables associated with the above primary outcomes. The regression included covariates age, sex, academic center/site, implantable cardioverter defibrillator (ICD) status (CRT‐D/ICD present or not), ischaemic cardiomyopathy (ICM), left ventricular ejection fraction (LVEF), block location (unilateral vs. bilateral), arrhythmia type (VT vs. VF), and intubation status. Statistics were done using SPSS V26 (IBM, Armonk, NY).
The registry included patients at Duke University Medical Center (Durham, USA) and Institute of Clinical and Experimental Medicine (IKEM) in Prague, CZ who were ≥18 years old and underwent SGB for treatment of refractory VT/VF between 2016 and 2022. This study utilizes the same registry as a recent investigation of SGB success and safety. Refractory VT/VF was defined as 3 or more episodes of the ventricular arrythmia requiring treatment within the 24 h prior to SGB. The VT/VF was considered refractory to treatment based on the clinical judgement of the primary team once the patient failed a combination of antiarrythmics, beta‐blockade, intubation/sedation, and/or ablation. There were no pre‐specified interventions that all patients required to be eligible for SGB. SGB was performed at bedside with ultrasound guidance by an anaesthesiologist or cardiologist. Technical details and safety considerations of SGB have been previously reported. This study was approved by both the Duke University and IKEM institutional review boards. Procedure details SGB was performed at bedside with ultrasound by an anaesthesiologist or cardiologist. Cardiologists were always present for SGB; however, at IKEM, the procedure was primarily conducted by cardiology while at Duke it was primarily conducted by anaesthesia. Technical and safety details can be found in previous review data. Once the injection needle was next to the stellate ganglion, 8–12 mL of local anaesthetic was then injected. Bilateral SGB was always attempted unless the patient was awake and not protected by intubation from bilateral recurrent laryngeal nerve paresis, or if a central line was in place that prevented the block. For unilateral SGB the left side was always given preference. If bilateral SGB was performed, both sides were done within 1 h. For repeat injections, if the initial procedure was unilateral, a unilateral SGB on the same side was attempted if bilateral block was still not feasible. If the initial block was bilateral, the repeat SGB was also bilateral.
SGB was performed at bedside with ultrasound by an anaesthesiologist or cardiologist. Cardiologists were always present for SGB; however, at IKEM, the procedure was primarily conducted by cardiology while at Duke it was primarily conducted by anaesthesia. Technical and safety details can be found in previous review data. Once the injection needle was next to the stellate ganglion, 8–12 mL of local anaesthetic was then injected. Bilateral SGB was always attempted unless the patient was awake and not protected by intubation from bilateral recurrent laryngeal nerve paresis, or if a central line was in place that prevented the block. For unilateral SGB the left side was always given preference. If bilateral SGB was performed, both sides were done within 1 h. For repeat injections, if the initial procedure was unilateral, a unilateral SGB on the same side was attempted if bilateral block was still not feasible. If the initial block was bilateral, the repeat SGB was also bilateral.
Data were collected from telemetry, cardiac implanted electronic devices, the electronic medical record and SGB procedural notes. Variables collected included age, sex, ethnicity, co‐morbidities, cardiac implantable electronic devices (CIED) status, VT/VF type and morphology, presence of mechanical circulatory support, inotrope use, cardiogenic shock, catheter ablation procedure (prior to SGB), antiarrhythmic use, beta blocker use and dose, left ventricular ejection fraction, and serum creatinine. Regarding morphology of arrythmia, data were captured via CIED and telemetry, and patients were categorized into two groups, monomorphic/polymorphic VT and VF. In the course of their electrical storm, if patients exhibited both VT and VF, they were categorized as VF for the purpose of statistical analysis. Co‐morbidities examined included the aetiology of cardiomyopathy, atrial fibrillation, and acute myocardial infarction. Procedural characteristics included anaesthetic used (lidocaine, bupivacaine, and ropivacaine), laterality (left‐sided, right‐sided, or bilateral) and repeat injections.
The primary outcome of the initial analysis of this database was the change in VT/VF burden and defibrillations before and after SGB. This manuscript expands on the initial analysis by examining a new primary outcome of absence of VT/VF at 24 h post SGB. This was defined as zero episodes of ventricular arrythmia in the period 24 h after SGB. The secondary outcomes of interest were VT/VF event rates and shocks before and after SGB. VT/VF events before and after SGB were ascertained via manual review of continuous telemetry recordings or device interrogation for patients with CIED. A VT/VF episode was defined as an episode lasting greater than 30 s or an episode that required treatment with a shock. Both implantable cardioverter defibrillator (ICD) and external shocks were counted as shocks for the analysis.
First, non‐parametric tests (Mann–Whitney U test) were used to compare the number of VT/VF episodes, and recorded number of shocks between cohorts at 24 and 48 h pre and post SGB. These analyses were utilized to compare outcomes based on cardiomyopathy aetiology, arrhythmia aetiology, laterality of SGB, presence of inotropes, and presence of MCS. Additionally, repeat injection rates and in‐hospital mortality were examined using chi‐squared tests. In the next portion of the analysis, binary logistic regression was used to examine variables associated with the above primary outcomes. The regression included covariates age, sex, academic center/site, implantable cardioverter defibrillator (ICD) status (CRT‐D/ICD present or not), ischaemic cardiomyopathy (ICM), left ventricular ejection fraction (LVEF), block location (unilateral vs. bilateral), arrhythmia type (VT vs. VF), and intubation status. Statistics were done using SPSS V26 (IBM, Armonk, NY).
Baseline demographics In total there were 117 patients with refractory VT/VF treated with SGB. Forty‐nine (41.9%) were at Duke and 68 (58.1%) were at IKEM. The majority of patients were male (94.0%), White (87.2%), and had an ICD in situ (70.1%). The mean age was 63.5 (SD 11.0) and the mean LVEF was 26.7% (SD 9.2). Approximately half of the patients had ICM (52.1%) and the most common arrythmia morphology was monomorphic VT (70.1%). Overall, 84.6% of patients were treated with amiodarone and 53.0% were treated with intravenous lidocaine. Ninety‐five (81.2%) patients were on inotropes and 38 (32.5%) were on MCS (9 IABP, 5 Impella, 9 ECMO, and 15 LVAD) ( Table ). Initial primary outcome As presented in our initial analysis, within 24 h prior to SGB (0–24 h), the median episodes of VT/VF were 7.5 [IQR: 3.0–27.0] and 24 h after SGB the median decreased to 1.0 [IQR: 0.0–4.5, P < 0.001]. Twenty‐four hours prior to SGB, the median defibrillation events were 2.0 [IQR: 0.0–8.0] and 24 h after SGB the median decreased to 0.0 [0.0–1.0, P < 0.001]. In the overall cohort, there was a significant decrease in both arrythmia burden and defibrillations with SGB. Predictors of stellate ganglion block effectiveness When examining the primary outcome of no VT/VF at 24 h following SGB, multivariable analysis demonstrated that increased age was associated with decreased odds (per year) of SGB success (OR: 0.96, CI: 0.92–0.99, P = 0.039) and that increased LVEF trended towards increased odds (per % EF) of SGB success (OR: 1.05, CI: 0.995–1.11, P = 0.077) ( Table ). SGB was associated with a decreased odds of success in older patients, with response rates of 10% in those >75 years of age. When a decrease in VT/VF by 50% or greater at 24 h was examined as the outcome, no variables were found to be significant. Also of note, there were no statistically significant differences in the rate of the primary outcome by cardiomyopathy type, arrythmia type, block laterality, inotropes, MCS, or intubation status. Effectiveness of stellate ganglion block according to patient phenotypes Patients with ischaemic and non‐ischaemic cardiomyopathy had a comparably favourable response to SGB, with no differences noted in the number of VT/VF events or shocks 24 and 48 h post‐block ( Figure ). There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups ( Table ). In regard to the type of ventricular arrhythmia, patients with VF had significantly more shocks 48 h (VF: 1.0 vs. VT: 0.0, P = 0.002) and 24 h pre‐SGB (VF: 2.8 vs. VT: 1.0, P < 0.001) ( Figure ), but both arrythmia types had similar favourable response to SGB with no differences noted in number of VT/VF events or shocks 24 and 48 h post‐block. There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups ( Table ). When comparing outcomes of patients receiving unilateral versus bilateral SGB, both groups had favourable responses with no differences noted in number of VT/VF events or shocks 24 and 48 h post‐block ( Figure ). There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups. Patients receiving bilateral SGB did have fewer median episodes of VT/VF in the 24 h pre‐block compared with those receiving unilateral SGB (bilateral: 2.0 vs. unilateral: 10.0, P = 0.016) ( Table ). When comparing outcomes of patients on or off inotropes, both groups had favourable responses to SGB with no differences noted in the number of VT/VF events or shocks 24 and 48 h post‐block. There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups. There were significantly more shocks 24 h pre‐SGB in the inotrope group (median; inotropes: 10.0 vs. no inotropes: 2.0, P = 0.011) (Table ). Lastly, compared with patients without MCS, those with MCS had higher median shocks 48 h pre‐SGB (MCS: 1.0 vs. no MCS: 0.0, P = 0.036), 24 h pre‐SGB (MCS: 6.0 vs. no MCS: 2.0, P = 0.003), and there was a higher mortality rate in the MCS group as well (MCS: 63.6% vs. no MCS: 33.8%, P = 0.004). While there were more frequent shocks in the MCS groups post‐SGB, there was no difference in the primary outcome (VT/VF at 24 h) (MCS patients also had significantly more shocks prior to SGB). As a result, no significant differences were present in SGB primary outcomes (Table ). As a supplemental cohort, outcomes were examined by intubation status and similarly there was difference in the primary outcome of 0 VT/VF at 24 h (not intubated 41.2% vs. intubated 48.5%, P = 0.690) (Table ). Shocks at 24 h post‐SGB for all cohorts can be found depicted graphically in Figure .
In total there were 117 patients with refractory VT/VF treated with SGB. Forty‐nine (41.9%) were at Duke and 68 (58.1%) were at IKEM. The majority of patients were male (94.0%), White (87.2%), and had an ICD in situ (70.1%). The mean age was 63.5 (SD 11.0) and the mean LVEF was 26.7% (SD 9.2). Approximately half of the patients had ICM (52.1%) and the most common arrythmia morphology was monomorphic VT (70.1%). Overall, 84.6% of patients were treated with amiodarone and 53.0% were treated with intravenous lidocaine. Ninety‐five (81.2%) patients were on inotropes and 38 (32.5%) were on MCS (9 IABP, 5 Impella, 9 ECMO, and 15 LVAD) ( Table ). Initial primary outcome As presented in our initial analysis, within 24 h prior to SGB (0–24 h), the median episodes of VT/VF were 7.5 [IQR: 3.0–27.0] and 24 h after SGB the median decreased to 1.0 [IQR: 0.0–4.5, P < 0.001]. Twenty‐four hours prior to SGB, the median defibrillation events were 2.0 [IQR: 0.0–8.0] and 24 h after SGB the median decreased to 0.0 [0.0–1.0, P < 0.001]. In the overall cohort, there was a significant decrease in both arrythmia burden and defibrillations with SGB. Predictors of stellate ganglion block effectiveness When examining the primary outcome of no VT/VF at 24 h following SGB, multivariable analysis demonstrated that increased age was associated with decreased odds (per year) of SGB success (OR: 0.96, CI: 0.92–0.99, P = 0.039) and that increased LVEF trended towards increased odds (per % EF) of SGB success (OR: 1.05, CI: 0.995–1.11, P = 0.077) ( Table ). SGB was associated with a decreased odds of success in older patients, with response rates of 10% in those >75 years of age. When a decrease in VT/VF by 50% or greater at 24 h was examined as the outcome, no variables were found to be significant. Also of note, there were no statistically significant differences in the rate of the primary outcome by cardiomyopathy type, arrythmia type, block laterality, inotropes, MCS, or intubation status.
As presented in our initial analysis, within 24 h prior to SGB (0–24 h), the median episodes of VT/VF were 7.5 [IQR: 3.0–27.0] and 24 h after SGB the median decreased to 1.0 [IQR: 0.0–4.5, P < 0.001]. Twenty‐four hours prior to SGB, the median defibrillation events were 2.0 [IQR: 0.0–8.0] and 24 h after SGB the median decreased to 0.0 [0.0–1.0, P < 0.001]. In the overall cohort, there was a significant decrease in both arrythmia burden and defibrillations with SGB.
When examining the primary outcome of no VT/VF at 24 h following SGB, multivariable analysis demonstrated that increased age was associated with decreased odds (per year) of SGB success (OR: 0.96, CI: 0.92–0.99, P = 0.039) and that increased LVEF trended towards increased odds (per % EF) of SGB success (OR: 1.05, CI: 0.995–1.11, P = 0.077) ( Table ). SGB was associated with a decreased odds of success in older patients, with response rates of 10% in those >75 years of age. When a decrease in VT/VF by 50% or greater at 24 h was examined as the outcome, no variables were found to be significant. Also of note, there were no statistically significant differences in the rate of the primary outcome by cardiomyopathy type, arrythmia type, block laterality, inotropes, MCS, or intubation status.
Patients with ischaemic and non‐ischaemic cardiomyopathy had a comparably favourable response to SGB, with no differences noted in the number of VT/VF events or shocks 24 and 48 h post‐block ( Figure ). There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups ( Table ). In regard to the type of ventricular arrhythmia, patients with VF had significantly more shocks 48 h (VF: 1.0 vs. VT: 0.0, P = 0.002) and 24 h pre‐SGB (VF: 2.8 vs. VT: 1.0, P < 0.001) ( Figure ), but both arrythmia types had similar favourable response to SGB with no differences noted in number of VT/VF events or shocks 24 and 48 h post‐block. There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups ( Table ). When comparing outcomes of patients receiving unilateral versus bilateral SGB, both groups had favourable responses with no differences noted in number of VT/VF events or shocks 24 and 48 h post‐block ( Figure ). There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups. Patients receiving bilateral SGB did have fewer median episodes of VT/VF in the 24 h pre‐block compared with those receiving unilateral SGB (bilateral: 2.0 vs. unilateral: 10.0, P = 0.016) ( Table ). When comparing outcomes of patients on or off inotropes, both groups had favourable responses to SGB with no differences noted in the number of VT/VF events or shocks 24 and 48 h post‐block. There was no difference in the primary outcome (VT/VF at 24 h) or in‐hospital mortality was also not different between the two groups. There were significantly more shocks 24 h pre‐SGB in the inotrope group (median; inotropes: 10.0 vs. no inotropes: 2.0, P = 0.011) (Table ). Lastly, compared with patients without MCS, those with MCS had higher median shocks 48 h pre‐SGB (MCS: 1.0 vs. no MCS: 0.0, P = 0.036), 24 h pre‐SGB (MCS: 6.0 vs. no MCS: 2.0, P = 0.003), and there was a higher mortality rate in the MCS group as well (MCS: 63.6% vs. no MCS: 33.8%, P = 0.004). While there were more frequent shocks in the MCS groups post‐SGB, there was no difference in the primary outcome (VT/VF at 24 h) (MCS patients also had significantly more shocks prior to SGB). As a result, no significant differences were present in SGB primary outcomes (Table ). As a supplemental cohort, outcomes were examined by intubation status and similarly there was difference in the primary outcome of 0 VT/VF at 24 h (not intubated 41.2% vs. intubated 48.5%, P = 0.690) (Table ). Shocks at 24 h post‐SGB for all cohorts can be found depicted graphically in Figure .
In this large multicentre, international registry of patients undergoing SGB for treatment of refractory VT/VF there are several important findings. In addition to our initial conclusions that SGB was an effective methodology for decreasing arrythmia burden, we found that there were no differences in SGB effectiveness (as judged by our primary outcome) regardless of cardiomyopathy aetiology (ischaemic vs. non‐ischaemic), arrythmia type (VT vs. VF), presence of MCS, and presence of inotropes. While different patient phenotypes may be associated with differences in arrythmia burden prior to SGB, these differences no longer existed 24–48 h following SGB, suggesting efficacy of the procedure across a broad range of phenotypes. Second, effectiveness of SGB was similar in those treated with unilateral versus bilateral SGB. Finally, as with many pharmacologic and interventional therapies for cardiovascular disease, SGB was associated with decreased odds of success in older patients, especially in those older than 75. The primary finding of this paper was that there were no differences in effectiveness of SGB by cardiomyopathy aetiology or type of VA. Regarding cardiomyopathy, previous data has suggested a similar decrease in arrythmia to SGB both in ischaemic and non‐ischaemic cardiomyopathy. Our data reflects this but with significantly higher power and sample size. Regarding VA, demonstrating a lack of difference among patients with VT and VF greatly expands on smaller sample size studies demonstrating similar efficacy across monomorphic and polymorphic VT. These findings are important since they demonstrate that SGB has the potential as a temporizing measure across many patient phenotypes. Also important is the lack of significant difference between unilateral and bilateral SGB. While intuitively it would seem that bilateral SGB would confer better results due to larger reduction of sympathetic tone to the heart, our data showed that unilateral blocks were not statistically different in terms of efficacy. As bilateral SGB confers the risk of bilateral recurrent laryngeal nerve blockade (an airway emergency for non‐intubated patients), a case could be made for starting first with unilateral SGB for patients with refractory VA. Lastly, patients with MCS who underwent SGB presented with more ventricular arrhythmias and their mortality was higher. This likely reflects more advanced heart failure with higher risk of mortality. In such condition, arrhythmias often reflect the severity of the disease and the device implanted is associated with arrhythmogenicity itself. , , , Of note though, future studies with larger sample sizes are needed to confirm these findings, given our limited power. In regard to predictors of SGB success, age was the only variable that had significance. Increased age was associated with lower odds of SGB success, defined by no VT/VF at 24 h post block. Increasing age can promote arrhythmogenesis in a variety of ways. While it is true that with aging there is an increasing predominance of sympathetic tone over parasympathetic tone, there is also a decrease in the density of cardiac sympathetic innervation, potentially decreasing the efficacy that SGB would have in this population. Older patients likely have greater dysfunction of their sympathetic nervous system, potentially interfering with potential impact and efficacy of SGB. Previous data has demonstrated that increased age is associated with higher morbidity and mortality in patients with VT or cardiac arrest. In addition to age, lower LVEF trended towards significance ( P = 0.077) as a negative predictor of SGB success. A higher degree of left ventricular dysfunction is an established risk factor for VT and sudden cardiac death. This is likely due to increased scarring and increased production/sensitivity to catecholamines in sympathetic nerve endings. Such condition is likely associated with a lower cardiac output and greater myocardial demand, where attenuation of sympathetic tone may have a lesser opportunity to decrease the likelihood and frequency of arrythmia. The absence of other predictors is likely due to the limited power given our small sample size. Despite our limited power, it is important to note that this cohort remains the largest SGB cohort published to date. Our study has several important limitations, including the use of retrospective chart review which is less optimal than prospectively collected data. The patient cohort was primarily male and White, and the findings may not be generalizable to other patient populations. Outside of in‐hospital mortality, we did not have procedural outcomes beyond 48 h. Additionally, variables of interest such as heart rates during VT/VF episodes, timing of VT/VF episodes, presence/extent of scar on cardiac imaging, and need for percutaneous coronary intervention during hospitalization were not included the registry. It would be important for future studies to evaluate this data to better elucidate cohorts more likely to undergo successful SGB. Although this study is one of the largest of its kind, a limited sample size still limits our covariates included in our analysis and our conclusions. Of note though, despite the above weakness, mortality was very high in our study, providing significant power to this outcome. Overall, this study demonstrated similar efficacy of SGB across major phenotypic cohorts of patients with a high ventricular arrhythmia burden. Sympathetic overdrive is an important driver of VT storm and is likely present regardless of the underlying aetiology. In our study population, SGB appeared to be less effective in decreasing VT/VF in older patients and likely less effective in those with lower LVEF. Future studies and randomized trials are needed to further evaluate the efficacy of SGB, but should not restrict enrolment to patients with particular aetiologies of cardiomyopathy or types of VT/VF.
Dr. Piccini is supported by R01AG074185 from the National Institutes of Aging. He also receives grants for clinical research from Abbott, the American Heart Association, Boston Scientific, iRhythm, and Philips and serves as a consultant to ABVF, Abbott, Abbvie, Boston Scientific, Element Science, ElectroPhysiology Frontiers, Medtronic, Milestone, Sanofi, Pacira, Philips, and Up‐to‐Date. Dr. Fudim is supported by the NIH (1OT2HL156812–01; 1R01HL171305–01), Bodyport, Sardocor, and Doris Duke. He is a consultant/has ownership interesting in Abbott, Ajax, Alio Health, Alleviant, Artha, Audicor, AxonTherapies, Bayer, Bodyguide, Bodyport, Boston Scientific, Broadview, Cadence, Cardioflow, Coridea, CVRx, Daxor, Deerfield Catalyst, Edwards LifeSciences, Echosens, EKO, Feldschuh Foundation, Fire1, FutureCardia, Galvani, Gradient, Hatteras, HemodynamiQ, Impulse Dynamics, Intershunt, Medtronic, Merck, NIMedical, NovoNordisk, NucleusRx, NXT Biomedical, Orchestra, Pharmacosmos, PreHealth, Presidio, Procyreon, ReCor, Rockley, SCPharma, Shifamed, Splendo, Summacor, SyMap, Verily, Vironix, Viscardia, Zoll. Dr KAutzner JK reports personal fees from Biosense Webster, Boston Scientific, GE Healthcare, Medtronic, and St. Jude Medical (Abbott) for participation in scientific advisory boards, and has received speaker honoraria from Biosense Webster, Biotronik, Boston Scientific, Medtronic, ProMed CS, St. Jude Medical (Abbott) and Viatris. All other authors have no relevant disclosures.
None.
Figure S1. VT Events Pre and Post SGB by Block Laterality. Table S1. SGB Outcomes and Arrythmia Burden by Use of Inotropes. Table S2. SGB Outcomes and Arrythmia Burden by Use of MCS. Table S3. SGB Outcomes and Arrythmia Burden by Intubation Status.
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Greater coordination and harmonisation of European occupational cohorts is needed | a2ecadd9-3977-455c-b6ea-1cfbd3ea5cd3 | 6035485 | Preventive Medicine[mh] | |
Diabetic retinopathy screening and the COVID-19 pandemic in
Brazil | 0cf0bc10-df9a-48f0-a137-10e236c5d447 | 11826596 | Ophthalmology[mh] | |
Editorial: Diversity and molecular diagnostics of fungi and oomycetes in plants | a05a107f-82cf-42c2-acbc-6baf9343a58e | 10598375 | Pathology[mh] | TX: Writing – original draft, Conceptualization, Investigation. TD: Writing – original draft, Writing – review & editing. JS: Formal Analysis, Writing – original draft, Writing – review & editing. XL: Conceptualization, Data curation, Methodology, Writing – original draft. |
Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter | 1714466f-efcc-4254-a29d-6df558a75b55 | 9973548 | Health Communication[mh] | Background Public health recommendations rapidly evolve when contending with a fast-developing pandemic like COVID-19, and optimized communication is critical to positively impact health-related behaviors and outcomes. Effective communication of trustworthy information has proven key to overcoming public health crises in the past, particularly when the coordinated effort of entire populations has been required . During global health crises, public institutions are considered trusted sources of information, but they face challenges in providing evidence-based guidance on real-time preventative measures . The Centers for Disease Control and Prevention (CDC) is one of the leading federal agencies in the United States charged with protecting public health. It provides primary directives for public health measures that are disseminated to the general public via various outlets, including social media platforms . Public Health Communication Messaging strategies are a key tenet of strategic communication. Public health communication in particular is driven by an ecological foundation, recognizing that public health is affected by social, behavioral, political, and environmental factors . As such, it requires multilevel strategies for disseminating information, including “tailored messages at the individual level, targeted messages at the group level, social marketing at the community level, media advocacy at the policy level, and media campaigns at the population level” . In 1993, the director of the CDC established that health communication should be considered an integral component of their prevention programs and created a 10-step messaging framework to promote changes in awareness, attitudes, and beliefs that may ultimately influence health behaviors . This framework has evolved over time, notably with the addition of the crisis and emergency risk communication (CERC) considerations in the aftermath of 9/11 and subsequent anthrax attacks . The CERC strategy generally follows a 5-phase paradigm: (1) the pre-crisis phase, involving potential response preparedness; (2) the initial phase, when the outbreak begins and information is often fluid and possibly confusing; (3) the maintenance phase, involving clarifying information on risk perceptions and correcting misinformation; (4) the resolution phase, when the outbreak is resolved; and (5) the evaluation phase, involving review of lessons learned . Over the past decade, public health organizations have struggled to adequately address public concerns during outbreaks of Ebola, H5N1 avian influenza, and Zika, and these organizations have encountered similar obstacles during the first 3 phases of the COVID-19 pandemic . This is especially apparent when countering misinformation regarding individual-level behaviors . Sentiment and Emotion Growing research demonstrates the association between trust in government and public health organizations and their effectiveness in communicating public health information for optimal individual-level compliance . According to a 2015 poll, only 19% of Americans trusted the US federal government always or most of the time, while 71% of Americans expressed trust in the CDC in 2017 . However, in 2022, trust in the CDC fell to 50% . Considering the stature of the CDC in society, its communications—especially those on social media, where they may get the most amount of attention by the general population—play an essential role in preparedness and response efforts during all phases of disease outbreaks. Health communication generally relies on adapting established theories and models of behavior for each public health campaign. These include the theory of reasoned action, health belief model, social learning/cognitive theory, extended parallel process model, diffusion of innovation, and social marketing . However, these decision-making theories do not effectively consider the influence of attitudes, emotions, and cultural norms on ultimate behaviors, as suggested by an assessment of HIV/AIDS communication campaigns for prevention . Additionally, disseminating evolving and corrective information throughout a communication campaign can also present challenges. As people receive newer information, interpretation of this updated information follows an attitude-consistent manner despite a willingness to accept the information as factual, wherein individuals are more willing to express distrust in the credibility of the information . Analysis of the CDC’s communication campaign during the Zika epidemic suggested that updated or corrective information positively impacted public health perceptions in the initial months of the epidemic and did not affect the credibility of the CDC . However, more recent research from the current COVID-19 pandemic has indicated that the positive effects of updates to information may be short-lived . The Role of Twitter During health crises, Twitter has proven effective at identifying public concerns over the health consequences of emerging disease outbreaks and tracking disease activity based on users’ health behavior . Prior studies have demonstrated that Twitter data can be used to understand public sentiment in real time and tailor individualized public health messages based on user interest and emotion . From February 2020 through May 2021, the CDC changed guidelines on face masks (herein referred to as masks) multiple times, from initially discouraging mask use at the beginning of the pandemic among non–health care workers, to recommending mask use for all individuals, to suggesting masks were optional for individuals who were vaccinated, to again recommending the use of masks for all individuals during another surge in case counts of COVID-19. During a February 2022 press call, CDC Director Rochelle Walensky cautioned that “None of us know what the future holds for us and for this virus.... And we need to be prepared and we need to be ready for whatever comes next. We want to give people a break from things like mask wearing when our levels are low, and then have the ability to reach for them again if things get worse in the future” . Given this evolving messaging toward mask guidelines, it is critical to explore how mask-related decisions thus far during the pandemic have impacted public sentiment and emotion. To evaluate how changes in CDC mask guidelines (ie, recommendation and relaxation) impacted social media discourse, this study applies methods from computational epidemiology and the social sciences to rapidly evaluate vast amounts of publicly accessible social media data . In particular, this study focuses on Twitter, given its role in the proliferation of public health communications . Our research highlights the complex issues of public health communication confronting federal agencies, particularly the CDC, and the public at large. Formally, our objective was to evaluate changes in public perception (as measured through sentiment and emotion expressed on Twitter) surrounding the April 3, 2020, and May 13, 2021, masking guidelines made by the CDC. We investigate the impacts of changing mask guidelines on public sentiment and emotions toward mask use and hypothesize that changing guidelines (1) influence public sentiment toward mask use but (2) do not change perceptions of the CDC’s credibility, specifically trustworthiness. Public health recommendations rapidly evolve when contending with a fast-developing pandemic like COVID-19, and optimized communication is critical to positively impact health-related behaviors and outcomes. Effective communication of trustworthy information has proven key to overcoming public health crises in the past, particularly when the coordinated effort of entire populations has been required . During global health crises, public institutions are considered trusted sources of information, but they face challenges in providing evidence-based guidance on real-time preventative measures . The Centers for Disease Control and Prevention (CDC) is one of the leading federal agencies in the United States charged with protecting public health. It provides primary directives for public health measures that are disseminated to the general public via various outlets, including social media platforms . Messaging strategies are a key tenet of strategic communication. Public health communication in particular is driven by an ecological foundation, recognizing that public health is affected by social, behavioral, political, and environmental factors . As such, it requires multilevel strategies for disseminating information, including “tailored messages at the individual level, targeted messages at the group level, social marketing at the community level, media advocacy at the policy level, and media campaigns at the population level” . In 1993, the director of the CDC established that health communication should be considered an integral component of their prevention programs and created a 10-step messaging framework to promote changes in awareness, attitudes, and beliefs that may ultimately influence health behaviors . This framework has evolved over time, notably with the addition of the crisis and emergency risk communication (CERC) considerations in the aftermath of 9/11 and subsequent anthrax attacks . The CERC strategy generally follows a 5-phase paradigm: (1) the pre-crisis phase, involving potential response preparedness; (2) the initial phase, when the outbreak begins and information is often fluid and possibly confusing; (3) the maintenance phase, involving clarifying information on risk perceptions and correcting misinformation; (4) the resolution phase, when the outbreak is resolved; and (5) the evaluation phase, involving review of lessons learned . Over the past decade, public health organizations have struggled to adequately address public concerns during outbreaks of Ebola, H5N1 avian influenza, and Zika, and these organizations have encountered similar obstacles during the first 3 phases of the COVID-19 pandemic . This is especially apparent when countering misinformation regarding individual-level behaviors . Growing research demonstrates the association between trust in government and public health organizations and their effectiveness in communicating public health information for optimal individual-level compliance . According to a 2015 poll, only 19% of Americans trusted the US federal government always or most of the time, while 71% of Americans expressed trust in the CDC in 2017 . However, in 2022, trust in the CDC fell to 50% . Considering the stature of the CDC in society, its communications—especially those on social media, where they may get the most amount of attention by the general population—play an essential role in preparedness and response efforts during all phases of disease outbreaks. Health communication generally relies on adapting established theories and models of behavior for each public health campaign. These include the theory of reasoned action, health belief model, social learning/cognitive theory, extended parallel process model, diffusion of innovation, and social marketing . However, these decision-making theories do not effectively consider the influence of attitudes, emotions, and cultural norms on ultimate behaviors, as suggested by an assessment of HIV/AIDS communication campaigns for prevention . Additionally, disseminating evolving and corrective information throughout a communication campaign can also present challenges. As people receive newer information, interpretation of this updated information follows an attitude-consistent manner despite a willingness to accept the information as factual, wherein individuals are more willing to express distrust in the credibility of the information . Analysis of the CDC’s communication campaign during the Zika epidemic suggested that updated or corrective information positively impacted public health perceptions in the initial months of the epidemic and did not affect the credibility of the CDC . However, more recent research from the current COVID-19 pandemic has indicated that the positive effects of updates to information may be short-lived . During health crises, Twitter has proven effective at identifying public concerns over the health consequences of emerging disease outbreaks and tracking disease activity based on users’ health behavior . Prior studies have demonstrated that Twitter data can be used to understand public sentiment in real time and tailor individualized public health messages based on user interest and emotion . From February 2020 through May 2021, the CDC changed guidelines on face masks (herein referred to as masks) multiple times, from initially discouraging mask use at the beginning of the pandemic among non–health care workers, to recommending mask use for all individuals, to suggesting masks were optional for individuals who were vaccinated, to again recommending the use of masks for all individuals during another surge in case counts of COVID-19. During a February 2022 press call, CDC Director Rochelle Walensky cautioned that “None of us know what the future holds for us and for this virus.... And we need to be prepared and we need to be ready for whatever comes next. We want to give people a break from things like mask wearing when our levels are low, and then have the ability to reach for them again if things get worse in the future” . Given this evolving messaging toward mask guidelines, it is critical to explore how mask-related decisions thus far during the pandemic have impacted public sentiment and emotion. To evaluate how changes in CDC mask guidelines (ie, recommendation and relaxation) impacted social media discourse, this study applies methods from computational epidemiology and the social sciences to rapidly evaluate vast amounts of publicly accessible social media data . In particular, this study focuses on Twitter, given its role in the proliferation of public health communications . Our research highlights the complex issues of public health communication confronting federal agencies, particularly the CDC, and the public at large. Formally, our objective was to evaluate changes in public perception (as measured through sentiment and emotion expressed on Twitter) surrounding the April 3, 2020, and May 13, 2021, masking guidelines made by the CDC. We investigate the impacts of changing mask guidelines on public sentiment and emotions toward mask use and hypothesize that changing guidelines (1) influence public sentiment toward mask use but (2) do not change perceptions of the CDC’s credibility, specifically trustworthiness. Data Collection Tweets containing at least one COVID-19–related keyword were collected using repeated searches via version 1.1 of the official Twitter application programming interface (API). The API was queried in several steps as part of a separate project conducted by team members at the University of Sydney. Starting on February 10, 2020, the Search Tweets end point was run on an automated schedule every 7 days to collect tweets based on a specific set of COVID-19–related queries . When running, the process would request 100 COVID-19–related tweets from the API, save those tweets to a database, and then request the next 100 tweets until it ran out of tweets to gather. The frequency of requests was 450 times per 15 minutes (due to rate limits imposed by the Twitter API), resulting in 45,000 tweets per 15 minutes. Starting on March 17, 2020, this process was switched to the Twitter Stream API, which had an ongoing open connection with Twitter . In this new process, whenever a tweet matching the keywords of interest was posted by a user, it was sent to the database within seconds. Analysis was restricted to original tweets (ie, retweets were omitted) in English from users based in the United States. The GeoNames geographical database was used to identify user location based on the account location field (ie, the location provided by a Twitter user in their public profile, if any). The data set was then restricted to only tweets that contained mask-related terminology, and these keywords were selected based on the collective expertise of the research team . The comparator data set was generated by first extracting tweets that contained at least one COVID-19 keyword but no mask keywords. A random number of comparator tweets were then selected for each day such that the number of comparator tweets for any given day was equivalent to the number of mask tweets on that day. For example, if there were 500 mask tweets on March 2, 500 random comparator tweets that contained COVID-19 terminology but no mask terminology would be selected for that day. The daily number of tweets used for analysis in 2020 and 2021 are provided in , Table S1, and , Table S2, respectively. Data were evaluated during 2 time periods: March 1, 2020, to June 30, 2020, and April 1, 2021, to June 13, 2021. During the first time period, on April 3, 2020, the CDC set new guidelines that cloth or fabric face coverings (eg, masks) be used as an additional and voluntary preventive measure that could protect others from COVID-19 transmission . This was a reversal of guidelines made during a tweet on February 27, 2020, which stated that the CDC did “not currently recommend the use of masks to help prevent novel coronavirus,” instead encouraging their Twitter followers (4.7 million on the main @CDCGov account as of April 5, 2022) to stay at home when sick and wash hands with soap and water to slow the spread of disease . Amid a shortage of personal protective equipment, CDC officials reasoned that this position might reduce the likelihood of stockpiling by the general public and save hospital-grade masks for health care workers . The second time period of analysis (ie, April 1, 2021, through June 13, 2021) was chosen based on a revision to the guidelines by the CDC, which noted on Twitter, “[i]f you are fully vaccinated against #COVID19, you can resume activities without wearing a mask.” Two months later, this recommendation was revoked amid a surge of the SARS-CoV-2 Delta variant . Sentiment Analysis and Emotion Analysis Links, hashtag symbols, and @ mentions were removed from tweets prior to calculating sentiment scores using the Valence Aware Dictionary and Sentiment Reasoner (VADER). This methodology, which was specifically designed for social media data, incorporates emojis, punctuation, capitalization, and negation when calculating the compound sentiment score (ranging from –1 to 1). Tweets with a score above 0.05 were labeled as “positive” and those below –0.05 were labeled as “negative”; all other tweets were labeled as “neutral” . Each tweet was also mapped to a set of emotions based on the National Research Council of Canada (NRC) Word Emotion Lexicon . The NRC associates each word with at least 1 of 8 emotions—anger, anticipation, disgust, fear, joy, sadness, surprise, and trust—on a scale from 0 to 1. Before calculating emotionality, all HTML escape characters, stop words, punctuation, and numbers were removed, followed by conversion to lower case and tokenization. For a given tweet, the final score corresponding to each emotion was calculated by summing emotion scores across tokens corresponding to that emotion. Statistical Analysis An interrupted time series analysis was used to evaluate the change in sentiment and emotion outcomes around the 2 shifts in guidelines. Each model contained a term for the pre-event trend (ie, recommendation for mask use or relaxation of this recommendation), an instantaneous effect on the day of the event, and a postevent trend. For each year, the outcomes of interest included change in average daily compound sentiment score, percent of tweets with a given sentiment (ie, positive, negative, or neutral, with individual models for each sentiment), and total emotion score (ie, the sum of words tagged with a given emotion of interest, with individual models for each emotion). For all outcomes, models were evaluated individually and relative to the comparator data set. Analysis was conducted in R (version 4.1.2; R Foundation for Statistical Computing) using the RStudio Integrated Development Environment (version 2021.09.0). A P value of less than .05 ( P <.05) was considered statistically significant, and the authors determined there were not enough statistical comparisons to warrant additional hypothesis correction methods. This was due to the exploratory nature of this study and the decision that type II errors (eg, failing to identify a true association) were more deleterious than type I errors (eg, identifying a spurious association) . Tweets containing at least one COVID-19–related keyword were collected using repeated searches via version 1.1 of the official Twitter application programming interface (API). The API was queried in several steps as part of a separate project conducted by team members at the University of Sydney. Starting on February 10, 2020, the Search Tweets end point was run on an automated schedule every 7 days to collect tweets based on a specific set of COVID-19–related queries . When running, the process would request 100 COVID-19–related tweets from the API, save those tweets to a database, and then request the next 100 tweets until it ran out of tweets to gather. The frequency of requests was 450 times per 15 minutes (due to rate limits imposed by the Twitter API), resulting in 45,000 tweets per 15 minutes. Starting on March 17, 2020, this process was switched to the Twitter Stream API, which had an ongoing open connection with Twitter . In this new process, whenever a tweet matching the keywords of interest was posted by a user, it was sent to the database within seconds. Analysis was restricted to original tweets (ie, retweets were omitted) in English from users based in the United States. The GeoNames geographical database was used to identify user location based on the account location field (ie, the location provided by a Twitter user in their public profile, if any). The data set was then restricted to only tweets that contained mask-related terminology, and these keywords were selected based on the collective expertise of the research team . The comparator data set was generated by first extracting tweets that contained at least one COVID-19 keyword but no mask keywords. A random number of comparator tweets were then selected for each day such that the number of comparator tweets for any given day was equivalent to the number of mask tweets on that day. For example, if there were 500 mask tweets on March 2, 500 random comparator tweets that contained COVID-19 terminology but no mask terminology would be selected for that day. The daily number of tweets used for analysis in 2020 and 2021 are provided in , Table S1, and , Table S2, respectively. Data were evaluated during 2 time periods: March 1, 2020, to June 30, 2020, and April 1, 2021, to June 13, 2021. During the first time period, on April 3, 2020, the CDC set new guidelines that cloth or fabric face coverings (eg, masks) be used as an additional and voluntary preventive measure that could protect others from COVID-19 transmission . This was a reversal of guidelines made during a tweet on February 27, 2020, which stated that the CDC did “not currently recommend the use of masks to help prevent novel coronavirus,” instead encouraging their Twitter followers (4.7 million on the main @CDCGov account as of April 5, 2022) to stay at home when sick and wash hands with soap and water to slow the spread of disease . Amid a shortage of personal protective equipment, CDC officials reasoned that this position might reduce the likelihood of stockpiling by the general public and save hospital-grade masks for health care workers . The second time period of analysis (ie, April 1, 2021, through June 13, 2021) was chosen based on a revision to the guidelines by the CDC, which noted on Twitter, “[i]f you are fully vaccinated against #COVID19, you can resume activities without wearing a mask.” Two months later, this recommendation was revoked amid a surge of the SARS-CoV-2 Delta variant . Links, hashtag symbols, and @ mentions were removed from tweets prior to calculating sentiment scores using the Valence Aware Dictionary and Sentiment Reasoner (VADER). This methodology, which was specifically designed for social media data, incorporates emojis, punctuation, capitalization, and negation when calculating the compound sentiment score (ranging from –1 to 1). Tweets with a score above 0.05 were labeled as “positive” and those below –0.05 were labeled as “negative”; all other tweets were labeled as “neutral” . Each tweet was also mapped to a set of emotions based on the National Research Council of Canada (NRC) Word Emotion Lexicon . The NRC associates each word with at least 1 of 8 emotions—anger, anticipation, disgust, fear, joy, sadness, surprise, and trust—on a scale from 0 to 1. Before calculating emotionality, all HTML escape characters, stop words, punctuation, and numbers were removed, followed by conversion to lower case and tokenization. For a given tweet, the final score corresponding to each emotion was calculated by summing emotion scores across tokens corresponding to that emotion. An interrupted time series analysis was used to evaluate the change in sentiment and emotion outcomes around the 2 shifts in guidelines. Each model contained a term for the pre-event trend (ie, recommendation for mask use or relaxation of this recommendation), an instantaneous effect on the day of the event, and a postevent trend. For each year, the outcomes of interest included change in average daily compound sentiment score, percent of tweets with a given sentiment (ie, positive, negative, or neutral, with individual models for each sentiment), and total emotion score (ie, the sum of words tagged with a given emotion of interest, with individual models for each emotion). For all outcomes, models were evaluated individually and relative to the comparator data set. Analysis was conducted in R (version 4.1.2; R Foundation for Statistical Computing) using the RStudio Integrated Development Environment (version 2021.09.0). A P value of less than .05 ( P <.05) was considered statistically significant, and the authors determined there were not enough statistical comparisons to warrant additional hypothesis correction methods. This was due to the exploratory nature of this study and the decision that type II errors (eg, failing to identify a true association) were more deleterious than type I errors (eg, identifying a spurious association) . April 3, 2020, CDC Mask Recommendation Guideline There were 1,106,756 mask-related tweets during the 4-month period surrounding the first guideline (ie, the CDC mask recommendation) with an equivalent quantity collected for the comparator. Between February 29, 2020, and June 30, 2020, mask-related tweets were more positive than comparator COVID-19 tweets (β=.06, 95% CI .05-.07; P <.001; ). In particular, the percent of positive tweets on any given day was 4.43 percentage points higher than concurrently observed in the comparator (95% CI 3.82-5.03; P <.001), while the percent of neutral tweets was lower (β=–3.94, 95% CI –4.68 to –3.21; P <.001). After the mask recommendation on April 3, 2020, the proportion of negative tweets within the mask-related data set increased (β=.51, 95% CI .43-.59; P <.001). However, the average number of negative tweets on any given day was not substantially different from the comparator (β=–.49, 95% CI –1.31 to .33; P =.24; ). In terms of emotion, mask-related tweets expressed an increasing level of trust (β=.004, 95% CI .003-.004; P <.001) but decreasing levels of both sadness (β=–.003, 95% CI –.004 to –.002 P <.001) and surprise (β=–.001, 95% CI –.001 to 0; P =.005) during the period preceding the April 3, 2020, CDC recommendation. However, the levels of sadness (β=.004, 95% CI .003-.005; P <.001) and surprise (β=.001, 95% CI 0-.001; P =.003) expressed in mask-related tweets increased following the CDC recommendation, while trust decreased (β=–.004, 95% CI –.004 to –.003; P <.001). The levels of anger, anticipation, disgust, or joy expressed on any given day did not substantially differ between the mask-related data set and the comparator. However, mask-related tweets expressed a higher level of trust (β=.131, 95% CI .122-.140; P <.001), but less sadness (β=–.042, 95% CI –.053 to –.031; P <.001) and surprise (β=–.026, 95% CI –.03 to –.021; P <.001) relative to the comparator data set. May 13, 2021, CDC Mask Relaxation Guideline There were 321,119 mask-related tweets during the 10-week period surrounding the second guideline shift (ie, the CDC mask relaxation), with an equivalent amount in the comparator. On any given day between April 1, 2021, and June 13, 2021, sentiment expressed in mask-related tweets was more negative than the comparator (β=–.06, 95% CI –.05 to –.06; P <.001; ). In particular, the proportion of negative tweets within the mask-related data set was 9.50 percentage points higher on average than in the comparator (95% CI 8.74-10.3; P <.001). During the same time period, the proportion of neutral tweets was 8.74 percentage points lower (95% CI –9.31 to –8.17; P <.001), and the proportion of positive tweets was 0.76 percentage points lower (95% CI –1.37 to –0.15; P =.02). Immediately after the mask relaxation on May 13, the proportion of negative tweets increased (β=3.43, 95% CI 1.61-5.26; P <.001), whereas the percent of neutral tweets decreased (β=–4.46, 95% CI –7.07 to –1.84; P =.001) On any given day, and in all categories except the emotion of surprise (β=–.004, 95% CI –.009 to .001; P =.09), mask-related tweets expressed higher levels of emotion than tweets in the comparator. Before the mask recommendation was revoked, the levels of anger (β=.001, 95% CI 0-.001; P =.007), fear (β=.001, 95% CI .001-.002; P <.001), sadness (β=.001, 95% CI 0-.002; P =.001), and trust (β=.001, 95% CI 0-.001; P <.001) expressed in mask-related tweets increased daily. Following the mask recommendation relaxation, the level of anger continued to increase (β=.001, 95% CI 0-.002; P =.02), whereas trust decreased (β=–.001, 95% CI –.002 to 0; P =.008). There were 1,106,756 mask-related tweets during the 4-month period surrounding the first guideline (ie, the CDC mask recommendation) with an equivalent quantity collected for the comparator. Between February 29, 2020, and June 30, 2020, mask-related tweets were more positive than comparator COVID-19 tweets (β=.06, 95% CI .05-.07; P <.001; ). In particular, the percent of positive tweets on any given day was 4.43 percentage points higher than concurrently observed in the comparator (95% CI 3.82-5.03; P <.001), while the percent of neutral tweets was lower (β=–3.94, 95% CI –4.68 to –3.21; P <.001). After the mask recommendation on April 3, 2020, the proportion of negative tweets within the mask-related data set increased (β=.51, 95% CI .43-.59; P <.001). However, the average number of negative tweets on any given day was not substantially different from the comparator (β=–.49, 95% CI –1.31 to .33; P =.24; ). In terms of emotion, mask-related tweets expressed an increasing level of trust (β=.004, 95% CI .003-.004; P <.001) but decreasing levels of both sadness (β=–.003, 95% CI –.004 to –.002 P <.001) and surprise (β=–.001, 95% CI –.001 to 0; P =.005) during the period preceding the April 3, 2020, CDC recommendation. However, the levels of sadness (β=.004, 95% CI .003-.005; P <.001) and surprise (β=.001, 95% CI 0-.001; P =.003) expressed in mask-related tweets increased following the CDC recommendation, while trust decreased (β=–.004, 95% CI –.004 to –.003; P <.001). The levels of anger, anticipation, disgust, or joy expressed on any given day did not substantially differ between the mask-related data set and the comparator. However, mask-related tweets expressed a higher level of trust (β=.131, 95% CI .122-.140; P <.001), but less sadness (β=–.042, 95% CI –.053 to –.031; P <.001) and surprise (β=–.026, 95% CI –.03 to –.021; P <.001) relative to the comparator data set. There were 321,119 mask-related tweets during the 10-week period surrounding the second guideline shift (ie, the CDC mask relaxation), with an equivalent amount in the comparator. On any given day between April 1, 2021, and June 13, 2021, sentiment expressed in mask-related tweets was more negative than the comparator (β=–.06, 95% CI –.05 to –.06; P <.001; ). In particular, the proportion of negative tweets within the mask-related data set was 9.50 percentage points higher on average than in the comparator (95% CI 8.74-10.3; P <.001). During the same time period, the proportion of neutral tweets was 8.74 percentage points lower (95% CI –9.31 to –8.17; P <.001), and the proportion of positive tweets was 0.76 percentage points lower (95% CI –1.37 to –0.15; P =.02). Immediately after the mask relaxation on May 13, the proportion of negative tweets increased (β=3.43, 95% CI 1.61-5.26; P <.001), whereas the percent of neutral tweets decreased (β=–4.46, 95% CI –7.07 to –1.84; P =.001) On any given day, and in all categories except the emotion of surprise (β=–.004, 95% CI –.009 to .001; P =.09), mask-related tweets expressed higher levels of emotion than tweets in the comparator. Before the mask recommendation was revoked, the levels of anger (β=.001, 95% CI 0-.001; P =.007), fear (β=.001, 95% CI .001-.002; P <.001), sadness (β=.001, 95% CI 0-.002; P =.001), and trust (β=.001, 95% CI 0-.001; P <.001) expressed in mask-related tweets increased daily. Following the mask recommendation relaxation, the level of anger continued to increase (β=.001, 95% CI 0-.002; P =.02), whereas trust decreased (β=–.001, 95% CI –.002 to 0; P =.008). Principal Findings This study is among the first to characterize the evolution of mask-related content on Twitter surrounding the recommendation and relaxation of mask guidelines by the CDC during the COVID-19 pandemic. In summary, our study found that after both the 2020 mask recommendation and the 2021 mask relaxation a pronounced decrease in neutral tweets occurred. Following the 2020 mask recommendation, sentiment expressed in mask-related tweets was substantially more positive than in other COVID-19 tweets. In contrast, sentiment expressed in mask-related tweets following the 2021 mask relaxation was more negative. Furthermore, both mask-related data sets suggested higher levels of emotions than other COVID-19 tweets. In particular, both time periods were marked by a higher proportion of tweets expressing disgust before the change in guidelines and lower proportion of tweets expressing trust following the change. Our main findings suggest that shifts in guidelines emanating from the CDC may have a tangible, negative impact on the perception of mask use among United States–based Twitter users, with implications for the design of mask-wearing policies and other similar preventative health measures in the future. Masks are a crucial public health tool to fight the spread of infections such as SARS-CoV-2. High adherence to mask-wearing policies may help reduce transmission during severe disease outbreaks, including pandemics . However, mask use in the United States has become increasingly politicized and polarizing. Recent work evaluating the state of mask-related discourse on Twitter found that corresponding tweets expressed increasingly negative sentiment between March and July 2020, although that research did not focus on CDC announcements as interventions or include an extended time period after the relaxation . Other research suggests that anti-mask rhetoric accounted for 10% of mask-related content between January and October 2020, with varying volume around key US guideline shifts . These results corroborate our findings, namely that the mask-related discourse on Twitter was increasingly more polarized after the CDC announced the mask recommendation on April 3, 2020. As online information-seeking behaviors increase, so do access and exposure to conflicting information and political infighting . False information quickly and easily spreads via online social networks and, in tandem with fluctuating and confusing messaging during the initial phase of a public health emergency, promotes negative public sentiments and difficulties in preserving public trust . Recent research indicates that efforts to disseminate corrective information during the maintenance phase of a public health crisis are ineffective at both countering misconceptions and gaining support for the adoption of preventive health-related behaviors . This finding suggests that, despite the quickly changing atmosphere, concise and consistent messaging is critical in the precrisis and initial phases of a public health emergency for highest individual-level adherence to preparedness and prevention measures. While the CDC attempted to provide clear messaging regarding mask use, its response was perceived as slow relative to the speed at which clinical findings were released. Furthermore, this perceived slow response, coupled with positions that conflicted with other global health organizations, such as the World Health Organization, may have inadvertently contributed to feelings of confusion and mistrust among the general public . This effect may have been captured within our data set as the decreased levels of trust-related terminology expressed within tweets following each shift in guidelines. Furthermore, the fact that mask tweets within our data were substantially more negative than the comparator in 2021 may suggest a high degree of preexisting mask fatigue, and the subsequent additional increase in negative tweets following the relaxation recommendation on May 13 may indicate discontent at the lack of transparency from the CDC. Health Communications Recommendations Although Twitter and other social media platforms can be leveraged to rapidly inform the public of important recommendations, this study suggests that there may be negative consequences for public support when such messages are not communicated effectively. In our study, this is illustrated by the decrease in levels of trust expressed by United States–based Twitter users following both guideline shifts in 2020 and 2021 . Based on these findings, we believe that there are several communication strategies that should be considered during future health emergencies to ensure that the general public maintains trust in government agencies. First, it is imperative that a consistent message is embraced by diverse, respected professionals in the field. Along with trusted government agencies like the CDC, this may also include public health and medical experts, research scientists, politicians, science communications specialists, and even popular influencers and celebrities in order to reach multiple demographics . This message should be authentic and transparent about the fact that information will likely evolve, especially during ongoing crises. Second, it is important for government agencies to monitor social media engagement and promote dialogue to understand perceptions and motives for health practice. Each social media platform reaches a different target audience, so multiple accounts across platforms may be warranted to ensure that as many individual opinions are considered as possible. While social media is not generalizable to the entire population, it can help supplement traditional epidemiologic measures of data collection, such as representative surveys, that may be more reliable but are more costly to coordinate. Third, it may be salient for government agencies to develop educational materials that directly address and correct incorrect perceptions, attitudes, and behaviors. These materials must be “living” documents that are continuously updated as new misperceptions emerge. They should also be made widely accessible and promoted through multiple media outlets, including social media. Taken together, the increased transparency and access afforded by consistent messaging, increased social media engagement, and easily understood education materials could help ensure that the general public continues to look to government agencies for guidance during future health emergencies, especially those that are tumultuous. Limitations and Future Directions Our study is the first to evaluate the sentiment and emotion of mask-related tweets in the United States surrounding 2 key guideline shifts made by the CDC relative to a matched comparator data set of other COVID-19 tweets during the same period. However, there are several limitations to note. First, the reliance on keywords to collect relevant tweets may introduce some selection bias. Specifically, filtering tweets with keywords may exclude tweets that discuss the topic of interest but contain a misspelling. Additionally, some tweets, such as automated advertisements, may contain the appropriate keywords but are not relevant to public opinion. Given the persuasive nature of advertising, it is likely that their inadvertent inclusion might have biased our results and skewed the estimation of positive sentiment to be higher than that which was present in the general public. Future work could use the –is:nullcast filter, which was not available in the version of the Twitter API that was used to collect the data for this study (version 1.1), to ensure that these tweets were removed. Second, tweets were restricted to those posted by users located within the United States based on the geotag in the user profile. However, users reporting location information in their profile may be different from those without such content. Future work should attempt to identify and leverage other methods to assess where Twitter users are located. Third, sociodemographic data were not available, which may impact generalizability. While social media studies can provide rapid insights during health emergencies, they are not necessarily representative of the overall US population; specifically, Twitter users tend to be younger, more educated, and have a higher average income than the general US population . Fourth, findings are based on aggregate analysis at the national level, and future work could characterize patterns at a state level. Lastly, future work could employ alternative natural language processing and sentiment analysis methods, such as emoji analysis or word embeddings, to understand how results may change. Conclusions Our study supports findings from prior research on the importance of formulating clear public health communications and disseminating accurate public health guidance on social media. Specifically, we found that tweets surrounding the 2020 mask recommendation and 2021 mask relaxation were more polarizing and contained less trust-related terminology than those before the guidelines were announced. Furthermore, while mask-related tweets posted in 2020 were more positive than other COVID-19 tweets, mask-related tweets in 2021 were more negative. The change in sentiment observed in 2021 may signal frustration among Twitter users about public health discourse centered around masks and recognition that the initial mask relaxation change may have been premature. Gaining insight into how the general public engages on social media platforms, perceives preventative public health measures imposed during the COVID-19 pandemic, and reacts to shifts in guidelines declared by the US government is of utmost importance for policy makers, health workers, and interested stakeholders. Official communications that include concise information backed by systematic data are critical to ensure widespread adoption and sustained adherence to public health interventions. However, the rapid spread of COVID-19 and the evolving evidence around its mitigation led to confusion from the public surrounding the fluctuating mask guidelines. When messaging remains unclear and lacks direction, public sentiment and trust in authoritative entities erode. This is especially true for masks, where policy recommendations pertaining to mask use constantly shifted throughout 2020 and 2021, sometimes without clear evidence presented to the public . Given that health officials have noted that mask guidelines may serve as a recurring tool to mitigate contagion spread during peak infection (both in the current pandemic and in response to future pandemic threats or emerging biothreats) it is imperative that institutions such as the CDC use consistent, clear communication strategies that align with other major health organizations and the broader scientific community. This will ensure that the potential for polarization is minimized while trust in the government and adherence to preventive measures is maximized. This study is among the first to characterize the evolution of mask-related content on Twitter surrounding the recommendation and relaxation of mask guidelines by the CDC during the COVID-19 pandemic. In summary, our study found that after both the 2020 mask recommendation and the 2021 mask relaxation a pronounced decrease in neutral tweets occurred. Following the 2020 mask recommendation, sentiment expressed in mask-related tweets was substantially more positive than in other COVID-19 tweets. In contrast, sentiment expressed in mask-related tweets following the 2021 mask relaxation was more negative. Furthermore, both mask-related data sets suggested higher levels of emotions than other COVID-19 tweets. In particular, both time periods were marked by a higher proportion of tweets expressing disgust before the change in guidelines and lower proportion of tweets expressing trust following the change. Our main findings suggest that shifts in guidelines emanating from the CDC may have a tangible, negative impact on the perception of mask use among United States–based Twitter users, with implications for the design of mask-wearing policies and other similar preventative health measures in the future. Masks are a crucial public health tool to fight the spread of infections such as SARS-CoV-2. High adherence to mask-wearing policies may help reduce transmission during severe disease outbreaks, including pandemics . However, mask use in the United States has become increasingly politicized and polarizing. Recent work evaluating the state of mask-related discourse on Twitter found that corresponding tweets expressed increasingly negative sentiment between March and July 2020, although that research did not focus on CDC announcements as interventions or include an extended time period after the relaxation . Other research suggests that anti-mask rhetoric accounted for 10% of mask-related content between January and October 2020, with varying volume around key US guideline shifts . These results corroborate our findings, namely that the mask-related discourse on Twitter was increasingly more polarized after the CDC announced the mask recommendation on April 3, 2020. As online information-seeking behaviors increase, so do access and exposure to conflicting information and political infighting . False information quickly and easily spreads via online social networks and, in tandem with fluctuating and confusing messaging during the initial phase of a public health emergency, promotes negative public sentiments and difficulties in preserving public trust . Recent research indicates that efforts to disseminate corrective information during the maintenance phase of a public health crisis are ineffective at both countering misconceptions and gaining support for the adoption of preventive health-related behaviors . This finding suggests that, despite the quickly changing atmosphere, concise and consistent messaging is critical in the precrisis and initial phases of a public health emergency for highest individual-level adherence to preparedness and prevention measures. While the CDC attempted to provide clear messaging regarding mask use, its response was perceived as slow relative to the speed at which clinical findings were released. Furthermore, this perceived slow response, coupled with positions that conflicted with other global health organizations, such as the World Health Organization, may have inadvertently contributed to feelings of confusion and mistrust among the general public . This effect may have been captured within our data set as the decreased levels of trust-related terminology expressed within tweets following each shift in guidelines. Furthermore, the fact that mask tweets within our data were substantially more negative than the comparator in 2021 may suggest a high degree of preexisting mask fatigue, and the subsequent additional increase in negative tweets following the relaxation recommendation on May 13 may indicate discontent at the lack of transparency from the CDC. Although Twitter and other social media platforms can be leveraged to rapidly inform the public of important recommendations, this study suggests that there may be negative consequences for public support when such messages are not communicated effectively. In our study, this is illustrated by the decrease in levels of trust expressed by United States–based Twitter users following both guideline shifts in 2020 and 2021 . Based on these findings, we believe that there are several communication strategies that should be considered during future health emergencies to ensure that the general public maintains trust in government agencies. First, it is imperative that a consistent message is embraced by diverse, respected professionals in the field. Along with trusted government agencies like the CDC, this may also include public health and medical experts, research scientists, politicians, science communications specialists, and even popular influencers and celebrities in order to reach multiple demographics . This message should be authentic and transparent about the fact that information will likely evolve, especially during ongoing crises. Second, it is important for government agencies to monitor social media engagement and promote dialogue to understand perceptions and motives for health practice. Each social media platform reaches a different target audience, so multiple accounts across platforms may be warranted to ensure that as many individual opinions are considered as possible. While social media is not generalizable to the entire population, it can help supplement traditional epidemiologic measures of data collection, such as representative surveys, that may be more reliable but are more costly to coordinate. Third, it may be salient for government agencies to develop educational materials that directly address and correct incorrect perceptions, attitudes, and behaviors. These materials must be “living” documents that are continuously updated as new misperceptions emerge. They should also be made widely accessible and promoted through multiple media outlets, including social media. Taken together, the increased transparency and access afforded by consistent messaging, increased social media engagement, and easily understood education materials could help ensure that the general public continues to look to government agencies for guidance during future health emergencies, especially those that are tumultuous. Our study is the first to evaluate the sentiment and emotion of mask-related tweets in the United States surrounding 2 key guideline shifts made by the CDC relative to a matched comparator data set of other COVID-19 tweets during the same period. However, there are several limitations to note. First, the reliance on keywords to collect relevant tweets may introduce some selection bias. Specifically, filtering tweets with keywords may exclude tweets that discuss the topic of interest but contain a misspelling. Additionally, some tweets, such as automated advertisements, may contain the appropriate keywords but are not relevant to public opinion. Given the persuasive nature of advertising, it is likely that their inadvertent inclusion might have biased our results and skewed the estimation of positive sentiment to be higher than that which was present in the general public. Future work could use the –is:nullcast filter, which was not available in the version of the Twitter API that was used to collect the data for this study (version 1.1), to ensure that these tweets were removed. Second, tweets were restricted to those posted by users located within the United States based on the geotag in the user profile. However, users reporting location information in their profile may be different from those without such content. Future work should attempt to identify and leverage other methods to assess where Twitter users are located. Third, sociodemographic data were not available, which may impact generalizability. While social media studies can provide rapid insights during health emergencies, they are not necessarily representative of the overall US population; specifically, Twitter users tend to be younger, more educated, and have a higher average income than the general US population . Fourth, findings are based on aggregate analysis at the national level, and future work could characterize patterns at a state level. Lastly, future work could employ alternative natural language processing and sentiment analysis methods, such as emoji analysis or word embeddings, to understand how results may change. Our study supports findings from prior research on the importance of formulating clear public health communications and disseminating accurate public health guidance on social media. Specifically, we found that tweets surrounding the 2020 mask recommendation and 2021 mask relaxation were more polarizing and contained less trust-related terminology than those before the guidelines were announced. Furthermore, while mask-related tweets posted in 2020 were more positive than other COVID-19 tweets, mask-related tweets in 2021 were more negative. The change in sentiment observed in 2021 may signal frustration among Twitter users about public health discourse centered around masks and recognition that the initial mask relaxation change may have been premature. Gaining insight into how the general public engages on social media platforms, perceives preventative public health measures imposed during the COVID-19 pandemic, and reacts to shifts in guidelines declared by the US government is of utmost importance for policy makers, health workers, and interested stakeholders. Official communications that include concise information backed by systematic data are critical to ensure widespread adoption and sustained adherence to public health interventions. However, the rapid spread of COVID-19 and the evolving evidence around its mitigation led to confusion from the public surrounding the fluctuating mask guidelines. When messaging remains unclear and lacks direction, public sentiment and trust in authoritative entities erode. This is especially true for masks, where policy recommendations pertaining to mask use constantly shifted throughout 2020 and 2021, sometimes without clear evidence presented to the public . Given that health officials have noted that mask guidelines may serve as a recurring tool to mitigate contagion spread during peak infection (both in the current pandemic and in response to future pandemic threats or emerging biothreats) it is imperative that institutions such as the CDC use consistent, clear communication strategies that align with other major health organizations and the broader scientific community. This will ensure that the potential for polarization is minimized while trust in the government and adherence to preventive measures is maximized. |
3D‐printed shell complete dentures as a diagnostic aid for implant planning and fabricating interim restorations for complete arch rehabilitations: A case series | a56e3df8-4bfa-4925-94dd-6f83e42f93e3 | 11795334 | Dentistry[mh] | Three partially edentulous patients presented to the Center for Implant, Esthetic, and Innovative Dentistry at Indiana University School of Dentistry seeking advanced prosthodontic care. The patients were treated using the 3D‐printed shell complete denture diagnostic protocol presented previously. An overview of the treatment sequence for each patient is described below. Patient 1 A 58‐year‐old Caucasian female presented with a maxillary complete denture and extensively compromised mandibular teeth. She expressed having had the maxillary prosthesis for over 10 years and denied having a mandibular removable partial denture. Clinical findings suggested a decreased vertical dimension of occlusion, irregular occlusal plane, and unstable occlusion. Furthermore, the patientdisliked the esthetics of the maxillary prosthesis (Figure ). Her medical history was contributory. She denied smoking or taking medications that could compromise the survival of endosteal implants. When her mental attitude was assessed, it was classified as philosophical according to House's classification. Different treatment options were presented after evaluating the clinical findings and the patient's expectations. The patient selected a treatment plan consisting of interim maxillary and mandibular prostheses, followed by a new maxillary complete denture and a mandibular implant‐supported fixed complete denture. The cameo surface of the patient's existing maxillary prosthesis was registered with an intraoral scanner (IOS) (TRIOS 4 Wireless: 3Shape. Copenhagen, Denmark). The maxillary complete denture was stabilized manually, and a centric relation record was made with elastomeric bite registration material (Blue Mousse; Parkell, Edgewood, NY) and a plastic leaf gauge (Leaf Gauge; Huffman Dental, Springfield, OH). Subsequently, the maxillary complete denture and maxillomandibular relationships were scanned and saved in standard tessellation language (STL) format. Additionally, a preliminary impression of the mandibular arch was made with irreversible hydrocolloid (Geltrate; Dentsply Sirona, Charlotte, NC) to record the posterior mandibular areas. Then, a mandibular diagnostic cast was fabricated with type 3 dental stone (MicroStone; Whip Mix, Louisville, KY). The mandibular diagnostic cast was digitized and aligned with the STL files of the maxillary complete denture and centric relation record using an open‐source 3D modeling computer program (Meshmixer; AutoCAD, San Francisco, CA). The incisal edge, midline, artificial teeth proportions, and root eminences of the maxillary prosthesis were enhanced digitally (Figure ). A diagnostic shell maxillary complete denture and removable partial denture were created following the protocol presented in previous research. The finalized digital designs were manufactured using a photopolymerizable resin (P Pro Try‐In Resin; Straumann, Andover, MA) in a digital light processing (DLP) 3D printer (Rapid Shape Straumann P30+; Straumann, Andover, MA) and post‐cured according to the manufacturer's recommendations. On the second appointment, the 3D‐printed maxillary shell complete denture was stabilized with elastomeric bite registration material (Blue Mousse; Parkell, Edgewood, NY) on its intaglio surface to define the orientation and vertical position of the occlusal plane (Figure ). Subsequently, the 3D‐printed prostheses were relined with tissue conditioner (COE Comfort; GC America, Alsip, IL) and the occlusal plane, incisal edge position, centric relation, and vertical dimension were reassessed (Figure ). Radiopaque fiducial markers were applied to the cameo surface and a dual scan was completed. Additionally, a facebow registration and centric occlusion record were performed to transfer the new maxillomandibular relationships to a semi‐adjustable articulator (Denar Mark II; Whip Mix, Louisville, KY). A maxillary preliminary silicone putty cast was created from the intaglio surface of the maxillary 3D‐printed shell complete denture to facilitate subsequent clinical and laboratory procedures. The mandibular teeth were substituted with a complete digital teeth arrangement in the same open‐source 3D modeling computer program; the anterior denture base was extended to the labial vestibule, and the interim mandibular complete denture design was finalized. The dual scan CBCT data were imported into a professional implant planning computer program (CoDiagnostiX‐Dental Wings; Straumann, Andover, MA), and the digital interim mandibular complete denture design was aligned with the dual scan of the diagnostic removable partial denture using the occlusal surface of the artificial teeth as a reference (Figure ). Subsequently, four endosteal implants (Bone Level X ⌀4.5 × 10 mm; Straumann, Andover, MA) were planned. Three computer‐generated surgical templates were 3D‐printed (Rapid Shape Straumann P30+, and P Pro Surgical Guide; Straumann, Andover, MA) to position the fixation pins, guide bone reduction, and direct the placement of the endosteal implants. 3D‐printed maxillary and mandibular interim complete dentures were manufactured before surgery with biocompatible denture base and artificial teeth photopolymers (Pro Resins Denture; Straumann, Andover, MA), and their occlusion was refined on the semi‐adjustable articulator (Figure ). On the third visit, the endosteal implants were placed using the 3D‐printed surgical templates (Figures , and ). The 3D‐printed maxillary and mandibular interim complete dentures were relined intraorally with soft tissue conditioner (COE Soft; GC America, Alsip, IL). Subsequently, the esthetics, vertical dimension, phonetics, centric relation, and overall patient satisfaction were re‐evaluated and deemed satisfactory by the patient. (Figure ) Patient 2 A 66‐year‐old Caucasian male expressed interest in complete maxillary rehabilitation supported by endosteal implants. A severely resorbed maxillary arch with significant vertical and horizontal residual ridge defects, and a partially edentulous mandible with an irregular occlusal plane were observed (Figure ). When the patient's existing maxillary complete denture was evaluated, clinical features suggestive of decreased vertical dimension of occlusion, overextended denture base extensions, deficient retention, and unsatisfactory dental esthetics were also noticed (Figure ). After discussing these findings, a treatment consisting of immediately loading six endosteal implants with an interim maxillary prosthesis followed by a definitive maxillary fixed complete denture, and an implant‐supported restoration on the edentulous site #30 was accepted by the patient. At the end of the consultation, the cameo surface of the patient's existing complete denture was scanned, and a preliminary impression of the opposing arch was made with irreversible hydrocolloid. A diagnostic mandibular cast was poured, and a maxillary 3D‐printed shell complete denture with the desired contours and incisal edge position was designed and 3D‐printed following the protocol presented previously (Figure ). On the second visit, the orientation of the occlusal plane, anterior teeth position, and the vertical dimension of occlusion were defined using the 3D‐printed maxillary shell complete denture. Subsequently, radiopaque fiducial markers were placed on the cameo surface (Figure ), and a dual scan was performed. A facebow and centric relation records were completed, and a maxillary preliminary silicone putty cast was created from the 3D‐printed prosthesis. A flangeless prototype was 3D‐printed from the dual scan CBCT data of the relined3D‐printed maxillary shell complete denture as an additional diagnostic step for planning maxillary endosteal implants. On the third visit, the flangeless prosthesis was used to assess the viability of an implant‐supported fixed rehabilitation considering the new prosthetic contours, lip support, formation of upper labial crease, and anterior residual ridge display during function (Figure ). Subsequently, the flangeless maxillary prototype was articulated with the diagnostic mandibular cast in a semi‐adjustable articulator (Hanau Wide‐Vue; Whip Mix, Louisville, KY) (Figure ) to evaluate restorative space available, design the maxillary incision and flap design, and to plan selective enameloplasty on the mandibular posterior teeth to gain posterior restorative space and prevent occlusal interferences (Figure ). The dual scan data were used to plan six endosteal implants (Bone Level X; Straumann, Andover, MA) in strategic positions to ensure an even distribution without cantilevers. Three 3D‐printed surgical templates were manufactured to guide bone reduction and endosteal implant placement. Additionally, a maxillary complete arch interim prosthesis was designed and manufactured using the contours of the flangeless prosthesis as a reference using polymethylmethacrylate (PMMA) resin (Ceramill A‐Temp Shade A2; Amann Girbach, Koblach, Austria) in a 5‐axis milling unit (Straumann‐Amann Girbach M Series; Straumann, Andover, MA). It is worth mentioning that adjustments were made to the buccolingual position of the maxillary posterior teeth digitally before the manufacture of the PMMA complete arch interim prosthesis to address the reverse articulation on the patient's right posterior teeth observed with the flangeless prototype (Figure ). On the fourth appointment, the endosteal implants were placed using the 3D‐printed surgical templates. During the procedure, care was taken to avoid severing anatomical structures in proximity to the implant sites as the nasopalatine neurovascular bundle, preserving attached gingiva around all the endosteal implant, and debulking the tuberosity areas to ensure a maxillary complete arch interim prosthesis with adequate thickness posteriorly (Figure ). At this stage, all endosteal implants achieved insertion torque values >40 Ncm, permitting immediate loading with the PMMA maxillary complete arch interim maxillary prosthesis (Figure ). On the subsequent visits, the patient expressed satisfaction with the esthetics, phonetics, and cleansability provided by the interim maxillary prosthesis (Figure ). Patient 3 A 67‐year‐old Caucasian female presented to the clinics looking for maxillary and mandibular implant‐supported prostheses. It is noteworthy that certain aspects of the treatment given to this patient are detailed more thoroughly in a previously published technique article. During the initial consultation, it was noticed that her existing prostheses presented excessive wear and unfavorable occlusion (Figure ). The anterior mandibular teeth were over‐erupted, and significant resorption was observed in the posterior residual ridges. Additionally, the maxillary arch was severely resorbed, and significant discoloration and multiple repairs with chemically polymerized acrylic were noticed on the maxillary and mandibular removable prostheses. These findings suggested anterior hyperfunction syndrome. The anatomical changes related to this syndrome, and their implications on the overall prosthodontic treatment were explained to the patient in detail. After evaluating the prostheses, these were deemed adequate to be used as a reference to fabricate a 3D‐printed maxillary shell complete denture and mandibular diagnostic removable partial denture. On the second appointment, the 3D‐printed maxillary shell complete and mandibular removable partial denture were stabilized and relined intraorally (Figure ) and used to perform a dual scan of both arches following the protocol presented previously. The limited bone available led to the consideration of zygomatic implants to rehabilitate the maxillary arch. For the mandibular arch, a new removable partial denture assisted by two dental implants located in the first molar sites was considered a favorable treatment given the significant resorption of the mandibular posterior ridge and maintainable condition of her mandibular dentition. On the third appointment, a flangeless maxillary prototype and a mandibular removable partial denture were used to evaluate the feasibility of a fixed restoration for the maxillary arch, establish the orientation of the occlusal plane, the restorative space, and the position of the mandibular dental implants following the contours of the mandibular 3D‐printed diagnostic prosthesis. The 3D‐printed diagnostic prostheses were used to articulate maxillary and mandibular diagnostic casts in a semiadjustable articulator (Denar Mark II; Whip Mix, Louisville, KY). Selective enameloplasty of the incisal edge of the mandibular incisors was planned to ensure favorable anterior teeth relationships (Figure ). Subsequently, bilateral occlusal windows extending from the occlusal surface of the posterior teeth to the palatal surface of the lateral incisors and horizontal channels 10 mm above the occlusal plane were created on the 3D‐printed flangeless prototype. These features were created to serve as a reference for the antero‐posterior and vertical positioning of the dental implants (Figure ) and were based on the implant positions defined digitally. Additionally, 3D‐printed, and milled interim complete arch maxillary prostheses were fabricated. On the fourth visit, the modified flangeless prototype was used as a reference to place four zygomatic implants (ZAGA Flat‐ Zygomatic Implant System ⌀4.3 × 47.5 mm and ⌀4.3 × 45 mm; Straumann, Andover, MA) (Figure ) in the operating room under general anesthesia. Additionally, two dental implants (Bone Level X ⌀3.75 × 8 mm) were placed in the mandible in the first molar area (Figure ). Due to time limitations, the zygomatic and mandibular endosteal implants were not loaded immediately after implant placement. Two weeks later, the 3D‐printed maxillary interim prosthesis was relined and delivered uneventfully (Figure ). Subsequently, after 8 weeks of undisturbed healing, the zygomatic implants were uncovered; and the milled monolithic PMMA maxillary implant‐supported interim complete arch prosthesis was delivered and used as interim maxillary prosthesis while the mandibular arch was treated (Figure ). It is important to mention that the second interim prosthesis was created from the same STL file produced from the 3D‐printed maxillary shell complete denture. Furthermore, the gingival portion of the maxillary interim prosthesis was customized with pink composite resin (Gradia GUM Shades; GC America, Alsip, IL) according to the patient's esthetic preferences. A 58‐year‐old Caucasian female presented with a maxillary complete denture and extensively compromised mandibular teeth. She expressed having had the maxillary prosthesis for over 10 years and denied having a mandibular removable partial denture. Clinical findings suggested a decreased vertical dimension of occlusion, irregular occlusal plane, and unstable occlusion. Furthermore, the patientdisliked the esthetics of the maxillary prosthesis (Figure ). Her medical history was contributory. She denied smoking or taking medications that could compromise the survival of endosteal implants. When her mental attitude was assessed, it was classified as philosophical according to House's classification. Different treatment options were presented after evaluating the clinical findings and the patient's expectations. The patient selected a treatment plan consisting of interim maxillary and mandibular prostheses, followed by a new maxillary complete denture and a mandibular implant‐supported fixed complete denture. The cameo surface of the patient's existing maxillary prosthesis was registered with an intraoral scanner (IOS) (TRIOS 4 Wireless: 3Shape. Copenhagen, Denmark). The maxillary complete denture was stabilized manually, and a centric relation record was made with elastomeric bite registration material (Blue Mousse; Parkell, Edgewood, NY) and a plastic leaf gauge (Leaf Gauge; Huffman Dental, Springfield, OH). Subsequently, the maxillary complete denture and maxillomandibular relationships were scanned and saved in standard tessellation language (STL) format. Additionally, a preliminary impression of the mandibular arch was made with irreversible hydrocolloid (Geltrate; Dentsply Sirona, Charlotte, NC) to record the posterior mandibular areas. Then, a mandibular diagnostic cast was fabricated with type 3 dental stone (MicroStone; Whip Mix, Louisville, KY). The mandibular diagnostic cast was digitized and aligned with the STL files of the maxillary complete denture and centric relation record using an open‐source 3D modeling computer program (Meshmixer; AutoCAD, San Francisco, CA). The incisal edge, midline, artificial teeth proportions, and root eminences of the maxillary prosthesis were enhanced digitally (Figure ). A diagnostic shell maxillary complete denture and removable partial denture were created following the protocol presented in previous research. The finalized digital designs were manufactured using a photopolymerizable resin (P Pro Try‐In Resin; Straumann, Andover, MA) in a digital light processing (DLP) 3D printer (Rapid Shape Straumann P30+; Straumann, Andover, MA) and post‐cured according to the manufacturer's recommendations. On the second appointment, the 3D‐printed maxillary shell complete denture was stabilized with elastomeric bite registration material (Blue Mousse; Parkell, Edgewood, NY) on its intaglio surface to define the orientation and vertical position of the occlusal plane (Figure ). Subsequently, the 3D‐printed prostheses were relined with tissue conditioner (COE Comfort; GC America, Alsip, IL) and the occlusal plane, incisal edge position, centric relation, and vertical dimension were reassessed (Figure ). Radiopaque fiducial markers were applied to the cameo surface and a dual scan was completed. Additionally, a facebow registration and centric occlusion record were performed to transfer the new maxillomandibular relationships to a semi‐adjustable articulator (Denar Mark II; Whip Mix, Louisville, KY). A maxillary preliminary silicone putty cast was created from the intaglio surface of the maxillary 3D‐printed shell complete denture to facilitate subsequent clinical and laboratory procedures. The mandibular teeth were substituted with a complete digital teeth arrangement in the same open‐source 3D modeling computer program; the anterior denture base was extended to the labial vestibule, and the interim mandibular complete denture design was finalized. The dual scan CBCT data were imported into a professional implant planning computer program (CoDiagnostiX‐Dental Wings; Straumann, Andover, MA), and the digital interim mandibular complete denture design was aligned with the dual scan of the diagnostic removable partial denture using the occlusal surface of the artificial teeth as a reference (Figure ). Subsequently, four endosteal implants (Bone Level X ⌀4.5 × 10 mm; Straumann, Andover, MA) were planned. Three computer‐generated surgical templates were 3D‐printed (Rapid Shape Straumann P30+, and P Pro Surgical Guide; Straumann, Andover, MA) to position the fixation pins, guide bone reduction, and direct the placement of the endosteal implants. 3D‐printed maxillary and mandibular interim complete dentures were manufactured before surgery with biocompatible denture base and artificial teeth photopolymers (Pro Resins Denture; Straumann, Andover, MA), and their occlusion was refined on the semi‐adjustable articulator (Figure ). On the third visit, the endosteal implants were placed using the 3D‐printed surgical templates (Figures , and ). The 3D‐printed maxillary and mandibular interim complete dentures were relined intraorally with soft tissue conditioner (COE Soft; GC America, Alsip, IL). Subsequently, the esthetics, vertical dimension, phonetics, centric relation, and overall patient satisfaction were re‐evaluated and deemed satisfactory by the patient. (Figure ) A 66‐year‐old Caucasian male expressed interest in complete maxillary rehabilitation supported by endosteal implants. A severely resorbed maxillary arch with significant vertical and horizontal residual ridge defects, and a partially edentulous mandible with an irregular occlusal plane were observed (Figure ). When the patient's existing maxillary complete denture was evaluated, clinical features suggestive of decreased vertical dimension of occlusion, overextended denture base extensions, deficient retention, and unsatisfactory dental esthetics were also noticed (Figure ). After discussing these findings, a treatment consisting of immediately loading six endosteal implants with an interim maxillary prosthesis followed by a definitive maxillary fixed complete denture, and an implant‐supported restoration on the edentulous site #30 was accepted by the patient. At the end of the consultation, the cameo surface of the patient's existing complete denture was scanned, and a preliminary impression of the opposing arch was made with irreversible hydrocolloid. A diagnostic mandibular cast was poured, and a maxillary 3D‐printed shell complete denture with the desired contours and incisal edge position was designed and 3D‐printed following the protocol presented previously (Figure ). On the second visit, the orientation of the occlusal plane, anterior teeth position, and the vertical dimension of occlusion were defined using the 3D‐printed maxillary shell complete denture. Subsequently, radiopaque fiducial markers were placed on the cameo surface (Figure ), and a dual scan was performed. A facebow and centric relation records were completed, and a maxillary preliminary silicone putty cast was created from the 3D‐printed prosthesis. A flangeless prototype was 3D‐printed from the dual scan CBCT data of the relined3D‐printed maxillary shell complete denture as an additional diagnostic step for planning maxillary endosteal implants. On the third visit, the flangeless prosthesis was used to assess the viability of an implant‐supported fixed rehabilitation considering the new prosthetic contours, lip support, formation of upper labial crease, and anterior residual ridge display during function (Figure ). Subsequently, the flangeless maxillary prototype was articulated with the diagnostic mandibular cast in a semi‐adjustable articulator (Hanau Wide‐Vue; Whip Mix, Louisville, KY) (Figure ) to evaluate restorative space available, design the maxillary incision and flap design, and to plan selective enameloplasty on the mandibular posterior teeth to gain posterior restorative space and prevent occlusal interferences (Figure ). The dual scan data were used to plan six endosteal implants (Bone Level X; Straumann, Andover, MA) in strategic positions to ensure an even distribution without cantilevers. Three 3D‐printed surgical templates were manufactured to guide bone reduction and endosteal implant placement. Additionally, a maxillary complete arch interim prosthesis was designed and manufactured using the contours of the flangeless prosthesis as a reference using polymethylmethacrylate (PMMA) resin (Ceramill A‐Temp Shade A2; Amann Girbach, Koblach, Austria) in a 5‐axis milling unit (Straumann‐Amann Girbach M Series; Straumann, Andover, MA). It is worth mentioning that adjustments were made to the buccolingual position of the maxillary posterior teeth digitally before the manufacture of the PMMA complete arch interim prosthesis to address the reverse articulation on the patient's right posterior teeth observed with the flangeless prototype (Figure ). On the fourth appointment, the endosteal implants were placed using the 3D‐printed surgical templates. During the procedure, care was taken to avoid severing anatomical structures in proximity to the implant sites as the nasopalatine neurovascular bundle, preserving attached gingiva around all the endosteal implant, and debulking the tuberosity areas to ensure a maxillary complete arch interim prosthesis with adequate thickness posteriorly (Figure ). At this stage, all endosteal implants achieved insertion torque values >40 Ncm, permitting immediate loading with the PMMA maxillary complete arch interim maxillary prosthesis (Figure ). On the subsequent visits, the patient expressed satisfaction with the esthetics, phonetics, and cleansability provided by the interim maxillary prosthesis (Figure ). A 67‐year‐old Caucasian female presented to the clinics looking for maxillary and mandibular implant‐supported prostheses. It is noteworthy that certain aspects of the treatment given to this patient are detailed more thoroughly in a previously published technique article. During the initial consultation, it was noticed that her existing prostheses presented excessive wear and unfavorable occlusion (Figure ). The anterior mandibular teeth were over‐erupted, and significant resorption was observed in the posterior residual ridges. Additionally, the maxillary arch was severely resorbed, and significant discoloration and multiple repairs with chemically polymerized acrylic were noticed on the maxillary and mandibular removable prostheses. These findings suggested anterior hyperfunction syndrome. The anatomical changes related to this syndrome, and their implications on the overall prosthodontic treatment were explained to the patient in detail. After evaluating the prostheses, these were deemed adequate to be used as a reference to fabricate a 3D‐printed maxillary shell complete denture and mandibular diagnostic removable partial denture. On the second appointment, the 3D‐printed maxillary shell complete and mandibular removable partial denture were stabilized and relined intraorally (Figure ) and used to perform a dual scan of both arches following the protocol presented previously. The limited bone available led to the consideration of zygomatic implants to rehabilitate the maxillary arch. For the mandibular arch, a new removable partial denture assisted by two dental implants located in the first molar sites was considered a favorable treatment given the significant resorption of the mandibular posterior ridge and maintainable condition of her mandibular dentition. On the third appointment, a flangeless maxillary prototype and a mandibular removable partial denture were used to evaluate the feasibility of a fixed restoration for the maxillary arch, establish the orientation of the occlusal plane, the restorative space, and the position of the mandibular dental implants following the contours of the mandibular 3D‐printed diagnostic prosthesis. The 3D‐printed diagnostic prostheses were used to articulate maxillary and mandibular diagnostic casts in a semiadjustable articulator (Denar Mark II; Whip Mix, Louisville, KY). Selective enameloplasty of the incisal edge of the mandibular incisors was planned to ensure favorable anterior teeth relationships (Figure ). Subsequently, bilateral occlusal windows extending from the occlusal surface of the posterior teeth to the palatal surface of the lateral incisors and horizontal channels 10 mm above the occlusal plane were created on the 3D‐printed flangeless prototype. These features were created to serve as a reference for the antero‐posterior and vertical positioning of the dental implants (Figure ) and were based on the implant positions defined digitally. Additionally, 3D‐printed, and milled interim complete arch maxillary prostheses were fabricated. On the fourth visit, the modified flangeless prototype was used as a reference to place four zygomatic implants (ZAGA Flat‐ Zygomatic Implant System ⌀4.3 × 47.5 mm and ⌀4.3 × 45 mm; Straumann, Andover, MA) (Figure ) in the operating room under general anesthesia. Additionally, two dental implants (Bone Level X ⌀3.75 × 8 mm) were placed in the mandible in the first molar area (Figure ). Due to time limitations, the zygomatic and mandibular endosteal implants were not loaded immediately after implant placement. Two weeks later, the 3D‐printed maxillary interim prosthesis was relined and delivered uneventfully (Figure ). Subsequently, after 8 weeks of undisturbed healing, the zygomatic implants were uncovered; and the milled monolithic PMMA maxillary implant‐supported interim complete arch prosthesis was delivered and used as interim maxillary prosthesis while the mandibular arch was treated (Figure ). It is important to mention that the second interim prosthesis was created from the same STL file produced from the 3D‐printed maxillary shell complete denture. Furthermore, the gingival portion of the maxillary interim prosthesis was customized with pink composite resin (Gradia GUM Shades; GC America, Alsip, IL) according to the patient's esthetic preferences. Planning the positions of endosteal implants for complete arch rehabilitations must follow a thorough data collection and pre‐surgical extraoral and intraoral assessment. , , Furthermore, communication between the prosthodontist, oral surgeon, and the patient, as well as a clear understanding of the prosthetic considerations involved in a complete‐arch implant, are critical to the overall success of the treatment. The use of the patient's existing prostheses as a diagnostic aid for complete denture therapy was proposed by Spriggs. He recommended repositioning the patient's existing prostheses using “stops” of impression material in the intaglio surface to present to the patient what can be accomplished with a new set of complete dentures. Similarly, in this case series article, the 3D‐printed shell complete dentures were generated from the scans of the patient's existing prostheses and were used to establish important prosthodontic parameters before surgery. These appliances ensured clear communication between the oral surgeon, the prosthodontist, and the patient since provided a tangible representation of the projected treatment outcome. Additionally, having a visual representation of how the final rehabilitation would look like, and feel ensured early patient commitment and motivation, both requirements for successful prosthodontic rehabilitation. Clinical protocols depicting accelerated treatment protocols for digital complete dentures, and the conversion of CAD‐CAM milled complete dentures for immediate loading have been presented in the literature. Furthermore, 3D‐printed interim complete dentures have gained popularity thanks to the continuous improvement in the mechanical properties of contemporary denture teeth and denture base photopolymers, improved manufacturing accuracy of contemporary 3D printers, and superior design capabilities provided by most dental CAD and 3D modeling computer programs. , Therefore, additive and subtractive CAD‐CAM technologies are valuable tools for managing complex clinical situations because custom‐made appliances can be created from different sources of diagnostic data to serve specific clinical functions, thus simplifying diagnosis, planning, and execution of the treatment. , As seen in this article, when the protocol presented is used, the delivery of the interim restorations can be done on the third, or fourth appointment depending on whether the implant‐supported rehabilitation is for the maxilla or the mandible. This represents a significant reduction in clinical time when compared to traditional protocols considering the extent of diagnostic data gathered to accurately plan the position of the endosteal implants, evaluate labial support, define anterior teeth display, and identify what adjustments were required to develop a biomechanically favorable intraoral environment for the future rehabilitation. This case series article depicted the implementation of auxiliary diagnostic 3D‐printed treatment removable partial dentures and a flangeless maxillary prototype generated from the dual scan data. These diagnostic devices permitted transferring the intraoral relationships defined clinically to the semi‐adjustable articulator and allowed defining what intraoral structures required adjustment before interim prosthesis delivery. In Patient #2, for example, the maxillary tuberosities and the mandibular posterior teeth were selectively reduced to gain restorative space, establish a harmonious occlusal plane, and prevent occlusal interferences that could compromise the performance and integrity of the interim prosthesis. This permitted designing and manufacturing an interim prosthesis with satisfactory prosthetic volume, occlusion, and intraorally validated contours, all required factors to ensure biomechanical stability and avoid prosthetic complications during the healing stage of the treatment. The present case series report presents limitations related to the reduced number of patients presented, the short follow‐up time, and the limited availability of the technologies used for planning the endosteal implants and manufacturing the interim prostheses. The authors acknowledge that the present clinical protocol can only be applied to specific clinical situations where the patients present with an existing complete denture that can be used as a starting point. Therefore, edentulous patients without complete dentures should be managed traditionally or with other diagnostic protocols depending on the clinical situation. Additionally, a longer follow‐up time would have been necessary to validate the use of this protocol in the subsequent stages of treatment, such as the feasibility of using the interim prosthetic design generated from the 3D shell complete denture as a blueprint for the definitive implant‐supported prostheses. Finally, a significant limitation of the technique presented lies in the planning computer programs and manufacturing technologies needed to implement the protocol presented. The authors recognize that not all dental offices or educational facilities have the equipment required to manufacture the presented appliances. However, the authors believe that despite the limitations of this case series report, the applicability of the 3D‐printed shell denture protocol can be a feasible alternative to simplify the diagnosis, planning, and treatment of partially and completely edentulous patients requiring extensive prosthodontic treatment. The present case series report used 3D‐printed shell complete dentures to plan and design the interim maxillary and mandibular prostheses for three patients rehabilitated with endosteal implants. These diagnostic appliances allowed for establishing and testing important prosthodontic parameters such as the vertical dimension of occlusion, anterior teeth position, and occlusal plane orientation, and reduced the need for time‐consuming occlusal adjustments. Furthermore, the 3D‐printed shell complete dentures were used as a reference to strategically define the endosteal implant positions, create treatment diagnostic prostheses, and serve as a blueprint for designing the interim prostheses used during the healing stage. |
Culture-Based Standard Methods for the Isolation of | 21354781-3a86-41a2-a946-1404f4cbac8d | 11639288 | Microbiology[mh] | Campylobacter genus is comprised of Gram-negative, non-spore-forming rods and spiral and coccoid/spherical bacteria . Campylobacter species such as C. hyointestinalis, C. jejuni, C. fetus, C. coli, C. upsaliensis , and C. lari are important human pathogens . They cause food and water-borne enteric infections worldwide, which occur after the consumption of non-chlorinated well water or contaminated surface water , undercooked red meat or poultry products , and unpasteurized milk . Direct contact with infected individuals might also transmit campylobacteriosis. Similarly, nosocomial infection can occur, but reports of congenital transmission are rare. Children can acquire campylobacteriosis from immature diarrhetic animals . During the past three decades, Campylobacter species have emerged as important clinical pathogens of acute enteritis in Western countries. C. coli and C. jejuni are particularly important regarding gastrointestinal infections. Moreover, a link has been established between Guillain-Barre syndrome (GBS) and C. jejuni infection, further enhancing this species’ importance . Campylobacteriosis occurrence is significantly higher in developing countries than in developed nations, and Campylobacter -associated infection affects a large number of children in developing countries. Community-based investigations in developing countries have revealed that 60,000/100,000 children (aged < 5 years) suffer from campylobacteriosis, which establishes it as a pediatric disease . Human campylobacteriosis cases (> 90%) in developed countries mainly occur in the summer season with the increased consumption of undercooked meats at outdoor facilities. Campylobacteriosis could occur in individuals of all ages, but the infection rate is high in children (< 4 years) and young adults (15-44 years) . A relatively low infectious dose of C. jejuni (500-800 organisms) has been estimated in humans . Standard Campylobacter spp. isolation from food and water is performed through selective enrichment and selective plating. Public Health England (PHE), US Food and Drug Administration (FDA), and International Organization for Standardization (ISO) have developed different Campylobacter spp. detection methods involving specific sample preparation steps, selective plating media, and enrichment broths. This study overviews standard culture-based methods (ISO, PHE, and USFDA) for isolating Campylobacter spp. from food and water samples. It assessed the efficiency of culture media, pre-enrichment, selective enrichment, and selective plating media for detecting and monitoring Campylobacter spp. The review also elaborates on novel chromogenic culture media (advantages and constraints) to differentiate Campylobacter spp. in different samples (food and water). The limitations associated with culture-based detection of viable but non-culturable (VBNC) cells are discussed as well. Moreover, the review highlights alternative techniques and improvements for precise and efficient detection of Campylobacter spp. Overall, the study provides detailed insights regarding detecting Campylobacter spp. in food and water samples. Standard Campylobacter spp. detection in food and water samples often requires pre-enrichment followed by selective enrichment (at certain intervals and temperatures) and selective plating. The complete isolation process (identification and confirmation) could take up to 7 days . Campylobacter spp. detection procedures of , ISO , and US-FDA Bacteriological Analytical Manual (FDA-BAM) share some similarities. However, FDA-BAM recommends the same Campylobacter spp. isolation procedure for all types of samples (shellfish, milk, cheese, and water). ISO recommends three different methods according to the Campylobacter spp. contamination levels and background bacteria in food and water samples. PHE also employs the same procedure for different surface water and environmental samples. FDA protocols FDA has established five processing procedures before Campylobacter spp. detection from food and water samples . Sample preparation differs, whereas the detection procedure remains similar for all sample types and food sample/homogenate quantiles. Campylobacter spp. isolation from most foods [vegetables, poultry , water , shellfish , milk , and cheese ] require a Bolton broth-based pre-enrichment under microaerobic conditions (N 2 : 85%, CO 2 : 10%, and O 2 : 5%). Pre-enrichment temperature and incubation time could vary among various sample types , which is followed by enrichment (20-44 hours, 42°C) under microaerobic conditions. The enrichment culture is streaked on an FDA-recommended selective plating media (Abeyta-Hunt-Bark agar (AHB), modified charcoal cefoperazone deoxycholate agar (mCCDA), or Abeyta-Hunt-Bark without antibiotics). Then, plates are incubated under microaerobic conditions (24-48 hours, 42°C) . FDA protocol for the identification and confirmation of presumptive Campylobacter spp. colonies often relies on biochemical features of Campylobacter spp. . Initially, suspected colonies are examined for oxidase and catalase and oxidase followed by physiological and biochemical tests such as nitrate reduction, Hippurate hydrolysis, reaction on triple sugar iron agar (TSI), nalidixic acid resistance, growth at different temperatures (42°C, 35-37°C, and 25°C), and growth in glycerin. enlists the biochemical and physiological features of different Campylobacter spp. to confirm their identification. ISO Protocols ISO proposed three procedures for Campylobacter spp. isolation according to their contamination levels and background bacteria . Samples with lower numbers of Campylobacter spp. and background bacteria are subjected to Bolton broth-based pre-enrichment (4-6 hours, 37°C) followed by enrichment under a microaerobic atmosphere (44 hours, 41.5°C). Then, selective plating is carried out using mCCDA and another media of choice, followed by incubation (44 hours, 41.5°C) (Procedure A, ) . Preston broth is used for the selective enrichment (24 hours, 41.5°C) of Campylobacter spp. in samples with their lower numbers and high background bacteria followed by mCCDA mediabased selective plating as mentioned in procedure A (Procedure B, ) . The samples with high Campylobacter spp. levels are subjected to direct plating on selective agar (mCCDA) without enrichment steps (Procedure C, ) . ISO recommends a colony count method for Campylobacter spp. enumeration in food and water samples . It is carried out by spreading water and milk samples (1 ml) or food homogenate (1 ml) on a well-dried mCCDA plate surface. This approach can also be followed for samples’ serial dilutions. Then, the plates are incubated (40-44 hours, 41.5°C) under microaerobic conditions without pre-enrichment or enrichment steps . ISO recommends the microscopic confirmation of suspected Campylobacter spp. colonies through motility and morphological appearance . Moreover, aerobic growth (25°C) and oxidase activity should also be analyzed. Other biochemical tests can be performed as well to differentiate Campylobacter spp. colonies . ISO protocols also suggest PCR-based molecular identification and confirmation of presumptive Campylobacter spp. colonies . PHE protocols PHE protocols of Campylobacter spp. isolation from food samples involve enrichment of homogenate (25 g) in Bolton broth (10 −1 dilution) and incubations for 5 hours at 37°C and 44 hours at 41.5°C . Then, enrichment cultures are streaked on mCCDA media plates and microaerobically incubated (44 hours, 41.5°C) . The microaerobic growth (41.5°C) of presumptive Campylobacter spp. colonies is compared to the aerobic growth (25°C) on blood agar plates to confirm their identity . The procedure involves the examination of five suspected colonies from each mCCDA plate. PHE protocol also recommends other confirmatory steps such as cell motility’s microscopic examination and Oxidase test. Furthermore, PHE also recommends optional confirmation through PCR assay and latex test kits [ Campylobacter Latex Kit (LIOFILCHEM ® S.r.l., Italy), Oxoid™ DrySpot™ Campylobacter Test Kit (Thermo Fisher Scientific, Inc., USA), and Campylobacter Confirm Latex kit (Bio-Rad Laboratories, Inc., USA)] . FDA has established five processing procedures before Campylobacter spp. detection from food and water samples . Sample preparation differs, whereas the detection procedure remains similar for all sample types and food sample/homogenate quantiles. Campylobacter spp. isolation from most foods [vegetables, poultry , water , shellfish , milk , and cheese ] require a Bolton broth-based pre-enrichment under microaerobic conditions (N 2 : 85%, CO 2 : 10%, and O 2 : 5%). Pre-enrichment temperature and incubation time could vary among various sample types , which is followed by enrichment (20-44 hours, 42°C) under microaerobic conditions. The enrichment culture is streaked on an FDA-recommended selective plating media (Abeyta-Hunt-Bark agar (AHB), modified charcoal cefoperazone deoxycholate agar (mCCDA), or Abeyta-Hunt-Bark without antibiotics). Then, plates are incubated under microaerobic conditions (24-48 hours, 42°C) . FDA protocol for the identification and confirmation of presumptive Campylobacter spp. colonies often relies on biochemical features of Campylobacter spp. . Initially, suspected colonies are examined for oxidase and catalase and oxidase followed by physiological and biochemical tests such as nitrate reduction, Hippurate hydrolysis, reaction on triple sugar iron agar (TSI), nalidixic acid resistance, growth at different temperatures (42°C, 35-37°C, and 25°C), and growth in glycerin. enlists the biochemical and physiological features of different Campylobacter spp. to confirm their identification. ISO proposed three procedures for Campylobacter spp. isolation according to their contamination levels and background bacteria . Samples with lower numbers of Campylobacter spp. and background bacteria are subjected to Bolton broth-based pre-enrichment (4-6 hours, 37°C) followed by enrichment under a microaerobic atmosphere (44 hours, 41.5°C). Then, selective plating is carried out using mCCDA and another media of choice, followed by incubation (44 hours, 41.5°C) (Procedure A, ) . Preston broth is used for the selective enrichment (24 hours, 41.5°C) of Campylobacter spp. in samples with their lower numbers and high background bacteria followed by mCCDA mediabased selective plating as mentioned in procedure A (Procedure B, ) . The samples with high Campylobacter spp. levels are subjected to direct plating on selective agar (mCCDA) without enrichment steps (Procedure C, ) . ISO recommends a colony count method for Campylobacter spp. enumeration in food and water samples . It is carried out by spreading water and milk samples (1 ml) or food homogenate (1 ml) on a well-dried mCCDA plate surface. This approach can also be followed for samples’ serial dilutions. Then, the plates are incubated (40-44 hours, 41.5°C) under microaerobic conditions without pre-enrichment or enrichment steps . ISO recommends the microscopic confirmation of suspected Campylobacter spp. colonies through motility and morphological appearance . Moreover, aerobic growth (25°C) and oxidase activity should also be analyzed. Other biochemical tests can be performed as well to differentiate Campylobacter spp. colonies . ISO protocols also suggest PCR-based molecular identification and confirmation of presumptive Campylobacter spp. colonies . PHE protocols of Campylobacter spp. isolation from food samples involve enrichment of homogenate (25 g) in Bolton broth (10 −1 dilution) and incubations for 5 hours at 37°C and 44 hours at 41.5°C . Then, enrichment cultures are streaked on mCCDA media plates and microaerobically incubated (44 hours, 41.5°C) . The microaerobic growth (41.5°C) of presumptive Campylobacter spp. colonies is compared to the aerobic growth (25°C) on blood agar plates to confirm their identity . The procedure involves the examination of five suspected colonies from each mCCDA plate. PHE protocol also recommends other confirmatory steps such as cell motility’s microscopic examination and Oxidase test. Furthermore, PHE also recommends optional confirmation through PCR assay and latex test kits [ Campylobacter Latex Kit (LIOFILCHEM ® S.r.l., Italy), Oxoid™ DrySpot™ Campylobacter Test Kit (Thermo Fisher Scientific, Inc., USA), and Campylobacter Confirm Latex kit (Bio-Rad Laboratories, Inc., USA)] . Campylobacter spp. isolation Enrichment media for Campylobacter spp Foodborne Campylobacter spp. is conventionally recovered by adopting culturing and isolation methodologies . Selective enrichment is the initial step in conventional Campylobacter spp. recovery methods, which is followed by selective plating for isolation and confirmatory tests (immunological, molecular, and biochemical). The enrichment broths could revive stressed and inhibitor-exposed bacteria in the tested matrix and facilitate the recovery of isolated bacteria even at low concentrations . Enrichment broths differ in nutrient composition, incubation time, oxygen-degradation, environment and temperature requirements, and antimicrobial substances are added to restrain the growth of other competing microorganisms . Numerous enrichment broth formulations have been formulated for Campylobacter spp. isolation including Exeter broth, Bolton broth (BB), Modified CCD broth, Preston broth (PB), Doyle and Roman broth, and Rosef and Kapperude Campylobacter enrichment broth . Bolton broth and Preston formula are crucial for primary selective enrichment and are recommended due to satisfactory output, particularly in low bacterial count and stressed bacteria . The enrichment stage enhances microfloral growth in the target samples. Therefore, selective substances should be used to optimize Campylobacter spp. growth conditions for better recovery. There is no specific standard method for recovering Campylobacter species, particularly non-thermotolerant species . Antimicrobials-supplemented basal medium (nutrient broth or Brucella broth) is the main ingredient of enrichment broths . Enrichment broths were initially supplemented with lysed sheep or horse blood to reduce oxidative toxins’ damage . However, comparatively high blood cost and inessential isolation of Campylobacter spp., from poultry meat reduced their applications . Blood-free formulas are more convenient and can also be integrated with molecular techniques for rapid pathogen detection and identification. Campylobacter spp. isolation does not require a rich basal medium. USDA Food Safety and Inspection Service also uses blood-free Bolton broth, the best enrichment alternative . The buffered peptone water is quite similar to Bolton broth’s basal component and is equally effective for Campylobacter spp. isolation from broiler meat . Bolton broth is recommended for the enrichment of all sample types, particularly the US FDA recommends it for the recovery of Campylobacters spp. from various types of samples (environmental, food, and clinical). ISO also recommends Bolton broth for samples’ enrichment with lower Campylobacter spp. and background bacterial count . Bolton broth contains different nutrients, including yeast and peptone extract, sodium pyruvate, alpha-ketoglutaric acid, hemin, and sodium metabisulphite. Hemin helps in overcoming trimethoprim antagonism of yeast extracts . The addition of sodium metabisulphite and sodium pyruvate allows aerobic incubation, whereas sodium carbonate provides carbon dioxide for bacterial growth . The medium contains antibiotics (cycloheximide, cefoperazone, trimethoprim, and vancomycin) and lysed horse blood. Antibiotics restrict the growth of non-specific contaminating microorganisms . Specific substrates in Bolton broth limit trimethoprim antagonism, whereas hemin, ferrous sulfate/sodium metabisulfite/sodium pyruvate (FBP) mixture, and blood enhance oxygen quenching . Vancomycin in Bolton broth suppresses Gram-positive cocci but has lower efficacy against Campylobacters spp. as compared to rifampicin in Exeter and Preston broths . However, Bolton broth is preferred for Campylobacter spp. isolation from poultry samples . Bolton broth remains unable to detect certain Campylobacter species ( C. coli and C. jejuni ) in vegetables and chicken . Antibiotics in Bolton broth enhance its selectivity . However, cefoperazone might reduce the selectivity in mCCDA (modified charcoal cefoperazone deoxycholate) agar and Bolton broth, which could be due to the absence of rifampicin and polymixin . However, it is still helpful for samples with lower numbers of sublethally damaged or stressed Campylobacter spp. and samples containing lower numbers of non-target organisms . Several modifications of incubation temperatures and selective agents have been suggested for accurate and improved Campylobacter spp. detection . Preston broth is another commonly used enrichment broth for the isolation of Campylobacter spp. from various complex samples, including environmental , turbid surface water, and food specimens . Preston medium is nutrient broth comprised of lysed horse blood and antibiotics (cycloheximide, rifampicin, polymyxin B, and trimethoprim). In contrast, it does not contain yeast extract (trimethoprim antagonist) . Rifampicin is highly effective against Gram-positive bacteria. The culture media is incubated at 42°C under a microaerobic atmosphere . The presence of cycloheximide/amphotericin B, polymyxin B, trimethoprim, and rifampicin significantly enhances the selectivity of Preston broth . Polymyxin B inhibits the growth of extended-spectrum beta-lactamase (ESBL) bacteria as it possesses high activity against Gram-negative bacteria . Therefore, samples with high background flora (ESBL bacteria) are preferably grown in Preston broth . Preston broth has demonstrated high selectivity against non-target flora during Campylobacter spp. enrichment . ISO also recommends Preston broth for Campylobacter spp. isolation from samples (poultry and milk) with high background bacteria . have compared different enrichment methods and noted better efficacy of Preston broth than Bolton broth, which allowed the growth of some Escherichia coli strains that could hinder Campylobacter spp. growth to produce false-negative outcomes. Contrarily, some studies have depicted inhibited growth of Campylobacter strains ( C. coli ) in Preston broth, leading to false negative results . Exeter broth is routinely used in various laboratories to analyze water and food samples. It is also a primary enrichment medium for freshwater microbiological investigations . Exeter selective broth’s formulation is based on a lysed horse blood (5%) supplemented nutrient broth . Later on, the formula was modified , and oxygen-quenching agents ferrous sulfate/sodium metabisulfite/sodium pyruvate (FBP) mixture of Boltonv et al. (1984a, b) were added, which allowed aerobic incubation of Exeter broth. Exeter broth also contained different antibiotics, including cefoperazone (against Pseudomonas spp., and Enterobacterales), rifampicin, polymyxin B, amphotericin (against yeasts and molds), and trimethoprim . Modified charcoal cefoperazone deoxycholate broth (mCCD) is another blood-free selective enrichment broth that was modified from the original charcoal cefazolin deoxycholate (CCD) medium . The mCCD broth was mainly comprised of nutrient broth, cefoperazone, casein hydrolysates, bacteriological charcoal, and FBP supplements (sodium pyruvate, sodium deoxycholate, and ferrous sulfate) . The mCCD broth contains different Campylobacter spp. growth-promoting components and helps in the direct isolation of Campylobacter spp. from animal and human feces . Charcoal, deoxycholate, and cefoperazone combination inhibits bacterial growth (commensal flora and common contaminants) in food and clinical samples. Rosef and Kapperud Campylobacter enrichment broth contains sodium chloride, peptone, and antimicrobials (polymyxin B, vancomycin, and trimethoprim). Cysteine hydrochloride and sodium succinate-supplemented Brucella broth served as the basal medium in Doyle and Roman enrichment broth (DREB) . Antibiotics (polymyxin B, vancomycin, cycloheximide, and trimethoprim) and lysed horse blood were also added for better enrichment efficiency. used Brucella broth as a basal medium and altered its selectivity through significantly increased concentrations of cycloheximide and polymyxin , facilitating the selective recovery of lower Campylobacter spp. numbers in food samples. Cysteine hydrochloride and Succinate were also added, whereas lysed horse blood (7%) acted as an oxygen-quenching system. The medium was able to analyze raw milk and hamburger (0.1 to 4.0 cells/gram) but remained ineffective for poultry samples, which might be due to the diverse types and amounts of flora in these samples. Therefore, the DREB medium was further modified to rapidly enrich C. jejuni from raw chicken carcass samples . Doyle and Roman enrichment broth was established as the most suitable for detecting lower C. jejuni levels in chicken meat samples after 12 months of storage at -18°C. performed a comparison study of Park and Stankiewiez enrichment broth, Doyle and Roman enrichment broth, and a newly developed enrichment broth for C. jejuni isolation from raw chicken and revealed the highest selectivity potential of Doyle and Roman enrichment broth . Plating media for Campylobacter spp All the Campylobacter spp. isolating plating media used for food samples are either direct compositions or modified forms of clinical media that were developed for Campylobacter spp. isolation from fecal and clinical samples. Different types of plating media are available for Campylobacter spp. isolation with varying selectivity. These media are divided into two groups such as bloodcontaining solid media known as Campylobacter blood agar plates [Skirrow agar, Campy Brucella agar (Campy-BAP), Butzler agar, and Preston agar], and charcoalbased solid plating media [Karmali agar, and mCCD agar] . Despite poor productivity and sensitivity in food samples, Karmali agar and mCCDA are the best media for Campylobacter spp. isolation as colonies are easily recognizable in both media . Charcoal compounds and blood can reduce the toxic oxygen derivatives to generate a microaerobic environment for Campylobacters growth. Agar plates were also developed without charcoal or blood, demonstrating considerably lower efficacy than charcoal or blood-added broths . The resistance of thermophilic Campylobacter spp. to various antibiotic combinations in media determines its efficacy. Antibiotics such as polymyxin, vancomycin, rifampicin, trimethoprim, cefoperazone, nystatin, cephalothin, cycloheximide, and colistin inhibit background microbiota growth in samples and allow the isolation of slow-growing Campylobacter spp. . The capability of contaminating-flora inhibition differentiates between various media. All the selective agents facilitate the growth of C. coli and C. jejuni . To date, no medium can inhibit C. coli while allowing the growth of C. jejuni or vice versa . Other Campylobacter species ( C. hyointestinalis, C. lari, C. fetus, C. upsaliensis , and C. helveticus ) also grow on most media to some extent, particularly at a less selective temperature of 37°C. Skirrow’s selective agar medium was the first widely recommended for C. coli and C. jejuni isolation from human feces . It replaced the complicated method of selective filtration through 0.65 μm pore-size membranes. Skirrow’s Campylobacter selective agar contains peptone, lysed horse blood (7%), and antibiotics (trimethoprim, vancomycin, and polymyxin B) . The addition of vancomycin (inhibits Gram-positives), trimethoprim (broad-spectrum antibiotic), and polymyxin B (antifungal) mixture enhances its selectivity. The addition of lysed horse blood neutralizes trimethoprim antagonists of basal medium, leading to promoted growth of polymyxins-resistant Gram-negative Proteus spp. The incubation temperature of 42°C also contributes to the medium’s selectivity. Thus, only thermophilic Campylobacter spp. can grow in Skirrow’s medium, whereas the growth of non-thermophilic strains ( C. fetus subsp. fetus ) is restricted at 42°C. Skirrow’s medium is sometimes used for Campylobacter spp. detection in food samples but remains ineffective for many other types of samples . Campylobacter -selective agars contain different antibiotic combinations. Blood-containing Campy Brucella agar plate, also known as Campy-BAP, has been widely used . Campy-BAP is a Brucella base agar that contains five antimicrobial agents (cephalothin, vancomycin, amphotericin B, polymyxin B, and trimethoprim), and is supplemented with sheep blood (10%) . Antibiotics such as polymyxin B, cephalothin, and colistin might inhibit the growth of C. coli, C. jejuni , and C. fetus subsp. fetus . compared various enrichment techniques and direct isolation media to enumerate five C. jejuni strains in stored/refrigerated chicken meat. Campy-BAP agar and blood-free Campylobacter medium exhibited higher C. jejuni strains detection capability than Doyle and Roman enrichment broth and modified Butzler agar . investigated five types of selective media, including Campy-BAP and charcoal cefazolin deoxycholate agar (CCDA). They noted a better recovery rate with the CCDA medium (83%) as compared to the Campy-BAP medium (75%). CCDA medium also effectively suppressed normal enteric flora contamination. Campylobacter spp. colonies, particularly C. coli , appeared atypical on the Campy-BAP medium. The strains mainly produced homogeneous, discrete, and grey colonies, which were difficult to differentiate from coliform colonies in several cases. Campylobacter spp. colonies exhibited transparent and moist growth on other media. The morphology of colonies on Campy-BAP medium complicated the Campylobacter spp. identification process . Preston Campylobacter selective agar was specifically developed for Campylobacter spp. isolation from diverse specimens (environmental, human, and animal) . prepared Preston medium by dissolving nutrient broth in New Zealand agar and adding horse blood (saponin-lysed) and antibiotics (trimethoprim, polymyxin, actidione, and rifampicin). Preston medium demonstrated high Campylobacter spp. isolation rate from all tested samples and remained the most selective medium compared to other media . Campylobacter agar (Butzler’s) is used to isolate Campylobacter species selectively from different specimens, including clinical samples. reported the first selective formulation containing sheep blood agar and five antimicrobials (cephalothin, novobiocin, colistin, actidione, and bacitracin) where bacitracin and cephazolin inhibited the Gram-positive bacteria, and colistin and novobiocin inhibited the Gram-negative enteric flora. Further addition of cycloheximide inhibited the growth of common clinical mycotic contaminants. This medium was developed as an alternative to filtration and culturing on an elective blood-thioglycollate agar medium employed to examine human blood and fecal samples for vibrios . Cephalothin, in addition to the original formula (bacitracin, cycloheximide, novobiocin, and colistin), significantly enhanced its selectivity with the filtration method. Sheep blood agar serves as the basal medium in Butzler’s agar . Initial incubation is carried out at 42°C, and the temperature gradually decrease to grow C. jejuni but hinders the growth of C. etus subspecies intestinalis . Modified charcoal cefoperazone deoxycholate agar (mCCDA) is enlisted in international standard protocols and is widely used worldwide, where it is recommended as the plating media of choice for the detection and enumeration of Campylobacter spp. . It generates satisfactory results and is recommended for selective plating. mCCDA medium is based on the formula and is comprised of New Zealand agar, nutrient broth, bacteriological charcoal, sodium pyruvate, casein hydrolysates, ferrous sulfate, and sodium deoxycholate . The selectivity of this media was further enhanced by replacing cephazolin with cefoperazone . Initially, its development was aimed at thermotolerant Campylobacter spp. isolation from human fecal samples but then emerged as a specified standard medium for Campylobacter spp. isolation from food samples. The blood was replaced with sodium pyruvate, charcoal, and ferrous sulfate in the mCCDA medium, increasing the aerotolerance and growth of Campylobacter spp. Casein hydrolysate in this medium promotes the growth of C. lari environmental strains, whereas sodium deoxycholate and cefoperazone provide the required selectivity . Campylobacter selective mCCDA agar is a widely used blood-free plating medium . Thus, it helps to avoid the disadvantages of blood, such as easy contamination, short life, and expensive nature . The stickiness of Campylobacter spp. colonies to the plate surface in some cases is the only limitation that complicates harvesting . mCCDA and Skirrow media containing different antimicrobials have been used for culturing Campylobacter spp. where cefoperazone in mCCDA media proved a more effective selective agent and efficiently suppressed the enteric flora . The higher efficacy of broad-spectrum cefoperazone (cephalosporin) has been established against Enterobacteriaceae family members and pseudomonads . Karmali is a charcoal-based, blood-free selective medium. It is comprised of Columbia agar base, hematin, activated charcoal, sodium pyruvate, cycloheximide, cefoperazone, and vancomycin . Karmali medium was developed to overcome mCCDA selective agar-associated limitations . demonstrated significantly higher selectivity of Karmali agar and better Campylobacter spp. isolation rate from fecal samples as compared to Skirrow’s medium. Similar to blood, charcoal also acts as a quenching agent for enhanced aerotolerance against oxygen derivatives’ toxicity . Thus, charcoal-based agar is a better alternative for blood-containing agar in developing countries, which face erratic availability of sterile blood. Karmali agar medium contains sodium pyruvate in the selective supplement, whereas it is found in the basal medium of other blood-free Campylobacter spp. isolation media (mCCDA). Ferrous sulphate in mCCDA media is replaced with hemin in the Karmali medium. Vancomycin in the Karmali medium replaces the deoxycholate of mCCDA media and strongly inhibits the growth of Gram-positive microorganisms. Vancomycin is particularly effective against enterococci and thus eliminates bile salts’ inherent variability. Cefoperazone in this medium efficiently suppresses the growth of Pseudomonas spp. whereas cycloheximide more effectively inhibits yeasts than amphotericin B . The three antibioticselective agents (cycloheximide, cefoperazone, and vancomycin) in the Karmali medium efficiently restrict the growth of Gram-negative and Grampositive bacteria, and yeasts. During the development of this media, the efficacy of these antibiotic-selective agents was individually assessed . Karmali medium has been proven more selective than Skirrow medium. Some C. coli strains are cephalosporins-susceptible and the Skirrow medium performs better for isolating these strains than the Karmali medium. During a study, combining Skirrow and Karmali mediums produced near-optimal results for thermotolerant Campylobacter spp. isolation from fecal samples . revealed that charcoal and cefoperazone-containing Campylobacter spp. isolation media (mCCDA) generated better outcomes than earlier formulations. Chromogenic plating media for Campylobacter spp Adding chromogenic agar media in isolation protocols enhanced Campylobacter species identification capability through distinctive colony color. Synthetic chromogenic enzyme substrates in chromogenic media aid in their utility as both differential and selective media to identify the target isolate through their enzyme activity . A few commercial chromogenic agar plates are available in Latin America, the USA, and Europe. These plates are utilized to isolate Campylobacter spp. from meat, carcass rinse, environmental samples, and poultry meat. Campylobacter spp. isolating (food samples) sensitivity of chromogenic agars is similar to traditional plates . CHROMagar™ Campylobacter (CHROMagar™, France), CampyFood ® agar (bioMérieux, France), R&F ® Campylobacter media (R&F Products, USA), and Brilliance™ CampyCount Agar (Thermo Scientific™, Thermo Fisher Scientific, Inc., USA) are Campylobacter chromogenic media, facilitating visual recognition of Campylobacter spp. colonies without requiring subsequent culturing and confirmation tests. Thus, these media decrease the analysis’s cost and time . Campy-Food ® agar was the first commercial chromogenic-like agar that matched CCDA capabilities to isolate and enumerate Campylobacter spp. ( C. coli and C. jejuni ) from poultry samples. CampyFood ® agar plating medium was recommended for its high selectivity and better performance than the specificity (68%) and sensitivity (100%) of mCCDA . Moreover, it eliminates or minimizes the contamination of swarming and spreading colonies in tested samples . CampyFood ® agar plates are easy to handle and produce results comparable to those of other media . However, some other bacterial species might also grow on the plates, leading to Campylobacter spp. colonies’ overestimation. Therefore, the CampyFood ® medium is not entirely different for Campylobacter spp. isolation . An investigation in Chile reported a higher CampyFood ® medium-based Campylobacter spp. isolation rate from chicken meat (83%) than mCCDA (67%) . A selective chromogenic medium, Brilliance™ Campy Count agar, was developed explicitly for Campylobacter spp. ( C. coli and C. jejuni ) enumeration from poultry samples. Brilliance™ CampyCount agar is comprised of an amino acid and salt mix that allows accurate, clear, and specific C. coli and C. jejuni enumeration on poultry carcass samples . Brilliance™ CampyCount medium was carefully developed to achieve C. coli and C. jejuni growth while inhibiting the growth of non-target microorganisms. This medium indicates the colonies through a color change to dark red. Thus, all C. jejuni / coli colonies become readily identifiable within 48 hours on a transparent BCC medium . indicated that Brilliance™ CampyCount and CampyFood ® media efficiencies were comparable to mCCDA for Campylobacters spp. enumeration in naturally contaminated chicken meat. Brilliance™ CampyCount agar can be a potential alternative to mCCDA, but further investigation is required to enhance its selectivity for improved accuracy of Campylobacter spp. enumeration and minimum background microflora . CHROMagar™ Campylobacter is a selective chromogenic medium that is widely used for presumptive identification, direct qualitative detection, and differentiation of main thermo-tolerant Campylobacter spp. ( C. lari, C. jejuni , and C. coli ) from environmental and food samples by following the method. CHROMagar™ Campylobacter comprises of a chromogenic substrate, agar, yeast extract, peptones, Sodium chloride, and a selective mix . CHROMagar™ Campylobacter is also a blood-free transparent agar-like CLA-S medium that helps visualize and enumerate Campylobacter spp. colony forming unit (CFU) by producing purple colonies . R&F ® Campylobacter chromogenic agar plating medium targets the C-2 esterase enzyme of C. coli and C. jejuni. C. coli and C. jejuni are C-2 esterase positive, whereas other microorganisms remain negative to this enzyme. R&F ® Campylobacter chromogenic medium has enhanced sensitivity, and visual identification can easily distinguish the colonies. All current Campylobacter spp. isolation broth, media, and plates are modifications of media, which were developed almost three decades ago when achieving microaerobic conditions in the laboratories was challenging . Campylobacter spp Foodborne Campylobacter spp. is conventionally recovered by adopting culturing and isolation methodologies . Selective enrichment is the initial step in conventional Campylobacter spp. recovery methods, which is followed by selective plating for isolation and confirmatory tests (immunological, molecular, and biochemical). The enrichment broths could revive stressed and inhibitor-exposed bacteria in the tested matrix and facilitate the recovery of isolated bacteria even at low concentrations . Enrichment broths differ in nutrient composition, incubation time, oxygen-degradation, environment and temperature requirements, and antimicrobial substances are added to restrain the growth of other competing microorganisms . Numerous enrichment broth formulations have been formulated for Campylobacter spp. isolation including Exeter broth, Bolton broth (BB), Modified CCD broth, Preston broth (PB), Doyle and Roman broth, and Rosef and Kapperude Campylobacter enrichment broth . Bolton broth and Preston formula are crucial for primary selective enrichment and are recommended due to satisfactory output, particularly in low bacterial count and stressed bacteria . The enrichment stage enhances microfloral growth in the target samples. Therefore, selective substances should be used to optimize Campylobacter spp. growth conditions for better recovery. There is no specific standard method for recovering Campylobacter species, particularly non-thermotolerant species . Antimicrobials-supplemented basal medium (nutrient broth or Brucella broth) is the main ingredient of enrichment broths . Enrichment broths were initially supplemented with lysed sheep or horse blood to reduce oxidative toxins’ damage . However, comparatively high blood cost and inessential isolation of Campylobacter spp., from poultry meat reduced their applications . Blood-free formulas are more convenient and can also be integrated with molecular techniques for rapid pathogen detection and identification. Campylobacter spp. isolation does not require a rich basal medium. USDA Food Safety and Inspection Service also uses blood-free Bolton broth, the best enrichment alternative . The buffered peptone water is quite similar to Bolton broth’s basal component and is equally effective for Campylobacter spp. isolation from broiler meat . Bolton broth is recommended for the enrichment of all sample types, particularly the US FDA recommends it for the recovery of Campylobacters spp. from various types of samples (environmental, food, and clinical). ISO also recommends Bolton broth for samples’ enrichment with lower Campylobacter spp. and background bacterial count . Bolton broth contains different nutrients, including yeast and peptone extract, sodium pyruvate, alpha-ketoglutaric acid, hemin, and sodium metabisulphite. Hemin helps in overcoming trimethoprim antagonism of yeast extracts . The addition of sodium metabisulphite and sodium pyruvate allows aerobic incubation, whereas sodium carbonate provides carbon dioxide for bacterial growth . The medium contains antibiotics (cycloheximide, cefoperazone, trimethoprim, and vancomycin) and lysed horse blood. Antibiotics restrict the growth of non-specific contaminating microorganisms . Specific substrates in Bolton broth limit trimethoprim antagonism, whereas hemin, ferrous sulfate/sodium metabisulfite/sodium pyruvate (FBP) mixture, and blood enhance oxygen quenching . Vancomycin in Bolton broth suppresses Gram-positive cocci but has lower efficacy against Campylobacters spp. as compared to rifampicin in Exeter and Preston broths . However, Bolton broth is preferred for Campylobacter spp. isolation from poultry samples . Bolton broth remains unable to detect certain Campylobacter species ( C. coli and C. jejuni ) in vegetables and chicken . Antibiotics in Bolton broth enhance its selectivity . However, cefoperazone might reduce the selectivity in mCCDA (modified charcoal cefoperazone deoxycholate) agar and Bolton broth, which could be due to the absence of rifampicin and polymixin . However, it is still helpful for samples with lower numbers of sublethally damaged or stressed Campylobacter spp. and samples containing lower numbers of non-target organisms . Several modifications of incubation temperatures and selective agents have been suggested for accurate and improved Campylobacter spp. detection . Preston broth is another commonly used enrichment broth for the isolation of Campylobacter spp. from various complex samples, including environmental , turbid surface water, and food specimens . Preston medium is nutrient broth comprised of lysed horse blood and antibiotics (cycloheximide, rifampicin, polymyxin B, and trimethoprim). In contrast, it does not contain yeast extract (trimethoprim antagonist) . Rifampicin is highly effective against Gram-positive bacteria. The culture media is incubated at 42°C under a microaerobic atmosphere . The presence of cycloheximide/amphotericin B, polymyxin B, trimethoprim, and rifampicin significantly enhances the selectivity of Preston broth . Polymyxin B inhibits the growth of extended-spectrum beta-lactamase (ESBL) bacteria as it possesses high activity against Gram-negative bacteria . Therefore, samples with high background flora (ESBL bacteria) are preferably grown in Preston broth . Preston broth has demonstrated high selectivity against non-target flora during Campylobacter spp. enrichment . ISO also recommends Preston broth for Campylobacter spp. isolation from samples (poultry and milk) with high background bacteria . have compared different enrichment methods and noted better efficacy of Preston broth than Bolton broth, which allowed the growth of some Escherichia coli strains that could hinder Campylobacter spp. growth to produce false-negative outcomes. Contrarily, some studies have depicted inhibited growth of Campylobacter strains ( C. coli ) in Preston broth, leading to false negative results . Exeter broth is routinely used in various laboratories to analyze water and food samples. It is also a primary enrichment medium for freshwater microbiological investigations . Exeter selective broth’s formulation is based on a lysed horse blood (5%) supplemented nutrient broth . Later on, the formula was modified , and oxygen-quenching agents ferrous sulfate/sodium metabisulfite/sodium pyruvate (FBP) mixture of Boltonv et al. (1984a, b) were added, which allowed aerobic incubation of Exeter broth. Exeter broth also contained different antibiotics, including cefoperazone (against Pseudomonas spp., and Enterobacterales), rifampicin, polymyxin B, amphotericin (against yeasts and molds), and trimethoprim . Modified charcoal cefoperazone deoxycholate broth (mCCD) is another blood-free selective enrichment broth that was modified from the original charcoal cefazolin deoxycholate (CCD) medium . The mCCD broth was mainly comprised of nutrient broth, cefoperazone, casein hydrolysates, bacteriological charcoal, and FBP supplements (sodium pyruvate, sodium deoxycholate, and ferrous sulfate) . The mCCD broth contains different Campylobacter spp. growth-promoting components and helps in the direct isolation of Campylobacter spp. from animal and human feces . Charcoal, deoxycholate, and cefoperazone combination inhibits bacterial growth (commensal flora and common contaminants) in food and clinical samples. Rosef and Kapperud Campylobacter enrichment broth contains sodium chloride, peptone, and antimicrobials (polymyxin B, vancomycin, and trimethoprim). Cysteine hydrochloride and sodium succinate-supplemented Brucella broth served as the basal medium in Doyle and Roman enrichment broth (DREB) . Antibiotics (polymyxin B, vancomycin, cycloheximide, and trimethoprim) and lysed horse blood were also added for better enrichment efficiency. used Brucella broth as a basal medium and altered its selectivity through significantly increased concentrations of cycloheximide and polymyxin , facilitating the selective recovery of lower Campylobacter spp. numbers in food samples. Cysteine hydrochloride and Succinate were also added, whereas lysed horse blood (7%) acted as an oxygen-quenching system. The medium was able to analyze raw milk and hamburger (0.1 to 4.0 cells/gram) but remained ineffective for poultry samples, which might be due to the diverse types and amounts of flora in these samples. Therefore, the DREB medium was further modified to rapidly enrich C. jejuni from raw chicken carcass samples . Doyle and Roman enrichment broth was established as the most suitable for detecting lower C. jejuni levels in chicken meat samples after 12 months of storage at -18°C. performed a comparison study of Park and Stankiewiez enrichment broth, Doyle and Roman enrichment broth, and a newly developed enrichment broth for C. jejuni isolation from raw chicken and revealed the highest selectivity potential of Doyle and Roman enrichment broth . Campylobacter spp All the Campylobacter spp. isolating plating media used for food samples are either direct compositions or modified forms of clinical media that were developed for Campylobacter spp. isolation from fecal and clinical samples. Different types of plating media are available for Campylobacter spp. isolation with varying selectivity. These media are divided into two groups such as bloodcontaining solid media known as Campylobacter blood agar plates [Skirrow agar, Campy Brucella agar (Campy-BAP), Butzler agar, and Preston agar], and charcoalbased solid plating media [Karmali agar, and mCCD agar] . Despite poor productivity and sensitivity in food samples, Karmali agar and mCCDA are the best media for Campylobacter spp. isolation as colonies are easily recognizable in both media . Charcoal compounds and blood can reduce the toxic oxygen derivatives to generate a microaerobic environment for Campylobacters growth. Agar plates were also developed without charcoal or blood, demonstrating considerably lower efficacy than charcoal or blood-added broths . The resistance of thermophilic Campylobacter spp. to various antibiotic combinations in media determines its efficacy. Antibiotics such as polymyxin, vancomycin, rifampicin, trimethoprim, cefoperazone, nystatin, cephalothin, cycloheximide, and colistin inhibit background microbiota growth in samples and allow the isolation of slow-growing Campylobacter spp. . The capability of contaminating-flora inhibition differentiates between various media. All the selective agents facilitate the growth of C. coli and C. jejuni . To date, no medium can inhibit C. coli while allowing the growth of C. jejuni or vice versa . Other Campylobacter species ( C. hyointestinalis, C. lari, C. fetus, C. upsaliensis , and C. helveticus ) also grow on most media to some extent, particularly at a less selective temperature of 37°C. Skirrow’s selective agar medium was the first widely recommended for C. coli and C. jejuni isolation from human feces . It replaced the complicated method of selective filtration through 0.65 μm pore-size membranes. Skirrow’s Campylobacter selective agar contains peptone, lysed horse blood (7%), and antibiotics (trimethoprim, vancomycin, and polymyxin B) . The addition of vancomycin (inhibits Gram-positives), trimethoprim (broad-spectrum antibiotic), and polymyxin B (antifungal) mixture enhances its selectivity. The addition of lysed horse blood neutralizes trimethoprim antagonists of basal medium, leading to promoted growth of polymyxins-resistant Gram-negative Proteus spp. The incubation temperature of 42°C also contributes to the medium’s selectivity. Thus, only thermophilic Campylobacter spp. can grow in Skirrow’s medium, whereas the growth of non-thermophilic strains ( C. fetus subsp. fetus ) is restricted at 42°C. Skirrow’s medium is sometimes used for Campylobacter spp. detection in food samples but remains ineffective for many other types of samples . Campylobacter -selective agars contain different antibiotic combinations. Blood-containing Campy Brucella agar plate, also known as Campy-BAP, has been widely used . Campy-BAP is a Brucella base agar that contains five antimicrobial agents (cephalothin, vancomycin, amphotericin B, polymyxin B, and trimethoprim), and is supplemented with sheep blood (10%) . Antibiotics such as polymyxin B, cephalothin, and colistin might inhibit the growth of C. coli, C. jejuni , and C. fetus subsp. fetus . compared various enrichment techniques and direct isolation media to enumerate five C. jejuni strains in stored/refrigerated chicken meat. Campy-BAP agar and blood-free Campylobacter medium exhibited higher C. jejuni strains detection capability than Doyle and Roman enrichment broth and modified Butzler agar . investigated five types of selective media, including Campy-BAP and charcoal cefazolin deoxycholate agar (CCDA). They noted a better recovery rate with the CCDA medium (83%) as compared to the Campy-BAP medium (75%). CCDA medium also effectively suppressed normal enteric flora contamination. Campylobacter spp. colonies, particularly C. coli , appeared atypical on the Campy-BAP medium. The strains mainly produced homogeneous, discrete, and grey colonies, which were difficult to differentiate from coliform colonies in several cases. Campylobacter spp. colonies exhibited transparent and moist growth on other media. The morphology of colonies on Campy-BAP medium complicated the Campylobacter spp. identification process . Preston Campylobacter selective agar was specifically developed for Campylobacter spp. isolation from diverse specimens (environmental, human, and animal) . prepared Preston medium by dissolving nutrient broth in New Zealand agar and adding horse blood (saponin-lysed) and antibiotics (trimethoprim, polymyxin, actidione, and rifampicin). Preston medium demonstrated high Campylobacter spp. isolation rate from all tested samples and remained the most selective medium compared to other media . Campylobacter agar (Butzler’s) is used to isolate Campylobacter species selectively from different specimens, including clinical samples. reported the first selective formulation containing sheep blood agar and five antimicrobials (cephalothin, novobiocin, colistin, actidione, and bacitracin) where bacitracin and cephazolin inhibited the Gram-positive bacteria, and colistin and novobiocin inhibited the Gram-negative enteric flora. Further addition of cycloheximide inhibited the growth of common clinical mycotic contaminants. This medium was developed as an alternative to filtration and culturing on an elective blood-thioglycollate agar medium employed to examine human blood and fecal samples for vibrios . Cephalothin, in addition to the original formula (bacitracin, cycloheximide, novobiocin, and colistin), significantly enhanced its selectivity with the filtration method. Sheep blood agar serves as the basal medium in Butzler’s agar . Initial incubation is carried out at 42°C, and the temperature gradually decrease to grow C. jejuni but hinders the growth of C. etus subspecies intestinalis . Modified charcoal cefoperazone deoxycholate agar (mCCDA) is enlisted in international standard protocols and is widely used worldwide, where it is recommended as the plating media of choice for the detection and enumeration of Campylobacter spp. . It generates satisfactory results and is recommended for selective plating. mCCDA medium is based on the formula and is comprised of New Zealand agar, nutrient broth, bacteriological charcoal, sodium pyruvate, casein hydrolysates, ferrous sulfate, and sodium deoxycholate . The selectivity of this media was further enhanced by replacing cephazolin with cefoperazone . Initially, its development was aimed at thermotolerant Campylobacter spp. isolation from human fecal samples but then emerged as a specified standard medium for Campylobacter spp. isolation from food samples. The blood was replaced with sodium pyruvate, charcoal, and ferrous sulfate in the mCCDA medium, increasing the aerotolerance and growth of Campylobacter spp. Casein hydrolysate in this medium promotes the growth of C. lari environmental strains, whereas sodium deoxycholate and cefoperazone provide the required selectivity . Campylobacter selective mCCDA agar is a widely used blood-free plating medium . Thus, it helps to avoid the disadvantages of blood, such as easy contamination, short life, and expensive nature . The stickiness of Campylobacter spp. colonies to the plate surface in some cases is the only limitation that complicates harvesting . mCCDA and Skirrow media containing different antimicrobials have been used for culturing Campylobacter spp. where cefoperazone in mCCDA media proved a more effective selective agent and efficiently suppressed the enteric flora . The higher efficacy of broad-spectrum cefoperazone (cephalosporin) has been established against Enterobacteriaceae family members and pseudomonads . Karmali is a charcoal-based, blood-free selective medium. It is comprised of Columbia agar base, hematin, activated charcoal, sodium pyruvate, cycloheximide, cefoperazone, and vancomycin . Karmali medium was developed to overcome mCCDA selective agar-associated limitations . demonstrated significantly higher selectivity of Karmali agar and better Campylobacter spp. isolation rate from fecal samples as compared to Skirrow’s medium. Similar to blood, charcoal also acts as a quenching agent for enhanced aerotolerance against oxygen derivatives’ toxicity . Thus, charcoal-based agar is a better alternative for blood-containing agar in developing countries, which face erratic availability of sterile blood. Karmali agar medium contains sodium pyruvate in the selective supplement, whereas it is found in the basal medium of other blood-free Campylobacter spp. isolation media (mCCDA). Ferrous sulphate in mCCDA media is replaced with hemin in the Karmali medium. Vancomycin in the Karmali medium replaces the deoxycholate of mCCDA media and strongly inhibits the growth of Gram-positive microorganisms. Vancomycin is particularly effective against enterococci and thus eliminates bile salts’ inherent variability. Cefoperazone in this medium efficiently suppresses the growth of Pseudomonas spp. whereas cycloheximide more effectively inhibits yeasts than amphotericin B . The three antibioticselective agents (cycloheximide, cefoperazone, and vancomycin) in the Karmali medium efficiently restrict the growth of Gram-negative and Grampositive bacteria, and yeasts. During the development of this media, the efficacy of these antibiotic-selective agents was individually assessed . Karmali medium has been proven more selective than Skirrow medium. Some C. coli strains are cephalosporins-susceptible and the Skirrow medium performs better for isolating these strains than the Karmali medium. During a study, combining Skirrow and Karmali mediums produced near-optimal results for thermotolerant Campylobacter spp. isolation from fecal samples . revealed that charcoal and cefoperazone-containing Campylobacter spp. isolation media (mCCDA) generated better outcomes than earlier formulations. Campylobacter spp Adding chromogenic agar media in isolation protocols enhanced Campylobacter species identification capability through distinctive colony color. Synthetic chromogenic enzyme substrates in chromogenic media aid in their utility as both differential and selective media to identify the target isolate through their enzyme activity . A few commercial chromogenic agar plates are available in Latin America, the USA, and Europe. These plates are utilized to isolate Campylobacter spp. from meat, carcass rinse, environmental samples, and poultry meat. Campylobacter spp. isolating (food samples) sensitivity of chromogenic agars is similar to traditional plates . CHROMagar™ Campylobacter (CHROMagar™, France), CampyFood ® agar (bioMérieux, France), R&F ® Campylobacter media (R&F Products, USA), and Brilliance™ CampyCount Agar (Thermo Scientific™, Thermo Fisher Scientific, Inc., USA) are Campylobacter chromogenic media, facilitating visual recognition of Campylobacter spp. colonies without requiring subsequent culturing and confirmation tests. Thus, these media decrease the analysis’s cost and time . Campy-Food ® agar was the first commercial chromogenic-like agar that matched CCDA capabilities to isolate and enumerate Campylobacter spp. ( C. coli and C. jejuni ) from poultry samples. CampyFood ® agar plating medium was recommended for its high selectivity and better performance than the specificity (68%) and sensitivity (100%) of mCCDA . Moreover, it eliminates or minimizes the contamination of swarming and spreading colonies in tested samples . CampyFood ® agar plates are easy to handle and produce results comparable to those of other media . However, some other bacterial species might also grow on the plates, leading to Campylobacter spp. colonies’ overestimation. Therefore, the CampyFood ® medium is not entirely different for Campylobacter spp. isolation . An investigation in Chile reported a higher CampyFood ® medium-based Campylobacter spp. isolation rate from chicken meat (83%) than mCCDA (67%) . A selective chromogenic medium, Brilliance™ Campy Count agar, was developed explicitly for Campylobacter spp. ( C. coli and C. jejuni ) enumeration from poultry samples. Brilliance™ CampyCount agar is comprised of an amino acid and salt mix that allows accurate, clear, and specific C. coli and C. jejuni enumeration on poultry carcass samples . Brilliance™ CampyCount medium was carefully developed to achieve C. coli and C. jejuni growth while inhibiting the growth of non-target microorganisms. This medium indicates the colonies through a color change to dark red. Thus, all C. jejuni / coli colonies become readily identifiable within 48 hours on a transparent BCC medium . indicated that Brilliance™ CampyCount and CampyFood ® media efficiencies were comparable to mCCDA for Campylobacters spp. enumeration in naturally contaminated chicken meat. Brilliance™ CampyCount agar can be a potential alternative to mCCDA, but further investigation is required to enhance its selectivity for improved accuracy of Campylobacter spp. enumeration and minimum background microflora . CHROMagar™ Campylobacter is a selective chromogenic medium that is widely used for presumptive identification, direct qualitative detection, and differentiation of main thermo-tolerant Campylobacter spp. ( C. lari, C. jejuni , and C. coli ) from environmental and food samples by following the method. CHROMagar™ Campylobacter comprises of a chromogenic substrate, agar, yeast extract, peptones, Sodium chloride, and a selective mix . CHROMagar™ Campylobacter is also a blood-free transparent agar-like CLA-S medium that helps visualize and enumerate Campylobacter spp. colony forming unit (CFU) by producing purple colonies . R&F ® Campylobacter chromogenic agar plating medium targets the C-2 esterase enzyme of C. coli and C. jejuni. C. coli and C. jejuni are C-2 esterase positive, whereas other microorganisms remain negative to this enzyme. R&F ® Campylobacter chromogenic medium has enhanced sensitivity, and visual identification can easily distinguish the colonies. All current Campylobacter spp. isolation broth, media, and plates are modifications of media, which were developed almost three decades ago when achieving microaerobic conditions in the laboratories was challenging . Campylobacter spp. detection and future directions Culture-based techniques are a standard cultivation method for bacterial detection and enumeration of food and water . However, some foodborne and waterborne enteric bacteria, including Campylobacter spp. could enter a viable but non-culturable (VBNC) state that can somehow lose their growing capability on culture media . Despite non-culturability, VBNC cells are not considered dead due to different dissimilarities. A damaged membrane is the main feature of dead cells that cannot retain plasmids and chromosomal DNA, whereas the membrane of VBNC cells remains intact with undamaged DNA and plasmids . Dead cells become inactive metabolically, but VBNC cells remain metabolically active and perform respiration . Gene expressions stop in dead cells and transcription continues in VBNC cells followed by the production of mRNA . VBNC cells, in contrast to dead cells, continue to uptake and incorporate amino acids into proteins . VBNC bacterial cells retain their virulence and cause infection upon entry into hosts. Thus, they are a serious concern for public health, particularly about water and foodborne pathogens . Several studies have reported VBNC C. jejuni colonization in the rat guts, suckling mice, fertilized chicken eggs, and chicks (1-week-old) . successfully used artificial seawater to resuscitate the C. jejuni VBNC cells after 142 days by passing through the mouse intestine. Thus, VBNC C. jejuni could retain the virulence and infectivity. However, the infective capability of environmental VBNC cells without resuscitation remains unclear . An in vitro study has also reported the invasion of Caco-2 human intestinal epithelial cells by VBNC C. jejuni . Disease diagnosis and etiological agents’ identification in clinical, water, and food samples are still highly dependent on culture-based techniques. The inability to culture microorganisms could be a major limitation in disease diagnosis and treatments. This situation complicates pathogen detection in environmental, water, and food samples. Thus, potentially hazardous contaminations could remain undetected, and water and foodborne VBNC bacteria could seriously threaten public health ( ; Pan and Ren, 2023). VBNC state in food and water could be generally attributed to low-grade or aseptic infections and could be mistakenly linked to viruses if no bacteria are detected . Generally, the enrichment step resuscitates VBNC and damaged cells. Therefore, enrichment culture of water and food bacteria in selective/basal broth notably enhances the retrieval of experimentally injured Campylobacter spp. . An enrichment regime involving incubation (4 hours, 37°C) in broth [lysed horse blood (5%), sodium metabisulphite (0.02%), sodium pyruvate (0.02%), and ferrous sulfate (0.05%)] followed by another incubation (44 hours, 43°C) significantly improved damaged Campylobacter spp. cells’ recovery from river water samples . It might have facilitated the repair of injured cells before exposure to high temperatures . Propidium monoazide (PMA)-viability-qPCR approach could successfully detect the natural occurrence of VBNC Campylobacter spp. cells in environmental samples (chicken manure and barn). The study further demonstrated the Campylobacter spp. viability in water and soil up to 63 and 28 days, respectively . PMA-qPCR technique also efficiently detected laboratory-induced C. jejuni VBNC cells in UHT and pasteurized milk . It can also quantify VBNC Campylobacter spp. to provide insights into the unculturable Campylobacter spp. prevalence in agri-food productions and environment . This method offers an effective solution to overcome the limitations of traditional culture-based methods. However, it requires costly apparatus and highly trained personnel during the pre-treatment of samples for a successful VBNC Campylobacter spp. DNA isolation. PCR-based direct Campylobacter spp. cell detection in environmental and food samples is a time-effective approach as compared to culture-based identification and confirmation. Different PCR protocols with diverse primers have been developed for Campylobacter spp. detection in wastewater and water samples . Most PCR-based studies analyzed the Campylobacter spp. absence or presence in samples whereas some studies obtained quantitative results by employing real-time PCR . These protocols facilitated the recovery from Campylobacter spp.-seeded cultures. Direct PCR assay could efficiently detect the natural occurrence of Campylobacter spp. in polluted drinking water without an enrichment step . also employed a direct PCR approach to successfully detect C. jejuni in naturally contaminated water without prior enrichment of samples. PCR-based direct Campylobacter spp. detection in clean drinking water might be feasible. However, it could generate false negative results in samples containing high levels of background bacteria . In contrast to contaminated drinking water samples, Campylobacter spp. presence in milk, poultry, and environmental murky water samples remains comparatively low with high levels of background microbiota and PCR inhibitors. Therefore, the enrichment step becomes mandatory before PCR detection . Similarly, multiple studies have performed enrichment steps before PCR detection of Campylobacter spp. in various types of samples such as river and spiked estuarine water samples , spiked and naturally polluted sewage samples , spiked and natural food contamination samples , samples of natural poultry and human fecal contaminations , spiked chicken rinse water , and murky pond water . Generally, enrichment incubation increases the target cell population for better PCR detection. Direct PCR, multiplex PCR, and qPCR can also amplify the DNA of dead cells and naked DNA fragments in water and food samples without the enrichment step . The presence of dead Campylobacter spp. cells in water samples depict contamination but are no longer harmful to public health . Therefore, the induction of an enrichment step before PCR assay enhances the detection of viable cells. Selective enrichment followed by PCR assay has emerged as a standard method for Campylobacter spp. detection in environmental samples . The FISH (fluorescence in situ hybridization) method differentiates DNA fragments and whole cells. A fluorescent Campylobacter spp.-specific oligonucleotide probe is used to label the whole cells, followed by epifluorescence microscopy. detected C. coli after membrane filtration of spiked tap water and noted hybridized cells with different fluorescence brightness, which helped separate senescent and actively growing C. coli cells. Immunebased assay could be another alternative to traditional culture-based methods. However, immune-assay kits are yet to be validated for Campylobacter spp. detection in food (poultry) samples, possibly due to matrix-induced sensitivity loss . Despite extensive developments and research of alternatives for precise and rapid Campylobacter spp. detection, identification, and quantification in samples (environmental, food, and clinical), and culture-based techniques are still the gold standard. Standard organizations recommend immune-based and molecular approaches for the identification and precise confirmation of presumptive Campylobacter spp. colonies along with conventional confirmatory tests . Campylobacter spp. in food and water Molecular and culture methods of Campylobacter spp. detection present particular advantages and disadvantages over each other, which are discussed below: Detection accuracy and specificity Traditional culturing grows only viable Campylobacter spp. cells via selective media and thus achieves high specificity by restricting the interference of other microorganisms. This approach detects only live pathogens to indicate a current risk of the infection. Molecular techniques (PCR and qPCR) can efficiently detect Campylobacter -specific DNA in complex samples. However, these methods can detect dead and live cells, including nonviable cells’ residual DNA, and potentially yield false positives related to infection risk. Limit of detection and sensitivity The sample’s initial bacterial load and competing flora could alleviate the sensitivity of culture-based methods. The pathogenic VBNC cells of Campylobacter spp. could remain undetected in selective media, which results in the underreporting of infections. On the other hand, Campylobacter spp. DNA can be detected by more sensitive molecular approaches even in background flora-contaminated samples. The sensitivity of PMA-qPCR is even better as it could exclude the dead cells in the sample. Completion time The enrichment, selective plating, and incubation steps lengthen the culture-based methods and take several days to produce results. This limits routine pathogen monitoring, where quick outputs are preferred. Conversely, PCR produces results within hours to help in real-time pathogen monitoring and timely response during outbreaks. Experimental cost Microbial culturing can be performed without costly equipment, so these methods are preferred in less developed laboratories. However, laborious culture-based approaches are time-consuming and require more manual handling. Conversely, expensive reagents and equipment (qPCR and PCR thermocyclers) are required for rapid molecular techniques. Moreover, highly trained personnel are required to perform these procedures, which limits their utility in settings with fewer resources. Strain typing and further analysis The cultured colonies facilitate further analysis through genotyping, biochemical tests, and antibiotic susceptibility testing, a prerequisite for outbreak tracking and epidemiological studies. Molecular approaches (qPCR, DNA sequencing, and multiplex PCR) facilitate precise and rapid identification of pathogens, genetic analysis, and epidemiological tracking. However, further analyses are restricted in this case, as these methods cannot provide live bacterial culture. Efficiency in diverse sample types Culture-based techniques can be applied to diverse types of water and food samples. However, complex food matrices can affect the detection process. Similarly, environmental and food samples can also alleviate the detection efficiency of molecular approaches. Therefore, an increase in bacterial cell numbers via pre-enrichment is often required before analysis. Standardization and regulatory acceptance ISO and FDA have standardized culture-based detection protocols as the gold standard for water and food safety testing. Conversely, rapidly emerging molecular techniques have yet to be universally standardized for Campylobacter spp. detection in water and food samples. Their consistency across laboratories and validation remains a challenge for regulatory acceptance. Briefly, the cost-effective culture-based techniques are highly reliable and essential for live pathogen detection and regulatory compliance. On the other hand, molecular approaches rapidly generate sensitive results and thus are particularly useful for prompt outbreak response. However, high cost and necessary technical assistance restrict their large-scale applicability. Integrating both approaches could provide comprehensive, timely detection of pathogens by balancing the culturebased specificity and speed of molecular methods. Traditional culturing grows only viable Campylobacter spp. cells via selective media and thus achieves high specificity by restricting the interference of other microorganisms. This approach detects only live pathogens to indicate a current risk of the infection. Molecular techniques (PCR and qPCR) can efficiently detect Campylobacter -specific DNA in complex samples. However, these methods can detect dead and live cells, including nonviable cells’ residual DNA, and potentially yield false positives related to infection risk. The sample’s initial bacterial load and competing flora could alleviate the sensitivity of culture-based methods. The pathogenic VBNC cells of Campylobacter spp. could remain undetected in selective media, which results in the underreporting of infections. On the other hand, Campylobacter spp. DNA can be detected by more sensitive molecular approaches even in background flora-contaminated samples. The sensitivity of PMA-qPCR is even better as it could exclude the dead cells in the sample. The enrichment, selective plating, and incubation steps lengthen the culture-based methods and take several days to produce results. This limits routine pathogen monitoring, where quick outputs are preferred. Conversely, PCR produces results within hours to help in real-time pathogen monitoring and timely response during outbreaks. Microbial culturing can be performed without costly equipment, so these methods are preferred in less developed laboratories. However, laborious culture-based approaches are time-consuming and require more manual handling. Conversely, expensive reagents and equipment (qPCR and PCR thermocyclers) are required for rapid molecular techniques. Moreover, highly trained personnel are required to perform these procedures, which limits their utility in settings with fewer resources. The cultured colonies facilitate further analysis through genotyping, biochemical tests, and antibiotic susceptibility testing, a prerequisite for outbreak tracking and epidemiological studies. Molecular approaches (qPCR, DNA sequencing, and multiplex PCR) facilitate precise and rapid identification of pathogens, genetic analysis, and epidemiological tracking. However, further analyses are restricted in this case, as these methods cannot provide live bacterial culture. Culture-based techniques can be applied to diverse types of water and food samples. However, complex food matrices can affect the detection process. Similarly, environmental and food samples can also alleviate the detection efficiency of molecular approaches. Therefore, an increase in bacterial cell numbers via pre-enrichment is often required before analysis. ISO and FDA have standardized culture-based detection protocols as the gold standard for water and food safety testing. Conversely, rapidly emerging molecular techniques have yet to be universally standardized for Campylobacter spp. detection in water and food samples. Their consistency across laboratories and validation remains a challenge for regulatory acceptance. Briefly, the cost-effective culture-based techniques are highly reliable and essential for live pathogen detection and regulatory compliance. On the other hand, molecular approaches rapidly generate sensitive results and thus are particularly useful for prompt outbreak response. However, high cost and necessary technical assistance restrict their large-scale applicability. Integrating both approaches could provide comprehensive, timely detection of pathogens by balancing the culturebased specificity and speed of molecular methods. Campylobacter spp. isolation and detection from water and food sources is necessary for public health as these pathogens are associated with widespread enteric infections. The specificity and regulatory acceptance of ISO, FDA, and PHE-recommended culture methods make them the gold standard for Campylobacter spp. detection. The lengthy procedures and background flora-associated lower sensitivity are major limitations. These can be overcome by adding selective enrichment and plating media steps for the reliable identification of Campylobacter spp. The use of chromogenic media is a cost-effective and rapid approach that yields varying colors in different Campylobacter spp. colonies. However, they should be standardized for consistent results at varying microbial contaminations in foods. The undetected VBNC cells of Campylobacter spp. are a major threat to food safety. The sensitivity of advanced immunological and molecular methods (PCR and PMA-qPCR) to Campylobacter spp. is higher than conventional procedures. However, the need for highly trained personnel and expensive apparatus limits their applications. Integrating conventional culturing and recent molecular techniques is the way forward that could improve the specificity, speed, and sensitivity for robust surveillance of foodborne pathogens. Simultaneously, sustained adaptations and innovations are mandatory for Campylobacter spp. detection to ensure public health safety, particularly in low-resource regions. Standardization and validation of novel methods are necessary for improving Campylobacter spp. monitoring to curb their global infections. |
Coaching approaches in early intervention and paediatric rehabilitation | c78f1df1-e5c3-4d75-b39d-86f569daeadb | 7187136 | Pediatrics[mh] | Coaching in early intervention is often used to strengthen the family members' capacity to support their child's development within the context of everyday routines and activities. In other words, coaching is used in parent‐implemented intervention. The definitions of coaching vary considerably. , , They range from pure intervener‐directed intervention forms, which mimic typical parent training interventions, to relationship‐directed forms based on principles of family‐centred practice. The heterogeneity in definitions has induced a training–coaching continuum in the intervention literature: at opposite ends of the spectrum there are two largely differing approaches, namely ‘parent training’ and ‘parent coaching’; and in‐between there is a mix of the two approaches. In the literature, all are covered by the term ‘coaching’. The two approaches differ in the following ways. ‘Parent training’ includes actions during which health care professionals instruct family members and demonstrate how to apply intervention strategies in a clear and strict way. The aim of parent training is that parents become enabled to reproduce the predetermined intervention strategies – often according to a specific protocol – in daily life at home. The professional adopts the role of a teacher and determines the what, how, and when of the intervention. The intervention's focus is on child development. The relationship between professional and family members is a supportive instructor–learner interaction. ‘Parent coaching’ includes actions during which the health care professional supports family members in the process of decision making on functional activity and participation in daily life with the aim of family empowerment and optimizing child development. The ultimate goal is optimal participation of the child and family. In this collaborative and interactive process of decision making, the coaching strategies described by Rush et al. are used. These strategies include joint planning, observation, action/practice, reflection, and reciprocal feedback. They are applied individually and flexibly as the result of the shared decision‐making process. In other words, parent coaching in early intervention has a dual aim: (1) to enhance the family's capacity to participate as an active and equal partner in the intervention process; (2) to be able to make informed decisions. The coach does not instruct family members what they have to do but creates explorative situations, so that family members may discover themselves how best to implement principles of developmental stimulation in daily life. The coach provides suggestions but no strict instruction. The focus of the intervention is on the family as a unit, and the relationship between the health care professional and family members is based on equal partnership. Studies on the effect of intervener‐directed interventions and RD‐FCI have almost always described child outcomes (for an overview of child and parent outcome measures, see Ward et al. and Kemp and Turnbull). For both approaches, positive effects have been reported for skills across the developmental domains. Parent or family outcomes have not been described as often, and, where they have been described, the primary focus has been on the fidelity of applying intervention strategies. Positive effects on the family itself, such as parental quality of life, parental sense of self‐efficacy, and family empowerment, have been mainly reported for RD‐FCI approaches. The study by Welterlin et al. on an intervener‐directed intervention is an exception to this rule: it reported a slight, but insignificant decrease in parental stress in the intervention group. Examples of programmes that use a mix of parent training and coaching are the Goal, Activity, Motor Enrichment programme and the Small Steps Program. These programmes have been associated with improved infant motor outcome, but with no effect on maternal well‐being in terms of anxiety, depression, or stress. , Over the years, the use of the term ‘coaching’ in intervener‐directed interventions has increased. The study by Kaiser and Roberts, in which parents were trained to use predetermined intervention strategies, serves as an example. In the intervener‐directed interventions, the primary aim of the educational actions towards the parents was strengthening the capacity of family members to replicate the programme's strategies. Relatively little attention has been paid to principles of family‐centred practice, such as equal partnership and supporting parents in making informed decisions. Literature , , , suggests that parent training and parent coaching are two different approaches with different goals, beliefs, and attitudes. Approaches using parent training focus on child development, whereas in approaches applying parent coaching both family and child are in the picture. In coaching using RD‐FCI, key elements are capacity building, and being non‐directive, reflective, and collaborative; parents' priorities are respected and the intervention builds on what parents know and already do. Parent training usually lacks these key elements. Therefore, it is crucial to clearly discriminate between the two methods. Hence, we suggest labelling intervener‐directed forms of intervention as ‘parent training’ and reserving the term ‘coaching’ in early intervention and paediatric rehabilitation exclusively for RD‐FCI.
The ambiguity on what coaching means has hampered its incorporation into the professional role of health care providers in early intervention. This is illustrated by the insufficient implementation of coaching in RD‐FCI. , , , , It is reflected by recent findings that health professionals spend a major part of treatment time in child‐focused activities and instruction, and relatively little time in coaching strategies directed to the family. Also, the fact that health professionals often remain in the role of decision maker, and do not meet caregivers as equal partners, suggests unsatisfactory implementation of relationship‐directed coaching. The data indicate that it is challenging for health care professionals to apply coaching in RD‐FCI as it demands behaviour changes in most health professionals. , , , , , , Presumably, one of the biggest challenges is to change the professional role, , for example from the child's therapist to the coach of the family, from the advice giver to the facilitator, or from decision maker to equal partner. Changing the professional role implies changing the primary focus of guidance, giving up the leader role, sharing power, or acknowledging the caregivers' autonomy. The motivation and capability to change the professional role demands particular attitudes and beliefs, for example beliefs in the family's capacity. The change in the role of the professional automatically changes the role of the family members. Typically, parents expect professionals to treat the child during intervention: they expect that the therapist does the job of treating while they watch the treatment and receive instructions, advice, and information. These expectations may be grounded in previous experience with interventions, or in ideas available on the Internet. In addition, receiving clear instructions may be comfortable and effective for short‐term outcomes. For parents, being involved in processes of decision making, joint planning, action, and reflection is often unexpected, challenging, and usually hard work, especially at the start of the intervention. However, studies have shown that most families are rapidly willing and able to overcome the initial effort, as they appreciate the collaborative intervention style addressing their priorities, enhancing their capacity, and increasing their confidence, self‐efficacy, and self‐determination. , Interestingly, Blauw‐Hospers et al. reported that infants of mothers with relatively little education profited more from RD‐FCI in terms of cognitive development than those of mothers with a better educational background. It is conceivable that the latter group of mothers already had better problem‐solving strategies before the intervention started than the former group. The above implies that when the health care professional takes on the role of coach, they also need to explain the novel role distribution, including its associated advantages and challenges, to the family. If this is overlooked, the risk of misunderstandings is high. A second challenge is the knowledge required for proper implementation of coaching in RD‐FCI. , , , The coaching strategies described by Rush et al., including observation, reflection, and reciprocal feedback, may differ from what health professionals learned in basic education. Coaching strategies are not spontaneously present: they have to be learned and practised. As the coaching is directed to the parents, it requires knowledge of adult learning, namely the processes that lead to modification of behaviour or the acquisition of new abilities or responses. A third challenge is the translation of knowledge and beliefs into practice. Consistent translation into practice requires ample opportunities to apply coaching skills, including active listening, flexible provision of relevant information, and reflection about what works and what does not, in such a way that the needs of the individual family are met. The attitudes/beliefs, knowledge, and skills needed for successful implementation of coaching in RD‐FCI are summarized in Table .
The implementation of coaching in RD‐FCI may be hindered by barriers. First, beliefs and attitudes of the professional that are radically different from those needed for coaching in RD‐FCPI may form a considerable barrier. Campbell and Sawyer highlighted how strongly personal factors of health care professionals may affect the practical implementation of RD‐FCI. Therefore, health care professionals becoming a coach in RD‐FCI need to be aware of their own beliefs and attitudes, as these may interfere with participative interaction with the families. In fact, coaching may be regarded as a complex interaction between the family and health care professional, in which beliefs and attitudes of both parties mutually affect each other. For instance, the attitude of an instructing therapist creates a relatively easy and attractive situation for the family members, but pairs this with facilitation of the family's dependency on therapeutic assistance in the long run. This contrasts with the attitude of a coach, who is prepared to cooperate in a relationship‐directed manner with autonomous families. The coach invites parents to reflect on what works and what does not. The resulting insight enables parents to improve self‐competences, to make meaningful and sustainable changes, and to reach higher independency of health care. , Studies on mothers' experiences highlighted the values and learning processes of mothers in different RD‐FCI approaches. , , Offering health care professionals the opportunity to understand their own attitudes allows them to understand what they perhaps need to change and whether they need to reconstruct personal beliefs and perceptions to be a coach of an autonomous family. , Second, the strong habits of the health care professional acquired during daily practice may form an obstacle to developing coaching skills. Strong habits are generally hard to unlearn. Michie et al. suggested that environmental restructuring, modelling, and enablement are the proper means to change habitual behaviour. This behavioural reprogramming requires ample practice. Ample practice paves the way for the emergence of new skills and the development of new, strong habits. Other important ingredients needed for the acquisition of new and long‐lasting automatic behaviour are illustrating new behaviour and a supportive environment, namely the presence of guidance and ongoing supervision and support. There is consensus in the literature , , , , that the implementation of coaching in RD‐FCI requires comprehensive and well‐designed professional education, which includes ongoing support in its practical implementation. For instance, Friedman et al. argued that formal training, time for practice, support from peers, ongoing support by supervision, and opportunities for reflection are indispensable to acquire coaching practice. Yet, the literature detailing the professional education of coaching skills varies. For instance, (1) the duration of the periods of education ranges from 12 hours to 12 days; , (2) contents include specific approaches on child development and general principles on collaboration with families and coaching; , , , , (3) educational methods vary from provision of theoretical knowledge through lectures, , , , , role‐play, , and group discussions on implementation. , , In the subsequent paragraphs, we critically discuss what the best options may be. Becoming a coach involves acquiring knowledge on adult learning processes, and changing habits, attitudes, and beliefs. This means that becoming a coach is a complex learning process; it requires time. Studies evaluating the development of coaching skills in health professionals showed that 1 to 4 days of education did not result in a satisfactory implementation of coaching skills. , , Yet, two other studies indicated that 12 days of professional education (offered in the format of six sets of 2 days over 2 years) did result in successful implementation of coaching skills. , Together, these results imply that professional education needs to be offered for more than 4 days to achieve a proper implementation of coaching skills. The successful implementation through the more intensive professional development presumably may be attributed to the prolonged duration of the education. A course set‐up with intervals of a few months allows for repetition, opportunity to practise in the real‐life setting, and offers time for reflection, , which are all essential ingredients for changing habitual behaviour, attitudes, and beliefs. Despite the varying ideas on the content of knowledge that professionals becoming a coach in RD‐FCI should ideally acquire, consensus , , , , , exists that the key content consists of: (1) principles of family‐centred practice and relationship‐directed collaboration; (2) a clear definition of coaching, and information on coaching strategies and required coaching skills; and (3) processes involved in adult learning. This brings us to the methods that function best in the education of coaching skills in RD‐FCI. The literature contains a wealth of didactic principles that are successfully applied to transfer knowledge, attitudes, and skills during contact days of education. , , , , These include provision of theoretical knowledge through lectures, , , , , presentation of video clips illustrating coaching strategies, , , , role‐play to practice coaching skills, , and the articulation of the beliefs and attitudes needed. The transfer of knowledge, attitudes, and skills only results in implementation in actual coaching when it is accompanied by translation of knowledge into practice, , , , namely when education also includes substantial periods of ample supervised practice in the professional's everyday work setting. , To be effective, the periods of translation into practice in the intervals between days of contact education need to be supplemented by self‐reflection and external feedback. , , , , For self‐reflection and external feedback, video‐tapes of the practicing professional may be used. External feedback may be provided by the teacher involved in the coaching education and by peers following the same coaching course. The teacher's external feedback may be provided multiple times in the course intervals by individual face‐to‐face feedback; the peer‐feedback may occur during the course and during the intervals.
In paediatric rehabilitation and early intervention, family‐centred practices have become the practice‐of‐choice. Coaching is an important ingredient of these practices. This review has highlighted that coaching is not a uniform method: it is applied with different approaches and different assumptions, and the role of the coach is interpreted in variable ways. To avoid ambiguity, we recommend that in the field of early intervention and paediatric rehabilitation the term ‘coaching’ is reserved for coaching provided in RD‐FDI. The incorporation of coaching in RD‐FCI into the professional role of health care providers is challenging, as it requires the acquisition of new knowledge and a transformation of attitudes, beliefs, and habits. The literature indicates that it takes time to become a coach in RD‐FCI. Professional education to achieve coaching skills presumably best consists of at least 5 contact days and multiple intervals with practice in the professional's own intervention setting. Ideally, this type of training would be embedded in the relevant health care professional's curriculum when undergoing initial education. Future studies need to address in which way coaching skills and attitudes may be best conveyed. Notwithstanding the promising evidence that coaching in RD‐FCI is beneficial for the family and child, our understanding of the merits and difficulties of the application of different forms of coaching is still insufficient. For instance, we do not know whether coaching in RD‐FCI is only effective in specific types of family, or whether certain families would profit more from intervener‐directed interventions than from coaching in RD‐FCI. In addition, we think that it is impossible to combine parent training and coaching in RD‐FCI, but this idea deserves critical testing. Another important question that we did not address and on which we still lack the answer is what does effective coaching mean: namely, which components of coaching are responsible for the positive results of coaching approaches in early intervention? A related question is whether it is generally possible to evaluate the contribution of an individual intervention component to a defined outcome, or whether it is more reasonable to evaluate the intervention as a package, as suggested by Hutchon et al. It is very clear that more research is required to answer these questions. Examples of studies that could shed light on effective intervention components are those exploring parents' experiences with coaching approaches and studies documenting details of the coaching process and examining the associations of the process components with clearly defined child and caregiver outcomes.
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Curcumin in Ophthalmology: Mechanisms, Challenges, and Emerging Opportunities | 599136e1-4771-45ee-b170-1aac179f69dd | 11820683 | Ophthalmology[mh] | Ocular diseases, encompassing retinal and corneal disorders alongside ocular surface conditions, such as eyelid pathologies, significantly contribute to the global burden of visual impairment . These conditions pose significant challenges in prevention and treatment. For instance, diabetic retinopathy (DR) affected over 100 million people globally in 2020, with projections surpassing 160 million by 2045 . Similarly, glaucoma, a leading cause of irreversible blindness, is estimated to impact 111.8 million people aged 40–80 worldwide by 2040 . Dry eye syndrome impacts a significant portion of the population, with prevalence rates varying widely between 5% and 50%, underscoring the growing burden of age-related ocular conditions, which are expected to increase with the aging population, projected to double to 2.1 billion by 2050 . Moreover, lifestyle factors, such as unhealthy eating habits, smoking, and the frequent use of digital devices, have intensified these challenges. Worryingly, projections from the Global Burden of Disease Study suggest that by 2050, approximately 474 million people may experience moderate to severe visual impairments, with 61 million potentially losing their sight entirely . In recent years, considering these obstacles, there has been growing interest in curcumin as a possible therapeutic agent in managing ocular diseases. Curcumin (C 21 H 20 O 6 ), a lipophilic polyphenol derived from the dried rhizome of Curcuma longa L. and related species, has gained significant attention due to its extensive pharmacological properties, including anti-inflammatory, antioxidant, antimicrobial, and antitumor activities . Alongside its primary forms—demethoxycurcumin and bis-demethoxycurcumin—turmeric contains over 50 additional curcuminoids, including bisabocurcumin, curcumalongin, cyclocurcumin, and terpecurcumin, as well as volatile oils and resins. These compounds broaden turmeric’s pharmacological profile, offering synergistic effects that enhance its therapeutic versatility and reinforce its global use both as a culinary spice and as a source of health benefits . Curcumin’s molecular structure, comprising two o-methoxy phenolic aromatic rings linked by a seven-carbon α, β-unsaturated β-diketone chain, underpins its pleiotropic effects. Its properties—anti-inflammatory, antioxidant, antibacterial, anti-angiogenic, and anti-apoptotic—show promise in ophthalmology . Research indicates its potential for treating corneal and retinal neovascularization, inhibiting lens epithelial cell proliferation, and modulating retinal pigment epithelium-related pathways, making it a valuable candidate for managing inflammatory and degenerative ocular diseases . Topical formulations, such as hydrogels, creams, and nanocarrier systems, have been developed to enhance their physicochemical properties, including solubility, permeability, and stability. These innovations protect curcumin from degradation and enable sustained release, proving effective in treating dermatological conditions, such as psoriasis, acne, and atopic dermatitis, due to its anti-inflammatory, wound-healing, and antioxidant properties. This success in dermatology has spurred interest in its application for ocular treatments due to similar physicochemical barriers . Recognized by the FDA as ‘Generally Recognized as Safe’ (GRAS) for human consumption, curcumin demonstrates significant therapeutic potential . Clinical trials have confirmed their excellent safety, tolerability, and efficacy, even at high oral doses ranging from 4 to 8 g per day and doses up to 12 g per day for curcuminoid formulations containing 95% curcumin, bisdemethoxycurcumin, and demethoxycurcumin . However, its clinical application is limited by critical pharmacokinetic challenges, including poor aqueous solubility, light sensitivity, low bioavailability, limited absorption, and rapid systemic metabolism and elimination. These factors complicate consistent therapeutic outcomes and pharmacological interpretations, particularly given curcumin’s classification as a PAIN (pan-assay interference compound) and an IMP (invalid metabolic panacea), which highlights its complex bioactivity. Its degradation of products and fluorescence further complicate pharmacological evaluations . These limitations not only hinder consistent therapeutic outcomes but also complicate the identification of the actual bioactive species responsible for its effects. In addition, the metabolism of curcumin and its interaction with the intestinal microbiota play a crucial role in determining its bioavailability and therapeutic efficacy. After oral administration, curcumin exhibits poor solubility and limited gastrointestinal absorption. The absorbed fraction undergoes rapid metabolism in the liver and intestine via reduction (yielding dihydrocurcumin and tetrahydrocurcumin) and conjugation (forming glucuronides and sulfates), leading to its swift elimination. The intestinal microbiota further converts curcumin into more stable and, in some cases, bioactive metabolites. Certain bacterial genera, such as Bifidobacterium and Lactobacillus , promote its reduction and demethylation, potentially enhancing biological activity. Conversely, curcumin modulates the gut microbiota, fostering beneficial species while inhibiting pathogens. These interactions have significant implications for curcumin’s therapeutic applications in ocular diseases, especially given the distinct metabolic pathways associated with oral and topical administration . Additionally, the wide range of commercially available formulations—ranging from turmeric powder to curcuminoid-enriched products and purified curcumin—adds complexity, raising concerns about reproducibility and efficacy in clinical trials . Despite these challenges, curcumin’s diverse therapeutic potential emphasizes the need for innovative delivery systems. Nanocarrier technologies, particularly vesicular systems, such as liposomes and proniosomes, have addressed some of these challenges by improving curcumin’s bioavailability, solubility, and stability . These systems encapsulate curcumin within surfactant vesicles, protecting it from enzymatic degradation and extending its therapeutic presence on ocular surfaces. Moreover, the sustained drug delivery provided by these systems reduces systemic side effects while targeting disease-specific sites . In ocular inflammation, curcumin has demonstrated efficacy in reducing complications, such as corneal opacity, cataract formation, and retinal detachment . It also holds promise as a prophylactic agent in proliferative vitreoretinopathy (PVR), with studies reporting reduced rates of retinal detachment following surgery . Furthermore, curcumin demonstrates therapeutic benefits in DR by modulating hyperglycemia-induced endothelial dysfunction . Topical drug delivery systems, such as eye drops, i.e., aqueous solutions and suspensions, and oil-based formulations, remain widely used for ocular treatment. These formulations are intended for direct application to the ocular surface, typically in the form of drops. However, they often face significant limitations, including excessive tear production, rapid drainage, and systemic absorption, leading to inefficient drug distribution and the loss of over 95% of the administered dose . This review explores curcumin’s therapeutic potential in ophthalmology, focusing on its molecular mechanisms, challenges in clinical application, and advanced strategies for optimized delivery. By addressing these barriers, curcumin could transform ocular disease management, highlighting the need for robust randomized trials to confirm its safety and efficacy. Delivering medications to the eye effectively remains a significant challenge due to its distinct pharmacokinetic and pharmacodynamic environment. The eye’s natural defense mechanisms—such as tear production, blinking, and the intricate clearance processes on the ocular surface—serve to protect it but simultaneously hinder drug retention and absorption. These barriers, coupled with the anatomical complexity of anterior and posterior segments, result in low bioavailability for many conventional therapies . Frequent application of traditional eye drops is often necessary to achieve therapeutic outcomes, but this practice can inadvertently lead to systemic side effects through absorption via the nasolacrimal pathway . Recent studies suggest that curcumin can be applied to various ophthalmic conditions, offering significant therapeutic potential for a wide range of ocular diseases and addressing many limitations of conventional approaches . Curcumin’s antimicrobial and immunomodulatory properties make it particularly effective in targeting the complex interplay of infection, inflammation, and oxidative stress underlying many ocular pathologies. It directly disrupts bacterial cell walls and inhibits enzymatic processes critical for bacterial survival while also downregulating pro-inflammatory cytokines and mitigating oxidative stress. These dual antibacterial and anti-inflammatory actions position curcumin as a versatile therapeutic agent, particularly when integrated into advanced drug delivery systems . As shown in , the development of advanced drug delivery systems, including in situ gels, nanostructured lipid carriers, and hydrogels, has emerged as a promising strategy to enhance the solubility, stability, and ocular bioavailability of curcumin. An in vitro study, supported by ex vivo assays using rabbit corneas, showed that polyethylene glycol-distearoylphosphatidylethanolamine (PEG-DSPE)/Solutol HS 15 mixed micelle-based in situ gels improve corneal penetration, ocular retention, and stability. This system also supports sustained drug release, reduces dosing frequency, and avoids ocular irritation, offering a promising alternative to conventional eye drops . Thiolated chitosan-coated nanostructured lipid carriers, characterized in vitro and further evaluated in vivo using animal models, enhance corneal contact through covalent bonding with mucus glycoproteins. This interaction ensures sustained release over 72 h without irritation, improving ocular distribution and therapeutic efficacy . Hydroxypropyl methylcellulose methacrylate hydrogels, tested in vivo, demonstrated strong bioadhesion and controlled curcumin release, contributing to the reduction of oxidative damage in trabecular meshwork cells. This effect helps mitigate the inflammatory and apoptotic processes that are key in glaucoma progression, confirming the safety and potential of this formulation for controlled ocular drug delivery . These studies highlight the potential of these technologies to improve ocular retention, reduce dosing frequency, and minimize systemic side effects. Such advancements enable sustained drug release, improve therapeutic outcomes, and alleviate the burden of frequent applications associated with traditional formulations in ocular diseases. To better understand the impact of delivery methods on curcumin’s bioavailability and therapeutic potential, provides a comparison of different routes of administration, including topical ocular systems, oral administration (including trial clinical phase I), and parenteral routes. Ocular drug delivery systems offer a distinct advantage by bypassing the first-pass metabolism typical of oral administration and directly targeting the eye. These formulations improve curcumin’s retention, permeability, and controlled release, leading to enhanced therapeutic efficacy when compared to oral or intravenous routes. Additionally, ocular systems minimize systemic exposure, reducing the likelihood of side effects and providing a more focused and controlled therapeutic approach. Curcumin serves as a central modulator in multiple molecular systems involved in ocular health. It promotes a dynamic equilibrium between cellular processes that sustain ocular tissue integrity . This bioactive compound uniquely interacts with key signaling pathways, adjusting their intensity and function to reach an ideal homeostatic state. For instance, its anti-inflammatory action arises from a strategic blockade of pro-inflammatory signals, such as nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and NLR family pyrin domain containing 3 (NLRP3), leading to a reduction in the excessive production of cytokines like tumor necrosis factor-alpha (TNF-α), interleukin 1 beta (IL-1β), and interleukin 6 (IL-6). This effect can be likened to the fine-tuning of an inflammatory thermostat, ensuring that inflammation required for tissue repair is preserved while preventing the collateral damage associated with chronic inflammation . In the antioxidant domain, curcumin stands out by activating nuclear factor erythroid 2-related factor 2 (NRF2), a regulatory protein that coordinates the expression of antioxidant enzymes, including superoxide dismutase (SOD), catalase, and glutathione peroxidase (GPX). This mechanism not only neutralizes reactive oxygen species (ROS) but also preserves mitochondrial metabolic functions, protecting ocular cells from oxidative stress. Thus, curcumin acts as a metabolic sentinel, preventing cumulative damage over time . Furthermore, its ability to inhibit vascular endothelial growth factor (VEGF) in angiogenic processes is particularly relevant in conditions characterized by pathological neovascularization, such as DR and age-related macular degeneration (AMD). This effect is not merely inhibitory but restorative, realigning angiogenic processes to meet the tissue’s physiological needs. Curcumin’s regulation of the apoptotic balance through modulators like B-cell lymphoma 2 (Bcl-2)/Bcl-2-associated X protein (Bax) ratio further solidifies its role as a cellular protector, preventing uncontrolled cell death while maintaining the selective elimination of damaged cells . Curcumin also exerts a significant antibacterial effect through its modulation of ROS and its ability to suppress bacterial cell wall synthesis. By neutralizing ROS and interfering with bacterial biofilm formation, curcumin enhances its antibacterial potential. This mechanism reduces bacterial load while maintaining a controlled inflammatory response. Through the modulation of the immune system, curcumin minimizes excessive inflammatory damage, contributing to a more effective defense mechanism against microbial infections . Finally, curcumin’s immunomodulatory effects ensure a favorable environment for tissue repair and regeneration, particularly in autoimmune and infectious diseases affecting the eye. This comprehensive action, combined with its extracellular matrix stabilization properties and regulation of endoplasmic reticulum stress, positions curcumin as a molecularly orchestrated intervention with therapeutic potential adaptable to a wide range of ocular conditions . 2.1. Retinal Diseases Retinal diseases, characterized by complex pathological processes, such as inflammation, oxidative stress, and pathological angiogenesis, are major contributors to vision impairment. Leveraging curcumin’s unique ability to target these mechanisms, recent research highlights its potential in mitigating retinal damage and preserving visual function . In DR, curcumin alleviates hyperglycemia-induced damage to retinal pigment epithelium (RPE) cells and helps maintain blood–retinal barrier integrity. A recent experimental study in diabetic rats showed that curcumin reduces pro-inflammatory cytokines (TNF-α, IL-1, and IFN-γ) and oxidative stress markers, such as malondialdehyde (MDA), GPX, CAT, and SOD . These findings align with its broader molecular actions, including modulation of extracellular signal-regulated kinase (ERK) and Akt (protein kinase B, PKB) pathways to protect RPE cells and inhibit retinal neovascularization, inhibition of chronic inflammation via NF-κB suppression, and oxidative stress reduction . In addition to DR, inflammation is a key driver in retinal diseases such as age-related macular degeneration (AMD) and best vitelliform macular dystrophy (BVMD). Curcumin suppresses pathways like NF-κB, reducing pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) and mitigating chronic inflammation . This anti-inflammatory effect, mediated through NF-κB modulation, is a common mechanism also observed in glaucoma, where curcumin regulates the NF-κB pathway to reduce inflammation and oxidative stress, helping protect retinal ganglion cells (RGCs) and improve the optic nerve integrity . Curcumin’s antioxidant effects are critical in combating oxidative stress, a major contributor to retinal degeneration. By enhancing endogenous antioxidant defenses, such as SOD and catalase, curcumin protects retinal cells from ROS, which are implicated in diseases like retinitis pigmentosa (RP), AMD, and BVMD. It also reduces oxidative stress and light-induced damage, especially relevant in BVMD . In all these conditions, curcumin also acts in glaucoma, where its ability to reduce ROS levels protects RGCs and modulates antioxidant pathways, such as the activation of Nrf2, which is critical for protecting cells against ROS-induced damage . Furthermore, curcumin may regulate calcium homeostasis in RPE cells, enhancing their function and survival, especially in BVMD . Neuroprotective effects of curcumin also extend to glaucoma, where it reduces RGC death by inhibiting caspase-3 activation and modulating factors such as Bcl-2 and Bax, providing additional protection against neuronal degeneration . Curcumin’s ability to modulate autophagy offers a dual benefit by not only preventing cellular degeneration but also enhancing the clearance of toxic protein aggregates and damaged organelles in RPE cells. This dual action reinforces its potential as a therapeutic agent for retinal diseases, highlighting its capacity to target multiple pathological mechanisms simultaneously, thereby preserving retinal structure and function . For wet AMD and other vascular-related conditions, PVR and retinal vascular obstruction (RVO), curcumin’s anti-angiogenic activity inhibits VEGF, preventing abnormal blood vessel formation and mitigating retinal damage . VEGF is essential for new blood vessel formation and vascular permeability, playing a key role in retinal diseases like DR, RVO, and exudative AMD. It is produced by retinal endothelial and pigment epithelial cells and is considered a key target in anti-angiogenic therapies. For instance, VEGF-A, a key driver in wet AMD progression, binds to VEGFR2, promoting angiogenesis and vascular leakage . Although glaucoma is not primarily an angiogenic disease, curcumin’s inhibition of VEGF may contribute to retinal vascular protection, especially in ischemic or injury contexts, with a positive impact on intraocular pressure regulation . Curcumin also exhibits neuroprotective and anti-apoptotic effects, reducing ganglion cell death and modulating apoptotic pathways. These effects are particularly significant in DR, AMD, and BVMD, where retinal cell survival is crucial for preserving vision . This mechanism is also present in glaucoma, where curcumin exerts similar effects to protect optic nerve cells from programmed cell death, an important feature of glaucoma pathogenesis . Curcumin regulates fibrosis, a hallmark of PVR and potentially BVMD, by inhibiting TGF-β1 activity and suppressing miR-21, a microRNA that promotes fibrogenesis, thereby further inhibiting the fibrotic process . This inhibition reduces the expression of fibrosis-related proteins, such as α-smooth muscle actin (α-SMA), type I collagen (COL1A1), and type III collagen (COL3A1), and potentially preserving retinal structure . In glaucoma, curcumin has shown a similar effect by modulating fibrotic processes associated with optic nerve injury through the regulation of TGF-β1 and other fibrosis-related molecular factors . Lastly, curcumin has demonstrated promising therapeutic potential in retinoblastoma (RB), the most common malignant intraocular tumor in children. It exerts anti-tumor effects by inhibiting cell proliferation, migration, and invasion while promoting apoptosis. These effects are primarily mediated through the upregulation of microRNA (miR-99a), which negatively regulates the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway, a crucial pathway involved in tumor progression and cell survival. This suggests that curcumin’s modulation of miRNA expression contributes significantly to its anti-cancer properties, making it a candidate for adjunct therapy in RB treatment . 2.2. Corneal Diseases The cornea faces distinct challenges, including infections, fibrosis, and inflammation, which can compromise its transparency and refractive function. In this context, curcumin’s ability to modulate oxidative stress, inflammation, and angiogenesis has shown promise in addressing these conditions . Inflammatory processes are central to keratitis and DED. Curcumin effectively inhibits p38 MAPK and NF-κB signaling, reducing pro-inflammatory cytokines like IL-1β, IL-6, and TNF-α. A study showed curcumin (5 μM) completely abolished hyperosmoticity-induced IL-1β elevation in human corneal epithelial cells . Oxidative stress exacerbates corneal injury and delays healing. Curcumin’s antioxidant capacity neutralizes ROS, protecting corneal cells and enhancing cellular survival under stress conditions. Guo et al. demonstrated that pretreatment with 12.5 µM curcumin enhances antioxidant defenses, including SOD1 and heme oxygenase-1, via the Keap1/Nrf2/ARE pathway, improving cell survival under oxidative stress . Curcumin also promotes corneal healing by stimulating cell migration and collagen synthesis, which reduces scarring and preserves corneal transparency. A dose-dependent effect was observed, where curcumin (10.0–12.5 mg/L) inhibited keratocyte proliferation and modulated fibrotic markers, upregulating decorin and CD90 (a glycoprotein marker of activated fibroblasts associated with tissue remodeling) while downregulating keratocan and aldehyde dehydrogenase . In corneal neovascularization, a severe complication often associated with corneal diseases, curcumin’s anti-angiogenic properties offer significant therapeutic advantages. By downregulating VEGF, curcumin impedes the formation of abnormal blood vessels, thereby reducing tissue damage and preserving vision. In an alkaline-burned rat model, the topical application of 40 μmol/L curcumin every 12 h for five days significantly reduced the area of new blood vessels compared to controls, showcasing its potential for managing angiogenesis-related corneal pathologies . 2.3. Bacterial Ocular Diseases Bacterial ocular infections, such as conjunctivitis, keratitis, and endophthalmitis, often involve severe inflammatory responses, biofilm formation, and resistance to conventional antibiotics. Curcumin’s molecular mechanisms address these challenges by targeting inflammation, oxidative stress, and bacterial survival strategies . Biofilm formation is a critical factor in bacterial persistence and resistance. Curcumin disrupts biofilm matrix integrity and inhibits bacterial efflux pumps, thereby increasing susceptibility to antibiotics. This effect is particularly relevant against multidrug-resistant (MDR) pathogens, including MRSA and Pseudomonas aeruginosa . Inflammation, a hallmark of bacterial ocular diseases, is modulated by curcumin through the inhibition of NF-κB and MAPK pathways, reducing cytokine storms and promoting ocular tissue recovery. In conjunctivitis, curcumin-based formulations like the product Haridra ® have shown anti-inflammatory and antibacterial efficacy . Oxidative stress exacerbates tissue damage during bacterial infections. Curcumin’s ability to neutralize ROS through the activation of the Keap1/Nrf2/ARE pathway preserves epithelial and retinal cell viability under stress conditions . Additionally, emerging research on the gut-ocular axis has opened new avenues for understanding how systemic factors, such as the gut microbiota, influence ocular immunity. Dietary interventions, including omega-3 fatty acids, carotenoids, and probiotics, have been shown to modulate both systemic and ocular immunity, reducing inflammation and improving overall eye health. Curcumin, with its anti-inflammatory and antioxidant effects, integrates into these strategies, offering a multifaceted approach to managing bacterial ocular diseases . 2.4. Periocular and Ocular Surface Disorders Chronic inflammation, immune dysregulation, and oxidative stress characterize eyelid diseases, such as blepharitis, blepharospasm, and eyelid dermatitis. Curcumin addresses these through its multi-targeted mechanisms, offering significant therapeutic potential . Curcumin suppresses NF-κB and TLR4 signaling pathways, reducing pro-inflammatory cytokines like TNF-α and IL-1β. Additionally, it inhibits inflammasome activity, specifically NRLP3 to reduce tissue damage in blepharitis and dermatitis. Its antioxidant activity neutralizes ROS, mitigating oxidative tissue damage, while modulation of Th17 cell activity reduces immune dysregulation in autoimmune eyelid conditions . In blepharospasm, curcumin exhibits neuroprotective effects by reducing neuroinflammation and oxidative stress, promoting cellular resilience . Additionally, curcumin demonstrates potential in managing allergic conjunctivitis, an inflammatory condition of the ocular surface driven by Th2 immune responses. Studies indicate that curcumin reduces IgE-mediated inflammation, suppressing eosinophilic infiltration and Th2 cytokine production, such as IL-4 and IL-5, in the conjunctiva . These actions extend curcumin’s therapeutic scope to inflammatory and immune-related ocular surface disorders. Further expanding its utility, curcumin shows promise in treating meibomian gland dysfunction (MGD), a leading cause of ocular discomfort, by reducing inflammation and improving the lipid composition of the tear film. In dry eye disease, which is often linked with MGD, curcumin alleviates inflammation and oxidative stress while enhancing mucin production, stabilizing the tear film, and improving ocular comfort . These combined actions position curcumin as a promising agent for managing complex periocular and ocular surface disorders. Retinal diseases, characterized by complex pathological processes, such as inflammation, oxidative stress, and pathological angiogenesis, are major contributors to vision impairment. Leveraging curcumin’s unique ability to target these mechanisms, recent research highlights its potential in mitigating retinal damage and preserving visual function . In DR, curcumin alleviates hyperglycemia-induced damage to retinal pigment epithelium (RPE) cells and helps maintain blood–retinal barrier integrity. A recent experimental study in diabetic rats showed that curcumin reduces pro-inflammatory cytokines (TNF-α, IL-1, and IFN-γ) and oxidative stress markers, such as malondialdehyde (MDA), GPX, CAT, and SOD . These findings align with its broader molecular actions, including modulation of extracellular signal-regulated kinase (ERK) and Akt (protein kinase B, PKB) pathways to protect RPE cells and inhibit retinal neovascularization, inhibition of chronic inflammation via NF-κB suppression, and oxidative stress reduction . In addition to DR, inflammation is a key driver in retinal diseases such as age-related macular degeneration (AMD) and best vitelliform macular dystrophy (BVMD). Curcumin suppresses pathways like NF-κB, reducing pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) and mitigating chronic inflammation . This anti-inflammatory effect, mediated through NF-κB modulation, is a common mechanism also observed in glaucoma, where curcumin regulates the NF-κB pathway to reduce inflammation and oxidative stress, helping protect retinal ganglion cells (RGCs) and improve the optic nerve integrity . Curcumin’s antioxidant effects are critical in combating oxidative stress, a major contributor to retinal degeneration. By enhancing endogenous antioxidant defenses, such as SOD and catalase, curcumin protects retinal cells from ROS, which are implicated in diseases like retinitis pigmentosa (RP), AMD, and BVMD. It also reduces oxidative stress and light-induced damage, especially relevant in BVMD . In all these conditions, curcumin also acts in glaucoma, where its ability to reduce ROS levels protects RGCs and modulates antioxidant pathways, such as the activation of Nrf2, which is critical for protecting cells against ROS-induced damage . Furthermore, curcumin may regulate calcium homeostasis in RPE cells, enhancing their function and survival, especially in BVMD . Neuroprotective effects of curcumin also extend to glaucoma, where it reduces RGC death by inhibiting caspase-3 activation and modulating factors such as Bcl-2 and Bax, providing additional protection against neuronal degeneration . Curcumin’s ability to modulate autophagy offers a dual benefit by not only preventing cellular degeneration but also enhancing the clearance of toxic protein aggregates and damaged organelles in RPE cells. This dual action reinforces its potential as a therapeutic agent for retinal diseases, highlighting its capacity to target multiple pathological mechanisms simultaneously, thereby preserving retinal structure and function . For wet AMD and other vascular-related conditions, PVR and retinal vascular obstruction (RVO), curcumin’s anti-angiogenic activity inhibits VEGF, preventing abnormal blood vessel formation and mitigating retinal damage . VEGF is essential for new blood vessel formation and vascular permeability, playing a key role in retinal diseases like DR, RVO, and exudative AMD. It is produced by retinal endothelial and pigment epithelial cells and is considered a key target in anti-angiogenic therapies. For instance, VEGF-A, a key driver in wet AMD progression, binds to VEGFR2, promoting angiogenesis and vascular leakage . Although glaucoma is not primarily an angiogenic disease, curcumin’s inhibition of VEGF may contribute to retinal vascular protection, especially in ischemic or injury contexts, with a positive impact on intraocular pressure regulation . Curcumin also exhibits neuroprotective and anti-apoptotic effects, reducing ganglion cell death and modulating apoptotic pathways. These effects are particularly significant in DR, AMD, and BVMD, where retinal cell survival is crucial for preserving vision . This mechanism is also present in glaucoma, where curcumin exerts similar effects to protect optic nerve cells from programmed cell death, an important feature of glaucoma pathogenesis . Curcumin regulates fibrosis, a hallmark of PVR and potentially BVMD, by inhibiting TGF-β1 activity and suppressing miR-21, a microRNA that promotes fibrogenesis, thereby further inhibiting the fibrotic process . This inhibition reduces the expression of fibrosis-related proteins, such as α-smooth muscle actin (α-SMA), type I collagen (COL1A1), and type III collagen (COL3A1), and potentially preserving retinal structure . In glaucoma, curcumin has shown a similar effect by modulating fibrotic processes associated with optic nerve injury through the regulation of TGF-β1 and other fibrosis-related molecular factors . Lastly, curcumin has demonstrated promising therapeutic potential in retinoblastoma (RB), the most common malignant intraocular tumor in children. It exerts anti-tumor effects by inhibiting cell proliferation, migration, and invasion while promoting apoptosis. These effects are primarily mediated through the upregulation of microRNA (miR-99a), which negatively regulates the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway, a crucial pathway involved in tumor progression and cell survival. This suggests that curcumin’s modulation of miRNA expression contributes significantly to its anti-cancer properties, making it a candidate for adjunct therapy in RB treatment . The cornea faces distinct challenges, including infections, fibrosis, and inflammation, which can compromise its transparency and refractive function. In this context, curcumin’s ability to modulate oxidative stress, inflammation, and angiogenesis has shown promise in addressing these conditions . Inflammatory processes are central to keratitis and DED. Curcumin effectively inhibits p38 MAPK and NF-κB signaling, reducing pro-inflammatory cytokines like IL-1β, IL-6, and TNF-α. A study showed curcumin (5 μM) completely abolished hyperosmoticity-induced IL-1β elevation in human corneal epithelial cells . Oxidative stress exacerbates corneal injury and delays healing. Curcumin’s antioxidant capacity neutralizes ROS, protecting corneal cells and enhancing cellular survival under stress conditions. Guo et al. demonstrated that pretreatment with 12.5 µM curcumin enhances antioxidant defenses, including SOD1 and heme oxygenase-1, via the Keap1/Nrf2/ARE pathway, improving cell survival under oxidative stress . Curcumin also promotes corneal healing by stimulating cell migration and collagen synthesis, which reduces scarring and preserves corneal transparency. A dose-dependent effect was observed, where curcumin (10.0–12.5 mg/L) inhibited keratocyte proliferation and modulated fibrotic markers, upregulating decorin and CD90 (a glycoprotein marker of activated fibroblasts associated with tissue remodeling) while downregulating keratocan and aldehyde dehydrogenase . In corneal neovascularization, a severe complication often associated with corneal diseases, curcumin’s anti-angiogenic properties offer significant therapeutic advantages. By downregulating VEGF, curcumin impedes the formation of abnormal blood vessels, thereby reducing tissue damage and preserving vision. In an alkaline-burned rat model, the topical application of 40 μmol/L curcumin every 12 h for five days significantly reduced the area of new blood vessels compared to controls, showcasing its potential for managing angiogenesis-related corneal pathologies . Bacterial ocular infections, such as conjunctivitis, keratitis, and endophthalmitis, often involve severe inflammatory responses, biofilm formation, and resistance to conventional antibiotics. Curcumin’s molecular mechanisms address these challenges by targeting inflammation, oxidative stress, and bacterial survival strategies . Biofilm formation is a critical factor in bacterial persistence and resistance. Curcumin disrupts biofilm matrix integrity and inhibits bacterial efflux pumps, thereby increasing susceptibility to antibiotics. This effect is particularly relevant against multidrug-resistant (MDR) pathogens, including MRSA and Pseudomonas aeruginosa . Inflammation, a hallmark of bacterial ocular diseases, is modulated by curcumin through the inhibition of NF-κB and MAPK pathways, reducing cytokine storms and promoting ocular tissue recovery. In conjunctivitis, curcumin-based formulations like the product Haridra ® have shown anti-inflammatory and antibacterial efficacy . Oxidative stress exacerbates tissue damage during bacterial infections. Curcumin’s ability to neutralize ROS through the activation of the Keap1/Nrf2/ARE pathway preserves epithelial and retinal cell viability under stress conditions . Additionally, emerging research on the gut-ocular axis has opened new avenues for understanding how systemic factors, such as the gut microbiota, influence ocular immunity. Dietary interventions, including omega-3 fatty acids, carotenoids, and probiotics, have been shown to modulate both systemic and ocular immunity, reducing inflammation and improving overall eye health. Curcumin, with its anti-inflammatory and antioxidant effects, integrates into these strategies, offering a multifaceted approach to managing bacterial ocular diseases . Chronic inflammation, immune dysregulation, and oxidative stress characterize eyelid diseases, such as blepharitis, blepharospasm, and eyelid dermatitis. Curcumin addresses these through its multi-targeted mechanisms, offering significant therapeutic potential . Curcumin suppresses NF-κB and TLR4 signaling pathways, reducing pro-inflammatory cytokines like TNF-α and IL-1β. Additionally, it inhibits inflammasome activity, specifically NRLP3 to reduce tissue damage in blepharitis and dermatitis. Its antioxidant activity neutralizes ROS, mitigating oxidative tissue damage, while modulation of Th17 cell activity reduces immune dysregulation in autoimmune eyelid conditions . In blepharospasm, curcumin exhibits neuroprotective effects by reducing neuroinflammation and oxidative stress, promoting cellular resilience . Additionally, curcumin demonstrates potential in managing allergic conjunctivitis, an inflammatory condition of the ocular surface driven by Th2 immune responses. Studies indicate that curcumin reduces IgE-mediated inflammation, suppressing eosinophilic infiltration and Th2 cytokine production, such as IL-4 and IL-5, in the conjunctiva . These actions extend curcumin’s therapeutic scope to inflammatory and immune-related ocular surface disorders. Further expanding its utility, curcumin shows promise in treating meibomian gland dysfunction (MGD), a leading cause of ocular discomfort, by reducing inflammation and improving the lipid composition of the tear film. In dry eye disease, which is often linked with MGD, curcumin alleviates inflammation and oxidative stress while enhancing mucin production, stabilizing the tear film, and improving ocular comfort . These combined actions position curcumin as a promising agent for managing complex periocular and ocular surface disorders. Curcumin predominantly exists in the keto-enol form in polar solvents and is hydrophobic, being insoluble in water but soluble in organic solvents. This characteristic poses challenges for its therapeutic application. However, advanced drug delivery systems, such as encapsulation, have significantly improved curcumin’s solubility and stability in aqueous environments . 3.1. Non-Ionic Surfactant-Based Delivery Systems Non-ionic surfactants enhance the bioavailability of hydrophobic drugs, especially curcumin, by forming stable and biocompatible carriers. These systems improve curcumin’s solubility, stability, and ocular residence time, thereby reducing systemic toxicity and enhancing therapeutic outcomes . Composed of non-ionic surfactants and cholesterol, niosomes enhance curcumin’s solubility, stability, and ocular residence time, reducing systemic toxicity . Nanoemulsion-based formulations improve drug dispersion in aqueous environments, enhancing curcumin’s corneal permeability and bioavailability. This approach ensures rapid therapeutic action, crucial for treating acute ocular conditions . Liposomes, a subclass of non-ionic surfactant carriers, enhance curcumin’s bioavailability and ocular distribution, supporting its use in retinal degeneration and inflammation . In addition, curcumin-loaded proniosomal gels have emerged as a promising alternative to traditional corticosteroid treatments for ocular inflammation. These formulations, composed of surfactants, such as cremophore RH, lecithin, and cholesterol, offer high encapsulation efficiency (96%) and 3.22-fold greater permeability than conventional dispersions. Comparative in vivo studies demonstrated that these proniosomal gels significantly reduced inflammatory symptoms, achieving complete recovery within four days, comparable to corticosteroid drops. Curcumin’s natural origin minimizes adverse effects, such as intraocular pressure elevation, positioning it as a safer yet equally effective anti-inflammatory treatment option. Curcumin encapsulated in proniosomal gel demonstrated exceptional biocompatibility and safety, coupled with potent anti-inflammatory properties. This innovative formulation enhanced ocular retention and significantly improved corneal permeability, delivering a sustained release effect over 24 h . Recent research underscores the value of transferosomes (TFSs), ultra-deformable vesicles comprising lipid bilayers and surfactants, such as Tween 80. TFS exhibits exceptional drug entrapment efficiency (>99%) and enhances drug penetration across corneal and conjunctival barriers, enabling deeper and more effective delivery to ocular tissues. They also improve precorneal retention, ensuring sustained therapeutic levels and superior bioavailability. Studies highlight their excellent compatibility with ocular tissues and their potential to optimize the delivery of curcumin and similar compounds in treating eye diseases . Additionally, lipophilic vehicles, such as medium-chain triglycerides (MCTs) and squalane, demonstrate varying degrees of effectiveness. Ex vivo studies reveal that squalane suspensions notably enhance curcumin’s penetration into ocular tissues compared to MCT solutions, emphasizing the role of vehicle partitioning in optimizing drug delivery . Polymeric in situ gelling systems represent an innovative approach for ocular curcumin delivery. These inserts, composed of biocompatible polymers such as HPMC, CMC, and Pluronic F127, provide sustained drug release and enhanced mucoadhesion. Characterization studies show that curcumin in these systems is dispersed molecularly, with smooth and uniform surfaces. Importantly, the inserts exhibit superior corneal permeation (5.4- to 8.86-fold increase) and retention times compared to conventional suspensions. These properties underscore their potential to replace traditional eye drops, offering improved therapeutic efficacy through prolonged action and reduced dosing frequency . 3.2. Nanoparticle-Based Systems Nanoparticles provide controlled drug release and enhanced stability for curcumin, making them suitable for various ocular conditions . Solid lipid nanoparticles ensure high drug loading, stability, and minimal systemic toxicity. They have demonstrated effectiveness in reducing oxidative stress in retinal cells, addressing posterior segment eye diseases, such as AMD and DR . Polymeric nanoparticles, such as PLGA(polylactic-co-glycolic acid)-based nanoparticles, enhance curcumin’s stability and bioavailability. An innovative approach involves biodegradable scleral plugs, which enable sustained drug release for up to 14 days. Studies show that scleral plugs with curcumin concentrations of 0.5 mg, 1.0 mg, and 1.5 mg achieve therapeutic levels (above 15 µg/mL) in vitro, with no adverse effects observed in vivo models, such as changes in intraocular pressure or retinal integrity. These findings underscore the safety and efficacy of scleral plugs for posterior ocular diseases . A promising strategy to address curcumin’s limitations involves using diphosphorylated curcumin (Cur-2p), a prodrug that generates curcumin nanoparticles in situ. This approach enhances curcumin’s stability and reduces aggregation in water. Upon enzymatic conversion by alkaline phosphatase (ALP) in cancer cells, Cur-2p exhibits selective cytotoxicity against ALP-overexpressing cancer cells while sparing normal cells. Additionally, intravitreal injections of Cur-2p demonstrate superior intraocular biocompatibility, preserving retinal morphology and function. In a rodent model of uveitis, Cur-2p effectively suppresses inflammation, outperforming unmodified curcumin. These findings highlight Cur-2p’s potential as a next-generation nanoparticle-based system for ocular drug delivery . Mixed micelle in situ gels, composed of Pluronic P123 and D-α-tocopherol polyethylene glycol succinate, have been developed to overcome curcumin’s poor water solubility and limited corneal permeability. The optimized micellar formulations, when combined with gellan gum, form transparent in situ gels that sustain drug release while enhancing corneal retention. In vitro studies confirmed a sustained drug release profile, while ex vivo corneal permeation tests demonstrated superior drug delivery, with cumulative drug permeation up to 1.32 times higher compared to standard curcumin solutions . Similarly, curcumin-loaded mixed micelle in situ gel (Cur-MM-ISG) improves ocular drug delivery. The system combines small, stable micelles with gellan gum to form a transparent gel upon application. Compared to free curcumin, Cur-MM-ISG significantly enhanced corneal permeation and retention time without causing irritation, highlighting its potential for sustained and efficient ocular therapy. This system supports sustained therapeutic effects with excellent ocular tolerance . Thermosensitive gels (CUR-CNLC-GEL) formulation demonstrated promising results in improving the bioavailability of curcumin for ocular therapy. With a sol-gel transition temperature of 34 °C, it ensured practical application. The nanogel exhibited 1.56-fold higher permeability and a 9.24-fold increase in bioavailability (AUC 0→∞ ) compared to a conventional curcumin solution. Additionally, the enhanced C max and prolonged mean residence time (MRT) indicated effective controlled release and retention properties. These attributes the position CUR-CNLC-GEL as a highly promising candidate for next-generation ocular drug delivery, offering superior corneal permeation and extended therapeutic efficacy . Thermosensitive hydrogels, especially when paired with nanoparticles, offer an innovative approach to achieving sustained drug release. For instance, hydrogels incorporating curcumin-loaded nanoparticles (CUR-NPs) and latanoprost have demonstrated notable improvements in bioavailability for glaucoma therapy. This dual-drug delivery system addresses oxidative stress in trabecular meshwork cells, effectively mitigating inflammation, reducing mitochondrial ROS production, and decreasing apoptosis levels. Additionally, it enhances both uveoscleral and trabecular outflow, highlighting its potential as a promising treatment for glaucoma. This system enables the development of topical eye drops capable of sustaining drug release for up to 7 days, enhancing residence time in the rabbit eye, and improving corneal permeation with minimal toxicity . The study on the development of a thermoresponsive ophthalmic in situ gel containing curcumin-loaded albumin nanoparticles (Cur-BSA-NPs-Gel) presents significant advancements in ocular drug delivery systems. By optimizing the formulation through a central composite design, the researchers achieved a gel that transitions from liquid to semi-solid under physiological conditions, ensuring easy application and sustained drug release. Incorporating albumin nanoparticles minimally impacted the gel’s structure while enhancing curcumin’s bioavailability in the aqueous humor, as confirmed by in vivo studies in rabbit models. The formulation demonstrated safety for ophthalmic use, with no signs of eye irritation, and offers potential for prolonged therapeutic effects, making it a promising candidate for ocular treatments . Recent advancements have introduced dissolvable hybrid microneedles (MNs) patches as a novel method for ocular delivery of curcumin. These patches incorporate curcumin-loaded polymeric micelles into a hyaluronic acid matrix, using a micromolding process to ensure efficient drug dispersion. Studies reveal that this system facilitates sustained drug release over eight hours and extends pre-corneal retention to more than 3.5 h, significantly improving bioavailability. MNs patch can create temporary microchannels in the corneal epithelium, enhancing permeability. In vivo testing demonstrated its superior efficacy in treating endotoxin-induced uveitis, reducing inflammatory cell infiltration more effectively than conventional eye drops, making it a promising tool for managing intraocular inflammatory disorders . The development of curcumin-loaded nanostructured lipid carriers (CUR-NLC) coated with thiolated chitosan (CS-NAC) offers a promising solution for topical ocular drug delivery. This innovative system achieves sustained drug release for up to 72 h and significantly enhances corneal permeability and retention. Compared to coatings using chitosan oligosaccharides (COS) and carboxymethyl chitosan (CMCS), the CS-NAC coating demonstrated superior performance, with permeability coefficients increasing by 6.4 and 18.8 times relative to uncoated CUR-NLC and conventional eye drops, respectively. Furthermore, ocular irritation tests confirmed the biocompatibility of CS-NAC-CUR-NLC . The formulation of curcumin-loaded nanostructured lipid carriers (NLCs) using hot-melt emulsification and ultrasonication has demonstrated significant potential for ocular drug delivery. Optimized through a central composite design, the resulting NLCs showcased a particle size of approximately 66.8 nm, high encapsulation efficiency (96%), and consistent drug loading. These properties contributed to enhanced stability over three months at low temperatures and superior transcorneal permeability. Ex vivo tests revealed a 2.5-fold increase in curcumin permeation across rabbit corneas compared to standard formulations, without evidence of adverse effects, underscoring the NLCs’ ability to improve drug delivery efficiency while maintaining safety . The development of a nanomicelle-based curcumin formulation utilizing a PVCL-PVA-PEG graft copolymer has shown promise for enhancing ocular drug delivery. This system significantly improves curcumin’s solubility and stability while offering robust antioxidant activity. In vitro and in vivo studies demonstrated that these nanomicelles enhance cellular uptake and corneal permeation compared to free curcumin solutions. Additionally, the formulation exhibited excellent ocular tolerance, with no signs of irritation in rabbit models. These results suggest that nanomicelles could serve as an effective platform for delivering curcumin topically in the treatment of ocular inflammation and related conditions . Recent advancements in curcumin-based therapies for AMD highlight the promise of aqueous nanomicellar formulations (CUR-NMF). This innovative approach overcomes curcumin’s poor aqueous solubility, a key limitation for its therapeutic use. CUR-NMF, developed using hydrogenated castor oil (HCO-40) and octoxynol-40 (OC-40), offers a stable delivery system optimized for retinal protection. Studies demonstrate its antioxidant, anti-inflammatory, and anti-angiogenic effects, showing significant protection against oxidative stress in retinal cells and a reduction in VEGF release, a critical factor in AMD pathology. Furthermore, sustained drug release profiles and favorable safety assessments suggest CUR-NMF could provide long-term therapeutic benefits for both dry and wet AMD . 3.3. Cyclodextrin Complexes Cyclodextrins (CDs) play a crucial role in enhancing curcumin’s solubility, stability, and bioavailability through the formation of inclusion complexes . These complexes significantly improve curcumin’s therapeutic effectiveness in both anterior and posterior ocular diseases. Among the CDs, β-cyclodextrins (βCD) and γ-cyclodextrins (γCD) stand out due to their higher solubility, capacity to self-assemble into nanoaggregates, and favorable safety profile for ocular applications . Since the mid-1990s, CD-based inclusion complexes have provided significant technological advantages for pharmaceutical formulations. By enhancing the stability, solubility, and bioavailability of bioactive compounds, these complexes address key challenges in drug delivery. A notable example is the use of cyclodextrins to improve the solubility and stability of chloramphenicol, a patented formulation still in use today . This approach enabled the development of stable pharmaceutical solutions and optimized separation processes, underscoring the enduring relevance of this technology . Methyl-β-cyclodextrin (M-β-CD) is the cyclodextrin used in commercial eye drop formulations, including those containing chloramphenicol. Hydroxypropyl-β-cyclodextrin (HP-β-CD) is also covered by this patent for chloramphenicol due to its superior solubility and biocompatibility . More recently, CD-based inclusion complexes have been explored for cannabinoid delivery, demonstrating promising potential in pain management and anti-inflammatory therapies. These developments highlight the versatility of cyclodextrins in modern drug delivery, particularly for ocular applications, where solubility, stability, and bioavailability are critical for therapeutic success . Modified CDs, such as ethylene diamine (EDA)-modified βCD, have demonstrated superior capabilities in improving curcumin (CUR) solubility and stability. These complexes provide enhanced thermodynamic properties, making CUR more bioavailable for ocular applications. Curcumin-EDA-βCD nanoparticles exhibit excellent corneal permeability, as shown in vitro porcine cornea experiments, and maintain high biocompatibility, confirmed by histological analyses of porcine corneas and bovine corneal epithelial cell viability. These properties make them particularly suitable for addressing anterior segment diseases like keratitis and dry eye disease . In a recent study, various CD-curcumin complexes were prepared and characterized, showing significant improvements in solubility. The freeze-drying method produced highly soluble complexes, and the optimal formulation provided sustained release for over 96 h. This approach offers a promising solution for curcumin’s use in ocular therapies, such as eye drops for conditions like retinitis pigmentosa . Inclusion complexes of CUR with hydroxypropyl-β-cyclodextrin (HP-βCD) were successfully developed using the cosolvency/lyophilization method, resulting in significant improvements in CUR solubility, stability, and therapeutic efficacy. The complexes demonstrated superior antioxidant and anti-inflammatory activities compared to free CUR. To facilitate ocular administration, an in-situ gel system was prepared using Pluronic F127 and chitosan, providing mucoadhesion and sol-gel transition between 26–35 °C. Viscosity, pH, and clarity tests confirmed the system’s suitability for ocular application. In vitro release studies showed sustained drug release for 6 h, fitting the Weibull kinetic model. This approach offers a promising drug delivery strategy for ocular diseases, supporting prolonged and controlled drug release . The poor solubility and stability of CUR limit its application in ocular drug delivery. To address this, CUR was complexed with βCD and HP-βCD using co-solvent, sonication, and freeze-drying methods in 1:1 and 1:2 molar ratios. The freeze-drying method produced the most water-soluble complexes. Among the 12 tested formulations, the F11 formulation, prepared with pH 6.8 phosphate buffer containing 1% Tween 80, demonstrated sustained drug release for over 96 h. The drug release followed a Higuchi non-Fickian diffusion model. These findings suggest that F11 could be developed as a once-daily eye drop formulation, offering a promising approach for the sustained delivery of curcumin in the treatment of ocular diseases, such as retinitis pigmentosa . The use of CDs to optimize corneal penetration of CUR has shown promising results. In ex vivo models using porcine corneas, the combination of CDs with nanoparticles demonstrated greater drug permeation. This improvement is attributed to the ability of CDs to form inclusion complexes, enhancing curcumin’s solubility and stability, while nanoparticles enable sustained release and protection against enzymatic degradation . Recent studies have demonstrated that curcumin-loaded hydrogels, such as those incorporating CUR nanoparticles encapsulated with βCD and hyaluronic acid, accelerate corneal healing in ulcerative keratitis. This system not only improves corneal clarity and reduces inflammation but also enhances the quality of healed tissues, requiring fewer applications compared to conventional treatments. These formulations hold promises for future therapeutic use in treating ulcerative keratitis and other ocular conditions, providing an innovative, herbal-based alternative to traditional treatments . The penetration of CUR into the cornea was evaluated using an ex vivo porcine eye model and a digital image analysis technique. Several formulation strategies, including oily solutions, oily suspensions, micelles, liposomes, nanosuspensions, and CD complexes, were explored to improve CUR corneal permeability. The results revealed that cyclodextrin-based formulations exhibited superior corneal penetration compared to other delivery systems. The image analysis approach effectively measured CUR penetration into corneal tissues, supporting the potential of cyclodextrin complexes as a delivery strategy for hydrophobic drugs in ocular applications. This technique offers a novel approach for optimizing the penetration of CUR and similar compounds into the cornea . Among the most effective formulations are those based on modified βCDs and conjugates with tetrahydrocurcumin nanoparticles, which exhibited deeper penetration into ocular tissues. These strategies hold significant potential for treating both anterior and posterior segment ocular diseases, as they increase bioavailability and extend therapeutic effects . γCD-based nanoparticles not only enhance drug permeation but also increase retention time on the ocular surface, promoting sustained drug release and reducing the frequency of administration. Additionally, the presence of tear enzymes like α-amylase facilitates drug release from γCD complexes, further boosting bioavailability. For instance, γCD-based eye drops containing dexamethasone achieved higher concentrations in ocular tissues compared to commercial formulations. Moreover, these formulations were well tolerated, with no significant ocular irritation or toxicity observed. γCD has also been employed in formulations for dorzolamide, telmisartan, and nepafenac, demonstrating improved pharmacokinetics and sustained drug release for up to 24 h . Inclusion complexes of CUR with HP-βCD enhance curcumin’s solubility, dissolution rate, and bioavailability, essential for ocular drug delivery. Studies using co-evaporation methods revealed a 1:1 molar ratio complex with a solubility constant of 30.09 mM −1 . Characterization techniques, such as XRD, confirmed the loss of curcumin’s crystalline structure, while FTIR and DTA indicated no chemical interactions. In vitro dissolution tests showed faster release of CUR from the complex compared to its pure form and physical mixtures. This approach improves curcumin’s bioavailability, making it a promising strategy for ocular drug delivery systems . The ocular delivery of CUR faces significant barriers due to anatomical and physiological constraints; however, advances in nanoengineered systems have shown promising results. The formation of inclusion complexes with HP-CDs through spray-drying significantly enhanced the solubility, permeability, and stability of CUR. Enhanced corneal and retinal permeability was observed, along with increased antioxidant activity in ocular epithelial cells, including upregulation of SOD1, CAT1, and HMOX1. Moreover, protection against oxidative stress was confirmed in rabbit corneal tissues. These findings highlight the potential of CUR:HP-CD complexes to improve ocular drug bioavailability, thereby enhancing therapeutic outcomes for ocular diseases . Cyclodextrin-based systems significantly enhance curcumin’s bioavailability, solubility, and therapeutic potential for ocular drug delivery. Advances in βCD, γCD, and HP-βCD systems, combined with nanoparticles or in situ gels, have demonstrated improved drug permeation, sustained release, and higher bioactivity. These strategies support the development of more effective ophthalmic treatments. 3.4. Drug Delivery for Antibacterial Agents Nanocomposites, such as cupriferous hollow nanoshells, combine silver and copper ions. These materials exhibit dual functionality: silver ions provide potent antibacterial activity, while copper ions promote tissue regeneration by stimulating fibroblast migration and angiogenesis. This dual approach is particularly beneficial in treating conditions like keratitis, where infections can impair spontaneous recovery and cause corneal damage. Nanocomposite-based treatments not only target the bacteria but also support the healing of damaged tissues, offering a comprehensive approach to managing complex infections . Moreover, curcumin enhances traditional antibiotics by inhibiting bacterial efflux pumps and disrupting biofilms—critical mechanisms in antibiotic resistance. When combined with biopolymers like chitosan, curcumin has shown enhanced antibacterial effects, even at low concentrations, especially against resistant bacterial strains. This makes curcumin-based formulations a valuable tool in combating antibiotic-resistant ocular infections, such as conjunctivitis and keratitis . Curcumin-based formulations have also demonstrated significant efficacy in the treatment of conjunctivitis. Products like Haridra ® and Ophthacare ® have been shown to combat pathogens like Escherichia coli , Staphylococcus aureus , Klebsiella pneumoniae , and Pseudomonas aeruginosa while also reducing inflammation and irritation. These formulations address not only the infection but also the underlying inflammation, providing a comprehensive treatment approach. Ophthacare ® , which combines Curcuma longa with other herbal extracts, offers an effective solution for a range of ocular conditions, including dry eye and inflammatory conjunctival disorders . Endophthalmitis, an intraocular infection characterized by extensive inflammation and retinal damage, has benefited from nanotechnology-based drug delivery systems. Hybrid frameworks that incorporate silver nanoparticles and photosensitizers have been developed to disrupt biofilms while preserving host tissues. These systems, combined with curcumin’s anti-inflammatory properties, can modulate cytokine storms, support retinal cell survival, and preserve ocular structures. This combination not only targets the infection but also helps to protect the delicate retinal tissues, improving patient outcomes . Recent innovations in drug delivery systems have further amplified the therapeutic potential of curcumin. Nanoparticles and liposomes are particularly effective at enhancing curcumin’s bioavailability and ocular penetration, ensuring sustained therapeutic effects. For example, dual-drug nanofibers, which combine curcumin with antibiotics, have shown enhanced bactericidal activity and accelerated tissue regeneration in preclinical models of ocular infections. These advanced delivery systems ensure that curcumin reaches the target site effectively, offering continuous antimicrobial action and supporting tissue healing . These systems not only enhance the effectiveness of conventional antibiotics but also provide innovative solutions to overcome the challenges posed by MDR bacteria, biofilms, and tissue damage . The integration of curcumin in these systems adds a further layer of therapeutic benefit, making it a promising tool in the management of ocular infections. Non-ionic surfactants enhance the bioavailability of hydrophobic drugs, especially curcumin, by forming stable and biocompatible carriers. These systems improve curcumin’s solubility, stability, and ocular residence time, thereby reducing systemic toxicity and enhancing therapeutic outcomes . Composed of non-ionic surfactants and cholesterol, niosomes enhance curcumin’s solubility, stability, and ocular residence time, reducing systemic toxicity . Nanoemulsion-based formulations improve drug dispersion in aqueous environments, enhancing curcumin’s corneal permeability and bioavailability. This approach ensures rapid therapeutic action, crucial for treating acute ocular conditions . Liposomes, a subclass of non-ionic surfactant carriers, enhance curcumin’s bioavailability and ocular distribution, supporting its use in retinal degeneration and inflammation . In addition, curcumin-loaded proniosomal gels have emerged as a promising alternative to traditional corticosteroid treatments for ocular inflammation. These formulations, composed of surfactants, such as cremophore RH, lecithin, and cholesterol, offer high encapsulation efficiency (96%) and 3.22-fold greater permeability than conventional dispersions. Comparative in vivo studies demonstrated that these proniosomal gels significantly reduced inflammatory symptoms, achieving complete recovery within four days, comparable to corticosteroid drops. Curcumin’s natural origin minimizes adverse effects, such as intraocular pressure elevation, positioning it as a safer yet equally effective anti-inflammatory treatment option. Curcumin encapsulated in proniosomal gel demonstrated exceptional biocompatibility and safety, coupled with potent anti-inflammatory properties. This innovative formulation enhanced ocular retention and significantly improved corneal permeability, delivering a sustained release effect over 24 h . Recent research underscores the value of transferosomes (TFSs), ultra-deformable vesicles comprising lipid bilayers and surfactants, such as Tween 80. TFS exhibits exceptional drug entrapment efficiency (>99%) and enhances drug penetration across corneal and conjunctival barriers, enabling deeper and more effective delivery to ocular tissues. They also improve precorneal retention, ensuring sustained therapeutic levels and superior bioavailability. Studies highlight their excellent compatibility with ocular tissues and their potential to optimize the delivery of curcumin and similar compounds in treating eye diseases . Additionally, lipophilic vehicles, such as medium-chain triglycerides (MCTs) and squalane, demonstrate varying degrees of effectiveness. Ex vivo studies reveal that squalane suspensions notably enhance curcumin’s penetration into ocular tissues compared to MCT solutions, emphasizing the role of vehicle partitioning in optimizing drug delivery . Polymeric in situ gelling systems represent an innovative approach for ocular curcumin delivery. These inserts, composed of biocompatible polymers such as HPMC, CMC, and Pluronic F127, provide sustained drug release and enhanced mucoadhesion. Characterization studies show that curcumin in these systems is dispersed molecularly, with smooth and uniform surfaces. Importantly, the inserts exhibit superior corneal permeation (5.4- to 8.86-fold increase) and retention times compared to conventional suspensions. These properties underscore their potential to replace traditional eye drops, offering improved therapeutic efficacy through prolonged action and reduced dosing frequency . Nanoparticles provide controlled drug release and enhanced stability for curcumin, making them suitable for various ocular conditions . Solid lipid nanoparticles ensure high drug loading, stability, and minimal systemic toxicity. They have demonstrated effectiveness in reducing oxidative stress in retinal cells, addressing posterior segment eye diseases, such as AMD and DR . Polymeric nanoparticles, such as PLGA(polylactic-co-glycolic acid)-based nanoparticles, enhance curcumin’s stability and bioavailability. An innovative approach involves biodegradable scleral plugs, which enable sustained drug release for up to 14 days. Studies show that scleral plugs with curcumin concentrations of 0.5 mg, 1.0 mg, and 1.5 mg achieve therapeutic levels (above 15 µg/mL) in vitro, with no adverse effects observed in vivo models, such as changes in intraocular pressure or retinal integrity. These findings underscore the safety and efficacy of scleral plugs for posterior ocular diseases . A promising strategy to address curcumin’s limitations involves using diphosphorylated curcumin (Cur-2p), a prodrug that generates curcumin nanoparticles in situ. This approach enhances curcumin’s stability and reduces aggregation in water. Upon enzymatic conversion by alkaline phosphatase (ALP) in cancer cells, Cur-2p exhibits selective cytotoxicity against ALP-overexpressing cancer cells while sparing normal cells. Additionally, intravitreal injections of Cur-2p demonstrate superior intraocular biocompatibility, preserving retinal morphology and function. In a rodent model of uveitis, Cur-2p effectively suppresses inflammation, outperforming unmodified curcumin. These findings highlight Cur-2p’s potential as a next-generation nanoparticle-based system for ocular drug delivery . Mixed micelle in situ gels, composed of Pluronic P123 and D-α-tocopherol polyethylene glycol succinate, have been developed to overcome curcumin’s poor water solubility and limited corneal permeability. The optimized micellar formulations, when combined with gellan gum, form transparent in situ gels that sustain drug release while enhancing corneal retention. In vitro studies confirmed a sustained drug release profile, while ex vivo corneal permeation tests demonstrated superior drug delivery, with cumulative drug permeation up to 1.32 times higher compared to standard curcumin solutions . Similarly, curcumin-loaded mixed micelle in situ gel (Cur-MM-ISG) improves ocular drug delivery. The system combines small, stable micelles with gellan gum to form a transparent gel upon application. Compared to free curcumin, Cur-MM-ISG significantly enhanced corneal permeation and retention time without causing irritation, highlighting its potential for sustained and efficient ocular therapy. This system supports sustained therapeutic effects with excellent ocular tolerance . Thermosensitive gels (CUR-CNLC-GEL) formulation demonstrated promising results in improving the bioavailability of curcumin for ocular therapy. With a sol-gel transition temperature of 34 °C, it ensured practical application. The nanogel exhibited 1.56-fold higher permeability and a 9.24-fold increase in bioavailability (AUC 0→∞ ) compared to a conventional curcumin solution. Additionally, the enhanced C max and prolonged mean residence time (MRT) indicated effective controlled release and retention properties. These attributes the position CUR-CNLC-GEL as a highly promising candidate for next-generation ocular drug delivery, offering superior corneal permeation and extended therapeutic efficacy . Thermosensitive hydrogels, especially when paired with nanoparticles, offer an innovative approach to achieving sustained drug release. For instance, hydrogels incorporating curcumin-loaded nanoparticles (CUR-NPs) and latanoprost have demonstrated notable improvements in bioavailability for glaucoma therapy. This dual-drug delivery system addresses oxidative stress in trabecular meshwork cells, effectively mitigating inflammation, reducing mitochondrial ROS production, and decreasing apoptosis levels. Additionally, it enhances both uveoscleral and trabecular outflow, highlighting its potential as a promising treatment for glaucoma. This system enables the development of topical eye drops capable of sustaining drug release for up to 7 days, enhancing residence time in the rabbit eye, and improving corneal permeation with minimal toxicity . The study on the development of a thermoresponsive ophthalmic in situ gel containing curcumin-loaded albumin nanoparticles (Cur-BSA-NPs-Gel) presents significant advancements in ocular drug delivery systems. By optimizing the formulation through a central composite design, the researchers achieved a gel that transitions from liquid to semi-solid under physiological conditions, ensuring easy application and sustained drug release. Incorporating albumin nanoparticles minimally impacted the gel’s structure while enhancing curcumin’s bioavailability in the aqueous humor, as confirmed by in vivo studies in rabbit models. The formulation demonstrated safety for ophthalmic use, with no signs of eye irritation, and offers potential for prolonged therapeutic effects, making it a promising candidate for ocular treatments . Recent advancements have introduced dissolvable hybrid microneedles (MNs) patches as a novel method for ocular delivery of curcumin. These patches incorporate curcumin-loaded polymeric micelles into a hyaluronic acid matrix, using a micromolding process to ensure efficient drug dispersion. Studies reveal that this system facilitates sustained drug release over eight hours and extends pre-corneal retention to more than 3.5 h, significantly improving bioavailability. MNs patch can create temporary microchannels in the corneal epithelium, enhancing permeability. In vivo testing demonstrated its superior efficacy in treating endotoxin-induced uveitis, reducing inflammatory cell infiltration more effectively than conventional eye drops, making it a promising tool for managing intraocular inflammatory disorders . The development of curcumin-loaded nanostructured lipid carriers (CUR-NLC) coated with thiolated chitosan (CS-NAC) offers a promising solution for topical ocular drug delivery. This innovative system achieves sustained drug release for up to 72 h and significantly enhances corneal permeability and retention. Compared to coatings using chitosan oligosaccharides (COS) and carboxymethyl chitosan (CMCS), the CS-NAC coating demonstrated superior performance, with permeability coefficients increasing by 6.4 and 18.8 times relative to uncoated CUR-NLC and conventional eye drops, respectively. Furthermore, ocular irritation tests confirmed the biocompatibility of CS-NAC-CUR-NLC . The formulation of curcumin-loaded nanostructured lipid carriers (NLCs) using hot-melt emulsification and ultrasonication has demonstrated significant potential for ocular drug delivery. Optimized through a central composite design, the resulting NLCs showcased a particle size of approximately 66.8 nm, high encapsulation efficiency (96%), and consistent drug loading. These properties contributed to enhanced stability over three months at low temperatures and superior transcorneal permeability. Ex vivo tests revealed a 2.5-fold increase in curcumin permeation across rabbit corneas compared to standard formulations, without evidence of adverse effects, underscoring the NLCs’ ability to improve drug delivery efficiency while maintaining safety . The development of a nanomicelle-based curcumin formulation utilizing a PVCL-PVA-PEG graft copolymer has shown promise for enhancing ocular drug delivery. This system significantly improves curcumin’s solubility and stability while offering robust antioxidant activity. In vitro and in vivo studies demonstrated that these nanomicelles enhance cellular uptake and corneal permeation compared to free curcumin solutions. Additionally, the formulation exhibited excellent ocular tolerance, with no signs of irritation in rabbit models. These results suggest that nanomicelles could serve as an effective platform for delivering curcumin topically in the treatment of ocular inflammation and related conditions . Recent advancements in curcumin-based therapies for AMD highlight the promise of aqueous nanomicellar formulations (CUR-NMF). This innovative approach overcomes curcumin’s poor aqueous solubility, a key limitation for its therapeutic use. CUR-NMF, developed using hydrogenated castor oil (HCO-40) and octoxynol-40 (OC-40), offers a stable delivery system optimized for retinal protection. Studies demonstrate its antioxidant, anti-inflammatory, and anti-angiogenic effects, showing significant protection against oxidative stress in retinal cells and a reduction in VEGF release, a critical factor in AMD pathology. Furthermore, sustained drug release profiles and favorable safety assessments suggest CUR-NMF could provide long-term therapeutic benefits for both dry and wet AMD . Cyclodextrins (CDs) play a crucial role in enhancing curcumin’s solubility, stability, and bioavailability through the formation of inclusion complexes . These complexes significantly improve curcumin’s therapeutic effectiveness in both anterior and posterior ocular diseases. Among the CDs, β-cyclodextrins (βCD) and γ-cyclodextrins (γCD) stand out due to their higher solubility, capacity to self-assemble into nanoaggregates, and favorable safety profile for ocular applications . Since the mid-1990s, CD-based inclusion complexes have provided significant technological advantages for pharmaceutical formulations. By enhancing the stability, solubility, and bioavailability of bioactive compounds, these complexes address key challenges in drug delivery. A notable example is the use of cyclodextrins to improve the solubility and stability of chloramphenicol, a patented formulation still in use today . This approach enabled the development of stable pharmaceutical solutions and optimized separation processes, underscoring the enduring relevance of this technology . Methyl-β-cyclodextrin (M-β-CD) is the cyclodextrin used in commercial eye drop formulations, including those containing chloramphenicol. Hydroxypropyl-β-cyclodextrin (HP-β-CD) is also covered by this patent for chloramphenicol due to its superior solubility and biocompatibility . More recently, CD-based inclusion complexes have been explored for cannabinoid delivery, demonstrating promising potential in pain management and anti-inflammatory therapies. These developments highlight the versatility of cyclodextrins in modern drug delivery, particularly for ocular applications, where solubility, stability, and bioavailability are critical for therapeutic success . Modified CDs, such as ethylene diamine (EDA)-modified βCD, have demonstrated superior capabilities in improving curcumin (CUR) solubility and stability. These complexes provide enhanced thermodynamic properties, making CUR more bioavailable for ocular applications. Curcumin-EDA-βCD nanoparticles exhibit excellent corneal permeability, as shown in vitro porcine cornea experiments, and maintain high biocompatibility, confirmed by histological analyses of porcine corneas and bovine corneal epithelial cell viability. These properties make them particularly suitable for addressing anterior segment diseases like keratitis and dry eye disease . In a recent study, various CD-curcumin complexes were prepared and characterized, showing significant improvements in solubility. The freeze-drying method produced highly soluble complexes, and the optimal formulation provided sustained release for over 96 h. This approach offers a promising solution for curcumin’s use in ocular therapies, such as eye drops for conditions like retinitis pigmentosa . Inclusion complexes of CUR with hydroxypropyl-β-cyclodextrin (HP-βCD) were successfully developed using the cosolvency/lyophilization method, resulting in significant improvements in CUR solubility, stability, and therapeutic efficacy. The complexes demonstrated superior antioxidant and anti-inflammatory activities compared to free CUR. To facilitate ocular administration, an in-situ gel system was prepared using Pluronic F127 and chitosan, providing mucoadhesion and sol-gel transition between 26–35 °C. Viscosity, pH, and clarity tests confirmed the system’s suitability for ocular application. In vitro release studies showed sustained drug release for 6 h, fitting the Weibull kinetic model. This approach offers a promising drug delivery strategy for ocular diseases, supporting prolonged and controlled drug release . The poor solubility and stability of CUR limit its application in ocular drug delivery. To address this, CUR was complexed with βCD and HP-βCD using co-solvent, sonication, and freeze-drying methods in 1:1 and 1:2 molar ratios. The freeze-drying method produced the most water-soluble complexes. Among the 12 tested formulations, the F11 formulation, prepared with pH 6.8 phosphate buffer containing 1% Tween 80, demonstrated sustained drug release for over 96 h. The drug release followed a Higuchi non-Fickian diffusion model. These findings suggest that F11 could be developed as a once-daily eye drop formulation, offering a promising approach for the sustained delivery of curcumin in the treatment of ocular diseases, such as retinitis pigmentosa . The use of CDs to optimize corneal penetration of CUR has shown promising results. In ex vivo models using porcine corneas, the combination of CDs with nanoparticles demonstrated greater drug permeation. This improvement is attributed to the ability of CDs to form inclusion complexes, enhancing curcumin’s solubility and stability, while nanoparticles enable sustained release and protection against enzymatic degradation . Recent studies have demonstrated that curcumin-loaded hydrogels, such as those incorporating CUR nanoparticles encapsulated with βCD and hyaluronic acid, accelerate corneal healing in ulcerative keratitis. This system not only improves corneal clarity and reduces inflammation but also enhances the quality of healed tissues, requiring fewer applications compared to conventional treatments. These formulations hold promises for future therapeutic use in treating ulcerative keratitis and other ocular conditions, providing an innovative, herbal-based alternative to traditional treatments . The penetration of CUR into the cornea was evaluated using an ex vivo porcine eye model and a digital image analysis technique. Several formulation strategies, including oily solutions, oily suspensions, micelles, liposomes, nanosuspensions, and CD complexes, were explored to improve CUR corneal permeability. The results revealed that cyclodextrin-based formulations exhibited superior corneal penetration compared to other delivery systems. The image analysis approach effectively measured CUR penetration into corneal tissues, supporting the potential of cyclodextrin complexes as a delivery strategy for hydrophobic drugs in ocular applications. This technique offers a novel approach for optimizing the penetration of CUR and similar compounds into the cornea . Among the most effective formulations are those based on modified βCDs and conjugates with tetrahydrocurcumin nanoparticles, which exhibited deeper penetration into ocular tissues. These strategies hold significant potential for treating both anterior and posterior segment ocular diseases, as they increase bioavailability and extend therapeutic effects . γCD-based nanoparticles not only enhance drug permeation but also increase retention time on the ocular surface, promoting sustained drug release and reducing the frequency of administration. Additionally, the presence of tear enzymes like α-amylase facilitates drug release from γCD complexes, further boosting bioavailability. For instance, γCD-based eye drops containing dexamethasone achieved higher concentrations in ocular tissues compared to commercial formulations. Moreover, these formulations were well tolerated, with no significant ocular irritation or toxicity observed. γCD has also been employed in formulations for dorzolamide, telmisartan, and nepafenac, demonstrating improved pharmacokinetics and sustained drug release for up to 24 h . Inclusion complexes of CUR with HP-βCD enhance curcumin’s solubility, dissolution rate, and bioavailability, essential for ocular drug delivery. Studies using co-evaporation methods revealed a 1:1 molar ratio complex with a solubility constant of 30.09 mM −1 . Characterization techniques, such as XRD, confirmed the loss of curcumin’s crystalline structure, while FTIR and DTA indicated no chemical interactions. In vitro dissolution tests showed faster release of CUR from the complex compared to its pure form and physical mixtures. This approach improves curcumin’s bioavailability, making it a promising strategy for ocular drug delivery systems . The ocular delivery of CUR faces significant barriers due to anatomical and physiological constraints; however, advances in nanoengineered systems have shown promising results. The formation of inclusion complexes with HP-CDs through spray-drying significantly enhanced the solubility, permeability, and stability of CUR. Enhanced corneal and retinal permeability was observed, along with increased antioxidant activity in ocular epithelial cells, including upregulation of SOD1, CAT1, and HMOX1. Moreover, protection against oxidative stress was confirmed in rabbit corneal tissues. These findings highlight the potential of CUR:HP-CD complexes to improve ocular drug bioavailability, thereby enhancing therapeutic outcomes for ocular diseases . Cyclodextrin-based systems significantly enhance curcumin’s bioavailability, solubility, and therapeutic potential for ocular drug delivery. Advances in βCD, γCD, and HP-βCD systems, combined with nanoparticles or in situ gels, have demonstrated improved drug permeation, sustained release, and higher bioactivity. These strategies support the development of more effective ophthalmic treatments. Nanocomposites, such as cupriferous hollow nanoshells, combine silver and copper ions. These materials exhibit dual functionality: silver ions provide potent antibacterial activity, while copper ions promote tissue regeneration by stimulating fibroblast migration and angiogenesis. This dual approach is particularly beneficial in treating conditions like keratitis, where infections can impair spontaneous recovery and cause corneal damage. Nanocomposite-based treatments not only target the bacteria but also support the healing of damaged tissues, offering a comprehensive approach to managing complex infections . Moreover, curcumin enhances traditional antibiotics by inhibiting bacterial efflux pumps and disrupting biofilms—critical mechanisms in antibiotic resistance. When combined with biopolymers like chitosan, curcumin has shown enhanced antibacterial effects, even at low concentrations, especially against resistant bacterial strains. This makes curcumin-based formulations a valuable tool in combating antibiotic-resistant ocular infections, such as conjunctivitis and keratitis . Curcumin-based formulations have also demonstrated significant efficacy in the treatment of conjunctivitis. Products like Haridra ® and Ophthacare ® have been shown to combat pathogens like Escherichia coli , Staphylococcus aureus , Klebsiella pneumoniae , and Pseudomonas aeruginosa while also reducing inflammation and irritation. These formulations address not only the infection but also the underlying inflammation, providing a comprehensive treatment approach. Ophthacare ® , which combines Curcuma longa with other herbal extracts, offers an effective solution for a range of ocular conditions, including dry eye and inflammatory conjunctival disorders . Endophthalmitis, an intraocular infection characterized by extensive inflammation and retinal damage, has benefited from nanotechnology-based drug delivery systems. Hybrid frameworks that incorporate silver nanoparticles and photosensitizers have been developed to disrupt biofilms while preserving host tissues. These systems, combined with curcumin’s anti-inflammatory properties, can modulate cytokine storms, support retinal cell survival, and preserve ocular structures. This combination not only targets the infection but also helps to protect the delicate retinal tissues, improving patient outcomes . Recent innovations in drug delivery systems have further amplified the therapeutic potential of curcumin. Nanoparticles and liposomes are particularly effective at enhancing curcumin’s bioavailability and ocular penetration, ensuring sustained therapeutic effects. For example, dual-drug nanofibers, which combine curcumin with antibiotics, have shown enhanced bactericidal activity and accelerated tissue regeneration in preclinical models of ocular infections. These advanced delivery systems ensure that curcumin reaches the target site effectively, offering continuous antimicrobial action and supporting tissue healing . These systems not only enhance the effectiveness of conventional antibiotics but also provide innovative solutions to overcome the challenges posed by MDR bacteria, biofilms, and tissue damage . The integration of curcumin in these systems adds a further layer of therapeutic benefit, making it a promising tool in the management of ocular infections. 4.1. Photodynamic Therapy (PDT) Curcumin’s photosensitizing properties make it a promising candidate for PDT, targeting pathological cells in conditions such as ocular tumors and infections. This approach is particularly relevant for eyelid-specific conditions, offering : Mechanisms: dual role as a photosensitizer and therapeutic agent. Applications: minimally invasive treatment for tumors, infections, and inflammatory disorders. Benefits: combines antioxidant and anti-inflammatory effects to enhance therapeutic outcomes for eyelid diseases. 4.2. Mucoadhesive Formulations Mucoadhesive drug delivery systems, including hydrogels and films, prolong curcumin’s contact time with the ocular surface, increasing its therapeutic efficacy. These systems can be tailored to eyelid disorders such as the following : Blepharitis and Dermatitis: prolonged retention enhances localized anti-inflammatory and antioxidant effects. Sustained Drug Release: mucoadhesive properties ensure better therapeutic outcomes for chronic eyelid conditions. Clinical Potential: effective for diseases requiring extended drug action, like anterior uveitis and diabetic retinopathy. 4.3. Neuroprotective Effects in Neurological Eyelid Disorders Curcumin offers neuroprotective benefits by reducing neuroinflammation and promoting cell survival, with applications in : Blepharospasm: reduces oxidative stress and neuroinflammation, alleviating involuntary twitching. Neuropathic Inflammation: modulates immune signaling, potentially relieving neuropathic eyelid pain. Mechanisms: targets inflammatory pathways (e.g., NF-κB and TLR4) and enhances antioxidant activity to protect against tissue damage. Curcumin’s photosensitizing properties make it a promising candidate for PDT, targeting pathological cells in conditions such as ocular tumors and infections. This approach is particularly relevant for eyelid-specific conditions, offering : Mechanisms: dual role as a photosensitizer and therapeutic agent. Applications: minimally invasive treatment for tumors, infections, and inflammatory disorders. Benefits: combines antioxidant and anti-inflammatory effects to enhance therapeutic outcomes for eyelid diseases. Mucoadhesive drug delivery systems, including hydrogels and films, prolong curcumin’s contact time with the ocular surface, increasing its therapeutic efficacy. These systems can be tailored to eyelid disorders such as the following : Blepharitis and Dermatitis: prolonged retention enhances localized anti-inflammatory and antioxidant effects. Sustained Drug Release: mucoadhesive properties ensure better therapeutic outcomes for chronic eyelid conditions. Clinical Potential: effective for diseases requiring extended drug action, like anterior uveitis and diabetic retinopathy. Curcumin offers neuroprotective benefits by reducing neuroinflammation and promoting cell survival, with applications in : Blepharospasm: reduces oxidative stress and neuroinflammation, alleviating involuntary twitching. Neuropathic Inflammation: modulates immune signaling, potentially relieving neuropathic eyelid pain. Mechanisms: targets inflammatory pathways (e.g., NF-κB and TLR4) and enhances antioxidant activity to protect against tissue damage. Curcumin’s potential in eyelid diseases is supported by its potent anti-inflammatory, immunomodulatory, antioxidant, and antibacterial properties. The antibacterial activity of curcumin could be particularly beneficial in treating eyelid infections, such as those caused by Staphylococcus aureus or other bacterial pathogens, which are common in conditions like blepharitis and eyelid dermatitis. Future research should focus on developing targeted delivery systems, such as mucoadhesive and nanoparticle formulations, to enhance efficacy in localized eyelid treatments. Well-designed clinical trials are needed to validate curcumin’s safety and effectiveness in eyelid conditions, including blepharitis, blepharospasm, and eyelid dermatitis. Additionally, exploring combination therapies that integrate curcumin with conventional treatments or other phytochemicals could provide solutions for refractory eyelid conditions. Given curcumin’s versatility as a therapeutic agent and advances in drug delivery technologies, it holds significant promise for addressing unmet needs in eyelid disease treatment. Curcumin demonstrates significant therapeutic potential in ophthalmology, particularly for retinal and corneal diseases, due to its anti-inflammatory, antioxidant, antibacterial, and anti-angiogenic properties. Its antibacterial activity could enhance treatment options for ocular surface infections, such as conjunctivitis or keratitis, by directly combating bacterial pathogens. However, challenges related to bioavailability and solubility need to be overcome through advanced drug delivery systems like nanoparticles, niosomes, and cyclodextrin complexes. Curcumin’s therapeutic value lies in its pleiotropic effects, including anti-inflammatory, antioxidant, and anti-angiogenic activities. In comparison to traditional treatments, curcumin offers a multi-targeted approach that may complement or enhance existing therapies. For example, its ability to prevent inflammation and oxidative damage positions it as a potential adjunct to anti-VEGF treatments for conditions like age-related macular degeneration. However, its clinical application is limited by poor bioavailability, necessitating further research to establish its clinical effectiveness relative to conventional treatments. In conclusion, curcumin holds promising therapeutic potential for ophthalmology, but further studies, especially clinical trials, are required to confirm its clinical efficacy and overcome existing limitations. The continued exploration of innovative delivery systems will be key to unlocking its full therapeutic potential. |
Radiographic identification of symptomless mandibular third molars without clinical pericoronitis | a5a99a4f-0d90-4136-8c31-eb7708ef3fff | 11442521 | Dentistry[mh] | One of the common radiographs interpreted by oral radiologists is dental panoramic radiography, which is also the most frequent choice for third molar imaging . Radiologists are occasionally obliged to make statements about panoramic radiographs (PANs) accompanied by incomplete or no clinical information. Based on a radiograph alone, it is challenging to determine whether third molars are potential infection foci. Therefore, the radiologist needs information on the clinical situation. However, it would be useful if one could identify from a PAN some characteristics typical of symptomless third molars. Among the common diagnoses to extract third molars are pericoronitis, caries, and impaction . Pericoronitis is a clinical diagnosis associated mostly with mandibular third molars, yet signs of pericoronitis may be visible in radiographs. When the tooth has perforated the marginal bone cortex and gingiva, the integrity of the dental follicle is breached, and subsequently, the third molar is exposed to oral bacterial flora. Hence, partial eruption is a widely recognized predisposing factor for the development of pericoronitis . A correlation between pericoronitis and position of the mandibular third molar has been widely reported . However, less scientific evidence is available on radiographic characteristics of mandibular third molars without clinical signs of pericoronal infection in symptomless persons. According to a Turkish study on 342 patients, completely unerupted mandibular third molars are less likely to have symptoms or pericoronitis than partially or fully erupted ones . Nevertheless, it is important to note that lack of symptoms does not equate to lack of pathology . The aim of this study was to determine radiographic characteristics of mandibular third molars in persons without symptoms or clinical signs of pericoronal infection. The hypothesis was that typical radiographic characteristics of such teeth can be identified.
Study design A retrospective study on existing cross-sectional data was designed to evaluate radiographic characteristics in clinically pericoronitis-free mandibular third molars of symptomless young adults. The data were collected at the Finnish Student Health Service (FSHS), Helsinki, Finland in 2002 . All first-year students at the University of Helsinki were routinely invited to participate in a free oral health examination at the FSHS. Of these, a cohort of 277 students was selected based on their being born in Helsinki in 1981 or 1982 and living in Helsinki at the beginning of their studies. Students of the cohort completed a questionnaire and after the clinical oral examination, they were offered a possibility to participate voluntarily in the radiography. Participants within a narrow age range and with similar backgrounds, including birthplace and current place of residence, were selected to minimize potential bias of the material. The criteria for exclusion from the study were a PAN not being available for the present analysis and no mandibular third molars visible on the PAN. Of the 277 invited students, 45 (16%) were excluded for not participating in the clinical oral examination (Fig. ). Another 16% were excluded for missing PANs or mandibular third molars. A missing data analysis of included and excluded participants showed that they did not differ by sex (χ 2 = 1.26; df = 1; p = 0.261) or age (Mann-Whitney U = 4160; p = 0.808). Study variables The material included responses to the questionnaire on symptoms of third molars, results of the clinical oral examination, and PANs. Age and sex of participants were recorded. Clinical features of the mandibular third molars included identification of the tooth, its clinical stage of eruption, and signs of clinical pericoronitis (Table ). Radiological variables of the third molars comprised pathological signs in the follicle, marginal bone level on the distal surface of mandibular second molar, depth of a tooth in the alveolar bone, inclination, stage of root development, and mesiodistal space for eruption (Table ). Mesiodistal space for eruption was evaluated according to the Pell and Gregory classification, as described elsewhere . The outcome variable was a symptomless mandibular third molar without clinical signs of pericoronal disease. Predictor variables were the clinical stage of eruption and the six radiographic characteristics of mandibular third molars on PANs. Radiological examination PANs were taken with Planmeca Promax 2D (Helsinki, Finland) with exposure values of 64‒68 kV voltage, 6.3‒10 mA current, and 15.8 s time. The PANs were analysed at the facilities of the FSHS by one of the authors. After analysis of all radiographs, 11% ( n = 23) of randomly chosen radiographs were analysed a second time after two weeks to obtain an estimate of intra-examiner reproducibility. Ethical considerations The FSHS Institutional Review Board approved the clinical and radiographic examinations in 2002. The oral health examinations adhered to the Declaration of Helsinki guidelines, and each student participated voluntarily after signing an informed consent. Following the European Commission guidelines for radiation protection, it is deemed unacceptable practice to conduct routine radiography without the patient’s history and a clinical examination . Therefore, an existing radiographic material was repurposed for the current analysis. The Finnish Social and Health Data Permit Authority (Findata) approved the secondary utilization of this health care data (THL/4680/14.02.00/2020). The FSHS also granted permission to employ the existing material for the present study. For reasons of data protection, results were not presented if the frequencies were less than 5, and therefore, in the analysis of variables some combinations of categories were made (marginal bone level and depth in alveolar bone). Statistical analysis Mandibular third molar was the unit of observation. In the analysis, characteristics of third molars were cross-tabulated according to symptomless and symptomatic persons. Differences between subgroups were examined using χ 2 test for frequencies and Mann-Whitney U test for means of independent groups. The significance level was set at p < 0.05. SPSS Statistics version 27 (IBM Corporation, Armonk, NY, USA) was used in the analyses.
A retrospective study on existing cross-sectional data was designed to evaluate radiographic characteristics in clinically pericoronitis-free mandibular third molars of symptomless young adults. The data were collected at the Finnish Student Health Service (FSHS), Helsinki, Finland in 2002 . All first-year students at the University of Helsinki were routinely invited to participate in a free oral health examination at the FSHS. Of these, a cohort of 277 students was selected based on their being born in Helsinki in 1981 or 1982 and living in Helsinki at the beginning of their studies. Students of the cohort completed a questionnaire and after the clinical oral examination, they were offered a possibility to participate voluntarily in the radiography. Participants within a narrow age range and with similar backgrounds, including birthplace and current place of residence, were selected to minimize potential bias of the material. The criteria for exclusion from the study were a PAN not being available for the present analysis and no mandibular third molars visible on the PAN. Of the 277 invited students, 45 (16%) were excluded for not participating in the clinical oral examination (Fig. ). Another 16% were excluded for missing PANs or mandibular third molars. A missing data analysis of included and excluded participants showed that they did not differ by sex (χ 2 = 1.26; df = 1; p = 0.261) or age (Mann-Whitney U = 4160; p = 0.808).
The material included responses to the questionnaire on symptoms of third molars, results of the clinical oral examination, and PANs. Age and sex of participants were recorded. Clinical features of the mandibular third molars included identification of the tooth, its clinical stage of eruption, and signs of clinical pericoronitis (Table ). Radiological variables of the third molars comprised pathological signs in the follicle, marginal bone level on the distal surface of mandibular second molar, depth of a tooth in the alveolar bone, inclination, stage of root development, and mesiodistal space for eruption (Table ). Mesiodistal space for eruption was evaluated according to the Pell and Gregory classification, as described elsewhere . The outcome variable was a symptomless mandibular third molar without clinical signs of pericoronal disease. Predictor variables were the clinical stage of eruption and the six radiographic characteristics of mandibular third molars on PANs.
PANs were taken with Planmeca Promax 2D (Helsinki, Finland) with exposure values of 64‒68 kV voltage, 6.3‒10 mA current, and 15.8 s time. The PANs were analysed at the facilities of the FSHS by one of the authors. After analysis of all radiographs, 11% ( n = 23) of randomly chosen radiographs were analysed a second time after two weeks to obtain an estimate of intra-examiner reproducibility.
The FSHS Institutional Review Board approved the clinical and radiographic examinations in 2002. The oral health examinations adhered to the Declaration of Helsinki guidelines, and each student participated voluntarily after signing an informed consent. Following the European Commission guidelines for radiation protection, it is deemed unacceptable practice to conduct routine radiography without the patient’s history and a clinical examination . Therefore, an existing radiographic material was repurposed for the current analysis. The Finnish Social and Health Data Permit Authority (Findata) approved the secondary utilization of this health care data (THL/4680/14.02.00/2020). The FSHS also granted permission to employ the existing material for the present study. For reasons of data protection, results were not presented if the frequencies were less than 5, and therefore, in the analysis of variables some combinations of categories were made (marginal bone level and depth in alveolar bone).
Mandibular third molar was the unit of observation. In the analysis, characteristics of third molars were cross-tabulated according to symptomless and symptomatic persons. Differences between subgroups were examined using χ 2 test for frequencies and Mann-Whitney U test for means of independent groups. The significance level was set at p < 0.05. SPSS Statistics version 27 (IBM Corporation, Armonk, NY, USA) was used in the analyses.
The number of participants included in the analyses was 189 (20% men, 80% women). Their mean age was 20.7 years (standard deviation (SD) ± 0.6 years, range 19.7–21.7 years). These 189 persons had 345 mandibular third molars. Regarding intra-examiner reliability of the radiographic characteristics, the kappa values were 0.95 for marginal bone level, 0.95 for depth of the tooth in the bone, 0.94 for stage of root development, and 1.00 for other characteristics. A value of 0.81 or above indicated almost perfect agreement. According to the questionnaire and the clinical oral examination, 58% ( n = 110) of the participants were symptomless and had no clinical signs of pericoronal infection in their mandibular third molars. No significant difference existed between men (68%) and women (56%) (χ 2 = 2.04; df = 1; p = 0.153). In this symptomless group, the number of mandibular third molars was 203 (59% of all 345 mandibular third molars). An analysis of mandibular third molars according to presence or absence of clinically detected pericoronitis and symptoms is presented in Table . Symptomless mandibular third molars without clinical pericoronitis were most likely clinically unerupted (78%; χ 2 = 59.44; df = 1; p < 0.001), and radiographically, were associated with reduced marginal bone level (all reduced levels combined: 70%; χ 2 = 12.62; df = 1; p < 0.001), located deeper in the bone (classes A, B, and C: 87%; χ 2 = 36.26; df = 2; p < 0.001), mesioangularly inclined (75%; χ 2 = 48.44; df = 3; p < 0.001), and had incomplete root development (68%; χ 2 = 10.67; df = 1; p = 0.001). Pathological signs in the follicle were not associated with clinical signs and symptoms (χ 2 = 3.81; df = 1; p = 0.051). Mesiodistal space for eruption also was not a significant predictor.
The purpose of this study was to identify radiographic characteristics of mandibular third molars without symptoms or clinical pericoronitis. Such teeth were radiographically most likely associated with reduced marginal bone level on the distal surface of the mandibular second molar, deep in bone or only just perforating the cortex, mesioangularly inclined, and had incomplete root development (Fig. ). In addition, symptomless teeth were most likely clinically unerupted. The most surprising finding was the significant association between reduced marginal bone level on the distal surface of the second molar and the lack of symptoms and clinical pericoronitis. Moreover, the greater the reduction in marginal bone level, the fewer the symptoms or clinical pericoronitis. Marginal bone loss is typically considered a pathological finding and often associated with mesial inclination . The present finding may be explained by the narrow age range (19.7–21.7 years) of the sample, and thus, the eruption phase of the third molar being underway . Therefore, the reduced alveolar bone level may be more related to the eruption process and bone remodelling around the dental follicle than to current pathology. This question is examined in a Japanese study on 241 patients with mesioangularly impacted mandibular third molars . That study concluded that bone resorption was not related to acute pericoronitis in young adults (18‒22 years) but was related in older patients (≥ 41 years). Still, it is important to note that third molars with reduced bone level and unable to erupt may be at risk for periodontal pathology if a connection to the oral cavity is later established . The present finding on the clinical stage of eruption of third molars is in line with earlier study in that the majority of unerupted teeth are symptomless and without clinical pericoronitis . This is also evident in a British study with the UK strategy to remove only symptomatic third molars, as 97% of removed teeth were partially or totally erupted . The present variable of clinical stage of eruption was similar to the radiographic depth in bone; superficially located teeth were often associated with symptoms or pericoronitis. This is consistent with a Spanish study on patients undergoing extraction of mandibular third molars, where the occurrence of pericoronitis was lower the deeper the tooth was located . Regarding inclinations of teeth, mesioangular third molars were more likely symptomless and pericoronitis-free than vertical or distoangular teeth. The finding of distoangular inclination as the most prone to pericoronitis has also been reported earlier . A recent meta-analysis notes similarly that vertical teeth are most frequently associated with pericoronitis but horizontal teeth least frequently . However, in that meta-analysis, most studies included patients referred to third molar extraction, while the material of the present study was gathered through a routine oral examination. Therefore, in the earlier studies, inclinations in symptomless and symptomatic persons are rarely compared, and consequently, certain inclinations may be overrepresented. Furthermore, in most of the studies of the above-mentioned meta-analysis, the inclination was assessed according to Winter’s classification, which differs slightly from the present study in the limit values of vertical and distoangular inclinations. Incomplete root development was associated with a lack of symptoms and clinical pericoronitis. This is surely related to the development of the third molar, as teeth with incomplete root formation are more likely unerupted. A similar finding was made in a Danish follow-up study on 132 adolescents, where the root development of erupted third molars by the age of 20 was ahead of that of impacted ones . Radiographic changes in the follicle occurred at the same rate in the symptomless and symptomatic groups, and thus, poorly predicted clinical status. Radiographic assessment of the pericoronal space as normal or pathological is complicated. In the literature, pericoronal space < 2.5–3 mm is often considered to be normal . However, in studies on patients referred to extraction of impacted third molars with < 2.4–2.5 mm pericoronal space, pathological changes in dental follicles were observed between 46% and 58.5% of the teeth in histopathological examination . This highlights the complexity of assessing pericoronal pathology based on radiographic changes in the follicle, increasing the challenge for radiologists when making statements about PANs with limited clinical information. The present findings on the identification of symptomless mandibular third molars without clinical pericoronitis are likely to be applicable to all young adults when interpreting a PAN of third molars. The age range in this study corresponded to the typical age of third molar eruption. A strength of this study was that the participants were not patients referred to extraction of third molars but regular students who participated voluntarily in a routine oral health examination. Thus, the volume of symptoms and pathology of present third molars were not as prominent as in studies on patients. A limitation of the present material was that although the presence of third molars was probed, the probing depths distal to second molars and around third molars were not obtained. Clinical probing depths combined with radiographic bone level data could have given more detailed knowledge of the current periodontal status of third molars. Another limitation was that the material was over 20 years old. This was because, according to the European Commission guidelines for radiation protection, it would be unacceptable to conduct a similar study solely for third molars . Thus, an existing radiographic material was utilised for the current analysis. A third limitation was that the participants were university students from the capital of the country. They may thus have had better access to dental care, including prevention of third molar pathology, than the rest of the same-aged population. However, the narrow age range and similar background homogenized the material. A fourth limitation was the sex distribution, which was female-dominated. This is explained by 64% of bachelor’s degree students and 68% of master’s degree students at the University of Helsinki being women. Furthermore, women were more active than men in participating in the oral health examination (88% vs. 74%) . The clinical relevance of the findings lies in situations where a patient has an ambiguous infection and infection foci are searched from the head and neck areas. In such cases, the initial assessment may be based solely on radiological findings. As the third molar is a potential focus of infection, the present findings may prove useful when trying to exclude non-pathological mandibular third molars from diseased teeth. The findings may also be useful when a radiologist is writing a statement, an expert body is making an insurance judgement, or in a consultation at the request of other clinicians.
Mandibular third molars without symptoms or clinical pericoronitis in 21-year-old adults can be assessed from a PAN with 68–87% certainty. The best predictor was the location deep in the bone or only just perforating the cortex, followed by mesioangular inclination, reduced marginal bone level on the distal surface of the second molar, and incomplete root development in this order of decreasing certainty. However, radiographic changes in the follicle were unreliable predictors.
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Pharmacogenomic Determinants of Interindividual Drug Response Variability: From Discovery to Implementation | 6dc828ee-34e1-4328-8cad-ef80f7a8cba3 | 7999913 | Pharmacology[mh] | |
Implementation of a Trauma-Informed Care Approach in a Gastroenterology Setting | 2488f9f0-e46f-4be3-866a-9809a4bf0ef4 | 11762216 | Internal Medicine[mh] | Patients with gastrointestinal (GI) issues often have a history of trauma, which confers additional risk for psychiatric disorders such as anxiety, depression, and posttraumatic stress disorder (PTSD). Trauma increases the risk of developing GI conditions, and is associated with worse GI symptoms, poorer quality of life, poorer adjustment to illness, adverse health outcomes, and increased healthcare needs and utilization of services . Patients with GI conditions are also vulnerable to experiencing illness-related traumatic stress or medical trauma—i.e., a frightening experience related to illness, injury, pain, medical events, medical treatment or procedures, and/or interactions with medical providers. Medical trauma can result from undergoing invasive procedures or surgeries, witnessing or experiencing medical errors or complications during treatment, or experiencing uncertainty related to one’s disease, and can result in posttraumatic stress symptoms. Histories of trauma, adverse life events (e.g., accident/injury/illness, physical and sexual abuse, domestic/community violence, imprisonment), and stressful experiences related to disease management and interactions within the healthcare system can increase patients’ risk of experiencing trauma reactions within GI settings. Trauma reactions can include overly anxious or fearful behavior, hypervigilance, increased startle responses (hyperreactivity), physiological distress, feeling numbed or detached, communication difficulties, and difficulty trusting healthcare providers. Given the range of trauma reactions, healthcare professionals may not recognize them in their patients or know how to respond to them effectively, which can leave patients feeling apprehensive or uncomfortable with their care and can interfere with treatment engagement and outcome. Additionally, healthcare professionals may feel frustrated, unprepared, or uncertain about how to care effectively for patients having trauma reactions. As such, they may be vulnerable to experiencing vicarious trauma, compassion fatigue, and burnout. When healthcare professionals understand the effects of trauma in patients with GI conditions, they can minimize the risk of retraumatizing their patients. Trauma-informed care (TIC) is a treatment philosophy and practice that recognizes the widespread impact of trauma and supports the understanding that patients may engage in behaviors that could be mistaken for resistance or noncompliance with care recommendations. TIC aims to increase awareness of practices and types of interactions that can mimic traumatic experiences and reduce risk of retraumatization. TIC promotes the physical and psychological safety of patients, providers, and staff; fosters opportunities for collaboration and patient empowerment; advocates for transparency across interactions; and values patients’ unique experiences. TIC significantly improves patient care and satisfaction and reduces burnout in healthcare professionals. Efforts are being made to understand the relationship between trauma, GI conditions, and patients’ vulnerability to posttraumatic stress reactions. A number of important considerations for members of a GI clinical team providing TIC have been identified, including engaging in patient-centered communication, minimizing patient distress, fostering physical and emotional safety, and empowering patients. While TIC may be helpful in many aspects of GI care, there is limited guidance on how best to implement this approach. As part of a larger initiative to enhance behavioral healthcare access and engagement in a GI setting within a large rural healthcare system, we identified history of trauma as a barrier to care. Thus, we sought to redesign care to offer trauma-focused services to patients and incorporate a trauma-informed care approach among providers and staff within the GI department. Specifically, we aimed to build and implement programming centered on increasing awareness and understanding of: The relationship between trauma and GI symptoms, trauma reactions in a healthcare setting, strategies for responding to patients in emotional distress, and opportunities to reduce risk of retraumatization in a GI setting. Setting This work was conducted at Dartmouth-Hitchcock Medical Center (DHMC) in the Section of Gastroenterology and Hepatology. DHMC is an academic medical center within the Dartmouth Health system serving residents of Northern New England. The Section of Gastroenterology and Hepatology includes 24 providers (physicians and advanced practice providers) and averages 15000 outpatient and 15000 endoscopy visits per year. Approach This work was supported by a health care delivery incubator that guides teams through a design-thinking informed curriculum to improve care for selected patient populations. Design thinking encourages an empathetic perspective by focusing on the user experience; this approach encourages multi-disciplinary teams, including the patient voice, to ensure that changes incorporate a diversity of perspectives within the healthcare system, increasing the likelihood of care innovations being sustainable. The project team for this work included expertise from psychologists, gastroenterologists, a practice manager, administrative staff and schedulers, a patient with lived GI experience, and an M.D./M.B.A student. This work was reviewed by the health system’s Institutional Review Board (IRB) and, consistent with the quality improvement goal, was considered non-human subjects research. Interviews To augment the perspectives on the team and ensure a broad perspective on the challenges and potential opportunities to improve behavioral healthcare, an extensive patient and stakeholder interviewing process was completed. As part of the initial design-thinking phase, the team conducted 37 interviews, including with nine GI providers (physicians, advanced practice providers, fellows), two GI clinic nurses, nine Dartmouth-affiliated stakeholders (from Psychiatry, Primary Care, the Student Health Center, and GI administrative staff), six DHMC psychologists, six external GI psychologists, and five patients. From these interviews, improvement in TIC in GI was identified as an area of needed exploration and improvement. To better understand the impact of and challenges working with trauma within a GI setting, additional interviews ( N = 8) were conducted with two GI providers (one physician, one nurse practitioner), one pelvic floor physical therapist, two psychologists, one licensed clinical social worker, one GI administrator, and one patient within the Dartmouth Health system. Interviewees were queried about experiences providing and receiving care within the GI department, important considerations when working with patients who might have histories of trauma, and support for responding to patients in emotional distress during procedures and clinical encounters. Because the goal of these interviews was to rapidly gather data and inform a larger program redesign effort, we utilized a rapid analytic process. Interview content was reviewed following each interview with the full program redesign team, enabling the diverse team to discuss and compare findings across interviews. This rapid process also enabled interviewers to probe further on emerging areas of interest in subsequent interviews. Accordingly, key themes from the interviews were derived through iterative discussion. Survey As part of the discovery process, the team also developed a needs assessment survey, informed by the stakeholder interviews, to identify barriers to engagement in GI care. This 36-item, 10-min survey queried patients about demographics, their experiences of care in GI, scheduling preferences, interest in GI behavioral health treatment, and barriers to care. It also included several short validated instruments, including the Single Item Literacy Screener, , PROMIS Self-Efficacy for Managing Chronic Conditions Questionnaire, Kemp Quality of Life scale, and Patient Health Questionnaire 4. The survey was accessible from June 2022 through December 2022. Paper copies of the survey were available to patients with in-person appointments and a link to a digital survey was embedded in the GI section website and within patients’ after visit summaries in their patient portals. Participation in this survey was voluntary, and patients who provided their email addresses were entered into a drawing for one of ten $100 Amazon gift cards upon completion of the survey. The interview and survey findings informed the development of innovative solutions to the identified need for improved trauma services and resources using an iterative, team-based approach. This work was conducted at Dartmouth-Hitchcock Medical Center (DHMC) in the Section of Gastroenterology and Hepatology. DHMC is an academic medical center within the Dartmouth Health system serving residents of Northern New England. The Section of Gastroenterology and Hepatology includes 24 providers (physicians and advanced practice providers) and averages 15000 outpatient and 15000 endoscopy visits per year. This work was supported by a health care delivery incubator that guides teams through a design-thinking informed curriculum to improve care for selected patient populations. Design thinking encourages an empathetic perspective by focusing on the user experience; this approach encourages multi-disciplinary teams, including the patient voice, to ensure that changes incorporate a diversity of perspectives within the healthcare system, increasing the likelihood of care innovations being sustainable. The project team for this work included expertise from psychologists, gastroenterologists, a practice manager, administrative staff and schedulers, a patient with lived GI experience, and an M.D./M.B.A student. This work was reviewed by the health system’s Institutional Review Board (IRB) and, consistent with the quality improvement goal, was considered non-human subjects research. To augment the perspectives on the team and ensure a broad perspective on the challenges and potential opportunities to improve behavioral healthcare, an extensive patient and stakeholder interviewing process was completed. As part of the initial design-thinking phase, the team conducted 37 interviews, including with nine GI providers (physicians, advanced practice providers, fellows), two GI clinic nurses, nine Dartmouth-affiliated stakeholders (from Psychiatry, Primary Care, the Student Health Center, and GI administrative staff), six DHMC psychologists, six external GI psychologists, and five patients. From these interviews, improvement in TIC in GI was identified as an area of needed exploration and improvement. To better understand the impact of and challenges working with trauma within a GI setting, additional interviews ( N = 8) were conducted with two GI providers (one physician, one nurse practitioner), one pelvic floor physical therapist, two psychologists, one licensed clinical social worker, one GI administrator, and one patient within the Dartmouth Health system. Interviewees were queried about experiences providing and receiving care within the GI department, important considerations when working with patients who might have histories of trauma, and support for responding to patients in emotional distress during procedures and clinical encounters. Because the goal of these interviews was to rapidly gather data and inform a larger program redesign effort, we utilized a rapid analytic process. Interview content was reviewed following each interview with the full program redesign team, enabling the diverse team to discuss and compare findings across interviews. This rapid process also enabled interviewers to probe further on emerging areas of interest in subsequent interviews. Accordingly, key themes from the interviews were derived through iterative discussion. As part of the discovery process, the team also developed a needs assessment survey, informed by the stakeholder interviews, to identify barriers to engagement in GI care. This 36-item, 10-min survey queried patients about demographics, their experiences of care in GI, scheduling preferences, interest in GI behavioral health treatment, and barriers to care. It also included several short validated instruments, including the Single Item Literacy Screener, , PROMIS Self-Efficacy for Managing Chronic Conditions Questionnaire, Kemp Quality of Life scale, and Patient Health Questionnaire 4. The survey was accessible from June 2022 through December 2022. Paper copies of the survey were available to patients with in-person appointments and a link to a digital survey was embedded in the GI section website and within patients’ after visit summaries in their patient portals. Participation in this survey was voluntary, and patients who provided their email addresses were entered into a drawing for one of ten $100 Amazon gift cards upon completion of the survey. The interview and survey findings informed the development of innovative solutions to the identified need for improved trauma services and resources using an iterative, team-based approach. Interview Findings The stakeholder interviews revealed important needs when working with patients in GI as they relate to realizing the prevalence of trauma and its impact in this patient population; recognizing the signs and symptoms of trauma; and effectively responding to trauma and minimizing potential for retraumatization. This process also revealed several clinical areas within GI where patients might be more vulnerable to experiencing trauma reactions, including the motility procedure suite and the endoscopy suite. Representative direct quotations are included to illustrate these key findings. Through the interview process, we identified a need for increased education for patients, providers, and staff to better understand the relationship between trauma and GI symptoms: “It is important to share with providers how trauma can show up in the exam room, why patients might be difficult.” “Recognition and validation of [patients’] responses are important—it makes sense that they are feeling protective of their bodies.” “It’s important for providers to know which patients might be at greater risk for pain or emotional discomfort.” In particular, interviews highlighted the need to bridge this awareness into actionable change in several areas, including: Effectively talking to patients about trauma and procedures: “We need advice on how best to broach certain issues, such a trauma, as we are usually unaware of [patients’ trauma] history.” “I think discussing with patients any traumas or anxieties might help inform how best to schedule them.” Evaluating patients’ understanding of and comfort with procedures: “It is important to clarify expectations around procedures and anesthesia”. Identifying and responding to signs of distress or discomfort during office visits and procedures: “Often trauma does not come up [directly in appointments]. If I sense resistance or hesitancy, I will probe further.” “When patients seem anxious during an exam or are exhibiting protective body language, I will call attention to it and check in with them.” “I was most appreciative when providers said ‘here are the choices, this is what is happening/going to happen,’ it doesn’t take all that much to connect with patients.” Navigating challenging patient interactions: “It’s helpful to have ways to engage staff so everyone is aware of the issues.” “We try to validate patients’ feelings and distress.” During these interviews, patients, providers, and staff also all requested more resources related to trauma-informed care, including a specific need for increased patient support before, during, and after procedures. Survey Findings One hundred thirty patients initiated the survey, and 100 patients completed the survey [mean age 58.4 ( SD = 17.3), 57.1% women, 96% White] (See Table ). As is described in detail elsewhere, a significant number of respondents reported symptoms of depression (27%) and anxiety (35%) impacting their ability to manage their overall GI health. Participants also reported that significant stress (27%) and trauma experiences (13%) impacted their ability to manage their GI health. Survey completers expressed interest in programming focused on worry and anxiety (42%), stress management (36%), and trauma coping (7%). Programs Developed We addressed three areas of improvement that arose from stakeholder interviews and the needs assessment: (1) increasing education on the relationship between trauma and GI conditions and trauma-informed care for providers and staff, (2) building and implementing trauma-informed patient interventions/supports , and (3) creating informational resources on TIC for providers/staff (e.g., reference sheets that can be accessed via an internal medical resource database) (See Table ). Education We developed educational programming targeted toward clinical providers and administrative staff. The objectives and strategies for increasing understanding of trauma and GI conditions and response to trauma reactions are detailed in Table . Increased awareness and understanding of how trauma exposure affects patients, providers, and staff; indicators of a trauma response during a medical encounter; and strategies for responding to patients in emotional distress can help reduce retraumatization and improve interactions between patients, providers, and staff. Clinical Provider Education The clinical provider educational sessions were designed for GI physicians and fellows, endoscopy technicians, and clinical nursing staff. These sessions lasted 30 to 60 min and were conducted virtually and in-person. The sessions included an overview of the signs, symptoms, and effects of trauma; the relationship between trauma and GI conditions; discussion of illness-related traumatic stress; applications of a trauma-informed care approach; inquiring about trauma and responding to patients when they share a history of trauma; identification of ways trauma and anxiety can present during clinic or procedure visits; and identification of strategies to help patients regulate their emotions or behaviors in a safe way. Administrative Education A 60-min educational training session was conducted virtually for the GI clinic administrative staff. This session centered on discussion of TIC and effective ways to respond to patients in distress on the telephone. The session emphasized recognizing trauma reactions, being aware of indicators of emotional distress, providing validation and reassurance, establishing support and safety, maintaining boundaries, and identifying an action plan or solution. Clinical providers and staff reported perceived benefit from the educational sessions on trauma-informed care. For example, they reported increased understanding of how trauma can affect emotional and behavioral responding and how trauma can present during a patient interaction. They also appreciated learning tools for supporting patients in regulating their emotions and behaviors in safe, effective ways. Patient Interventions and Supports Patient interventions and supports included skills building and psychoeducation groups, skills building posters, and improved patient communications. Skills Building and Psychoeducation Groups Patients were offered an opportunity to participate in a multi-session group centered on building skills to help manage emotions about medical procedures. Unfortunately, this group program was less successful than other similar skills groups offered in the GI department, as evidenced by very low enrollment. Thus, it was never fully deployed. Instead, a single session psychoeducation workshop was created to increase patients’ knowledge about the overarching effects of trauma on physical health, the relationship between trauma and GI symptoms, and strategies for coping with trauma reactions. This program was designed and implemented as a 90-min virtual group session. This workshop centered on defining trauma; identifying the signs and symptoms of trauma; examining the association among trauma, mental health, and GI conditions; increasing awareness of the body’s response to stress; and identifying strategies for regulating one’s emotions and behaviors (see Table for learning objectives and strategies). This program was led three times during the project period. Twenty-one patients (out of 31 total enrolled) attended across the three psychoeducation groups delivered. This program continues to be offered to patients through the GI behavioral health program and has been well attended and received. Skills Building Posters To help patients learn and implement coping skills during clinic or procedure visits, a poster was developed that provided instructions on diaphragmatic breathing and sensory and cognitive grounding skills. Skills posters were displayed in patient waiting areas and procedure rooms within the motility testing and endoscopy suites, and in the infusion clinic. This poster is included in the supplemental materials and is available to download and use. Improved Communication and Patient Comfort To improve communication between patients and members of their care team, existing patient-facing instructions throughout the GI department were edited to be more trauma-informed. For example, the colonoscopy prep letter was updated to acknowledge that prior procedures and life experiences could increase anxiety or concern about the procedures and the colonoscopy findings, and encouraged patients to share concerns proactively. We also created a patient-centered, plain language handout on monitored anesthesia care (MAC) versus moderate sedation for patients scheduled for colonoscopies, as this is an aspect of care that may elicit concern, anxiety, or uncertainty due to potential for increased vulnerability. To help patients feel cared for and supported, we partnered with local restaurants to offer patients meal discounts following colonoscopy. Resources We also developed TIC reference sheets for providers and staff that can be accessed via a medical resources database within the electronic medical record system. These resources provide tips on discussing trauma during a clinic visit, identifying ways trauma might present, and responding to patients’ concerns and emotional distress during visits. These resources were created to reinforce knowledge and skills learned during the educational programs. They are included in the supplemental materials and are available to download and use. The stakeholder interviews revealed important needs when working with patients in GI as they relate to realizing the prevalence of trauma and its impact in this patient population; recognizing the signs and symptoms of trauma; and effectively responding to trauma and minimizing potential for retraumatization. This process also revealed several clinical areas within GI where patients might be more vulnerable to experiencing trauma reactions, including the motility procedure suite and the endoscopy suite. Representative direct quotations are included to illustrate these key findings. Through the interview process, we identified a need for increased education for patients, providers, and staff to better understand the relationship between trauma and GI symptoms: “It is important to share with providers how trauma can show up in the exam room, why patients might be difficult.” “Recognition and validation of [patients’] responses are important—it makes sense that they are feeling protective of their bodies.” “It’s important for providers to know which patients might be at greater risk for pain or emotional discomfort.” In particular, interviews highlighted the need to bridge this awareness into actionable change in several areas, including: Effectively talking to patients about trauma and procedures: “We need advice on how best to broach certain issues, such a trauma, as we are usually unaware of [patients’ trauma] history.” “I think discussing with patients any traumas or anxieties might help inform how best to schedule them.” Evaluating patients’ understanding of and comfort with procedures: “It is important to clarify expectations around procedures and anesthesia”. Identifying and responding to signs of distress or discomfort during office visits and procedures: “Often trauma does not come up [directly in appointments]. If I sense resistance or hesitancy, I will probe further.” “When patients seem anxious during an exam or are exhibiting protective body language, I will call attention to it and check in with them.” “I was most appreciative when providers said ‘here are the choices, this is what is happening/going to happen,’ it doesn’t take all that much to connect with patients.” Navigating challenging patient interactions: “It’s helpful to have ways to engage staff so everyone is aware of the issues.” “We try to validate patients’ feelings and distress.” During these interviews, patients, providers, and staff also all requested more resources related to trauma-informed care, including a specific need for increased patient support before, during, and after procedures. One hundred thirty patients initiated the survey, and 100 patients completed the survey [mean age 58.4 ( SD = 17.3), 57.1% women, 96% White] (See Table ). As is described in detail elsewhere, a significant number of respondents reported symptoms of depression (27%) and anxiety (35%) impacting their ability to manage their overall GI health. Participants also reported that significant stress (27%) and trauma experiences (13%) impacted their ability to manage their GI health. Survey completers expressed interest in programming focused on worry and anxiety (42%), stress management (36%), and trauma coping (7%). We addressed three areas of improvement that arose from stakeholder interviews and the needs assessment: (1) increasing education on the relationship between trauma and GI conditions and trauma-informed care for providers and staff, (2) building and implementing trauma-informed patient interventions/supports , and (3) creating informational resources on TIC for providers/staff (e.g., reference sheets that can be accessed via an internal medical resource database) (See Table ). We developed educational programming targeted toward clinical providers and administrative staff. The objectives and strategies for increasing understanding of trauma and GI conditions and response to trauma reactions are detailed in Table . Increased awareness and understanding of how trauma exposure affects patients, providers, and staff; indicators of a trauma response during a medical encounter; and strategies for responding to patients in emotional distress can help reduce retraumatization and improve interactions between patients, providers, and staff. Clinical Provider Education The clinical provider educational sessions were designed for GI physicians and fellows, endoscopy technicians, and clinical nursing staff. These sessions lasted 30 to 60 min and were conducted virtually and in-person. The sessions included an overview of the signs, symptoms, and effects of trauma; the relationship between trauma and GI conditions; discussion of illness-related traumatic stress; applications of a trauma-informed care approach; inquiring about trauma and responding to patients when they share a history of trauma; identification of ways trauma and anxiety can present during clinic or procedure visits; and identification of strategies to help patients regulate their emotions or behaviors in a safe way. Administrative Education A 60-min educational training session was conducted virtually for the GI clinic administrative staff. This session centered on discussion of TIC and effective ways to respond to patients in distress on the telephone. The session emphasized recognizing trauma reactions, being aware of indicators of emotional distress, providing validation and reassurance, establishing support and safety, maintaining boundaries, and identifying an action plan or solution. Clinical providers and staff reported perceived benefit from the educational sessions on trauma-informed care. For example, they reported increased understanding of how trauma can affect emotional and behavioral responding and how trauma can present during a patient interaction. They also appreciated learning tools for supporting patients in regulating their emotions and behaviors in safe, effective ways. The clinical provider educational sessions were designed for GI physicians and fellows, endoscopy technicians, and clinical nursing staff. These sessions lasted 30 to 60 min and were conducted virtually and in-person. The sessions included an overview of the signs, symptoms, and effects of trauma; the relationship between trauma and GI conditions; discussion of illness-related traumatic stress; applications of a trauma-informed care approach; inquiring about trauma and responding to patients when they share a history of trauma; identification of ways trauma and anxiety can present during clinic or procedure visits; and identification of strategies to help patients regulate their emotions or behaviors in a safe way. A 60-min educational training session was conducted virtually for the GI clinic administrative staff. This session centered on discussion of TIC and effective ways to respond to patients in distress on the telephone. The session emphasized recognizing trauma reactions, being aware of indicators of emotional distress, providing validation and reassurance, establishing support and safety, maintaining boundaries, and identifying an action plan or solution. Clinical providers and staff reported perceived benefit from the educational sessions on trauma-informed care. For example, they reported increased understanding of how trauma can affect emotional and behavioral responding and how trauma can present during a patient interaction. They also appreciated learning tools for supporting patients in regulating their emotions and behaviors in safe, effective ways. Patient interventions and supports included skills building and psychoeducation groups, skills building posters, and improved patient communications. Skills Building and Psychoeducation Groups Patients were offered an opportunity to participate in a multi-session group centered on building skills to help manage emotions about medical procedures. Unfortunately, this group program was less successful than other similar skills groups offered in the GI department, as evidenced by very low enrollment. Thus, it was never fully deployed. Instead, a single session psychoeducation workshop was created to increase patients’ knowledge about the overarching effects of trauma on physical health, the relationship between trauma and GI symptoms, and strategies for coping with trauma reactions. This program was designed and implemented as a 90-min virtual group session. This workshop centered on defining trauma; identifying the signs and symptoms of trauma; examining the association among trauma, mental health, and GI conditions; increasing awareness of the body’s response to stress; and identifying strategies for regulating one’s emotions and behaviors (see Table for learning objectives and strategies). This program was led three times during the project period. Twenty-one patients (out of 31 total enrolled) attended across the three psychoeducation groups delivered. This program continues to be offered to patients through the GI behavioral health program and has been well attended and received. Skills Building Posters To help patients learn and implement coping skills during clinic or procedure visits, a poster was developed that provided instructions on diaphragmatic breathing and sensory and cognitive grounding skills. Skills posters were displayed in patient waiting areas and procedure rooms within the motility testing and endoscopy suites, and in the infusion clinic. This poster is included in the supplemental materials and is available to download and use. Improved Communication and Patient Comfort To improve communication between patients and members of their care team, existing patient-facing instructions throughout the GI department were edited to be more trauma-informed. For example, the colonoscopy prep letter was updated to acknowledge that prior procedures and life experiences could increase anxiety or concern about the procedures and the colonoscopy findings, and encouraged patients to share concerns proactively. We also created a patient-centered, plain language handout on monitored anesthesia care (MAC) versus moderate sedation for patients scheduled for colonoscopies, as this is an aspect of care that may elicit concern, anxiety, or uncertainty due to potential for increased vulnerability. To help patients feel cared for and supported, we partnered with local restaurants to offer patients meal discounts following colonoscopy. Patients were offered an opportunity to participate in a multi-session group centered on building skills to help manage emotions about medical procedures. Unfortunately, this group program was less successful than other similar skills groups offered in the GI department, as evidenced by very low enrollment. Thus, it was never fully deployed. Instead, a single session psychoeducation workshop was created to increase patients’ knowledge about the overarching effects of trauma on physical health, the relationship between trauma and GI symptoms, and strategies for coping with trauma reactions. This program was designed and implemented as a 90-min virtual group session. This workshop centered on defining trauma; identifying the signs and symptoms of trauma; examining the association among trauma, mental health, and GI conditions; increasing awareness of the body’s response to stress; and identifying strategies for regulating one’s emotions and behaviors (see Table for learning objectives and strategies). This program was led three times during the project period. Twenty-one patients (out of 31 total enrolled) attended across the three psychoeducation groups delivered. This program continues to be offered to patients through the GI behavioral health program and has been well attended and received. To help patients learn and implement coping skills during clinic or procedure visits, a poster was developed that provided instructions on diaphragmatic breathing and sensory and cognitive grounding skills. Skills posters were displayed in patient waiting areas and procedure rooms within the motility testing and endoscopy suites, and in the infusion clinic. This poster is included in the supplemental materials and is available to download and use. To improve communication between patients and members of their care team, existing patient-facing instructions throughout the GI department were edited to be more trauma-informed. For example, the colonoscopy prep letter was updated to acknowledge that prior procedures and life experiences could increase anxiety or concern about the procedures and the colonoscopy findings, and encouraged patients to share concerns proactively. We also created a patient-centered, plain language handout on monitored anesthesia care (MAC) versus moderate sedation for patients scheduled for colonoscopies, as this is an aspect of care that may elicit concern, anxiety, or uncertainty due to potential for increased vulnerability. To help patients feel cared for and supported, we partnered with local restaurants to offer patients meal discounts following colonoscopy. We also developed TIC reference sheets for providers and staff that can be accessed via a medical resources database within the electronic medical record system. These resources provide tips on discussing trauma during a clinic visit, identifying ways trauma might present, and responding to patients’ concerns and emotional distress during visits. These resources were created to reinforce knowledge and skills learned during the educational programs. They are included in the supplemental materials and are available to download and use. Given the prevalence of trauma and its potential impact on patients, there have been increasing efforts to promote delivery of TIC within healthcare settings . As part of a larger initiative to enhance GI behavioral healthcare access and engagement , a needs assessment revealed history of trauma as a barrier to care from both patient and provider perspectives. Survey and interview data indicated that patients viewed trauma symptoms as interfering with their overall health and healthcare engagement. Staff and providers believed they would benefit from additional training in the identification and management of trauma/stress reactions. These findings support building trauma-informed programs and practices within healthcare settings. To address these needs, we designed a variety of trauma-focused programs and supports for patients, providers, and staff with the overarching goal of reducing trauma burden and preventing retraumatization. The perspectives of patients, providers, and staff who participated in our needs assessment are consistent with past research on trauma in the GI setting . For patients, aspects of their GI conditions and medical care can range from stressful to traumatic. Illness-related factors that can be traumatic include diagnosis and illness management, the unpredictable nature of GI conditions, the impact on overall functioning, and loss of control or autonomy as it relates to changes or disruptions in bodily functions . Healthcare-related factors that can be traumatic include hospitalizations, surgeries, and invasive medical procedures; vulnerable physical positioning and removal of clothing; how information is communicated to patients; and how staff and providers receive and respond to patients’ communications . Regardless of whether patients have experienced prior trauma (medical or otherwise), stressful and vulnerable experiences in the healthcare setting can negatively affect patients’ sense of autonomy and safety, increase their risk of experiencing trauma reactions, and affect their overall healthcare engagement. For staff and providers, it can be challenging to recognize and respond to these reactions effectively while assisting patients and delivering care. Likewise, patients may feel uncomfortable or mistrustful and have difficulty engaging in treatment. TIC underscores the widespread nature of trauma—it assumes that all individuals may be impacted by past and/or current trauma, whether they identify it or not and whether healthcare professionals are aware of it or not. Further, trauma has the potential to affect all individuals at every level of care or interaction—from point of referral to scheduling an appointment or procedure, followed by checking in with administrative staff at the time of appointment, waiting, and being roomed, meeting with healthcare providers, engaging in treatment, and ongoing management of one’s illness and associated care. TIC emphasizes recognizing how trauma affects all individuals within a system of care. Therefore, it was important that we address trauma directly (i.e., help patients better understand and manage trauma symptoms), as well as target both system-related and patient-centered gaps in care. To meet this need, we designed TIC reference materials, tools to support patients in the context of their care, and face-to-face programming for patients, providers, and staff, with the goals of increasing awareness of trauma and its effects and reducing potential for retraumatization. GI providers and staff identified caring for patients with trauma histories and responding to their emotional distress as a specific training need. Increased knowledge of how trauma can affect emotional and behavioral responding and how trauma can present during a patient interaction can empower providers and staff in the care and support of patients with GI conditions by increasing confidence in their ability to respond more effectively when patients are exhibiting trauma reactions. In turn, patients may feel more supported and confident in their medical team’s responsiveness to their needs. Patient-focused trauma programming was designed to provide a helpful foundation on trauma and its impact on health and well-being. These programs and supports were a step in rounding out existing GI behavioral health programming, with a focus on mind–body/brain-gut connection and placing patients’ trauma and GI symptoms in context. Additionally, the patient-focused materials were distributed broadly, had high reach, and communicated to patients and staff that their emotional well-being is valued within GI. These materials complemented available behavioral health treatment resources. Ultimately, these programs and materials can help to facilitate comfort and enhance patient-centered communication as it relates to distress experiences (e.g., appreciation knowing that there are supports available, increased willingness to speak to one’s provider about their concerns) . Likewise, these programs and resources may enable providers to be more responsive to reports of past trauma (i.e., with a referral for psychiatric care and/or trauma-focused treatment) without feeling like they are operating outside their scope of practice. The next steps in this line of work include expanding access to TIC, both for patients and providers/staff. To expand access, we need to explore additional modes of dissemination, while being mindful of potential stigma or discomfort discussing traumatic experiences. For example, advertising supportive programs for any patient who might be nervous about an upcoming procedure will likely include patients with trauma, while also expanding a TIC-based program to patients with other sources of anxiety. Additional avenues for dissemination may include embedding providers or support staff in settings that increase vulnerability (e.g., motility procedure and endoscopy suites) or creating alternate delivery modalities for treatment resources (e.g., webinars). Evaluation of the feasibility and acceptability of these programs, and the degree to which they support engagement in care will be critical as the use of TIC in GI settings grows. The vulnerability associated with past traumatization and its impact on patient’s experience of GI care supports this initiative’s promotion of trauma-informed practices in a GI setting. However, this initiative is limited by lack of formal evaluation of these efforts, including objective measurement of changes in knowledge about trauma and its impact before and after implementation of programming, as well as of facilitators and barriers to use of these tools and programs over time. In the future, we hope to study the impact of these initiatives on patient, provider, and staff engagement and well-being. TIC programming specific to the needs of patients with GI conditions is desired by patients, providers, and staff. Education and resources can be implemented without major system changes; these initiatives have the potential to improve patients’ care and their interactions with the medical system. TIC can also help clinical teams respond to unique trauma-related challenges, thereby improving their experiences as well. Within our clinic, we plan to continue offering trauma-focused programming for patients, providers, and staff through a variety of channels and more effectively evaluate these different approaches to promoting TIC. Below is the link to the electronic supplementary material. Supplementary file1 (PDF 2466 KB) Supplementary file2 (PDF 348 KB) Supplementary file3 (PDF 382 KB) Supplementary file4 (PDF 252 KB) |
Mechanisms of ROS-mediated interactions between | e9aaa745-b817-45f9-9cd3-c636eea7ad0a | 11378622 | Microbiology[mh] | Plants have been in a symbiotic relationship with soil microorganisms during their growth and development. As a key member of the soil ecosystem, plant growth-promoting rhizobacteria (PGPR) is mainly distributed in the roots and rhizosphere of plants and participates in a variety of biological activities in the soil ecosystem. PGPR can improve crop productivity and resistance to pathogens by inducing complex changes in plant growth and development . In addition, PGPR also competitively settles in plant roots and plays a crucial role in promoting plant growth through different mechanisms such as phosphate solubilization, nitrogen fixation, IAA production, siderophores, biofilm synthesis, VOCs production, and induction of plant systemic resistance . To date, many PGPR strains have been isolated for extensive and in-depth research, which is of great significance for promoting sustainable agricultural development . However, so far, the mechanism of plant-rhizosphere microbiome interaction is extremely complex, and little is known about how beneficial bacteria interact with the plant immune system. In general, the growth and stress effects of plants under the action of PGPR could be determined by changes in hormone levels and related signaling pathways. Each plant has its specific microflora, and the structure of the microflora in the rhizosphere of plants is composed of root secretions produced by plant roots and signal molecules produced by plants and microorganisms . With the help of these signaling molecules, a variety of close relationships have been established between plant roots and microorganisms. Acturally, plant roots can interact with a large number of bacteria in the surrounding soil. When bacteria migrate from bulk soil to the root surface and colonize further, the bacterial diversity decreases, which seems to indicate that plants exert selective forces on their colonizing bacteria . An early filter used by plants to identify and respond to bacteria is their immune system , which recognizes bacterial flagella, peptidoglycans and bacterial elongation factors through MAMPs . When plant roots recognize these molecules, a series of molecular events will occur. The earliest stage is the outflow of calcium ions and the outbreak of reactive oxygen species (ROS) . Under the condition of pathogen infection, the recognition and activation of plant immune system has been widely described, and MAMP receptors can recognize molecules in all bacteria, and it is found that beneficial bacteria can also induce immune responses similar to pathogenic bacteria . Therefore, the effect of plant immune system on healthy root microbiota and how beneficial microorganisms respond to plant immune system is still an active research field, and there are still many issues that need to be explored in depth . Previously, we found that B. aryabhattai LAD, as a good PGPR strain, significantly promotes maize growth . Therefore, in order to understand the interaction between B. aryabhattai LAD and maize roots to further understand the interaction between beneficial bacteria and plant immune system, we co-cultured the strain LAD with maize to explore its IAA synthesis level, intracellular ROS level and the relationship between ROS and IAA synthesis. Subsequently, we further analyzed the changes of intracellular transcriptome and metabolome of B. aryabhattai LAD under the stimulation of maize root secretions. These results provide a relevant model for exploring the effects of plant-soil microbial interactions on plant defense functions and thus promoting plant growth, and also lay a solid foundation for the future application of PGPR to field production for sustainable agricultural development.
Strain and culture conditions The strain B. aryabhattai LAD used in this study was isolated from the rhizosphere soil of maize and preserved in the China General Microbiological Culture Collection Center ( CGMCC18653 ), the NCBI accession number is PRJNA716506. B. aryabhattai LAD was inoculated in beef extract peptone medium and cultured to logarithmic phase at 37 °C and 180 rpm. Subsequently, the LAD bacterial suspension was transferred to 50 mL beef extract peptone liquid medium at 1% inoculation amount, and cultured at 37 °C and 180 rpm for 24 h as seed solution. The plant material used in this study was maize and the seeds were sourced from Dalian Baisite Seed Co., Ltd. The maize seeds were surface sterilized by soaking in 70% ethanol for 2 min and then in 1% sodium hypochlorite solution for 20 min. After soaking, the seeds were rinsed three times in sterile desalinated water and prepared for use. Plants were kept in climate cabinets at 21 °C (180 µmol light m − 2 ·s − 1 at plant level; 16 h:8 h, light: dark). Effects of exogenous IAA and B. aryabhattai LAD on the growth of maize seedlings The B. aryabhattai LAD was inoculated into beef extract peptone medium at 1% inoculation amount, and cultured at 37 °C and 180 rpm for 72 h until OD600 nm was 1.4–1.5. The fermentation broth was taken and the IAA content was detected by Angilent ultra-high performance liquid chromatograph 1290 Infinity II ( Agilent Technologies Inc., California, USA ). The chromatographic column was Agilent Polaris C18-A ( 250 mm × 4.6 mm ), the flow rate was 1 mL / min, the injection volume was 10 µL, the column temperature was 35 °C, the wavelength was 254 nm, the mobile phase A was pure methanol, and the mobile phase B was glacial acetic acid aqueous solution with pH value of 3.2 [ V ( A ) : V ( B ) = 5.5 : 4.5 ]. In addition, the bacterial suspension cultured for 72 h was diluted in a gradient of 10 times, and the B. aryabhattai LAD bacterial suspension diluted to 10 2 CFU mL − 1 was used to soak the maize seeds for 24 h. The seeds were placed in a hydroponic tank containing B. aryabhattai LAD bacterial suspension and IAA for 14 days. The normal culture medium was used as a blank control to measure the roots of maize seedlings. The root development was measured by WinRHIZO Reg STD4800 Root Analysis System (Beijing Ruiding Environmental Technology Co., Ltd., Beijing, China). The growth promotion indexes of maize seedlings and their roots were counted using percentage values calculated as [(treatment group - control group)/control group]*100%. Collection of maize root secretions To test the effect of maize root secretions on IAA synthesis in LAD, root secretions were collected by hydroponics. The seeds soaked with LAD were cultured in a hydroponic tank containing B. aryabhattai LAD bacterial suspension, and the normal culture medium was used as a blank control. After 14 days of culture, the root secretions were collected and filtered with 0.22 μm filter membrane and stored at 4 °C. At the same time, the IAA content was detected by Angilent ultra-high performance liquid chromatograph 1290 Infinity II ( Agilent Technologies Inc., California, USA ). Effects of maize root secretions and H 2 O 2 on B. aryabhattai LAD The B. aryabhattai LAD was inoculated into beef extract peptone medium supplemented with 0.1%, 0.2% and 0.4% H 2 O 2 and 1%, 2% and 4% maize root secretions at a 1% inoculation amount, respectively. The blank beef extract peptone medium inoculated with B. aryabhattai LAD bacterial liquid was used as a blank control. One part was placed in a 12-well plate at 37 °C, 180 rpm for 24 h in a microplate reader, and the OD ( 600 nm ) was measured every 1 h. The other part was in a 50 mL conical flask. IAA production was determined by high performance liquid chromatography after 72 h of shaking culture at 180 rpm. Determination of ROS levels in cells and maize roots Maize roots were collected at 2,4,6,8,10 and 12 h, respectively. At the same time, bacterial cells were collected by centrifugation at 8000 rpm for 10 min, and then the bacterial cells were fully washed with PBS ( pH 7.0 ) and suspended in 1 mL phosphate buffer. The relative levels of intracellular reactive oxygen species (ROS) in B. aryabhattai LAD were determined by fluorescence assay, mainly using the oxidant-sensitive probe 2′,7′-dichlorodihydrofluorescein diacetate ( DCFH-DA ) (Beijing Solarbio Science & Technology Co., Ltd, Beijing, China). The fluorescence intensity was detected using a Bio Tek Cytation5 microplate reader (Beijing Derica Biotechnology Co., Ltd, Beijing, China), and the emission wavelength was set at 525 nm and the excitation wavelength was set at 488 nm. The relative level of ROS in maize roots was measured by Plant Reactive Oxygen Species ELISA Kit instruction at 450 nm to reflect the ROS level. Each sample was performed using three independent biological replicates. Total RNA extraction and transcriptome analysis B. aryabhattai LAD treated with maize root secretions was selected as the treatment group (G), and B. aryabhattai LAD cultured under normal conditions was used as the control group (CK). 1 mL bacterial suspension was centrifuged at 10,000 r min − 1 for 2 min at 4 °C in a 1.5 mL enzyme-free tube, and the supernatant was discarded to collect the bacteria and quickly frozen in liquid nitrogen for 15 min. The total RNA was extracted using the Trizol kit ( takara, dalian, China ) according to the kit instructions. High-quality RNA samples were collected by NEB Next Ultra RNA Library Preparation Kit ( NEB, CA ) for the preparation of cDNA library construction. Next-Generation Sequencing ( NGS ) was used to perform transcriptome sequencing analysis and comparison of samples based on the Illumina HiSeq sequencing platform. GO and KEGG enrichment analysis was performed using Blast2GO ( v2.5 ) and KOBAS ( v3.0 ) software. Differentially expressed genes ( DEGs ) were performed using the DESeq ( v1.32.0 ) program, and log2 ( fold change ) ≥ 1 and p ( padj ) ≤ 0.05 were considered to be DEGs. Pathway analysis of DEGs was performed using the KEGG PATHWAY database and Blast2GO. Metabolite extraction and metabolome analysis 2 mL of pre-cooled 60% methanol water was placed in a 5 mL centrifuge tube, and then 2 mL of bacterial solution was quickly added to it. The mixture was mixed manually for 5 s. The quenched bacterial solution was centrifuged at 3,000 r min − 1 , 4 °C for 10 min, and the supernatant was removed and placed in dry ice. The metabolites were detected by Thermo Vanquish ( Thermo Fisher Scientific, USA ) ultra-high performance liquid chromatography system combined with Thermo Orbitrap Exploris 120 mass spectrometry detector ( Thermo Fisher Scientific, USA ). The identification of relevant metabolites in the metabolome was based on the databases of HMDB ( http://www.hmdb.ca ), Metlin ( http://metlin.scripps.edu ), MassBank ( http://www.massbank.jp ), LipidMaps ( http://www.lipidmaps.org ) and mzClound ( https://www.mzcloud.org ) databases were performed. Differently accumulated metabolites (DAMs) were assessed by partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models using variable importance in prediction (VIP) scores. Thresholds for the analytical models were set at VIP ≥ 1, fold change ≥ 1.5 or ≤ 0.667, and p ≤ 0.05. Integration analyses of metabolomics and transcriptomics were performed via Pearson correlation coefficients, as previously described . Real-time quantitative polymerase chain reaction (qPCR) analysis To further elucidate the ROS-mediated interactions between B. aryabhattai LAD and maize rhizosphere to promote growth, we first examined the changes in the expression of genes related to growth hormone synthesis in B. aryabhattai LAD after exogenous additions of root secretions and H 2 O 2 . Subsequently, changes in the expression of growth hormone synthesis and antioxidant-related genes in the maize root system after exogenous addition of B. aryabhattai LAD treatment were further examined to determine the relationship between activation of the plant immune system and growth hormone synthesis following B. aryabhattai LAD interactions with the maize root system. The SYBR Green Premix Pro Taq HS qPCR Kit (AG11718, ACCURATE BIOTECHNOLOGY, HUNAN, Co., Ltd, Changsha, China) was used to perform qPCR in a Quant Studio6 Flex system (Thermo Fisher Scientific, USA). 16 S rDNA and Actin were selected as the internal reference genes for B. aryabhattai LAD and maize roots, respectively. To analyze the qPCR results, the relative expression of each gene was calculated by the comparative crossover (CP) method and expressed as 2 −∆∆CT . Each gene expression analysis was performed using three independent biological replicates. Specific primers used for qPCR are listed in Table . Statistical analysis IBM SPSS 25.0 (SPSS Inc., Chicago, IL, USA) software was used to statistically analyze the experimental data. One-way ANOVA ( One-way ANOVA ) was used to determine significant differences between the following: different treatments on maize root growth, different treatments on LAD growth and its IAA yield, and different treatments on the level of ROS in LAD and in the maize root system. All trials were conducted in triplicate and data were averaged and expressed as mean ± standard error (SE). The qPCR data of selected gene expression profiles were analyzed using the software package IBM SPSS 25.0 of Windows (SPSS Inc., Chicago, IL, USA). Prior to analysis, data were normalized by transforming as ln (x + 1). All data were expressed as means ± standard error of at least triplicates of independent cultures. The means of different treatments were compared by one-way ANOVA using Turkey’s honestly signifcant difference test at the 5% probability level ( p < 0.05). Metabolomics analysis was evaluated using variable importance in the projection (VIP) in the frst principal component of each OPLS-DA model. Thresholds with P < 0.05 and VIP > 1 were considered statistically significant. MetaboAnalyst software (version 3.0) was used for pathway enrichment analysis . Differentially expressed genes were analyzed for differences using DESeq, and the threshold for identifying DEGs was set at |log2 (fold change)|≥1,padj ≤ 0.05.
The strain B. aryabhattai LAD used in this study was isolated from the rhizosphere soil of maize and preserved in the China General Microbiological Culture Collection Center ( CGMCC18653 ), the NCBI accession number is PRJNA716506. B. aryabhattai LAD was inoculated in beef extract peptone medium and cultured to logarithmic phase at 37 °C and 180 rpm. Subsequently, the LAD bacterial suspension was transferred to 50 mL beef extract peptone liquid medium at 1% inoculation amount, and cultured at 37 °C and 180 rpm for 24 h as seed solution. The plant material used in this study was maize and the seeds were sourced from Dalian Baisite Seed Co., Ltd. The maize seeds were surface sterilized by soaking in 70% ethanol for 2 min and then in 1% sodium hypochlorite solution for 20 min. After soaking, the seeds were rinsed three times in sterile desalinated water and prepared for use. Plants were kept in climate cabinets at 21 °C (180 µmol light m − 2 ·s − 1 at plant level; 16 h:8 h, light: dark).
B. aryabhattai LAD on the growth of maize seedlings The B. aryabhattai LAD was inoculated into beef extract peptone medium at 1% inoculation amount, and cultured at 37 °C and 180 rpm for 72 h until OD600 nm was 1.4–1.5. The fermentation broth was taken and the IAA content was detected by Angilent ultra-high performance liquid chromatograph 1290 Infinity II ( Agilent Technologies Inc., California, USA ). The chromatographic column was Agilent Polaris C18-A ( 250 mm × 4.6 mm ), the flow rate was 1 mL / min, the injection volume was 10 µL, the column temperature was 35 °C, the wavelength was 254 nm, the mobile phase A was pure methanol, and the mobile phase B was glacial acetic acid aqueous solution with pH value of 3.2 [ V ( A ) : V ( B ) = 5.5 : 4.5 ]. In addition, the bacterial suspension cultured for 72 h was diluted in a gradient of 10 times, and the B. aryabhattai LAD bacterial suspension diluted to 10 2 CFU mL − 1 was used to soak the maize seeds for 24 h. The seeds were placed in a hydroponic tank containing B. aryabhattai LAD bacterial suspension and IAA for 14 days. The normal culture medium was used as a blank control to measure the roots of maize seedlings. The root development was measured by WinRHIZO Reg STD4800 Root Analysis System (Beijing Ruiding Environmental Technology Co., Ltd., Beijing, China). The growth promotion indexes of maize seedlings and their roots were counted using percentage values calculated as [(treatment group - control group)/control group]*100%.
To test the effect of maize root secretions on IAA synthesis in LAD, root secretions were collected by hydroponics. The seeds soaked with LAD were cultured in a hydroponic tank containing B. aryabhattai LAD bacterial suspension, and the normal culture medium was used as a blank control. After 14 days of culture, the root secretions were collected and filtered with 0.22 μm filter membrane and stored at 4 °C. At the same time, the IAA content was detected by Angilent ultra-high performance liquid chromatograph 1290 Infinity II ( Agilent Technologies Inc., California, USA ).
2 O 2 on B. aryabhattai LAD The B. aryabhattai LAD was inoculated into beef extract peptone medium supplemented with 0.1%, 0.2% and 0.4% H 2 O 2 and 1%, 2% and 4% maize root secretions at a 1% inoculation amount, respectively. The blank beef extract peptone medium inoculated with B. aryabhattai LAD bacterial liquid was used as a blank control. One part was placed in a 12-well plate at 37 °C, 180 rpm for 24 h in a microplate reader, and the OD ( 600 nm ) was measured every 1 h. The other part was in a 50 mL conical flask. IAA production was determined by high performance liquid chromatography after 72 h of shaking culture at 180 rpm.
Maize roots were collected at 2,4,6,8,10 and 12 h, respectively. At the same time, bacterial cells were collected by centrifugation at 8000 rpm for 10 min, and then the bacterial cells were fully washed with PBS ( pH 7.0 ) and suspended in 1 mL phosphate buffer. The relative levels of intracellular reactive oxygen species (ROS) in B. aryabhattai LAD were determined by fluorescence assay, mainly using the oxidant-sensitive probe 2′,7′-dichlorodihydrofluorescein diacetate ( DCFH-DA ) (Beijing Solarbio Science & Technology Co., Ltd, Beijing, China). The fluorescence intensity was detected using a Bio Tek Cytation5 microplate reader (Beijing Derica Biotechnology Co., Ltd, Beijing, China), and the emission wavelength was set at 525 nm and the excitation wavelength was set at 488 nm. The relative level of ROS in maize roots was measured by Plant Reactive Oxygen Species ELISA Kit instruction at 450 nm to reflect the ROS level. Each sample was performed using three independent biological replicates.
B. aryabhattai LAD treated with maize root secretions was selected as the treatment group (G), and B. aryabhattai LAD cultured under normal conditions was used as the control group (CK). 1 mL bacterial suspension was centrifuged at 10,000 r min − 1 for 2 min at 4 °C in a 1.5 mL enzyme-free tube, and the supernatant was discarded to collect the bacteria and quickly frozen in liquid nitrogen for 15 min. The total RNA was extracted using the Trizol kit ( takara, dalian, China ) according to the kit instructions. High-quality RNA samples were collected by NEB Next Ultra RNA Library Preparation Kit ( NEB, CA ) for the preparation of cDNA library construction. Next-Generation Sequencing ( NGS ) was used to perform transcriptome sequencing analysis and comparison of samples based on the Illumina HiSeq sequencing platform. GO and KEGG enrichment analysis was performed using Blast2GO ( v2.5 ) and KOBAS ( v3.0 ) software. Differentially expressed genes ( DEGs ) were performed using the DESeq ( v1.32.0 ) program, and log2 ( fold change ) ≥ 1 and p ( padj ) ≤ 0.05 were considered to be DEGs. Pathway analysis of DEGs was performed using the KEGG PATHWAY database and Blast2GO.
2 mL of pre-cooled 60% methanol water was placed in a 5 mL centrifuge tube, and then 2 mL of bacterial solution was quickly added to it. The mixture was mixed manually for 5 s. The quenched bacterial solution was centrifuged at 3,000 r min − 1 , 4 °C for 10 min, and the supernatant was removed and placed in dry ice. The metabolites were detected by Thermo Vanquish ( Thermo Fisher Scientific, USA ) ultra-high performance liquid chromatography system combined with Thermo Orbitrap Exploris 120 mass spectrometry detector ( Thermo Fisher Scientific, USA ). The identification of relevant metabolites in the metabolome was based on the databases of HMDB ( http://www.hmdb.ca ), Metlin ( http://metlin.scripps.edu ), MassBank ( http://www.massbank.jp ), LipidMaps ( http://www.lipidmaps.org ) and mzClound ( https://www.mzcloud.org ) databases were performed. Differently accumulated metabolites (DAMs) were assessed by partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) models using variable importance in prediction (VIP) scores. Thresholds for the analytical models were set at VIP ≥ 1, fold change ≥ 1.5 or ≤ 0.667, and p ≤ 0.05. Integration analyses of metabolomics and transcriptomics were performed via Pearson correlation coefficients, as previously described .
To further elucidate the ROS-mediated interactions between B. aryabhattai LAD and maize rhizosphere to promote growth, we first examined the changes in the expression of genes related to growth hormone synthesis in B. aryabhattai LAD after exogenous additions of root secretions and H 2 O 2 . Subsequently, changes in the expression of growth hormone synthesis and antioxidant-related genes in the maize root system after exogenous addition of B. aryabhattai LAD treatment were further examined to determine the relationship between activation of the plant immune system and growth hormone synthesis following B. aryabhattai LAD interactions with the maize root system. The SYBR Green Premix Pro Taq HS qPCR Kit (AG11718, ACCURATE BIOTECHNOLOGY, HUNAN, Co., Ltd, Changsha, China) was used to perform qPCR in a Quant Studio6 Flex system (Thermo Fisher Scientific, USA). 16 S rDNA and Actin were selected as the internal reference genes for B. aryabhattai LAD and maize roots, respectively. To analyze the qPCR results, the relative expression of each gene was calculated by the comparative crossover (CP) method and expressed as 2 −∆∆CT . Each gene expression analysis was performed using three independent biological replicates. Specific primers used for qPCR are listed in Table .
IBM SPSS 25.0 (SPSS Inc., Chicago, IL, USA) software was used to statistically analyze the experimental data. One-way ANOVA ( One-way ANOVA ) was used to determine significant differences between the following: different treatments on maize root growth, different treatments on LAD growth and its IAA yield, and different treatments on the level of ROS in LAD and in the maize root system. All trials were conducted in triplicate and data were averaged and expressed as mean ± standard error (SE). The qPCR data of selected gene expression profiles were analyzed using the software package IBM SPSS 25.0 of Windows (SPSS Inc., Chicago, IL, USA). Prior to analysis, data were normalized by transforming as ln (x + 1). All data were expressed as means ± standard error of at least triplicates of independent cultures. The means of different treatments were compared by one-way ANOVA using Turkey’s honestly signifcant difference test at the 5% probability level ( p < 0.05). Metabolomics analysis was evaluated using variable importance in the projection (VIP) in the frst principal component of each OPLS-DA model. Thresholds with P < 0.05 and VIP > 1 were considered statistically significant. MetaboAnalyst software (version 3.0) was used for pathway enrichment analysis . Differentially expressed genes were analyzed for differences using DESeq, and the threshold for identifying DEGs was set at |log2 (fold change)|≥1,padj ≤ 0.05.
Effect of exogenous addition of B. aryabhattai LAD and IAA on the growth of maize roots The results of root development of maize seedlings under different treatment conditions measured by root analyzer are shown in Fig. and Table . The main root length of maize seedlings increased by 197% and 167% respectively after exogenous addition of B. aryabhattai LAD and IAA. The main root thickness increased by 22% and 16% respectively, and the seedling length of maize seedlings increased by 107% and 78% respectively. Exogenous addition of B. aryabhattai LAD and IAA increased root surface area by 89% and 61%, root volume by 75% and 34%, and total root length by 97% and 63%, respectively. Exogenous addition of B. aryabhattai LAD and direct exogenous addition of IAA with the same content could promote the growth of maize seedlings, but the growth of maize roots in the exogenous addition of B. aryabhattai LAD group was significantly higher than that in the IAA group with the same concentration. Effect of root secretion and H 2 O 2 addition on the growth and IAA production of B. aryabhattai LAD The effects of root secretion and H 2 O 2 addition on the growth of B. aryabhattai LAD and its IAA production are shown in Fig. A, B. The growth of B. aryabhattai LAD was strongly inhibited by the addition of H 2 O 2 treatment, and its level of IAA production was significantly lower than that of the control group, and the levels of IAA synthesized after the addition of 0.1%, 0.2%, and 0.4% of H 2 O 2 to the B. aryabhattai LAD culture for 72 h were 15.1, 17.5, and 15.8 µg/mL, respectively, while the growth inhibition of B. aryabhattai LAD was strongly alleviated after the addition of IAA to its culture. Subsequently, the growth of B. aryabhattai LAD was also inhibited by the addition of root secretion, but the level of IAA production was significantly higher than that of the control group and the other treatment groups, and the levels of IAA synthesized after 72 h of incubation of B. aryabhattai LAD with 1%, 2%, and 4% of root secretion were 26.7, 24.2, and 23.4 µg/mL, respectively. Effect of different treatment conditions on ROS levels in B. aryabhattai LAD and maize roots The ROS levels in the roots of maize at different times are shown in Fig. C, and the ROS levels were determined by taking the maize roots on the third day from the start of the submerged seed culture, and both the control group and the treatment group showed a trend of increasing and then decreasing, and the ROS levels of the maize roots were significantly higher than those of the control group after the addition of the B. aryabhattai LAD treatment. The ROS levels of B. aryabhattai LAD strains at different culture stages were shown in Fig. D, which combined with the B. aryabhattai LAD growth curve showed that the intracellular ROS in the culture to 2 h, the concentration of the bacteria was small, and the difference of its intracellular ROS levels was not significant, after 2 h, the bacteria multiplied a lot and entered into the logarithmic growth period, and the ROS levels in the control group began to be significantly higher than that of the treatment group, and by 8 h, the growth of the strains began to slow down, and the ROS levels in the treatment group began to decrease and the control group was still at a high level. Transcriptome analysis To identify DEGs in B. aryabhattai LAD under maize root secretion treatment conditions, we constructed 6 cDNA libraries and filtered the sequencing data of transcriptome samples to obtain a total of 17.71 Gb of data. Gene expression was differentially analyzed using DESeq, and the threshold for identifying DEGs was set at |log 2 (fold change)| ≥ 1, padj ≤ 0.05. Compared with the control group, there were 93 DEGs in B. aryabhattai LAD under root secretion treatment conditions, of which 57 genes were up-regulated and 36 genes were down-regulated . Subsequently, we performed GO and KEGG enrichment analysis to further understand the biological functions of these DEGs and the related biological processes involved. As shown in Fig. A, in terms of GO enrichment analysis, the DEGs of B. aryabhattai LAD under root secretions treatment were mainly enriched in molecular functions (MF) and biological processes (BP). The top three GO terms significantly enriched in the MF category were phosphoribosylformylglycinamidine synthase activity (GO:0004642), carbon-nitrogen ligase activity, with glutamine as amido-N-donor (GO:0016884), ligase activity, forming carbon-nitrogen bonds (GO:0016879). In the BP category, the top three GOs significantly enriched were phospholipid catabolic process (GO:0009395), urea cycle (GO:000050), and urea metabolic process (GO:0019627). KEGG enrichment analysis showed (Fig. B) that the top 20 significantly enriched pathways of DEGs in B. aryabhattai LAD under root secretion treatment conditions were mainly associated with Metabolism, Genetic Information Processing, Environmental Information Processing in KEGG level 1 and Purine metabolism (ko00230), Inositol phosphate metabolism (ko00562), Alanine, aspartate and glutamate metabolism (ko00250), Glycerophospholipid metabolism (ko00564), ABC transporters (ko02010), Tyrosine metabolism (ko00350), Lysine degradation (ko00310), Oxidative phosphorylation (ko00190) Glycolysis / Gluconeogenesis (ko00010), Pyruvate metabolism (ko00620) in KEGG level 2. These results may be importantly related to the promotion of maize growth and resistance to environmental stresses by B. aryabhattai LAD. Metabolome analysis In order to evaluate the changes of intracellular metabolism of B. aryabhattai LAD after root secretions treatment, LC-MS / MS was used to evaluate the metabolic profile. The results showed that a total of 1,572 metabolites were identified based on the MS2 spectral database. The identified metabolites were classified according to chemical classification statistics, including 82 classifications, of which Carboxylic acids and derivatives were up to 361. Secondly, there are 113 Steroids and steroid derivatives, 105 Benzene and substituted derivatives, 105 Fatty Acyls, 105 Prenol lipids, 94 Organooxygen compounds, 46 Indoles and derivatives, 45 Glycerophospholipids and 30 Organonitrogens ( Fig. A ). At a threshold setting of VIP ≥ 1, fold change ≥ 1.5 or ≤ 0.667, and p ≤ 0.05, a total of 1,574 metabolites were detected in the treatment and control groups, of which 967 were detected in the positive ion mode and 607 were detected in the negative ion mode. Differential analysis of the detected metabolites showed a total of 45 differential metabolites, of which 8 differential metabolites were up-regulated and 37 differential metabolites were down-regulated (Fig. B). Subsequently, we performed KEGG enrichment analysis to better understand the biological functions of these differential metabolites and their involvement in relevant biological processes. The results showed that a total of 87 KEGG pathways were enriched by differential metabolites under root secretion treatment conditions. As shown in the figure, the first 20 significantly enriched pathways were mainly distributed in Metabolism, Environmental Information Processing and Organismal Systems at KEGG level 1, and Amino acid metabolism, Carbohydrate metabolism and Lipid metabolism at KEGG level 2 (Fig. C). Therefore, these metabolic pathways are important for B. aryabhattai LAD to respond to root secretions to resist environmental stresses and promote plant growth. Furthermore, the differentially expressed metabolites and all transcripts were simultaneously mapped to the KEGG pathway database, and there were 69 relevant metabolic pathways, including 213 genes. The main metabolic pathways included Tryptophan biosynthesis, Tryptophan metabolism, Zeatin synthesis, ABC transport system and Two-component system. Among them, 9 differential genes and 14 differential metabolites were annotated in the Tryptophan Metabolism and Tryptophan Biosynthesis pathways, which are closely related to IAA synthesis. Among them, K03781 (catalase: katE, CAT, catB, srpA), KO00453 (tryptophan 2,3 dioxygenase: TOD2, kynA), K00817 (histidyl-phosphate aminotransferase: hisC), K00891 (manganic acid kinase: aroK, aroL), K03786 (3-dehydroquinate dehydratase II: aroQ, qutE), KO01426 (amidase: amiE), and KO00128 (aldehyde dehydrogenase: ALDH) genes were significantly up-regulated after root secretion treatment; K16901 (monooxygenase), K01696 (tryptophan synthase β-chain: trpB), and K01817 (phosphoribosyl o-aminobenzoate isoform: trpF) were significantly down-regulated after root secretion treatment, and the results of integration of differential genes and differential metabolites related to IAA synthesis are shown in Fig. . Changes in the expression of genes related to IAA synthesis in B. aryabhattai LAD and maize roots The expression changes of IAA synthesis related genes YUC , GH3 and PIN genes in maize roots under the condition of interaction with B. aryabhattai LAD are shown in the Fig. A. Among them, YUC gene was up-regulated on the 6d and 9d, and down-regulated on the 12d. The GH3 gene was down-regulated on 6d and day 9d, and the GH3 gene began to be up-regulated on 12d. PIN gene showed an upward trend at 6,9 and 12 d. The changes in the expression of antioxidant genes POD, SDO and CAT genes in maize roots showed that the expression of antioxidant-related genes decreased gradually on the 6d, 9d and 12d after adding B. aryabhattai LAD to maize roots (Fig. B). In the B. aryabhattai LAD strain, both root secretion and hydrogen peroxide treatments up-regulated the amiE and ALDH genes (Fig. C). The amiE gene was significantly up-regulated by root secretion, and the strain was induced by hydrogen peroxide to synthesize more growth hormone by up-regulating the transcript level of ALDH gene.
B. aryabhattai LAD and IAA on the growth of maize roots The results of root development of maize seedlings under different treatment conditions measured by root analyzer are shown in Fig. and Table . The main root length of maize seedlings increased by 197% and 167% respectively after exogenous addition of B. aryabhattai LAD and IAA. The main root thickness increased by 22% and 16% respectively, and the seedling length of maize seedlings increased by 107% and 78% respectively. Exogenous addition of B. aryabhattai LAD and IAA increased root surface area by 89% and 61%, root volume by 75% and 34%, and total root length by 97% and 63%, respectively. Exogenous addition of B. aryabhattai LAD and direct exogenous addition of IAA with the same content could promote the growth of maize seedlings, but the growth of maize roots in the exogenous addition of B. aryabhattai LAD group was significantly higher than that in the IAA group with the same concentration.
2 O 2 addition on the growth and IAA production of B. aryabhattai LAD The effects of root secretion and H 2 O 2 addition on the growth of B. aryabhattai LAD and its IAA production are shown in Fig. A, B. The growth of B. aryabhattai LAD was strongly inhibited by the addition of H 2 O 2 treatment, and its level of IAA production was significantly lower than that of the control group, and the levels of IAA synthesized after the addition of 0.1%, 0.2%, and 0.4% of H 2 O 2 to the B. aryabhattai LAD culture for 72 h were 15.1, 17.5, and 15.8 µg/mL, respectively, while the growth inhibition of B. aryabhattai LAD was strongly alleviated after the addition of IAA to its culture. Subsequently, the growth of B. aryabhattai LAD was also inhibited by the addition of root secretion, but the level of IAA production was significantly higher than that of the control group and the other treatment groups, and the levels of IAA synthesized after 72 h of incubation of B. aryabhattai LAD with 1%, 2%, and 4% of root secretion were 26.7, 24.2, and 23.4 µg/mL, respectively.
B. aryabhattai LAD and maize roots The ROS levels in the roots of maize at different times are shown in Fig. C, and the ROS levels were determined by taking the maize roots on the third day from the start of the submerged seed culture, and both the control group and the treatment group showed a trend of increasing and then decreasing, and the ROS levels of the maize roots were significantly higher than those of the control group after the addition of the B. aryabhattai LAD treatment. The ROS levels of B. aryabhattai LAD strains at different culture stages were shown in Fig. D, which combined with the B. aryabhattai LAD growth curve showed that the intracellular ROS in the culture to 2 h, the concentration of the bacteria was small, and the difference of its intracellular ROS levels was not significant, after 2 h, the bacteria multiplied a lot and entered into the logarithmic growth period, and the ROS levels in the control group began to be significantly higher than that of the treatment group, and by 8 h, the growth of the strains began to slow down, and the ROS levels in the treatment group began to decrease and the control group was still at a high level.
To identify DEGs in B. aryabhattai LAD under maize root secretion treatment conditions, we constructed 6 cDNA libraries and filtered the sequencing data of transcriptome samples to obtain a total of 17.71 Gb of data. Gene expression was differentially analyzed using DESeq, and the threshold for identifying DEGs was set at |log 2 (fold change)| ≥ 1, padj ≤ 0.05. Compared with the control group, there were 93 DEGs in B. aryabhattai LAD under root secretion treatment conditions, of which 57 genes were up-regulated and 36 genes were down-regulated . Subsequently, we performed GO and KEGG enrichment analysis to further understand the biological functions of these DEGs and the related biological processes involved. As shown in Fig. A, in terms of GO enrichment analysis, the DEGs of B. aryabhattai LAD under root secretions treatment were mainly enriched in molecular functions (MF) and biological processes (BP). The top three GO terms significantly enriched in the MF category were phosphoribosylformylglycinamidine synthase activity (GO:0004642), carbon-nitrogen ligase activity, with glutamine as amido-N-donor (GO:0016884), ligase activity, forming carbon-nitrogen bonds (GO:0016879). In the BP category, the top three GOs significantly enriched were phospholipid catabolic process (GO:0009395), urea cycle (GO:000050), and urea metabolic process (GO:0019627). KEGG enrichment analysis showed (Fig. B) that the top 20 significantly enriched pathways of DEGs in B. aryabhattai LAD under root secretion treatment conditions were mainly associated with Metabolism, Genetic Information Processing, Environmental Information Processing in KEGG level 1 and Purine metabolism (ko00230), Inositol phosphate metabolism (ko00562), Alanine, aspartate and glutamate metabolism (ko00250), Glycerophospholipid metabolism (ko00564), ABC transporters (ko02010), Tyrosine metabolism (ko00350), Lysine degradation (ko00310), Oxidative phosphorylation (ko00190) Glycolysis / Gluconeogenesis (ko00010), Pyruvate metabolism (ko00620) in KEGG level 2. These results may be importantly related to the promotion of maize growth and resistance to environmental stresses by B. aryabhattai LAD.
In order to evaluate the changes of intracellular metabolism of B. aryabhattai LAD after root secretions treatment, LC-MS / MS was used to evaluate the metabolic profile. The results showed that a total of 1,572 metabolites were identified based on the MS2 spectral database. The identified metabolites were classified according to chemical classification statistics, including 82 classifications, of which Carboxylic acids and derivatives were up to 361. Secondly, there are 113 Steroids and steroid derivatives, 105 Benzene and substituted derivatives, 105 Fatty Acyls, 105 Prenol lipids, 94 Organooxygen compounds, 46 Indoles and derivatives, 45 Glycerophospholipids and 30 Organonitrogens ( Fig. A ). At a threshold setting of VIP ≥ 1, fold change ≥ 1.5 or ≤ 0.667, and p ≤ 0.05, a total of 1,574 metabolites were detected in the treatment and control groups, of which 967 were detected in the positive ion mode and 607 were detected in the negative ion mode. Differential analysis of the detected metabolites showed a total of 45 differential metabolites, of which 8 differential metabolites were up-regulated and 37 differential metabolites were down-regulated (Fig. B). Subsequently, we performed KEGG enrichment analysis to better understand the biological functions of these differential metabolites and their involvement in relevant biological processes. The results showed that a total of 87 KEGG pathways were enriched by differential metabolites under root secretion treatment conditions. As shown in the figure, the first 20 significantly enriched pathways were mainly distributed in Metabolism, Environmental Information Processing and Organismal Systems at KEGG level 1, and Amino acid metabolism, Carbohydrate metabolism and Lipid metabolism at KEGG level 2 (Fig. C). Therefore, these metabolic pathways are important for B. aryabhattai LAD to respond to root secretions to resist environmental stresses and promote plant growth. Furthermore, the differentially expressed metabolites and all transcripts were simultaneously mapped to the KEGG pathway database, and there were 69 relevant metabolic pathways, including 213 genes. The main metabolic pathways included Tryptophan biosynthesis, Tryptophan metabolism, Zeatin synthesis, ABC transport system and Two-component system. Among them, 9 differential genes and 14 differential metabolites were annotated in the Tryptophan Metabolism and Tryptophan Biosynthesis pathways, which are closely related to IAA synthesis. Among them, K03781 (catalase: katE, CAT, catB, srpA), KO00453 (tryptophan 2,3 dioxygenase: TOD2, kynA), K00817 (histidyl-phosphate aminotransferase: hisC), K00891 (manganic acid kinase: aroK, aroL), K03786 (3-dehydroquinate dehydratase II: aroQ, qutE), KO01426 (amidase: amiE), and KO00128 (aldehyde dehydrogenase: ALDH) genes were significantly up-regulated after root secretion treatment; K16901 (monooxygenase), K01696 (tryptophan synthase β-chain: trpB), and K01817 (phosphoribosyl o-aminobenzoate isoform: trpF) were significantly down-regulated after root secretion treatment, and the results of integration of differential genes and differential metabolites related to IAA synthesis are shown in Fig. .
B. aryabhattai LAD and maize roots The expression changes of IAA synthesis related genes YUC , GH3 and PIN genes in maize roots under the condition of interaction with B. aryabhattai LAD are shown in the Fig. A. Among them, YUC gene was up-regulated on the 6d and 9d, and down-regulated on the 12d. The GH3 gene was down-regulated on 6d and day 9d, and the GH3 gene began to be up-regulated on 12d. PIN gene showed an upward trend at 6,9 and 12 d. The changes in the expression of antioxidant genes POD, SDO and CAT genes in maize roots showed that the expression of antioxidant-related genes decreased gradually on the 6d, 9d and 12d after adding B. aryabhattai LAD to maize roots (Fig. B). In the B. aryabhattai LAD strain, both root secretion and hydrogen peroxide treatments up-regulated the amiE and ALDH genes (Fig. C). The amiE gene was significantly up-regulated by root secretion, and the strain was induced by hydrogen peroxide to synthesize more growth hormone by up-regulating the transcript level of ALDH gene.
Our results indicate that there is a feedback loop between the plant immune system and bacterial auxin synthesis (Fig. ). When bacteria colonize the roots of plants, they will trigger the immune response of plants and the production of ROS, while ROS in turn will induce bacteria to synthesize auxin to reduce the toxicity of ROS to cells. At the same time, it promotes the spread of bacteria on roots and the formation of colonies, induces the expression of immune receptors in plants, and further accelerates the feedback loop . Moreover, auxin, as an important plant hormone, plays a vital role in plant development . Many bacterial species, such as Agrobacterium tumefaciens and Pseudomonas syringae , can control plant growth by synthesizing and secreting auxin . However, despite decades of research on the production of bacterial auxin and its effects on plants, little is known about the role of bacterial auxin in bacterial physiology and its interaction with plants. In this study, we found that when B. aryabhattai LAD responded to maize root secretions, the root secretion produced a stress response to B. aryabhattai LAD resulting in a significant increase in intracellular ROS levels, which acted as a feedback to regulate B. aryabhattai LAD intracellularly to respond to this stress effect, such as the increase in the synthesis of IAA production, while amino acid metabolism, carbohydrate metabolism and lipid metabolism pathways were significantly enriched. Free amino acids, carbohydrates and lipids are important regulators of cellular responses to environmental stresses and promote plant growth . The joint analysis showed that tryptophan synthesis, tryptophan metabolism, glutamate metabolism, cysteine metabolism, glycine metabolism and glutathione metabolism were significantly enriched in amino acid metabolic pathways and metabolites such as glutathione were significantly accumulated. Tryptophan synthesis and tryptophan metabolism are the main metabolic pathways for IAA synthesis. When B. aryabhattai LAD feels environmental stress, cells act as a feedback effect to activate IAA synthesis-related pathways to synthesize IAA to help cells resist environmental stress and promote plant growth. In the B. aryabhattai LAD tryptophan metabolic pathway, the tryptophan content was significantly elevated and the amiE gene transcript level was significantly up-regulated. Under the action of amiE, indoleacetamide was converted to indoleacetic acid, which in turn was secreted extracellularly through the ABC transport system and was absorbed and utilized by plants. In addition, the enrichment of glutamate metabolism, cysteine metabolism, and glycine metabolism may be mainly used for the synthesis of glutathione, because glutathione, as a substance possessing an extremely strong antioxidant capacity to scavenge ROS, inhibit the formation of free radicals, and lipid peroxidation, helps the B. aryabhattai LAD to play an important role in regulating the intracellular ROS in the event of environmental stress . In carbohydrate metabolism, glycolysis and gluconeogenesis, fructose and mannose metabolism, galactose metabolism, starch and sucrose metabolism, glyoxylate and dicarboxylic acid metabolism, oxidative phosphorylation and other metabolic pathways were significantly enriched, among which glucose, fructose, UDP-D-G, NAD and so on were significantly accumulated. As energy substances of cells, on the one hand, they provide energy sources for their own growth to accelerate cell metabolism, on the other hand, they can help cells improve their ability to resist osmotic stress and help cells resist environmental stress . Moreover, it is worth noting that glyoxalate and dicarboxylic acid metabolism were also significantly enriched in B. aryabhattai LAD, and the antioxidant enzyme CAT was significantly up-regulated. Previous studies have shown that the glyoxylate cycle plays an important role in stress defense and resistance to environmental stress, especially when some bacteria activate the glyoxylate cycle to help cells resist environmental stress and activate related antioxidant enzyme systems to scavenge the toxic effects of ROS on the cells when they are subjected to environmental stress . Furthermore, inositol is also significantly accumulated in B. aryabhattai LAD, which is involved in a variety of physiological and biochemical processes as a precursor of many important metabolites. Cells resist the stress response produced by plant roots to maintain their own growth by up-regulating inositol . In the lipid metabolism pathway, the metabolic pathways related to glycerol synthesis were also significantly enriched, including glycerolipid metabolism and glycerol phospholipid metabolism, and the accumulation of lipids such as glycerol was significantly increased. It can not only help B. aryabhattai LAD resist the stress effect of plant roots, but also provide substrates and energy for other metabolic pathways, and improve the antioxidant capacity of cells in an indirect way. The cross-talk between auxin and ROS has been increasingly emphasized. On the one hand, stress treatments cause an increase in ROS in the plant, which in turn regulates the activity of the root zone by controlling the accumulation of auxin; on the other hand, auxin can also reduce the redox state in the cell by modulating the activity of scavenging enzymes in vivo, which can alter the growth and development of the plant. In addition, ROS produced by plant roots also activates the immune response of rhizosphere bacteria to synthesize more IAA to further promote plant growth . In this study, it was shown that exogenous addition of B. aryabhattai LAD could significantly promote the growth of maize seedlings. The verification of the expression changes of IAA synthesis-related genes in maize showed that the IAA synthesis-related genes YUC , GH3 and PIN in maize roots were significantly up-regulated. They are closely related to the synthesis of IAA in plants and play an important role in the growth and development of plants , in which the YUC gene was up-regulated on the 6th and 9th days, indicating that IAA was synthesized in large quantities in maize roots at this time, while on the 12 th day, the YUC gene was down-regulated. It may be that the accumulation of IAA in the plant itself reaches a certain level, and the synthesis rate begins to decline. The GH3 gene was down-regulated on the 6th and 9th days, indicating that the IAA metabolism was relatively slow at the accumulation stage. At 12 days, the GH3 gene began to be up-regulated, and the IAA effect of plant roots may be relatively obvious. After exogenous addition of B. aryabhattai LAD, the PIN gene in maize roots mainly controlled IAA transport, and most of its genes were up-regulated in each period to promote maize root development. Together, plants promote their own growth through this ROS-mediated interaction with B. aryabhattai LAD, and plants interact with a wide variety of bacteria in nature. The composition of these microbial populations is affected by microbial diversity, immune system activation, bacteria and other bacteria, fungi and phages. The interaction of other organisms and other factors, understanding each of these components can reasonably manipulate the plant microbiome to benefit plants. Therefore, these results may provide some ideas for understanding microbial-plant interactions and provide a theoretical basis for the development of biofertilizers and sustainable agriculture.
Here, we explored the interaction between B. aryabhattai LAD and maize roots. The results showed that the interaction between auxin-secreting bacteria B. aryabhattai LAD and maize roots promoted their connection with plants to further help plant growth, and found that there was a feedback effect between plant immune system and bacterial auxin. Bacteria activate the immune response of plant roots to produce ROS, which in turn stimulates bacteria to synthesize IAA, and the synthesized IAA further promotes plant growth. This result provides a theoretical basis for exploring the endogenous mechanism of maize development, and also provides a relevant model for exploring the effect of plant-soil microbial interaction on plant defense function and promoting plant growth.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Antimicrobial Resistance in the Context of Animal Production and Meat Products in Poland—A Critical Review and Future Perspective | 19520f23-534d-4d2f-be94-a7cda33ca47f | 11676418 | Microbiology[mh] | Antibiotic resistance is one of the most serious threats to public health worldwide . The development and spread of antibiotic resistance are influenced by a variety of factors, including the misuse and overuse of antibiotics in human medicine, environmental contamination, and agricultural practices. Among these, the use of antibiotics in animal husbandry and meat contamination plays a particularly significant role, as resistant bacteria and resistance genes can infiltrate the food chain and impact human health . It is increasingly shown that one of the key factors leading to this phenomenon is the failure to comply with regulations on the use of antibiotics in animal husbandry (in animals raised for food) . Exceeding permitted doses, the inappropriate use of antibiotics for disease prevention in healthy animals, and the use of drugs critical for the treatment of human infections in livestock farming contribute to the selection of resistant bacteria that can infiltrate the food chain and pose a threat to consumers . Despite the introduction of regulations and recommendations to limit antibiotic use in the animal husbandry sector, significant compliance gaps remain, making it difficult to effectively combat the spread of antibiotic resistance . Antibiotic-resistant microorganisms represent one of the most serious challenges of modern medicine and agriculture . The World Health Organization (WHO) has identified antimicrobial resistance (AMR) as a global health and food security threat, emphasizing the need for a “One Health” approach that integrates human, animal, and environmental health strategies . The ability of bacteria to develop resistance to antimicrobial drugs is becoming increasingly widespread, and it affects not only the treatment of infections in humans but also the food sector . Meat and meat products can be a reservoir of antibiotic-resistant pathogens, raising concerns for public health and the effectiveness of treating infectious diseases . As one of the important meat producers in Europe, Poland faces the challenge of monitoring and controlling microbial resistance in the meat sector . Resistance to drugs such as ampicillin, tetracycline, or gentamicin has been observed in numerous bacterial isolates ( Escherichia coli , Staphylococcus spp., Enterococcus spp., Klebsiella pneumoniae , and Citrobacter spp.) . The main factors contributing to the spread of antimicrobial resistance in foods of animal origin, with a particular focus on meat and meat products, are the inappropriate and excessive use of antimicrobials . In practice, about 80% of globally produced antibiotics are used in animal production; however, some that are classified as antibiotics have other purposes in animal production than for treating diseases. Some farmers use subtherapeutic doses of antibiotics to obtain various aims such as animal growth increase, weight gain acceleration, digestion improvement, a higher feed conversion ratio (FCR) and to prevent or reduce disease outbreaks . Residues of veterinary medicines may be present in food of animal origin (ASF) even if their use is fully regulated by law . However, some farmers do not pay sufficient attention to withdrawal periods (WDPs) which increases the risk of spreading antimicrobial resistance in food worldwide, especially in developing countries . The European Medicines Agency (EMA) defines a Maximum Residue Limit (MRL) as an acceptable concentration of residues in food products, and the European Union requires that foods do not contain residues of veterinary medicines above the MRL. The European Union (EU) legally requires that foods like meat, milk, or eggs not contain residue levels of veterinary medicines or biocidal products that could endanger the consumer’s health. Regulation (EC) No 470/2009 of the European Parliament and of the Council defines rules for setting maximum permissible levels (MRLs), measured in milligrams per kilogram for solid products and milligrams per liter for liquids . Antibiotics can accumulate in tissues such as muscles and organs, and their residues act as selection factors that promote the development of resistance in the microorganisms present . Antibiotic residues in muscles post-mortem represent a selection stress that allows only those bacteria with appropriate resistance mechanisms (including enzymatic degradation of the antibiotic, modification of the antibiotic’s target site, or active removal of the substance from the cell) to survive . Such strains not only survive but can also transfer resistance genes to other bacteria through a process of horizontal gene transfer . This requires the interaction of regulatory authorities in monitoring and enforcement and using accurate analytical methods to detect AMR in meat products . The use of antimicrobials in animal husbandry is inevitable . AMR bacteria are frequently detected in meat and meat products, which results from the use of antibiotics during the treatment of sick animals or the preventive treatment of healthy ones . Among pharmaceutical residues, the most common are antibiotics and anthelmintic agents, with antibiotics being the most extensively used in both human and veterinary medicine . Due to health concerns, antibiotics for food preservation have been banned in many countries . This review aims to critically discuss the available literature, based on an expert analysis of the topic of antimicrobial resistance in microorganisms isolated from meat and meat products in Poland, as well as the use of antimicrobial agents in animal production in this country. The review focuses on the main factors contributing to the spreading of antibiotic resistance, such as the excessive and improper use of antimicrobial agents in animal husbandry. It also discusses the legal regulations regarding veterinary drug residues in animal-derived food products, as well as the importance of monitoring and enforcing these regulations to protect public health. The study aims to highlight the risks associated with antimicrobial resistance in meat and meat products and the need for further research and monitoring in this area. 2.1. Importance of Antibiotic Use in Livestock Production Animal husbandry is of considerable importance in agriculture in countries of the European Union. Obtaining the best results from animal husbandry depends primarily on the use of high-quality feed . Ensuring the free circulation of safe and valuable food and feed products is a key element of the internal market, which has a significant impact on consumer health and satisfaction . The use of antibiotics is inextricably linked to obtaining the best results from animal husbandry . Most of the residues of these agents are found in various food products—both of animal and plant origin . Humans can come into contact with antibiotics from two main sources: firstly, from medicines prescribed by doctors, and secondly, from substances used in animal husbandry . These antibiotics can cause serious health problems in humans, which has prompted the introduction of maximum residue limits in food safety legislation. The most important factor contributing to the presence of antibiotics in food is their overuse (including overdosing and ignoring the withdrawal period), as well as the use of antibiotic-contaminated water and improper disposal of animal manure . The use of antibiotics in animal feed for growth promotion became more prominent in the 1950s and 1960s, when various antibiotics with different mechanisms of action were introduced into animal feed. Supplementation of animal feed with antibiotics and antibiotic growth promoters (AGPs) continued until public health concerns arose about off-target drug levels in meat and animal products, increased antimicrobial resistance, intestinal dysbiosis, etc. . Based on the results of studies showing an increase in the number of resistant bacteria under the influence of the cessation of AGP use in various countries, the European Union banned the use of antibiotic growth promoters in all Member States as of 1 January 2006 (Regulation (EC) No 1831/2003) . As of that year, antibiotics in animal husbandry must be used for therapeutic purposes. The cost of producing medicated feed is high, and meeting veterinary requirements is difficult for small- and medium-sized farms, which can lead to non-compliance . Pharmaceutical and veterinary control often lack the tools to prevent illegal trade in veterinary medicines . A monitoring carried out in Poland showed that antibiotics were used in animal farms, especially on turkey and broiler farms. The monitoring results indicated legitimate concerns about the impact on public health now and in the future . 2.2. Challenges of Antibiotic Use The main purpose of antimicrobial use is to control and treat bacterial infections. Antibiotics are administered to symptomatic animals, and the agent dose is adjusted according to their condition. Among farm animals, individual treatment is used for dairy cows and calves . It should be noted that such treatment is ineffective for animals in large flocks, e.g., more than 30,000 poultry or 100 piglets . Antimicrobials are administered to the whole herd for large groups of animals when individual animals show signs of disease. This is known as metaphylaxis . Early treatment of the entire herd reduces the number of sick or dead animals and lowers the use of antibiotics, resulting in lower treatment costs . The prophylactic use of antibiotics is a way of preventing possible infections to which animals are exposed . In this case, agents are administered to individuals or the entire herd when there are no clinical signs of disease, but there is a high probability of infection . Antibiotics are also administered prophylactically at so-called critical moments for the animals, e.g., when mixing animals from different herds, transport, or at the end of lactation of dairy cows . AGPs were another way of using antibiotics in animal production . However, the use of antimicrobial substances in animal husbandry was banned by law in 2006 . The effect of growth promoters was not only to increase weight gain (by 4–28%) but also to improve nutrient absorption, leading to more efficient feed conversion (by 0.8–7.6%) . In addition, there were also reductions in methane and ammonia emissions and more efficient phosphorus utilization . In addition, the use of AGPs reduced the number of sick animals and livestock losses . The use of such agents prevented gastrointestinal infections and maintained the balance of the intestinal microflora . 2.3. Antibiotic Use in Poland The use of antibiotics in livestock production is a globally important issue, and the challenges of monitoring and reducing their use have been repeatedly highlighted in the literature. Pyzik et al. note the lack of global reporting systems for antibiotic use and call for mandatory reporting in every country, not just in Europe. There is also a need to implement monitoring procedures, more effective biosecurity, better governance, and educational efforts targeting groups such as food producers and growers to raise awareness of the risks of antibiotic use. In Poland, as the report of the Supreme Chamber of Control (NIK) indicates, the use of antibiotics in livestock production is widespread, and supervision proves ineffective. For example, in the Lubuskie Voivodeship, as many as 70% of farmers on monitored farms used antibiotics, always justifying their use for therapeutic reasons. However, the NIK points to the lack of full documentation of treatment and weaknesses in the surveillance system, which often relies on breeders’ statements. The scale of the use of antibiotics remains unknown, although data show a 23% increase in their sale between 2011 and 2015. The NIK recommends making reporting mandatory, creating a nationwide database and implementing educational programs for breeders to better control the situation and counter antibiotic resistance. A report by the European Medicines Agency (EMA) shows that although Poland has seen a decline in sales of veterinary antibiotics, their use per kilogram of body weight of production animals still exceeds the EU average. The most-used classes of antibiotics in Poland are tetracyclines, penicillins, and sulfonamides, and the use of critically important antibiotics for human medicine has been limited. Programs being implemented, such as the National Program for the Protection of Antibiotics, aim to rationalize their use and educate farmers and veterinarians. Despite progress, continuing to reduce the use of these agents, especially those critical to human health, remains a challenge. The World Health Organization (WHO) reports that some 27 different antimicrobials are used in animals, including critically important macrolides, ketolides, glycopeptides, quinolones, polymyxins, and cephalosporins (third and fourth generation) for human medicine. The lack of a global surveillance system for the use of antibiotics in the livestock sector is a major gap. In human medicine, the Global Antimicrobial Surveillance System (GLASS) has been implemented to collect and analyze antibiotic resistance data. An analogous system is lacking in the animal sector, although the Scandinavian countries that have implemented advanced monitoring systems can serve as an example of good practice. In low- and middle-income countries, this surveillance is only just developing, with global resistance trends mapped mainly by point prevalence surveys . Studies have shown that between 2000 and 2018, resistance levels increased in chickens and pigs, while stabilizing in cattle, with significant geographic differences . These data underscore the urgent need for global action to reduce antibiotic use in animal husbandry, implement more effective surveillance mechanisms, and promote the rational use of antimicrobials in animal production. Animal husbandry is of considerable importance in agriculture in countries of the European Union. Obtaining the best results from animal husbandry depends primarily on the use of high-quality feed . Ensuring the free circulation of safe and valuable food and feed products is a key element of the internal market, which has a significant impact on consumer health and satisfaction . The use of antibiotics is inextricably linked to obtaining the best results from animal husbandry . Most of the residues of these agents are found in various food products—both of animal and plant origin . Humans can come into contact with antibiotics from two main sources: firstly, from medicines prescribed by doctors, and secondly, from substances used in animal husbandry . These antibiotics can cause serious health problems in humans, which has prompted the introduction of maximum residue limits in food safety legislation. The most important factor contributing to the presence of antibiotics in food is their overuse (including overdosing and ignoring the withdrawal period), as well as the use of antibiotic-contaminated water and improper disposal of animal manure . The use of antibiotics in animal feed for growth promotion became more prominent in the 1950s and 1960s, when various antibiotics with different mechanisms of action were introduced into animal feed. Supplementation of animal feed with antibiotics and antibiotic growth promoters (AGPs) continued until public health concerns arose about off-target drug levels in meat and animal products, increased antimicrobial resistance, intestinal dysbiosis, etc. . Based on the results of studies showing an increase in the number of resistant bacteria under the influence of the cessation of AGP use in various countries, the European Union banned the use of antibiotic growth promoters in all Member States as of 1 January 2006 (Regulation (EC) No 1831/2003) . As of that year, antibiotics in animal husbandry must be used for therapeutic purposes. The cost of producing medicated feed is high, and meeting veterinary requirements is difficult for small- and medium-sized farms, which can lead to non-compliance . Pharmaceutical and veterinary control often lack the tools to prevent illegal trade in veterinary medicines . A monitoring carried out in Poland showed that antibiotics were used in animal farms, especially on turkey and broiler farms. The monitoring results indicated legitimate concerns about the impact on public health now and in the future . The main purpose of antimicrobial use is to control and treat bacterial infections. Antibiotics are administered to symptomatic animals, and the agent dose is adjusted according to their condition. Among farm animals, individual treatment is used for dairy cows and calves . It should be noted that such treatment is ineffective for animals in large flocks, e.g., more than 30,000 poultry or 100 piglets . Antimicrobials are administered to the whole herd for large groups of animals when individual animals show signs of disease. This is known as metaphylaxis . Early treatment of the entire herd reduces the number of sick or dead animals and lowers the use of antibiotics, resulting in lower treatment costs . The prophylactic use of antibiotics is a way of preventing possible infections to which animals are exposed . In this case, agents are administered to individuals or the entire herd when there are no clinical signs of disease, but there is a high probability of infection . Antibiotics are also administered prophylactically at so-called critical moments for the animals, e.g., when mixing animals from different herds, transport, or at the end of lactation of dairy cows . AGPs were another way of using antibiotics in animal production . However, the use of antimicrobial substances in animal husbandry was banned by law in 2006 . The effect of growth promoters was not only to increase weight gain (by 4–28%) but also to improve nutrient absorption, leading to more efficient feed conversion (by 0.8–7.6%) . In addition, there were also reductions in methane and ammonia emissions and more efficient phosphorus utilization . In addition, the use of AGPs reduced the number of sick animals and livestock losses . The use of such agents prevented gastrointestinal infections and maintained the balance of the intestinal microflora . The use of antibiotics in livestock production is a globally important issue, and the challenges of monitoring and reducing their use have been repeatedly highlighted in the literature. Pyzik et al. note the lack of global reporting systems for antibiotic use and call for mandatory reporting in every country, not just in Europe. There is also a need to implement monitoring procedures, more effective biosecurity, better governance, and educational efforts targeting groups such as food producers and growers to raise awareness of the risks of antibiotic use. In Poland, as the report of the Supreme Chamber of Control (NIK) indicates, the use of antibiotics in livestock production is widespread, and supervision proves ineffective. For example, in the Lubuskie Voivodeship, as many as 70% of farmers on monitored farms used antibiotics, always justifying their use for therapeutic reasons. However, the NIK points to the lack of full documentation of treatment and weaknesses in the surveillance system, which often relies on breeders’ statements. The scale of the use of antibiotics remains unknown, although data show a 23% increase in their sale between 2011 and 2015. The NIK recommends making reporting mandatory, creating a nationwide database and implementing educational programs for breeders to better control the situation and counter antibiotic resistance. A report by the European Medicines Agency (EMA) shows that although Poland has seen a decline in sales of veterinary antibiotics, their use per kilogram of body weight of production animals still exceeds the EU average. The most-used classes of antibiotics in Poland are tetracyclines, penicillins, and sulfonamides, and the use of critically important antibiotics for human medicine has been limited. Programs being implemented, such as the National Program for the Protection of Antibiotics, aim to rationalize their use and educate farmers and veterinarians. Despite progress, continuing to reduce the use of these agents, especially those critical to human health, remains a challenge. The World Health Organization (WHO) reports that some 27 different antimicrobials are used in animals, including critically important macrolides, ketolides, glycopeptides, quinolones, polymyxins, and cephalosporins (third and fourth generation) for human medicine. The lack of a global surveillance system for the use of antibiotics in the livestock sector is a major gap. In human medicine, the Global Antimicrobial Surveillance System (GLASS) has been implemented to collect and analyze antibiotic resistance data. An analogous system is lacking in the animal sector, although the Scandinavian countries that have implemented advanced monitoring systems can serve as an example of good practice. In low- and middle-income countries, this surveillance is only just developing, with global resistance trends mapped mainly by point prevalence surveys . Studies have shown that between 2000 and 2018, resistance levels increased in chickens and pigs, while stabilizing in cattle, with significant geographic differences . These data underscore the urgent need for global action to reduce antibiotic use in animal husbandry, implement more effective surveillance mechanisms, and promote the rational use of antimicrobials in animal production. Modern consumers pay attention to the health-promoting properties of food. Meat and meat products are perceived as a source of protein, vitamins, and minerals . Meat is also a source of bioactive compounds such as L-carnitine, taurine, anserine, carnosine, coenzyme Q10, glutathione, bioactive peptides, isomers of linoleic acid (CLA), creatin, and haem iron . In addition to compounds essential for supporting human health, meat may contain drug residues. They result from the inappropriate use of veterinary medicines and the failure to comply with the withdrawal period . This, in turn, can significantly reduce the quality and safety of meat and meat products, which is a major challenge in the context of producing healthy and safe food . Most raw materials of animal origin undergo heat treatment or other processing methods before being consumed. The purpose of these is, among other things, to increase digestibility, improve sensory properties and ensure food safety—by eliminating pathogens . Heat treatment of meat also reduces the concentration of drug residues through protein denaturation, loss of water and fat, and a change in pH . For example, the concentration of doxycycline in meat decreases during cooking, and the residues are excreted from the muscle with cooking loss . Different food processing techniques affect changes in antibiotic content (degree of reduction) in various ways, which include the type and parameters of processing, the kind of meat, the type of antibiotic, or the initial antibiotic content . Boiling proved to be one of the most effective methods of heat treatment. For poultry boiled at 100 °C for 5 min, the enrofloxacin (ENO) concentration decreased from 746.34 ± 5.62 μg/kg to 237.53 ± 2.13 μg/kg, representing a 68.17% reduction . Similarly, oxytetracycline (OTC) decreased from 824.16 ± 7.20 μg/kg to 383.33 ± 3.70 μg/kg (53.49% reduction), and ciprofloxacin (CIP) dropped from 643.14 ± 6.97 μg/kg to 205.46 ± 9.72 μg/kg, achieving a 68.05% reduction. Prolonged boiling, such as for 15 min, resulted in even greater decreases in antibiotic content. For instance, OTC in pork showed a reduction of 52.69%, with the concentration decreasing to 236.56 ± 7.96 μg/kg . Sulfonamides, including sulfadiazine (SDZ), sulfamethoxazole (SMX), sulfamonomethoxine (SMM), and sulfaquinoxaline (SQ), demonstrated gradual reductions in concentration with extended boiling times. For example, SDZ in poultry boiled at 100 °C for 3 min showed a 40.48% reduction, while a 12 min boiling time resulted in a 60.71% reduction . Roasting was another processing method analyzed. Roasting poultry at 200 °C for 30 min reduced the ENO concentration from 746.34 ± 5.62 μg/kg to 233.23 ± 10.19 μg/kg, corresponding to a 68.75% reduction . Similarly, CIP levels dropped from 643.14 ± 6.97 μg/kg to 200.98 ± 10.02 μg/kg, also achieving a 68.75% reduction. However, roasting at lower temperatures (170 °C) for varying durations was less effective in reducing sulfonamide levels. For instance, roasting for 6 min reduced SQ by 21.66%, while roasting for 12 min achieved a 37.73% reduction. Microwave cooking showed high effectiveness, particularly at higher power levels and longer cooking times. Cooking poultry in a microwave at 900 W for 3 min reduced OTC levels from 824.16 ± 7.20 μg/kg to 227.67 ± 2.10 μg/kg, corresponding to a 72.38% reduction . CIP levels decreased by 55.16%, reaching 288.40 ± 3.23 μg/kg. Shorter microwave times and lower power settings (440 W for 45 s) were less effective but still resulted in notable reductions. For instance, tetracycline (TET) levels in poultry decreased by 59.89%, while in pork, the reduction reached 80.54% . The data suggest a clear correlation between the intensity of microwave processing and the effectiveness of antibiotic reduction. Grilling, despite utilizing high temperatures, was less effective than other methods. For poultry grilled at 8 kW for 2.5 min, ENO levels decreased by only 33.33%, while OTC levels dropped by just 16.67% . Reductions for CIP and doxycycline (DOX) were similarly modest, at approximately 16.66–16.67%. This suggests that the short duration of grilling, combined with high intensity, resulted in less degradation of antibiotic residues compared to longer and more evenly distributed heating processes. The analysis of the data indicates that the effectiveness of antibiotic reduction in meat depends on the processing method, the duration of the process, and the type of antibiotic. Boiling and microwave cooking were the most effective methods, with longer durations and higher intensities achieving reductions of over 70%. Roasting and grilling, despite employing high temperatures, were less effective, particularly for shorter durations. Additionally, studies reveal that while thermal processing reduces antibiotic residues, it may lead to the formation of degradation products with potential health implications. For example, Gratacós-Cubarsí et al. observed that tetracyclines in poultry and pork degrade under heat, forming anhydrotetracyclines, which retain some biological activity. Nguyen et al. highlighted the toxic potential of oxytetracycline degradation products in animal models, and Furusawa and Hanabusa found that cooking significantly reduces sulfonamide levels, though complete elimination remains challenging. These findings emphasize the dual role of food processing in reducing antibiotics and potentially generating bioactive or toxic degradation products, underlining the need for further research to optimize processing techniques and assess their implications for consumer safety. The presence of drug residues in meat might cause a serious problem in the production of fermented meat products since the components of industrial starter cultures for fermented meat products might be susceptible to antibiotic residues. In this case, a fermentation process might be disrupted or altered, which not only results in obtaining meat products with changed sensory properties but also poses a risk to public health. Previous studies by Darwish et al. and Moyane et al. showed that the altered fermentation process caused an outbreak of foodborne illness as pathogens present in the raw material persisted after poor fermentation. According to a study by Kjeldgaarda et al. , it appears that the permitted levels of antibiotics in meat can negatively affect the fermentation process. They showed that bacteria used as starter cultures are susceptible to antibiotic residues, even at levels close to those allowed by law, which can lead to the presence of pathogens in processed sausages. Their findings suggest that such residues could be the cause of disease outbreaks associated with the consumption of fermented meat products, providing an argument for reducing the use of antibiotics in animal husbandry . Studies presented here show that the choice of heat treatment method plays a key role in reducing antibiotic residues in meat products, which is directly relevant to food safety and public health. Antibiotic resistance among pathogenic bacteria increases morbidity and mortality and is therefore a challenge worldwide . Of particular concern is the emergence of multidrug resistance . The scale of antibiotic-resistant bacteria in the environment of animal farms observed worldwide today is a consequence of the widespread use of antibiotics at least a decade earlier . Very often, the same antibiotics that were used in agriculture and veterinary medicine were also used to treat humans. For therapeutic purposes, they should only be administered to animals with a confirmed infection . However, it is common practice to administer antibiotics to the whole herd by giving prophylactic doses of antibiotics in poultry, cattle, and pig farming, which are much higher than those used for therapeutic purposes . The Chief Veterinary Inspectorate has been monitoring the drug resistance of zoonotic bacteria in Poland since 2014, and the results show an increase in the drug resistance of microorganisms. Intensive agriculture has a high level of pollutants emitted into the environment, such as air, soil, surface, and rainwater . The use of manure as a fertilizer carries the risk of environmental contamination by pathogens, antibiotics, and antibiotic-resistant pathogens . summarizes the main causes of antibiotic resistance, such as overuse of antibiotics in agriculture, poor veterinary practices, and environmental pollution. It also outlines the health, economic, and environmental implications of resistance, and emphasizes the importance of regulation and preventive measures such as bioassurance programs, vaccination, and One Health approach initiatives. 4.1. Regulations in Antibiotic Use The European Medicines Agency sets maximum residue limits and requires that food not contain harmful amounts of veterinary medicines. Illegal practices, such as off-label use of approved drugs, also contribute to the problem . The use of antibiotics in veterinary medicine has been uncontrolled, but legislation is now being introduced to regulate the practice . However, it is difficult to assess practice on animal farms in Poland due to inconsistencies between reports of antibiotic use and the surveillance system for these drugs . In Poland, one of the laws regulating medicinal products, including antibiotics, is the Act of 6 September 2001 on Pharmaceutical Law. It defines the use of medicinal products in humans and animals, establishes rules for the production and authorization of medicines, and regulates the conduct of clinical trials . The Act of 11 March 2004 on the protection of animal health and the control of infectious animal diseases imposes an obligation on veterinarians to keep veterinary medical records of the treatment carried out. Regulation (EU) 2019/6 of the European Parliament and of the Council of 11 December 2018 on veterinary medicinal products , repealing Directive 2001/82/EC, defines the use of antimicrobials in the treatment of animal diseases. The provisions of this regulation entered into force on 28 January 2022. It introduces important requirements for medicinal products for use in animals, aiming to improve public health and animal health, and reduce antibiotic resistance. Most notably, it bans the prophylactic use of antimicrobials in healthy animals (except in exceptional cases), places restrictions on the use of antibiotics important for human treatment, and requires detailed monitoring and reporting of their sale and use. It sets stricter conditions for registration and introduces a single authorization system in the EU market to increase the quality, safety, and availability of medicinal products. Only veterinarians can prescribe medicines for animals, limiting independent use by pet owners. The regulation also promotes research into new, safe medicinal products and tightens import rules to ensure they comply with EU standards. All these regulations are part of the European Union’s strategy for health safety and the fight against antimicrobial resistance . However, none of the above legal requirements prohibit the therapeutic use of antimicrobial substances but only restrict their unjustified use . In the European Union, since January 2006, following Regulation No 1831/2003 of the European Parliament and of the Council of 22 August 2003 , the marketing and use of antibiotics as feed additives have been prohibited. In Poland, veterinarians providing veterinary services are responsible for keeping drug circulation records and veterinary documentation, including prescription medicinal products for use in both livestock and pets . Currently, the use of antibiotics for growth promotion in farm animals and poultry is banned throughout the EU. However, this ban has not significantly reduced the use of antimicrobials, and subtherapeutic use has been replaced by metaphylaxis and prophylaxis . 4.2. Implications of Antibiotic Resistance Antibiotic resistance leads to higher rates of morbidity and mortality, particularly because of infections with multidrug-resistant bacteria . These bacteria are more difficult to treat, resulting in longer hospital stays and an increased risk of complications and deaths . Antibiotic resistance in Poland leads to serious health risks. Another problem is global bacterial resistance, which can lead to ineffective standard antibiotic therapies and higher hospital admissions . The costs associated with antibiotic resistance are enormous, both for healthcare systems and the economy. Inappropriate use of antibiotics in Poland, especially in primary care, leads to high treatment costs for infections caused by resistant bacterial strains. Research shows that the overuse of antibiotics in regions with high levels of unemployment and intensive population mobility contributes to increased resistance and economic burden, including prolonged hospitalization and higher treatment expenditure . The costs associated with treating infections caused by resistant bacteria from food are significant . High levels of antibiotic resistance, especially in egg products, affect consumer health, leading to increased healthcare expenditure, including longer hospital stays and the cost of additional diagnostic tests and treatment . In an economic context, bacterial resistance in the agricultural sector in Poland also leads to losses in agricultural production, as animals infected with resistant bacteria require more complex treatment, which increases the cost of breeding . These costs also include losses associated with product recalls and the costs of monitoring and controlling infections in agricultural production . Combating antibiotic resistance in the food production sector is a complex process that requires cooperation at local and national levels. These costs also extend to the agricultural sector, where the use of antibiotics in animal husbandry leads to production losses due to increasing drug resistance in both humans and animals . Research indicates that vaccines can be an economically viable tool in the fight against antibiotic resistance, reducing the number of cases of resistant infections and reducing the overall need for antibiotics . Antibiotic resistance also has a significant impact on the environment. The use of antibiotics in agriculture and animal husbandry leads to contamination of soil and water, which promotes the spread of resistance genes in the environment . Excessive use of antibiotics in animal husbandry and poor waste management lead to antibiotics and resistant bacteria entering the environment, including soil and groundwater . Studies on isolated strains from food products indicate that resistant bacteria can infiltrate the ecosystem through agricultural and industrial waste, increasing the risk of resistance genes spreading in the environment . Antibiotic resistance in Poland, associated with isolated bacteria from food, is a serious health, economic, and environmental threat. Effective measures are needed to reduce the use of antibiotics in food production and to monitor the spread of resistance. 4.3. Strategies to Prevent Antibiotic Resistance There is a need to integrate water, sanitation, and hygiene (WaSH) programs with biosecurity in animal husbandry. This approach can reduce the transmission of antibiotic-resistant bacteria . Biosequestration and improved hygiene in animal husbandry can significantly reduce the risk of exposure to resistant bacteria, protecting both humans and animals . The One Health approach emphasizes the importance of the interdependence between human, animal, and environmental health . The implementation of integrated measures, such as reducing the overuse of antibiotics and improving sanitation and hygiene in animal husbandry, are key actions in the fight against antibiotic resistance . These programs should be combined with better monitoring and surveillance systems to effectively prevent the further spread of resistant bacteria . Intensive animal husbandry in Poland results in the emission of bioaerosols containing antibiotic-resistant bacteria. These bacteria can enter the environment, threatening the health of humans and animals in the vicinity of farms . Action is needed to reduce the spread of antibiotic-resistant bacteria on farms and in the animal food supply chain . In Poland, monitoring and surveillance of the spread of antibiotic-resistant bacteria in the agricultural environment is insufficient . Studies to date show the presence of antibiotic-resistant bacteria on farms in Poland, but data are limited to individual farms and a small number of samples . Larger surveys and more extensive monitoring programs are needed to better assess the scale of the problem . The European Medicines Agency sets maximum residue limits and requires that food not contain harmful amounts of veterinary medicines. Illegal practices, such as off-label use of approved drugs, also contribute to the problem . The use of antibiotics in veterinary medicine has been uncontrolled, but legislation is now being introduced to regulate the practice . However, it is difficult to assess practice on animal farms in Poland due to inconsistencies between reports of antibiotic use and the surveillance system for these drugs . In Poland, one of the laws regulating medicinal products, including antibiotics, is the Act of 6 September 2001 on Pharmaceutical Law. It defines the use of medicinal products in humans and animals, establishes rules for the production and authorization of medicines, and regulates the conduct of clinical trials . The Act of 11 March 2004 on the protection of animal health and the control of infectious animal diseases imposes an obligation on veterinarians to keep veterinary medical records of the treatment carried out. Regulation (EU) 2019/6 of the European Parliament and of the Council of 11 December 2018 on veterinary medicinal products , repealing Directive 2001/82/EC, defines the use of antimicrobials in the treatment of animal diseases. The provisions of this regulation entered into force on 28 January 2022. It introduces important requirements for medicinal products for use in animals, aiming to improve public health and animal health, and reduce antibiotic resistance. Most notably, it bans the prophylactic use of antimicrobials in healthy animals (except in exceptional cases), places restrictions on the use of antibiotics important for human treatment, and requires detailed monitoring and reporting of their sale and use. It sets stricter conditions for registration and introduces a single authorization system in the EU market to increase the quality, safety, and availability of medicinal products. Only veterinarians can prescribe medicines for animals, limiting independent use by pet owners. The regulation also promotes research into new, safe medicinal products and tightens import rules to ensure they comply with EU standards. All these regulations are part of the European Union’s strategy for health safety and the fight against antimicrobial resistance . However, none of the above legal requirements prohibit the therapeutic use of antimicrobial substances but only restrict their unjustified use . In the European Union, since January 2006, following Regulation No 1831/2003 of the European Parliament and of the Council of 22 August 2003 , the marketing and use of antibiotics as feed additives have been prohibited. In Poland, veterinarians providing veterinary services are responsible for keeping drug circulation records and veterinary documentation, including prescription medicinal products for use in both livestock and pets . Currently, the use of antibiotics for growth promotion in farm animals and poultry is banned throughout the EU. However, this ban has not significantly reduced the use of antimicrobials, and subtherapeutic use has been replaced by metaphylaxis and prophylaxis . Antibiotic resistance leads to higher rates of morbidity and mortality, particularly because of infections with multidrug-resistant bacteria . These bacteria are more difficult to treat, resulting in longer hospital stays and an increased risk of complications and deaths . Antibiotic resistance in Poland leads to serious health risks. Another problem is global bacterial resistance, which can lead to ineffective standard antibiotic therapies and higher hospital admissions . The costs associated with antibiotic resistance are enormous, both for healthcare systems and the economy. Inappropriate use of antibiotics in Poland, especially in primary care, leads to high treatment costs for infections caused by resistant bacterial strains. Research shows that the overuse of antibiotics in regions with high levels of unemployment and intensive population mobility contributes to increased resistance and economic burden, including prolonged hospitalization and higher treatment expenditure . The costs associated with treating infections caused by resistant bacteria from food are significant . High levels of antibiotic resistance, especially in egg products, affect consumer health, leading to increased healthcare expenditure, including longer hospital stays and the cost of additional diagnostic tests and treatment . In an economic context, bacterial resistance in the agricultural sector in Poland also leads to losses in agricultural production, as animals infected with resistant bacteria require more complex treatment, which increases the cost of breeding . These costs also include losses associated with product recalls and the costs of monitoring and controlling infections in agricultural production . Combating antibiotic resistance in the food production sector is a complex process that requires cooperation at local and national levels. These costs also extend to the agricultural sector, where the use of antibiotics in animal husbandry leads to production losses due to increasing drug resistance in both humans and animals . Research indicates that vaccines can be an economically viable tool in the fight against antibiotic resistance, reducing the number of cases of resistant infections and reducing the overall need for antibiotics . Antibiotic resistance also has a significant impact on the environment. The use of antibiotics in agriculture and animal husbandry leads to contamination of soil and water, which promotes the spread of resistance genes in the environment . Excessive use of antibiotics in animal husbandry and poor waste management lead to antibiotics and resistant bacteria entering the environment, including soil and groundwater . Studies on isolated strains from food products indicate that resistant bacteria can infiltrate the ecosystem through agricultural and industrial waste, increasing the risk of resistance genes spreading in the environment . Antibiotic resistance in Poland, associated with isolated bacteria from food, is a serious health, economic, and environmental threat. Effective measures are needed to reduce the use of antibiotics in food production and to monitor the spread of resistance. There is a need to integrate water, sanitation, and hygiene (WaSH) programs with biosecurity in animal husbandry. This approach can reduce the transmission of antibiotic-resistant bacteria . Biosequestration and improved hygiene in animal husbandry can significantly reduce the risk of exposure to resistant bacteria, protecting both humans and animals . The One Health approach emphasizes the importance of the interdependence between human, animal, and environmental health . The implementation of integrated measures, such as reducing the overuse of antibiotics and improving sanitation and hygiene in animal husbandry, are key actions in the fight against antibiotic resistance . These programs should be combined with better monitoring and surveillance systems to effectively prevent the further spread of resistant bacteria . Intensive animal husbandry in Poland results in the emission of bioaerosols containing antibiotic-resistant bacteria. These bacteria can enter the environment, threatening the health of humans and animals in the vicinity of farms . Action is needed to reduce the spread of antibiotic-resistant bacteria on farms and in the animal food supply chain . In Poland, monitoring and surveillance of the spread of antibiotic-resistant bacteria in the agricultural environment is insufficient . Studies to date show the presence of antibiotic-resistant bacteria on farms in Poland, but data are limited to individual farms and a small number of samples . Larger surveys and more extensive monitoring programs are needed to better assess the scale of the problem . Bacteria such as Campylobacter spp., Staphylococcus spp., Enterococcus spp., Listeria monocytogenes , and Enterobacterales (including Salmonella spp. and E. coli ) are found in the animal farm environment and are emitted into the air and surface water, which can cause infections in humans and are a source of antibiotic resistance genes . Many bacteria have evolved multiple mechanisms of antibiotic resistance, including the production of inactivating enzymes, blockade of target sites, alteration in cell membrane permeability, and active efflux of antibiotics from the cell . Bacteria may have resistance genes for many different drugs, as well as transport proteins that can actively pump drugs and substances out of the cell into the external environment . presents the occurrence and antimicrobial resistance of microorganisms isolated from meat and meat products in Poland. 5.1. Campylobacter spp. Campylobacter spp. is a major cause of foodborne illness in humans, which results from improper processing or consumption of undercooked poultry meat . For severe or chronic infections caused by Campylobacter spp., treatment with antibiotics (e.g., fluoroquinolones and macrolides) may be necessary, which is problematic because of the uncontrolled use of these drugs in clinical medicine and animal production . Campylobacter spp. is one of the main causes of foodborne gastroenteritis responsible for zoonosis—campylobacteriosis. Campylobacter , especially Campylobacter jejuni and to a lesser extent Campylobacter coli , is one of the leading causes of foodborne infections worldwide . The main source of infection is contaminated poultry meat , and high contamination poses a threat to public health. It is estimated that 50% to 80% of human campylobacteriosis cases are directly linked to poultry meat, particularly Campylobacter jejuni . In recent years, Campylobacter has been increasing in resistance to antibiotics (especially quinolones and macrolides) due to their widespread use in agriculture . Although campylobacteriosis usually resolves spontaneously, macrolides (erythromycin), fluoroquinolones, and tetracyclines are used in severe cases . Since chickens are the main reservoir of Campylobacter , antibiotic resistance in these bacteria isolated from poultry is of serious concern. The use of antimicrobials in animal production, especially in veterinary medicine, may contribute to the buildup of resistance in human isolates, especially to quinolones . The aim of the study by Woźniak-Biel et al. was to identify Campylobacter strains, isolated from turkeys and chickens, using polymerase chain reaction (PCR) and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) methods, and assess their antibiotic resistance. The results obtained from MALDI-TOF were consistent with those from multiplex PCR. There was 100% resistance to ciprofloxacin in strains from turkeys and chickens, and 58.1% and 78.6% resistance to tetracycline in these groups, respectively. No multidrug-resistant strains were detected, and all ciprofloxacin-resistant strains had a mutation in the gyrA gene at the Thr-86 position. The presence of the tetO gene was present in 71.0% of turkey strains and 100% of chickens, and this gene was also found in five turkey strains and three chickens that were sensitive to tetracycline. The results indicate a high prevalence of Campylobacter strains that are phenotypically and genetically resistant to fluoroquinolones and tetracycline. A study by Maćkiw et al. on the antibiotic resistance of C. jejuni and C. coli strains isolated from food in Poland showed that Campylobacter spp. is often isolated from poultry, which is the main source of human infections with these bacteria. High levels of resistance to fluoroquinolones, including ciprofloxacin, were found, which is in line with trends observed in other European countries. Resistance to tetracyclines was also common, which may be due to the widespread use of these antibiotics in animal husbandry. The tet (O) genes responsible for resistance to tetracyclines and gyrA associated with resistance to fluoroquinolones were identified. Some strains showed resistance to macrolides such as erythromycin, but this was less prevalent compared to fluoroquinolones and tetracyclines. It was also noted that multidrug resistance was relatively common. These results suggest the need to monitor Campylobacter sp. resistance in food to prevent the spread of resistant strains, which can threaten public health. A study by Wieczorek and Osek analyzing the antibiotic resistance of C. jejuni and C. coli strains of poultry carcass samples collected between 2009 and 2013 showed that 54.4% of samples were positive for Campylobacter . Resistance to ciprofloxacin was 81.6%, to tetracycline 56.1%, and only 2.4% of isolates were resistant to erythromycin. In contrast, resistance was higher among C. coli than C. jejuni , and an increase in resistance to ciprofloxacin and tetracycline was noted over the five-year study period. A later study by Wieczorek et al. on the prevalence and antibiotic resistance of Campylobacter strains isolated from chicken carcasses in Poland between 2014 and 2018 reported that 53.4% of samples (in total 2367 samples collected from slaughterhouses across the country) were positive for Campylobacter . Mainly, C. coli (31.2%) and C. jejuni (22.2%) were identified. The strains showed high resistance to ciprofloxacin (93.1%), nalidixic acid (92.3%), and tetracycline (70.9%). Only a small percentage of isolated strains were resistant to erythromycin (4.2%), with C. coli (6.4%) showing more resistance than C. jejuni (1.1%). Multidrug resistance was found in 25.1% of C. coli and 20.6% of C. jejuni strains. The study showed an increase in the percentage of multidrug-resistant strains compared to earlier years, indicating the necessity of taking measures to control Campylobacter at the poultry slaughter stage and restricting the use of antibiotics in poultry production. Rożynek et al. analyzed in detail the emergence of macrolide-resistant Campylobacter strains in poultry meat in Poland and the resistance mechanisms responsible for the problem. Macrolides, such as erythromycin, are key antibiotics used to treat infections caused by these bacteria . The study found a significant number of strains resistant to macrolides, which poses an important therapeutic challenge. The mechanism of resistance to these antibiotics was mainly related to mutations in domain V of the 23S rRNA gene, which encodes the ribosomal subunit responsible for macrolide binding. These mutations, particularly at nucleotide positions 2074 and 2075, lead to a reduced ability of macrolides to inhibit bacterial protein synthesis . Also identified were erm (B) genes that encode methyltransferases, enzymes that modify ribosomes and cause macrolide resistance. In addition, other resistance mechanisms, such as the pumping of antibiotics out of bacterial cells by the efflux pump CmeABC, were also identified as an important factor in the development of resistance. The study also found a link between resistance and intensive antibiotic use in poultry farming, which promotes the selection of resistant strains. The authors emphasize the need to monitor antibiotic resistance and to introduce stricter regulations on the use of macrolides in animal food production to prevent the further spread of resistant strains of Campylobacter spp. Another source of Campylobacter is beef and pork. It was reported that the prevalence of Campylobacter spp. in retail beef products was about 10.0% , whereas its prevalence in beef and pork carcasses was 10.0% and 30.0%, respectively . Antibiotic profiling revealed that Campylobacter isolated from pork and cattle carcasses during the slaughter process in Poland most often showed resistance to quinolones (57.1%) and tetracycline (51.4%) . One strain of C. coli from a pork sample was resistant to three antibiotics simultaneously. This is worrisome given the public health concerns arising from the increasing antibiotic resistance of microorganisms to antimicrobials that are used as first-line drugs in the clinical treatment of campylobacteriosis . As reported by Wieczorek and Osek , 100% of Campylobacter strains isolated from pork and beef carcasses were sensitive to gentamicin and chloramphenicol. Significant differences were found between C. coli and C. jejuni , especially in resistance to streptomycin ( p < 0.001) and tetracycline ( p < 0.05). All C. jejuni isolates were sensitive to streptomycin, while 80.5% and 66.7% of C. coli strains from pigs and cattle, respectively, were resistant. C. coli also showed higher resistance to tetracycline, quinolones (nalidixic acid), and fluoroquinolones (ciprofloxacin). Four C. coli isolates from pig carcasses were resistant to erythromycin. Multidrug resistance was found in 61.4% of strains, with the highest levels of resistance to quinolones, fluoroquinolones, aminoglycosides, and tetracyclines, mainly in C. coli . Campylobacter spp. is also prevalent in geese and poses a potential risk for human campylobacteriosis through the consumption of goose meat. Campylobacter was found in 83.3% of goose cecum samples and 52.5% of neck skin samples from carcasses, with C. jejuni being the predominant species (87.7% of isolates) . The isolates exhibited high levels of antimicrobial resistance, particularly to quinolones (90.8%) and tetracycline (79.8%), while resistance to macrolides was rare (0.6%) . This aligns with findings from other studies showing high resistance of Campylobacter isolates to ciprofloxacin, tetracycline, and nalidixic acid in various bird species . Campylobacter spp. in meat and meat products in Poland indicates the presence of this pathogen in both beef, pork, and poultry, with poultry meat being the main source of human infections. Studies have shown significant levels of antibiotic resistance, especially to quinolones and tetracycline, posing a serious public health challenge. Macrolide resistance, although rarer, is also a problem, especially in C. coli . Campylobacter strains, which have also shown multidrug resistance, underscoring the need for the close monitoring of antibiotic resistance and limiting the use of antibiotics in animal production. The increase in the number of multi-resistant strains in recent years poses an epidemiological threat and calls for action to control Campylobacter at all stages of food production. 5.2. Staphylococcus spp. Antibiotic resistance in staphylococci isolated from meat and meat products has become an important public health problem worldwide . Both coagulase-positive staphylococci (CPS) and coagulase-negative staphylococci (CNS) have been found to carry antibiotic-resistant genes, posing a potential threat to consumers . Studies have shown a high prevalence of antibiotic-resistant Staphylococcus species in a variety of meat products, including chicken, beef, and processed meat products . Interestingly, the distribution of antibiotic resistance varies by Staphylococcus species and meat type . The pathogenesis of CNS species depends on the factors required for their commensal lifestyle, and one such factor that increases the importance of these microorganisms in the pathology of mammals and birds is their resistance to numerous antimicrobial agents . Poultry has been identified as one of the most important carriers of foodborne pathogens and antimicrobial resistance genes . A detailed analysis of resistance genes in staphylococci associated with livestock revealed a wide variety of these genes. These mainly include genes known to be commonly present in staphylococci of human and animal origin, such as the beta-lactamase gene blaZ , the methicillin resistance gene mecA , the tetracycline resistance genes tet (K), tet (L), tet (M), and tet (O), macrolysine–lincosamide–estreptogramin B (MLSB) resistance genes erm (A) and erm (B), erythromycin-inducible resistance gene msr A/B, aac (6′) Ie-aph (2″) Ia gene of aminoglycoside-modifying enzymes, and florfenicol/chloramphenicol resistance gene ( cfr ) . Methicillin resistance in Staphylococcus is now a global problem . In CNS, the mechanisms of resistance are like those observed in S. aureus . However, resistance mediated by the mecA gene in CNS is often expressed at lower levels compared to methicillin-resistant S. aureus (MRSA) . This lower expression can complicate its detection, highlighting the need for further studies to understand and address these diagnostic challenges . Pyzik et al. analyzed antibiotic resistance in coagulase-negative staphylococci isolated from poultry in Poland. CNS, despite being less pathogenic than coagulase-positive strains, is becoming a significant health threat due to increasing antibiotic resistance . The study detected numerous resistance genes, including the mecA gene, suggesting the presence of methicillin-resistant strains of coagulase-negative staphylococci (MR-CNS). Also identified were the ermA , ermB , and ermC genes, which confer resistance to macrolides, lincosamides, and streptogramins, limiting the effectiveness of these antibiotic groups in treating infections. The tetK and tetM genes, associated with resistance to tetracyclines, were also commonly present, indicating widespread CNS resistance to these frequently used antibiotics in animal treatment. In addition, the study revealed the presence of blaZ genes encoding beta-lactamases, which leads to the degradation of beta-lactam antibiotics such as penicillins, further limiting the therapeutic options. Also, in a study by Chajęcka-Wierzchowska et al., the pheno- and geno-typical antimicrobial resistance profile of CNS from ready-to-eat cured meat was studied . Mainly, S. epidermidis and S. xylosus were identified. Phenotypic analysis showed that isolates exhibited resistance to FOX, TGC, QD, DA, TET, CN, RD, CIP, W, and SXT, containing the following genes encoding antibiotic resistance in their genome: mec(A) , tet(L) , tet(M) , and tet(K) . Notably, two strains of the S. xylosus species showed simultaneous antibiotic resistance from nine different classes. This species is a component of the cultures used in the production of meat products, so it also becomes reasonable to control the strains used as starter and protective cultures, which have not been regulated for years and are not mandatorily tested for AMR . A study by Krupa et al. analyzed the antibiotic resistance of S. aureus strains isolated from poultry meat in Poland . The study found that a significant percentage of these strains showed resistance to oxacillin, indicating the presence of methicillin-resistant strains of Staphylococcus aureus (MRSA). The poultry meat tested in the study also contained MRSA strains, posing a potential risk to consumers. MRSA strains are a serious public health risk due to limited treatment options for infections caused by them . The study observed genotypic diversity in these strains, suggesting multiple sources of infection and transmission between livestock and humans. Another study by Krupa et al. focused on the population structure and oxacillin resistance in S. aureus strains from pork in southwestern Poland. The study found the presence of antibiotic-resistant S. aureus strains, including methicillin-resistant S. aureus , which exhibit resistance to oxacillin. This resistance is associated with the presence of the mecA gene . Other resistance genes such as erm (encoding macrolide resistance) and tet (encoding tetracycline resistance) were also detected, indicating multidrug resistance in some strains. Phylogenetic analysis revealed a diversity of S. aureus clones. Podkowik et al. analyzed in detail the presence of antibiotic-resistant genes in staphylococci isolated from ready-to-eat meat products such as sausages, hams, and pates. The study revealed the presence of numerous resistance genes, suggesting that these products may harbor pathogens resistant to antibiotic treatment. Particular attention was paid to the mecA gene. In addition, erm genes encoding resistance to macrolides, lincosamides, and streptogramins were detected, further complicating therapy, as these antibiotics are often used to treat staphylococcal infections. Tet genes have also been identified that cause resistance to tetracyclines, a group of antibiotics widely used in veterinary medicine and agriculture, suggesting that the use of these drugs in animal husbandry may contribute to the spread of resistant strains in food . The presence of the blaZ gene, which encodes beta-lactamases, enzymes that degrade beta-lactam antibiotics (such as penicillins), indicates a wide range of resistance, further limiting treatment options for infections. The study underscores that the high prevalence of these genes in ready-to-eat products poses a real threat to public health, as consumption of contaminated foods can lead to infections that are difficult to treat. The presence of antibiotic-resistant staphylococci in meat and meat products is a growing food safety concern. The high prevalence of resistance genes and multidrug-resistant strains highlights the need for improved monitoring systems and stricter regulation of antibiotic use in animal husbandry. These findings highlight the necessity of ongoing surveillance of MRSA and other resistant bacteria in animal products to mitigate the risk of transmission to humans and prevent the spread of resistance in the food chain. Additionally, further research is required to better understand resistance mechanisms, develop effective strategies to control them, and address this complex public health issue in the context of food production and processing. 5.3. Enterococcus spp. Enterococci, which are the natural intestinal flora of mammals, birds, and humans, are often responsible for nosocomial infections such as urinary tract infections, endocarditis, and catheter- and wound-related infections . The most frequently isolated species are Enterococcus faecalis and Enterococcus faecium , whereas Enterococcus gallinarum and Enterococcus casseliflavus appear less frequently . In poultry, enterococci cause, among others, endocarditis and arthritis . The use of antibiotics in human and veterinary medicine promotes the selection of resistant strains, which can transfer resistance genes between different bacteria, posing a risk to human health . In Europe, due to resistance to vancomycin and aminoglycosides, infections caused by enterococci are a serious clinical problem . An example is the use of avoparcin in animal feed, which contributed to the increase in vancomycin resistance before its use was banned in 1997 . Molecular mechanisms of resistance include genes such as vanA , vanB , tetM , or ermB , and biofilm-forming enterococci are particularly difficult to control . Biofilms, which are complex communities of microorganisms, protect bacteria from antibiotics and the immune system, making it difficult to treat infections such as wounds or urinary tract infections . The ability to form a biofilm also increases contamination in the food industry and promotes gene transfer between bacteria . A study by Chajęcka-Wierzechowska et al. analyzed 390 samples of ready-to-eat meat products, of which Enterococcus strains were detected in 74.1%. A total of 302 strains were classified: E. faecalis (48.7%), E. faecium (39.7%), E. casseliflavus (4.3%), E. durans (3.0%), E. hirae (2.6%), and another Enterococcus spp. (1.7%). A high percentage of isolates showed resistance to streptomycin (45.0%), erythromycin (42.7%), fosfomycin (27.2%), rifampicin (19.2%), tetracycline (36.4%), and tigecycline (19.9%). The most frequently detected resistance gene was ant(6′)-Ia (79.6%). Other significant genes were aac(6′)-Ie-aph(2″)-Ia (18.5%), aph(3″)-IIIa (16.6%), and tetracycline resistance genes: tetM (43.7%), tetL (32.1%), and tetK (14.6%). The ermB and ermA genes were found in 33.8% and 18.9% of isolates, respectively, and almost half of the isolates contained the conjugative transposon Tn916/Tn1545. The study revealed that enterococci are widespread in ready-to-eat meat products. Many of the isolated strains show antibiotic resistance and carry resistance genes that pose a potential risk due to their ability to transmit resistance genes to bacteria present in the human body, which may interact with enterococci isolated from food products. Knowledge of antibiotic resistance in food strains outside the E. faecalis and E. faecium species is very limited . The experiments conducted in this study analyzed in detail the antibiotic resistance of strains of species such as E. casseliflavus , E. durans , E. hirae , and E. gallinarum . The results indicate that these species may also harbor resistance genes to several important classes of antibiotics. Ławniczek-Wałczyk et al. analyzed the prevalence of antibiotic-resistant Enterococcus sp. strains in meat and the production environment of meat plants in Poland. Different Enterococcus species were identified, including E. faecalis and E. faecium . These strains showed significant antibiotic resistance, especially to erythromycin, tetracycline, and vancomycin. Resistance to vancomycin is of particular concern because vancomycin is often the drug of last resort in the treatment of infections caused by multidrug-resistant bacteria. Resistance genes such as vanA , vanB (for vancomycin), and ermB (for erythromycin) are commonly present in strains from both environmental and meat samples. A study by Stępień-Pyśniak et al. examined the prevalence and antibiotic resistance patterns of Enterococcus strains isolated from poultry. It focused on E. faecalis and E. faecium , which are common in poultry and known for their antibiotic resistance. The results showed that a significant proportion of isolates exhibited multidrug resistance, particularly to antibiotics frequently used in both veterinary and human medicine. High resistance rates were observed for antibiotics such as erythromycin, tetracycline, and vancomycin, with some strains showing resistance to multiple classes of antibiotics. Woźniak-Biel et al. analyzed the antibiotic resistance of Enterococcus strains isolated from turkeys. In the study, 51 strains from turkeys showed high resistance to tetracycline (94.1%) and erythromycin (76.5%). About 43.1% of the strains were multi-resistant, and 15.7% showed vancomycin resistance, associated with the presence of the vanA gene. A macrolide resistance gene ( ermB ) was also detected in 68.6% of the strains. All isolates showed the ability to form biofilms, which may contribute to their greater resistance and difficulty in treatment. The studies presented the widespread occurrence of antibiotic-resistant Enterococcus strains in meat and meat products, particularly in ready-to-eat foods and poultry. Multiple studies consistently show that E. faecalis and E. faecium are the most frequently isolated species, with significant resistance to antibiotics such as tetracycline, erythromycin, and vancomycin. The research points to the frequent presence of antibiotic-resistant genes like vanA , ermB , tetM , and ermA . In addition to their high resistance levels, these strains often exhibit the ability to form biofilms, further complicating their treatment and increasing the risk of gene transfer between bacteria. Studies conducted in Poland have revealed that both environmental and meat production facilities are affected by the presence of antibiotic-resistant enterococci, particularly those resistant to clinically important antibiotics like vancomycin, which is often a last-resort treatment. This resistance poses a significant threat to public health by facilitating the transmission of resistant strains through the food chain, from animals to humans. 5.4. Listeria monocytogenes L. monocytogenes , a foodborne pathogen that causes listeriosis zoonosis, is increasingly being detected in meat and meat products, raising concerns about food safety and public health. Studies have shown different rates of L. monocytogenes in different meats, with chicken, pork, and ready-to-eat meat products being common sources of contamination . The emergence of antibiotic-resistant strains of L. monocytogenes in these foods poses a serious threat to human health, as it could compromise the effectiveness of antibiotic therapy for listeriosis . Interestingly, the prevalence and patterns of antibiotic resistance in L. monocytogenes isolates from meat and meat products vary across studies and geographic locations . While some studies indicate a relatively low prevalence of antibiotic resistance in L. monocytogenes , others report a high prevalence of resistant and multidrug-resistant strains . This discrepancy underscores the need for ongoing monitoring and surveillance of antibiotic resistance in L. monocytogenes across regions and food sources. Kurpas et al. described a detailed genomic analysis of L. monocytogenes strains isolated from ready-to-eat meats and surfaces in meat processing plants in Poland. The study identified a variety of L. monocytogenes strains that possessed genes encoding resistance to antibiotics from several classes . The fosB gene, responsible for resistance to fosfomycin, was detected in several strains. Genes for tetracycline resistance, such as tetM , have also been identified. L. monocytogenes strains also showed resistance to macrolides due to the presence of the ermB gene. Macrolides, such as erythromycin, are often used to treat respiratory and other bacterial infections, and resistance is a major challenge . The study also identified multidrug-resistant strains that simultaneously possessed genes encoding resistance to antibiotics from different classes, including aminoglycosides (e.g., aacA gene), β-lactams (e.g., blaZ gene), and sulfonamides (e.g., sul1 gene). These strains have been isolated both from ready-to-eat meat products and from surfaces in processing environments, suggesting that meat processing plants may be a reservoir of antibiotic-resistant strains . The detection of multi-resistant strains in processing environments indicates the possibility of long-term contamination at these sites and the risk of transmission of these strains into meat products . Antibiotic-resistant strains, which can cause severe infections in humans, especially in immunocompromised individuals, pose a serious epidemiological threat . Similar results were reported by Maćkiw et al. , who investigated the occurrence and characterization of L. monocytogenes in ready-to-eat meat products in Poland. The study revealed the presence of this pathogen in several food samples. L. monocytogenes strains were tested for resistance to various antibiotics, and the results showed significant resistance to several key antibiotics. Of most concern was resistance to erythromycin and tetracycline, which are frequently used to treat listeriosis infections. Kawacka et al. present a detailed study on the resistance of L. monocytogenes strains isolated from meat products and meat processing environments in Poland. The results showed that most of the analyzed isolates were antibiotic-susceptible to the most-used antibiotics, such as penicillins, macrolides, and tetracyclines, suggesting that current therapies are effective in treating infections associated with food of animal origin . Particular attention was paid to fluoroquinolones, particularly ciprofloxacin, where rare cases of reduced susceptibility were identified, which is worrisome given that fluoroquinolones are key antibiotics in the treatment of many bacterial infections . In contrast, in the study by Skowron et al. assessing the prevalence and antibiotic resistance of L. monocytogenes strains isolated from meat, researchers analyzed samples from pork, beef, and poultry over three years. They found that 2.1% of the collected meat samples were contaminated with L. monocytogenes , with poultry showing the highest contamination levels. The antibiotic resistance of these strains was concerning, as 6.7% were resistant to all five tested antibiotics. Specifically, the highest resistance rates were observed against cotrimoxazole (45.8%), meropenem (43.3%), erythromycin (40.0%), penicillin (25.8%), and ampicillin (17.5%). Only 32.5% of the strains were sensitive to all antibiotics tested. The occurrence of L. monocytogenes in meat and meat products raises serious food safety and public health concerns, especially due to the emergence of antibiotic-resistant strains. The diversity of prevalence rates and resistance patterns depending on the region and type of product indicates the need for continuous monitoring. Studies in Poland have identified resistance genes to multiple classes of antibiotics, raising concerns about the long-term contamination of meat processing environments and the risk of resistant strains contaminating finished products. Multidrug-resistant strains can significantly hinder the treatment of listeriosis infections, which requires strengthening food safety regulations and further research into resistance mechanisms. Furthermore, the findings emphasize the importance of microbiological monitoring and control in meat processing plants to prevent the spread of resistant L. monocytogenes . Regular research into antibiotic resistance among food-related pathogens is crucial, alongside the implementation of appropriate control procedures in food production. Ultimately, further research into resistance mechanisms and their implications is needed to better protect public health. 5.5. Enterobacterales The annual report on trends and sources of zoonoses published in December 2021 by the European Food Safety Authority (EFSA) and the European Center for Disease Prevention and Control (ECDC) shows that nearly one in four foodborne outbreaks in the European Union (EU) in 2020 were caused by Salmonella spp., making this bacterium the most reported causative agent of foodborne outbreaks (694 foodborne outbreaks in 2020) . Salmonella spp. infections in humans are usually caused by the consumption of food of animal origin, mainly eggs, poultry, or pork . An analysis by Gutema et al. show that beef and veal can also be a source of Salmonella spp. infection because these animals are potential asymptomatic carriers. Multidrug-resistant Salmonella poses a serious threat to public health after foodborne infections . Today, such multidrug-resistant strains are increasingly being isolated from beef, pork , and poultry . According to the monitoring of antimicrobial resistance in food and food-producing bacteria, as specified in Commission Implementing Decision 2013/652/EU, Salmonella antibiotic resistance isolated from food and food-producing animals should target broilers, fattening pigs, calves under one year old, and their meat . A study by Szewczyk et al. on the antibiotic resistance of Enterobacterales strains isolated from food showed that most strains (28.0–65.1%) were resistant to a single antibiotic, but 15 strains (34.9%) were resistant to two or more antibiotics. Particularly prominent among them were strains of Escherichia coli and Proteus mirabilis , which were resistant to multiple antibiotics, including beta-lactams (piperacillin, cefuroxime, and cefotaxime), fluoroquinolones, and carbapenems. All isolates were sensitive to gentamicin, and none showed ESBL-type resistance. Strains resistant to high concentrations of antibiotics (256 μg/mL) included Salmonella spp., Hafnia alvei , P. mirabilis , and E. coli . Beta-lactamase-resistant and piperacillin- and cefuroxime-resistant Klebsiella strains (including K. ozaenae and K. rhinoscleromatis ) suggested the ability to produce beta-lactamase enzymes (AmpC and CTX-M), which allows resistance transfer between species. Zarzecka et al. examined in detail the incidence of antibiotic resistance in Enterobacterales strains isolated from raw meat and ready-to-eat meat products. The highest number of isolated strains was identified as E. cloacae (42.4%), followed by E. coli (9.8%), P. mirabilis , S. enterica , P. penneri , and C. freundii (7.6% each), and C. braakii (6.6%), K. pneumoniae , and K. oxytoca (5.4% each). More than half of the isolated strains (52.2%) showed resistance to at least one antibiotic, with the highest number of resistant strains found against amoxicillin with clavulanic acid (28.3%) and ampicillin (19.5%). The ESBL phenotype was found in 26 strains, while the AmpC phenotype was found in 32 strains. The bla CTX-M gene was present in 53.8% of the ESBL-positive strains, and the CIT family gene was present in 43.8% of the AmpC-positive strains . Raw meat has been identified as a key source of resistant strains, posing a significant public health risk, especially in the context of ready-to-eat products, which can be exposed to improper processing, lack of proper sanitary–epidemiological control and improper storage . Both phenotypic analyses, such as antibiotic susceptibility tests, and genotypic analyses were used in the study, which made it possible to accurately determine the resistance profiles of the tested strains. Mąka et al. analyzed the antibiotic resistance profiles of Salmonella strains isolated from retail meat products in Poland between 2008 and 2012. The results of the study showed that more than 90.0% of the strains exhibited resistance to at least one antibiotic, indicating a high level of resistance in the bacterial population. The highest resistance was found against tetracycline, streptomycin, and sulfonamides, reflecting the widespread use of these antibiotics in animal husbandry. Strains of S. typhimurium were more resistant than other serotypes, with about 20.0% of them showing resistance to five or more classes of antibiotics, classifying them as multi-resistant. Resistance to fluoroquinolones, which are often used to treat Salmonella sp. infections in humans, was also found. In a study by Pławińska-Czernak et al. , researchers analyzed the occurrence of multidrug resistance in Salmonella strains isolated from raw meat products such as poultry, beef, and pork. The study showed that 64.3% of the isolates showed resistance to at least three classes of antibiotics, with the highest resistance reported against tetracyclines (56.5%), aminoglycosides (47.8%), beta-lactams (34.8%), and quinolones (30.4%). A key aspect of the study was the identification of genes encoding resistance, including the tetA , blaTEM , aadA , and qnrS genes, which were responsible for resistance to tetracyclines, beta-lactams, aminoglycosides, and quinolones, respectively. The presence of these genes indicates the widespread spread of genetic resistance among food-related pathogens, which poses a serious threat to public health. Sarowska et al. examined the antibiotic resistance and pathogenicity of E. coli strains from poultry farms, retail meat, and human urinary tract infections. The strains showed significant resistance to a variety of antibiotic classes, including β-lactams, tetracyclines, aminoglycosides, fluoroquinolones, and sulfonamides, indicating the widespread selection pressure exerted by antibiotic use in poultry farming. E. coli strains from meat and poultry farms showed some commonalities with isolates causing human infections, suggesting the possibility that potentially pathogenic strains could be transmitted through the food chain. In the presented studies, the researchers highlight the urgent need for continuous monitoring of antibiotic resistance in animal products, along with the implementation of stricter sanitary standards in the food industry. The researchers emphasize educating producers and consumers about the risks of antibiotic resistance to minimize the risk of foodborne infections. Considering the changing resistance profiles, the researchers recommend regular monitoring and restriction of antibiotic use in agriculture, supported by stricter regulations to prevent the spread of resistant strains, especially Salmonella . Multidrug-resistant strains of Salmonella , which are increasingly resistant to tetracyclines, aminoglycosides, and beta-lactams, pose a serious threat to public health. Similarly, high levels of antibiotic resistance have been observed in Enterobacterales strains, including E. coli , isolated from raw meat and animal products. Particular attention was paid to ESBL and AmpC strains, highlighting the importance of reducing antibiotic use in animal husbandry and strengthening sanitary controls in meat processing. The study also highlights the importance of monitoring food safety and zoonotic infection risks to reduce the spread of multidrug-resistant pathogens via food. Campylobacter spp. is a major cause of foodborne illness in humans, which results from improper processing or consumption of undercooked poultry meat . For severe or chronic infections caused by Campylobacter spp., treatment with antibiotics (e.g., fluoroquinolones and macrolides) may be necessary, which is problematic because of the uncontrolled use of these drugs in clinical medicine and animal production . Campylobacter spp. is one of the main causes of foodborne gastroenteritis responsible for zoonosis—campylobacteriosis. Campylobacter , especially Campylobacter jejuni and to a lesser extent Campylobacter coli , is one of the leading causes of foodborne infections worldwide . The main source of infection is contaminated poultry meat , and high contamination poses a threat to public health. It is estimated that 50% to 80% of human campylobacteriosis cases are directly linked to poultry meat, particularly Campylobacter jejuni . In recent years, Campylobacter has been increasing in resistance to antibiotics (especially quinolones and macrolides) due to their widespread use in agriculture . Although campylobacteriosis usually resolves spontaneously, macrolides (erythromycin), fluoroquinolones, and tetracyclines are used in severe cases . Since chickens are the main reservoir of Campylobacter , antibiotic resistance in these bacteria isolated from poultry is of serious concern. The use of antimicrobials in animal production, especially in veterinary medicine, may contribute to the buildup of resistance in human isolates, especially to quinolones . The aim of the study by Woźniak-Biel et al. was to identify Campylobacter strains, isolated from turkeys and chickens, using polymerase chain reaction (PCR) and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) methods, and assess their antibiotic resistance. The results obtained from MALDI-TOF were consistent with those from multiplex PCR. There was 100% resistance to ciprofloxacin in strains from turkeys and chickens, and 58.1% and 78.6% resistance to tetracycline in these groups, respectively. No multidrug-resistant strains were detected, and all ciprofloxacin-resistant strains had a mutation in the gyrA gene at the Thr-86 position. The presence of the tetO gene was present in 71.0% of turkey strains and 100% of chickens, and this gene was also found in five turkey strains and three chickens that were sensitive to tetracycline. The results indicate a high prevalence of Campylobacter strains that are phenotypically and genetically resistant to fluoroquinolones and tetracycline. A study by Maćkiw et al. on the antibiotic resistance of C. jejuni and C. coli strains isolated from food in Poland showed that Campylobacter spp. is often isolated from poultry, which is the main source of human infections with these bacteria. High levels of resistance to fluoroquinolones, including ciprofloxacin, were found, which is in line with trends observed in other European countries. Resistance to tetracyclines was also common, which may be due to the widespread use of these antibiotics in animal husbandry. The tet (O) genes responsible for resistance to tetracyclines and gyrA associated with resistance to fluoroquinolones were identified. Some strains showed resistance to macrolides such as erythromycin, but this was less prevalent compared to fluoroquinolones and tetracyclines. It was also noted that multidrug resistance was relatively common. These results suggest the need to monitor Campylobacter sp. resistance in food to prevent the spread of resistant strains, which can threaten public health. A study by Wieczorek and Osek analyzing the antibiotic resistance of C. jejuni and C. coli strains of poultry carcass samples collected between 2009 and 2013 showed that 54.4% of samples were positive for Campylobacter . Resistance to ciprofloxacin was 81.6%, to tetracycline 56.1%, and only 2.4% of isolates were resistant to erythromycin. In contrast, resistance was higher among C. coli than C. jejuni , and an increase in resistance to ciprofloxacin and tetracycline was noted over the five-year study period. A later study by Wieczorek et al. on the prevalence and antibiotic resistance of Campylobacter strains isolated from chicken carcasses in Poland between 2014 and 2018 reported that 53.4% of samples (in total 2367 samples collected from slaughterhouses across the country) were positive for Campylobacter . Mainly, C. coli (31.2%) and C. jejuni (22.2%) were identified. The strains showed high resistance to ciprofloxacin (93.1%), nalidixic acid (92.3%), and tetracycline (70.9%). Only a small percentage of isolated strains were resistant to erythromycin (4.2%), with C. coli (6.4%) showing more resistance than C. jejuni (1.1%). Multidrug resistance was found in 25.1% of C. coli and 20.6% of C. jejuni strains. The study showed an increase in the percentage of multidrug-resistant strains compared to earlier years, indicating the necessity of taking measures to control Campylobacter at the poultry slaughter stage and restricting the use of antibiotics in poultry production. Rożynek et al. analyzed in detail the emergence of macrolide-resistant Campylobacter strains in poultry meat in Poland and the resistance mechanisms responsible for the problem. Macrolides, such as erythromycin, are key antibiotics used to treat infections caused by these bacteria . The study found a significant number of strains resistant to macrolides, which poses an important therapeutic challenge. The mechanism of resistance to these antibiotics was mainly related to mutations in domain V of the 23S rRNA gene, which encodes the ribosomal subunit responsible for macrolide binding. These mutations, particularly at nucleotide positions 2074 and 2075, lead to a reduced ability of macrolides to inhibit bacterial protein synthesis . Also identified were erm (B) genes that encode methyltransferases, enzymes that modify ribosomes and cause macrolide resistance. In addition, other resistance mechanisms, such as the pumping of antibiotics out of bacterial cells by the efflux pump CmeABC, were also identified as an important factor in the development of resistance. The study also found a link between resistance and intensive antibiotic use in poultry farming, which promotes the selection of resistant strains. The authors emphasize the need to monitor antibiotic resistance and to introduce stricter regulations on the use of macrolides in animal food production to prevent the further spread of resistant strains of Campylobacter spp. Another source of Campylobacter is beef and pork. It was reported that the prevalence of Campylobacter spp. in retail beef products was about 10.0% , whereas its prevalence in beef and pork carcasses was 10.0% and 30.0%, respectively . Antibiotic profiling revealed that Campylobacter isolated from pork and cattle carcasses during the slaughter process in Poland most often showed resistance to quinolones (57.1%) and tetracycline (51.4%) . One strain of C. coli from a pork sample was resistant to three antibiotics simultaneously. This is worrisome given the public health concerns arising from the increasing antibiotic resistance of microorganisms to antimicrobials that are used as first-line drugs in the clinical treatment of campylobacteriosis . As reported by Wieczorek and Osek , 100% of Campylobacter strains isolated from pork and beef carcasses were sensitive to gentamicin and chloramphenicol. Significant differences were found between C. coli and C. jejuni , especially in resistance to streptomycin ( p < 0.001) and tetracycline ( p < 0.05). All C. jejuni isolates were sensitive to streptomycin, while 80.5% and 66.7% of C. coli strains from pigs and cattle, respectively, were resistant. C. coli also showed higher resistance to tetracycline, quinolones (nalidixic acid), and fluoroquinolones (ciprofloxacin). Four C. coli isolates from pig carcasses were resistant to erythromycin. Multidrug resistance was found in 61.4% of strains, with the highest levels of resistance to quinolones, fluoroquinolones, aminoglycosides, and tetracyclines, mainly in C. coli . Campylobacter spp. is also prevalent in geese and poses a potential risk for human campylobacteriosis through the consumption of goose meat. Campylobacter was found in 83.3% of goose cecum samples and 52.5% of neck skin samples from carcasses, with C. jejuni being the predominant species (87.7% of isolates) . The isolates exhibited high levels of antimicrobial resistance, particularly to quinolones (90.8%) and tetracycline (79.8%), while resistance to macrolides was rare (0.6%) . This aligns with findings from other studies showing high resistance of Campylobacter isolates to ciprofloxacin, tetracycline, and nalidixic acid in various bird species . Campylobacter spp. in meat and meat products in Poland indicates the presence of this pathogen in both beef, pork, and poultry, with poultry meat being the main source of human infections. Studies have shown significant levels of antibiotic resistance, especially to quinolones and tetracycline, posing a serious public health challenge. Macrolide resistance, although rarer, is also a problem, especially in C. coli . Campylobacter strains, which have also shown multidrug resistance, underscoring the need for the close monitoring of antibiotic resistance and limiting the use of antibiotics in animal production. The increase in the number of multi-resistant strains in recent years poses an epidemiological threat and calls for action to control Campylobacter at all stages of food production. Antibiotic resistance in staphylococci isolated from meat and meat products has become an important public health problem worldwide . Both coagulase-positive staphylococci (CPS) and coagulase-negative staphylococci (CNS) have been found to carry antibiotic-resistant genes, posing a potential threat to consumers . Studies have shown a high prevalence of antibiotic-resistant Staphylococcus species in a variety of meat products, including chicken, beef, and processed meat products . Interestingly, the distribution of antibiotic resistance varies by Staphylococcus species and meat type . The pathogenesis of CNS species depends on the factors required for their commensal lifestyle, and one such factor that increases the importance of these microorganisms in the pathology of mammals and birds is their resistance to numerous antimicrobial agents . Poultry has been identified as one of the most important carriers of foodborne pathogens and antimicrobial resistance genes . A detailed analysis of resistance genes in staphylococci associated with livestock revealed a wide variety of these genes. These mainly include genes known to be commonly present in staphylococci of human and animal origin, such as the beta-lactamase gene blaZ , the methicillin resistance gene mecA , the tetracycline resistance genes tet (K), tet (L), tet (M), and tet (O), macrolysine–lincosamide–estreptogramin B (MLSB) resistance genes erm (A) and erm (B), erythromycin-inducible resistance gene msr A/B, aac (6′) Ie-aph (2″) Ia gene of aminoglycoside-modifying enzymes, and florfenicol/chloramphenicol resistance gene ( cfr ) . Methicillin resistance in Staphylococcus is now a global problem . In CNS, the mechanisms of resistance are like those observed in S. aureus . However, resistance mediated by the mecA gene in CNS is often expressed at lower levels compared to methicillin-resistant S. aureus (MRSA) . This lower expression can complicate its detection, highlighting the need for further studies to understand and address these diagnostic challenges . Pyzik et al. analyzed antibiotic resistance in coagulase-negative staphylococci isolated from poultry in Poland. CNS, despite being less pathogenic than coagulase-positive strains, is becoming a significant health threat due to increasing antibiotic resistance . The study detected numerous resistance genes, including the mecA gene, suggesting the presence of methicillin-resistant strains of coagulase-negative staphylococci (MR-CNS). Also identified were the ermA , ermB , and ermC genes, which confer resistance to macrolides, lincosamides, and streptogramins, limiting the effectiveness of these antibiotic groups in treating infections. The tetK and tetM genes, associated with resistance to tetracyclines, were also commonly present, indicating widespread CNS resistance to these frequently used antibiotics in animal treatment. In addition, the study revealed the presence of blaZ genes encoding beta-lactamases, which leads to the degradation of beta-lactam antibiotics such as penicillins, further limiting the therapeutic options. Also, in a study by Chajęcka-Wierzchowska et al., the pheno- and geno-typical antimicrobial resistance profile of CNS from ready-to-eat cured meat was studied . Mainly, S. epidermidis and S. xylosus were identified. Phenotypic analysis showed that isolates exhibited resistance to FOX, TGC, QD, DA, TET, CN, RD, CIP, W, and SXT, containing the following genes encoding antibiotic resistance in their genome: mec(A) , tet(L) , tet(M) , and tet(K) . Notably, two strains of the S. xylosus species showed simultaneous antibiotic resistance from nine different classes. This species is a component of the cultures used in the production of meat products, so it also becomes reasonable to control the strains used as starter and protective cultures, which have not been regulated for years and are not mandatorily tested for AMR . A study by Krupa et al. analyzed the antibiotic resistance of S. aureus strains isolated from poultry meat in Poland . The study found that a significant percentage of these strains showed resistance to oxacillin, indicating the presence of methicillin-resistant strains of Staphylococcus aureus (MRSA). The poultry meat tested in the study also contained MRSA strains, posing a potential risk to consumers. MRSA strains are a serious public health risk due to limited treatment options for infections caused by them . The study observed genotypic diversity in these strains, suggesting multiple sources of infection and transmission between livestock and humans. Another study by Krupa et al. focused on the population structure and oxacillin resistance in S. aureus strains from pork in southwestern Poland. The study found the presence of antibiotic-resistant S. aureus strains, including methicillin-resistant S. aureus , which exhibit resistance to oxacillin. This resistance is associated with the presence of the mecA gene . Other resistance genes such as erm (encoding macrolide resistance) and tet (encoding tetracycline resistance) were also detected, indicating multidrug resistance in some strains. Phylogenetic analysis revealed a diversity of S. aureus clones. Podkowik et al. analyzed in detail the presence of antibiotic-resistant genes in staphylococci isolated from ready-to-eat meat products such as sausages, hams, and pates. The study revealed the presence of numerous resistance genes, suggesting that these products may harbor pathogens resistant to antibiotic treatment. Particular attention was paid to the mecA gene. In addition, erm genes encoding resistance to macrolides, lincosamides, and streptogramins were detected, further complicating therapy, as these antibiotics are often used to treat staphylococcal infections. Tet genes have also been identified that cause resistance to tetracyclines, a group of antibiotics widely used in veterinary medicine and agriculture, suggesting that the use of these drugs in animal husbandry may contribute to the spread of resistant strains in food . The presence of the blaZ gene, which encodes beta-lactamases, enzymes that degrade beta-lactam antibiotics (such as penicillins), indicates a wide range of resistance, further limiting treatment options for infections. The study underscores that the high prevalence of these genes in ready-to-eat products poses a real threat to public health, as consumption of contaminated foods can lead to infections that are difficult to treat. The presence of antibiotic-resistant staphylococci in meat and meat products is a growing food safety concern. The high prevalence of resistance genes and multidrug-resistant strains highlights the need for improved monitoring systems and stricter regulation of antibiotic use in animal husbandry. These findings highlight the necessity of ongoing surveillance of MRSA and other resistant bacteria in animal products to mitigate the risk of transmission to humans and prevent the spread of resistance in the food chain. Additionally, further research is required to better understand resistance mechanisms, develop effective strategies to control them, and address this complex public health issue in the context of food production and processing. Enterococci, which are the natural intestinal flora of mammals, birds, and humans, are often responsible for nosocomial infections such as urinary tract infections, endocarditis, and catheter- and wound-related infections . The most frequently isolated species are Enterococcus faecalis and Enterococcus faecium , whereas Enterococcus gallinarum and Enterococcus casseliflavus appear less frequently . In poultry, enterococci cause, among others, endocarditis and arthritis . The use of antibiotics in human and veterinary medicine promotes the selection of resistant strains, which can transfer resistance genes between different bacteria, posing a risk to human health . In Europe, due to resistance to vancomycin and aminoglycosides, infections caused by enterococci are a serious clinical problem . An example is the use of avoparcin in animal feed, which contributed to the increase in vancomycin resistance before its use was banned in 1997 . Molecular mechanisms of resistance include genes such as vanA , vanB , tetM , or ermB , and biofilm-forming enterococci are particularly difficult to control . Biofilms, which are complex communities of microorganisms, protect bacteria from antibiotics and the immune system, making it difficult to treat infections such as wounds or urinary tract infections . The ability to form a biofilm also increases contamination in the food industry and promotes gene transfer between bacteria . A study by Chajęcka-Wierzechowska et al. analyzed 390 samples of ready-to-eat meat products, of which Enterococcus strains were detected in 74.1%. A total of 302 strains were classified: E. faecalis (48.7%), E. faecium (39.7%), E. casseliflavus (4.3%), E. durans (3.0%), E. hirae (2.6%), and another Enterococcus spp. (1.7%). A high percentage of isolates showed resistance to streptomycin (45.0%), erythromycin (42.7%), fosfomycin (27.2%), rifampicin (19.2%), tetracycline (36.4%), and tigecycline (19.9%). The most frequently detected resistance gene was ant(6′)-Ia (79.6%). Other significant genes were aac(6′)-Ie-aph(2″)-Ia (18.5%), aph(3″)-IIIa (16.6%), and tetracycline resistance genes: tetM (43.7%), tetL (32.1%), and tetK (14.6%). The ermB and ermA genes were found in 33.8% and 18.9% of isolates, respectively, and almost half of the isolates contained the conjugative transposon Tn916/Tn1545. The study revealed that enterococci are widespread in ready-to-eat meat products. Many of the isolated strains show antibiotic resistance and carry resistance genes that pose a potential risk due to their ability to transmit resistance genes to bacteria present in the human body, which may interact with enterococci isolated from food products. Knowledge of antibiotic resistance in food strains outside the E. faecalis and E. faecium species is very limited . The experiments conducted in this study analyzed in detail the antibiotic resistance of strains of species such as E. casseliflavus , E. durans , E. hirae , and E. gallinarum . The results indicate that these species may also harbor resistance genes to several important classes of antibiotics. Ławniczek-Wałczyk et al. analyzed the prevalence of antibiotic-resistant Enterococcus sp. strains in meat and the production environment of meat plants in Poland. Different Enterococcus species were identified, including E. faecalis and E. faecium . These strains showed significant antibiotic resistance, especially to erythromycin, tetracycline, and vancomycin. Resistance to vancomycin is of particular concern because vancomycin is often the drug of last resort in the treatment of infections caused by multidrug-resistant bacteria. Resistance genes such as vanA , vanB (for vancomycin), and ermB (for erythromycin) are commonly present in strains from both environmental and meat samples. A study by Stępień-Pyśniak et al. examined the prevalence and antibiotic resistance patterns of Enterococcus strains isolated from poultry. It focused on E. faecalis and E. faecium , which are common in poultry and known for their antibiotic resistance. The results showed that a significant proportion of isolates exhibited multidrug resistance, particularly to antibiotics frequently used in both veterinary and human medicine. High resistance rates were observed for antibiotics such as erythromycin, tetracycline, and vancomycin, with some strains showing resistance to multiple classes of antibiotics. Woźniak-Biel et al. analyzed the antibiotic resistance of Enterococcus strains isolated from turkeys. In the study, 51 strains from turkeys showed high resistance to tetracycline (94.1%) and erythromycin (76.5%). About 43.1% of the strains were multi-resistant, and 15.7% showed vancomycin resistance, associated with the presence of the vanA gene. A macrolide resistance gene ( ermB ) was also detected in 68.6% of the strains. All isolates showed the ability to form biofilms, which may contribute to their greater resistance and difficulty in treatment. The studies presented the widespread occurrence of antibiotic-resistant Enterococcus strains in meat and meat products, particularly in ready-to-eat foods and poultry. Multiple studies consistently show that E. faecalis and E. faecium are the most frequently isolated species, with significant resistance to antibiotics such as tetracycline, erythromycin, and vancomycin. The research points to the frequent presence of antibiotic-resistant genes like vanA , ermB , tetM , and ermA . In addition to their high resistance levels, these strains often exhibit the ability to form biofilms, further complicating their treatment and increasing the risk of gene transfer between bacteria. Studies conducted in Poland have revealed that both environmental and meat production facilities are affected by the presence of antibiotic-resistant enterococci, particularly those resistant to clinically important antibiotics like vancomycin, which is often a last-resort treatment. This resistance poses a significant threat to public health by facilitating the transmission of resistant strains through the food chain, from animals to humans. L. monocytogenes , a foodborne pathogen that causes listeriosis zoonosis, is increasingly being detected in meat and meat products, raising concerns about food safety and public health. Studies have shown different rates of L. monocytogenes in different meats, with chicken, pork, and ready-to-eat meat products being common sources of contamination . The emergence of antibiotic-resistant strains of L. monocytogenes in these foods poses a serious threat to human health, as it could compromise the effectiveness of antibiotic therapy for listeriosis . Interestingly, the prevalence and patterns of antibiotic resistance in L. monocytogenes isolates from meat and meat products vary across studies and geographic locations . While some studies indicate a relatively low prevalence of antibiotic resistance in L. monocytogenes , others report a high prevalence of resistant and multidrug-resistant strains . This discrepancy underscores the need for ongoing monitoring and surveillance of antibiotic resistance in L. monocytogenes across regions and food sources. Kurpas et al. described a detailed genomic analysis of L. monocytogenes strains isolated from ready-to-eat meats and surfaces in meat processing plants in Poland. The study identified a variety of L. monocytogenes strains that possessed genes encoding resistance to antibiotics from several classes . The fosB gene, responsible for resistance to fosfomycin, was detected in several strains. Genes for tetracycline resistance, such as tetM , have also been identified. L. monocytogenes strains also showed resistance to macrolides due to the presence of the ermB gene. Macrolides, such as erythromycin, are often used to treat respiratory and other bacterial infections, and resistance is a major challenge . The study also identified multidrug-resistant strains that simultaneously possessed genes encoding resistance to antibiotics from different classes, including aminoglycosides (e.g., aacA gene), β-lactams (e.g., blaZ gene), and sulfonamides (e.g., sul1 gene). These strains have been isolated both from ready-to-eat meat products and from surfaces in processing environments, suggesting that meat processing plants may be a reservoir of antibiotic-resistant strains . The detection of multi-resistant strains in processing environments indicates the possibility of long-term contamination at these sites and the risk of transmission of these strains into meat products . Antibiotic-resistant strains, which can cause severe infections in humans, especially in immunocompromised individuals, pose a serious epidemiological threat . Similar results were reported by Maćkiw et al. , who investigated the occurrence and characterization of L. monocytogenes in ready-to-eat meat products in Poland. The study revealed the presence of this pathogen in several food samples. L. monocytogenes strains were tested for resistance to various antibiotics, and the results showed significant resistance to several key antibiotics. Of most concern was resistance to erythromycin and tetracycline, which are frequently used to treat listeriosis infections. Kawacka et al. present a detailed study on the resistance of L. monocytogenes strains isolated from meat products and meat processing environments in Poland. The results showed that most of the analyzed isolates were antibiotic-susceptible to the most-used antibiotics, such as penicillins, macrolides, and tetracyclines, suggesting that current therapies are effective in treating infections associated with food of animal origin . Particular attention was paid to fluoroquinolones, particularly ciprofloxacin, where rare cases of reduced susceptibility were identified, which is worrisome given that fluoroquinolones are key antibiotics in the treatment of many bacterial infections . In contrast, in the study by Skowron et al. assessing the prevalence and antibiotic resistance of L. monocytogenes strains isolated from meat, researchers analyzed samples from pork, beef, and poultry over three years. They found that 2.1% of the collected meat samples were contaminated with L. monocytogenes , with poultry showing the highest contamination levels. The antibiotic resistance of these strains was concerning, as 6.7% were resistant to all five tested antibiotics. Specifically, the highest resistance rates were observed against cotrimoxazole (45.8%), meropenem (43.3%), erythromycin (40.0%), penicillin (25.8%), and ampicillin (17.5%). Only 32.5% of the strains were sensitive to all antibiotics tested. The occurrence of L. monocytogenes in meat and meat products raises serious food safety and public health concerns, especially due to the emergence of antibiotic-resistant strains. The diversity of prevalence rates and resistance patterns depending on the region and type of product indicates the need for continuous monitoring. Studies in Poland have identified resistance genes to multiple classes of antibiotics, raising concerns about the long-term contamination of meat processing environments and the risk of resistant strains contaminating finished products. Multidrug-resistant strains can significantly hinder the treatment of listeriosis infections, which requires strengthening food safety regulations and further research into resistance mechanisms. Furthermore, the findings emphasize the importance of microbiological monitoring and control in meat processing plants to prevent the spread of resistant L. monocytogenes . Regular research into antibiotic resistance among food-related pathogens is crucial, alongside the implementation of appropriate control procedures in food production. Ultimately, further research into resistance mechanisms and their implications is needed to better protect public health. The annual report on trends and sources of zoonoses published in December 2021 by the European Food Safety Authority (EFSA) and the European Center for Disease Prevention and Control (ECDC) shows that nearly one in four foodborne outbreaks in the European Union (EU) in 2020 were caused by Salmonella spp., making this bacterium the most reported causative agent of foodborne outbreaks (694 foodborne outbreaks in 2020) . Salmonella spp. infections in humans are usually caused by the consumption of food of animal origin, mainly eggs, poultry, or pork . An analysis by Gutema et al. show that beef and veal can also be a source of Salmonella spp. infection because these animals are potential asymptomatic carriers. Multidrug-resistant Salmonella poses a serious threat to public health after foodborne infections . Today, such multidrug-resistant strains are increasingly being isolated from beef, pork , and poultry . According to the monitoring of antimicrobial resistance in food and food-producing bacteria, as specified in Commission Implementing Decision 2013/652/EU, Salmonella antibiotic resistance isolated from food and food-producing animals should target broilers, fattening pigs, calves under one year old, and their meat . A study by Szewczyk et al. on the antibiotic resistance of Enterobacterales strains isolated from food showed that most strains (28.0–65.1%) were resistant to a single antibiotic, but 15 strains (34.9%) were resistant to two or more antibiotics. Particularly prominent among them were strains of Escherichia coli and Proteus mirabilis , which were resistant to multiple antibiotics, including beta-lactams (piperacillin, cefuroxime, and cefotaxime), fluoroquinolones, and carbapenems. All isolates were sensitive to gentamicin, and none showed ESBL-type resistance. Strains resistant to high concentrations of antibiotics (256 μg/mL) included Salmonella spp., Hafnia alvei , P. mirabilis , and E. coli . Beta-lactamase-resistant and piperacillin- and cefuroxime-resistant Klebsiella strains (including K. ozaenae and K. rhinoscleromatis ) suggested the ability to produce beta-lactamase enzymes (AmpC and CTX-M), which allows resistance transfer between species. Zarzecka et al. examined in detail the incidence of antibiotic resistance in Enterobacterales strains isolated from raw meat and ready-to-eat meat products. The highest number of isolated strains was identified as E. cloacae (42.4%), followed by E. coli (9.8%), P. mirabilis , S. enterica , P. penneri , and C. freundii (7.6% each), and C. braakii (6.6%), K. pneumoniae , and K. oxytoca (5.4% each). More than half of the isolated strains (52.2%) showed resistance to at least one antibiotic, with the highest number of resistant strains found against amoxicillin with clavulanic acid (28.3%) and ampicillin (19.5%). The ESBL phenotype was found in 26 strains, while the AmpC phenotype was found in 32 strains. The bla CTX-M gene was present in 53.8% of the ESBL-positive strains, and the CIT family gene was present in 43.8% of the AmpC-positive strains . Raw meat has been identified as a key source of resistant strains, posing a significant public health risk, especially in the context of ready-to-eat products, which can be exposed to improper processing, lack of proper sanitary–epidemiological control and improper storage . Both phenotypic analyses, such as antibiotic susceptibility tests, and genotypic analyses were used in the study, which made it possible to accurately determine the resistance profiles of the tested strains. Mąka et al. analyzed the antibiotic resistance profiles of Salmonella strains isolated from retail meat products in Poland between 2008 and 2012. The results of the study showed that more than 90.0% of the strains exhibited resistance to at least one antibiotic, indicating a high level of resistance in the bacterial population. The highest resistance was found against tetracycline, streptomycin, and sulfonamides, reflecting the widespread use of these antibiotics in animal husbandry. Strains of S. typhimurium were more resistant than other serotypes, with about 20.0% of them showing resistance to five or more classes of antibiotics, classifying them as multi-resistant. Resistance to fluoroquinolones, which are often used to treat Salmonella sp. infections in humans, was also found. In a study by Pławińska-Czernak et al. , researchers analyzed the occurrence of multidrug resistance in Salmonella strains isolated from raw meat products such as poultry, beef, and pork. The study showed that 64.3% of the isolates showed resistance to at least three classes of antibiotics, with the highest resistance reported against tetracyclines (56.5%), aminoglycosides (47.8%), beta-lactams (34.8%), and quinolones (30.4%). A key aspect of the study was the identification of genes encoding resistance, including the tetA , blaTEM , aadA , and qnrS genes, which were responsible for resistance to tetracyclines, beta-lactams, aminoglycosides, and quinolones, respectively. The presence of these genes indicates the widespread spread of genetic resistance among food-related pathogens, which poses a serious threat to public health. Sarowska et al. examined the antibiotic resistance and pathogenicity of E. coli strains from poultry farms, retail meat, and human urinary tract infections. The strains showed significant resistance to a variety of antibiotic classes, including β-lactams, tetracyclines, aminoglycosides, fluoroquinolones, and sulfonamides, indicating the widespread selection pressure exerted by antibiotic use in poultry farming. E. coli strains from meat and poultry farms showed some commonalities with isolates causing human infections, suggesting the possibility that potentially pathogenic strains could be transmitted through the food chain. In the presented studies, the researchers highlight the urgent need for continuous monitoring of antibiotic resistance in animal products, along with the implementation of stricter sanitary standards in the food industry. The researchers emphasize educating producers and consumers about the risks of antibiotic resistance to minimize the risk of foodborne infections. Considering the changing resistance profiles, the researchers recommend regular monitoring and restriction of antibiotic use in agriculture, supported by stricter regulations to prevent the spread of resistant strains, especially Salmonella . Multidrug-resistant strains of Salmonella , which are increasingly resistant to tetracyclines, aminoglycosides, and beta-lactams, pose a serious threat to public health. Similarly, high levels of antibiotic resistance have been observed in Enterobacterales strains, including E. coli , isolated from raw meat and animal products. Particular attention was paid to ESBL and AmpC strains, highlighting the importance of reducing antibiotic use in animal husbandry and strengthening sanitary controls in meat processing. The study also highlights the importance of monitoring food safety and zoonotic infection risks to reduce the spread of multidrug-resistant pathogens via food. Alternatives to antibiotic therapy in agriculture and animal husbandry are increasingly being explored to combat the rising challenge of antimicrobial resistance and the negative environmental impacts of excessive antibiotic use . 6.1. Probiotics and Prebiotics Probiotics and prebiotics represent a promising alternative . Probiotics are live microorganisms, typically beneficial bacteria, which confer health benefits to the host when administered adequately . Several health and nutritional benefits have been observed to be provided to animals by probiotics. They promote animal growth and maturation and increase feed intake, digestibility, and performance . Other benefits include improved health outcomes and immune responses , egg production , meat yield and its quality , and milk composition and its production in ruminants . In turn, prebiotics are compounds that induce the growth or activity of beneficial microorganisms, particularly in the gut . When used together, as symbiotics, they promote gut health by enhancing the balance of gut microbiota, which is crucial for maintaining the immune system’s strength . According to Low et al. , these supplements can enhance animal health, improve feed efficiency, and boost growth without relying on antibiotics. This approach is particularly promising in preventing intestinal infections and supporting overall gut immunity, thereby reducing the need for antibiotic interventions. Gupta et al. suggested that symbiotics can help mitigate the need for antibiotics by boosting the animal’s natural defenses against infections. This dual approach is seen as an effective way to improve productivity and animal welfare without the overuse of antibiotics, particularly in poultry and swine production. Śmiałek et al. used a multispecies probiotic (Lavipan, JHJ, Poland) containing Lactococcus lactis , Carnobacterium divergens , Lactiplantibacillus casei , Lactiplantibacillus plantarum , and Saccharomyces cerevisiae in broiler feeding to effectively reduce contamination of poultry with Campylobacter spp. The use of the probiotic reduced colonization of the chickens’ digestive tract and reduced environmental and poultry carcass contamination. In addition, the probiotic supported the poultry’s immune system, improving carcass hygiene parameters and reducing the risk of pathogen transmission in the food chain. The results of the presented research highlight the potential of probiotics as an alternative to antibiotics in poultry farming, supporting sustainable agricultural practices and food safety . Future research should focus on multi-strain probiotic formulations tailored to specific livestock species and regional conditions. Advances in genetic engineering could lead to probiotics with enhanced functionalities, such as targeted pathogen inhibition or increased gut resilience . 6.2. Bacteriophages Bacteriophages (phages) are emerging as an innovative and natural alternative to traditional antibiotics, particularly in the battle against multidrug-resistant (MDR) bacteria. These viruses specifically infect and lyse bacterial cells, with a high degree of host specificity, making them valuable tools for targeting pathogenic bacteria without disrupting beneficial microbiota . In agriculture, phages are being explored for controlling bacterial infections in livestock and crops, offering environmentally friendly solutions. They can be administered via water, feed, or directly to infected plants or animals, making them versatile agents in sustainable farming systems . Recent advancements include genetically engineered phages and phage-derived enzymes like lysins, which significantly enhance antibacterial efficacy by breaking down bacterial cell walls. Such innovations have shown promise not only in agriculture but also in clinical settings for wound care and biofilm eradication, where MDR pathogens pose severe threats . Phage–antibiotic synergy (PAS) is another area of growing interest, where the combination of phages and sub-lethal doses of antibiotics enhances bacterial clearance while reducing the likelihood of resistance development . Phage therapy’s specificity is particularly advantageous in addressing biofilms, which are notoriously resistant to antibiotics. Phage cocktails, designed to target multiple bacterial strains, have shown substantial efficacy in disrupting biofilms in healthcare settings . Additionally, bacteriophages offer a unique potential for antivirulence strategies, where phage-induced bacterial resistance may simultaneously reduce bacterial fitness and virulence, further attenuating infections . Despite their vast potential, challenges persist. Regulatory barriers, the need for standardized safety profiles, and the risk of phage resistance require further research and policy development . Nevertheless, with advancements in genetic engineering and better understanding of phage biology, bacteriophages hold immense promise as versatile and sustainable alternatives to antibiotics in diverse applications. 6.3. Natural Compounds Natural compounds play a pivotal role in addressing the global challenge of antimicrobial resistance (AMR), as demonstrated by their diverse mechanisms of action and potential benefits widely discussed in the scientific literature. The use of natural compounds in combating antibiotic resistance is widely discussed in the scientific literature, demonstrating their various mechanisms of action and potential benefits. For example, polyphenolic compounds such as curcumin, resveratrol, and gallic acid can act as photosensitizers in photodynamic therapy, effectively destroying bacterial biofilms and aiding in the treatment of infections . Marine-derived products, on the other hand, offer unique chemical structures that can be effective against multidrug-resistant bacteria . Phytogenic compounds derived from medicinal plants, including essential oils, alkaloids, and phenolic compounds, have gained traction for their antimicrobial, antioxidant, and anti-inflammatory properties. These plant-based alternatives include essential oils, alkaloids, and phenolic compounds, which possess antimicrobial, antioxidant, and anti-inflammatory properties. Gao et al. explained that phenolic compounds from medicinal plants can inhibit bacterial growth and modulate the gut microbiome in animals, thus supporting health and growth. These natural extracts are also being studied for their role in enhancing the animal immune system, which further reduces the need for antibiotics . Phytogenic is seen as a sustainable alternative that can improve both animal welfare and productivity. The use of phytotherapeutics has pointed to their bactericidal properties and ability to reverse drug resistance, although challenges such as overexploitation of resources and climate impacts limit their wider use . Another innovative approach involves essential oils (EOs), which show multifaceted bactericidal activity and potential as coatings in me-too devices to prevent infections, highlighting their versatility and efficacy compared to synthetic antibiotics . Moreover, molecular docking studies of plant-derived compounds against specific pathogenic targets illustrate their untapped potential in combating protozoan and bacterial resistance . Plant extracts and secondary metabolites, such as terpenoids or alkaloids, also show promising antimicrobial activity, as detailed in reviews of their use as bioactive food preservatives and potential therapeutic candidates . 6.4. Enzymes and Peptides Another promising approach is the use of ribosomal antimicrobial peptides (AMPs), which disrupt bacterial processes and serve as a potential alternative to conventional antibiotics . AMPs are known for their multifunctional role in disrupting bacterial processes, offering a promising alternative to conventional antibiotics . AMPs, along with enzymes like lysozymes, can be incorporated into animal feed to reduce pathogenic bacteria in the gut and improve growth performance while avoiding resistance development . Enzymes and antimicrobial peptides also show great potential as alternatives to antibiotics. Enzymes, such as proteases and lysozymes, help break down microbial cell walls, while AMPs are small proteins found naturally in many organisms that exhibit broad-spectrum antimicrobial activity. Wang et al. emphasized that these compounds can be incorporated into animal feed to reduce pathogenic bacteria in the gut and improve the overall growth performance of animals. Synthetic AMPs offer a natural, non-toxic method of reducing pathogen loads without leading to resistance, making them an ideal candidate for replacing antibiotics in animal production systems . Zhang et al. highlighted synthetic AMPs as a promising advancement, combining stability with cost-effectiveness. In addition, natural products such as antimicrobial peptides and fungal-derived compounds offer new opportunities to modulate multidrug resistance . It is also important to consider biotechnological modifications of natural sources to increase their availability and effectiveness . Research on nano-antioxidants and phage therapy as additional methods to combat AMR is also groundbreaking . The past successes of naturally derived antibiotics underscore the importance of integrating traditional knowledge with modern research methods . All this evidence points to the crucial role of natural products in the development of future antimicrobial therapies. 6.5. Vaccines The research also observes the design of vaccines with the specific purpose of minimizing antibiotic resistance for specific groups of microorganisms. Śmiałek et al. indicated that the use of a live attenuated vaccine against E. coli can effectively reduce the use of antibiotics in broiler breeding. The use of the vaccine showed a significant reduction in the number of multi-resistant E. coli strains, increasing their sensitivity to antibiotics. At the same time, vaccinated broilers showed better production parameters, such as faster weight gain and lower mortality, and the vaccination did not adversely affect the effectiveness of other vaccines. The results suggest that the routine use of E. coli vaccine in immunoprophylaxis programs can help improve flock health, reduce the risk of antibiotic resistance, and improve production performance, which is crucial for sustainable poultry farming management . 6.6. Emerging Innovations One innovative solution is the use of nanoparticles (NPs), which exhibit antibacterial properties, raising hopes for their use in the fight against drug-resistant pathogens . Thanks to their properties, they not only have antibacterial effects themselves, but can also be carriers for antibiotics and natural antimicrobial compounds . Examples of such nanoparticles include Ag-NP, Zn-NP, Au-NP, Al-NP, Cu-NP, and Ti-NP, and metal oxide nanoparticles such as ZnO-NP, CdO-NP, CuO-NP, and TiO 2 -NP, among others. All these structures have shown effectiveness in destroying bacteria . A study by Joost et al. confirmed that treatment with TiO 2 nanoparticles can lead to an increase in the volume of bacterial cells, causing damage to their cell membranes and death. They have also been shown to be effective against multidrug-resistant (MDR) pathogens such as E. coli , K. pneumoniae , Pseudomonas aeruginosa , Acinetobacter baumannii , methicillin-resistant S. aureus , and E. faecalis . The mechanism involves the generation of reactive oxygen species (ROS), which leads to oxidative stress in pathogen cells . Nanoparticles are also being explored as carriers for antibiotics to increase the effectiveness of therapy and minimize the risk of developing bacterial resistance . The conjugation of antibiotics, such as ampicillin, kanamycin, or streptomycin, with gold NPs has achieved lower minimum inhibitory concentrations against Gram-positive and Gram-negative bacteria than with the drugs used alone . Similarly, vancomycin-loaded gold nanoparticles showed enhanced efficacy against strains resistant to this antibiotic by disrupting the stability of bacterial cell membranes . Studies have also shown that bimetallic nanoparticles, such as combinations of two different metals, are more effective than their monometallic counterparts . They have better electron, optical, and catalytic properties, which translates into many times greater efficacy against MDR pathogens while reducing the required therapeutic dose The growing focus on alternatives to antibiotics in agriculture and animal husbandry is a response to the urgent need to combat AMR and reduce the environmental footprint of traditional farming practices. Probiotics, prebiotics, vaccines, phage therapy, medicinal plant extracts, enzymes, and antimicrobial peptides all represent promising tools in this effort. These strategies help maintain animal health, improve productivity, and reduce dependency on antibiotics, thus offering a sustainable path forward for the agricultural industry. Probiotics and prebiotics represent a promising alternative . Probiotics are live microorganisms, typically beneficial bacteria, which confer health benefits to the host when administered adequately . Several health and nutritional benefits have been observed to be provided to animals by probiotics. They promote animal growth and maturation and increase feed intake, digestibility, and performance . Other benefits include improved health outcomes and immune responses , egg production , meat yield and its quality , and milk composition and its production in ruminants . In turn, prebiotics are compounds that induce the growth or activity of beneficial microorganisms, particularly in the gut . When used together, as symbiotics, they promote gut health by enhancing the balance of gut microbiota, which is crucial for maintaining the immune system’s strength . According to Low et al. , these supplements can enhance animal health, improve feed efficiency, and boost growth without relying on antibiotics. This approach is particularly promising in preventing intestinal infections and supporting overall gut immunity, thereby reducing the need for antibiotic interventions. Gupta et al. suggested that symbiotics can help mitigate the need for antibiotics by boosting the animal’s natural defenses against infections. This dual approach is seen as an effective way to improve productivity and animal welfare without the overuse of antibiotics, particularly in poultry and swine production. Śmiałek et al. used a multispecies probiotic (Lavipan, JHJ, Poland) containing Lactococcus lactis , Carnobacterium divergens , Lactiplantibacillus casei , Lactiplantibacillus plantarum , and Saccharomyces cerevisiae in broiler feeding to effectively reduce contamination of poultry with Campylobacter spp. The use of the probiotic reduced colonization of the chickens’ digestive tract and reduced environmental and poultry carcass contamination. In addition, the probiotic supported the poultry’s immune system, improving carcass hygiene parameters and reducing the risk of pathogen transmission in the food chain. The results of the presented research highlight the potential of probiotics as an alternative to antibiotics in poultry farming, supporting sustainable agricultural practices and food safety . Future research should focus on multi-strain probiotic formulations tailored to specific livestock species and regional conditions. Advances in genetic engineering could lead to probiotics with enhanced functionalities, such as targeted pathogen inhibition or increased gut resilience . Bacteriophages (phages) are emerging as an innovative and natural alternative to traditional antibiotics, particularly in the battle against multidrug-resistant (MDR) bacteria. These viruses specifically infect and lyse bacterial cells, with a high degree of host specificity, making them valuable tools for targeting pathogenic bacteria without disrupting beneficial microbiota . In agriculture, phages are being explored for controlling bacterial infections in livestock and crops, offering environmentally friendly solutions. They can be administered via water, feed, or directly to infected plants or animals, making them versatile agents in sustainable farming systems . Recent advancements include genetically engineered phages and phage-derived enzymes like lysins, which significantly enhance antibacterial efficacy by breaking down bacterial cell walls. Such innovations have shown promise not only in agriculture but also in clinical settings for wound care and biofilm eradication, where MDR pathogens pose severe threats . Phage–antibiotic synergy (PAS) is another area of growing interest, where the combination of phages and sub-lethal doses of antibiotics enhances bacterial clearance while reducing the likelihood of resistance development . Phage therapy’s specificity is particularly advantageous in addressing biofilms, which are notoriously resistant to antibiotics. Phage cocktails, designed to target multiple bacterial strains, have shown substantial efficacy in disrupting biofilms in healthcare settings . Additionally, bacteriophages offer a unique potential for antivirulence strategies, where phage-induced bacterial resistance may simultaneously reduce bacterial fitness and virulence, further attenuating infections . Despite their vast potential, challenges persist. Regulatory barriers, the need for standardized safety profiles, and the risk of phage resistance require further research and policy development . Nevertheless, with advancements in genetic engineering and better understanding of phage biology, bacteriophages hold immense promise as versatile and sustainable alternatives to antibiotics in diverse applications. Natural compounds play a pivotal role in addressing the global challenge of antimicrobial resistance (AMR), as demonstrated by their diverse mechanisms of action and potential benefits widely discussed in the scientific literature. The use of natural compounds in combating antibiotic resistance is widely discussed in the scientific literature, demonstrating their various mechanisms of action and potential benefits. For example, polyphenolic compounds such as curcumin, resveratrol, and gallic acid can act as photosensitizers in photodynamic therapy, effectively destroying bacterial biofilms and aiding in the treatment of infections . Marine-derived products, on the other hand, offer unique chemical structures that can be effective against multidrug-resistant bacteria . Phytogenic compounds derived from medicinal plants, including essential oils, alkaloids, and phenolic compounds, have gained traction for their antimicrobial, antioxidant, and anti-inflammatory properties. These plant-based alternatives include essential oils, alkaloids, and phenolic compounds, which possess antimicrobial, antioxidant, and anti-inflammatory properties. Gao et al. explained that phenolic compounds from medicinal plants can inhibit bacterial growth and modulate the gut microbiome in animals, thus supporting health and growth. These natural extracts are also being studied for their role in enhancing the animal immune system, which further reduces the need for antibiotics . Phytogenic is seen as a sustainable alternative that can improve both animal welfare and productivity. The use of phytotherapeutics has pointed to their bactericidal properties and ability to reverse drug resistance, although challenges such as overexploitation of resources and climate impacts limit their wider use . Another innovative approach involves essential oils (EOs), which show multifaceted bactericidal activity and potential as coatings in me-too devices to prevent infections, highlighting their versatility and efficacy compared to synthetic antibiotics . Moreover, molecular docking studies of plant-derived compounds against specific pathogenic targets illustrate their untapped potential in combating protozoan and bacterial resistance . Plant extracts and secondary metabolites, such as terpenoids or alkaloids, also show promising antimicrobial activity, as detailed in reviews of their use as bioactive food preservatives and potential therapeutic candidates . Another promising approach is the use of ribosomal antimicrobial peptides (AMPs), which disrupt bacterial processes and serve as a potential alternative to conventional antibiotics . AMPs are known for their multifunctional role in disrupting bacterial processes, offering a promising alternative to conventional antibiotics . AMPs, along with enzymes like lysozymes, can be incorporated into animal feed to reduce pathogenic bacteria in the gut and improve growth performance while avoiding resistance development . Enzymes and antimicrobial peptides also show great potential as alternatives to antibiotics. Enzymes, such as proteases and lysozymes, help break down microbial cell walls, while AMPs are small proteins found naturally in many organisms that exhibit broad-spectrum antimicrobial activity. Wang et al. emphasized that these compounds can be incorporated into animal feed to reduce pathogenic bacteria in the gut and improve the overall growth performance of animals. Synthetic AMPs offer a natural, non-toxic method of reducing pathogen loads without leading to resistance, making them an ideal candidate for replacing antibiotics in animal production systems . Zhang et al. highlighted synthetic AMPs as a promising advancement, combining stability with cost-effectiveness. In addition, natural products such as antimicrobial peptides and fungal-derived compounds offer new opportunities to modulate multidrug resistance . It is also important to consider biotechnological modifications of natural sources to increase their availability and effectiveness . Research on nano-antioxidants and phage therapy as additional methods to combat AMR is also groundbreaking . The past successes of naturally derived antibiotics underscore the importance of integrating traditional knowledge with modern research methods . All this evidence points to the crucial role of natural products in the development of future antimicrobial therapies. The research also observes the design of vaccines with the specific purpose of minimizing antibiotic resistance for specific groups of microorganisms. Śmiałek et al. indicated that the use of a live attenuated vaccine against E. coli can effectively reduce the use of antibiotics in broiler breeding. The use of the vaccine showed a significant reduction in the number of multi-resistant E. coli strains, increasing their sensitivity to antibiotics. At the same time, vaccinated broilers showed better production parameters, such as faster weight gain and lower mortality, and the vaccination did not adversely affect the effectiveness of other vaccines. The results suggest that the routine use of E. coli vaccine in immunoprophylaxis programs can help improve flock health, reduce the risk of antibiotic resistance, and improve production performance, which is crucial for sustainable poultry farming management . One innovative solution is the use of nanoparticles (NPs), which exhibit antibacterial properties, raising hopes for their use in the fight against drug-resistant pathogens . Thanks to their properties, they not only have antibacterial effects themselves, but can also be carriers for antibiotics and natural antimicrobial compounds . Examples of such nanoparticles include Ag-NP, Zn-NP, Au-NP, Al-NP, Cu-NP, and Ti-NP, and metal oxide nanoparticles such as ZnO-NP, CdO-NP, CuO-NP, and TiO 2 -NP, among others. All these structures have shown effectiveness in destroying bacteria . A study by Joost et al. confirmed that treatment with TiO 2 nanoparticles can lead to an increase in the volume of bacterial cells, causing damage to their cell membranes and death. They have also been shown to be effective against multidrug-resistant (MDR) pathogens such as E. coli , K. pneumoniae , Pseudomonas aeruginosa , Acinetobacter baumannii , methicillin-resistant S. aureus , and E. faecalis . The mechanism involves the generation of reactive oxygen species (ROS), which leads to oxidative stress in pathogen cells . Nanoparticles are also being explored as carriers for antibiotics to increase the effectiveness of therapy and minimize the risk of developing bacterial resistance . The conjugation of antibiotics, such as ampicillin, kanamycin, or streptomycin, with gold NPs has achieved lower minimum inhibitory concentrations against Gram-positive and Gram-negative bacteria than with the drugs used alone . Similarly, vancomycin-loaded gold nanoparticles showed enhanced efficacy against strains resistant to this antibiotic by disrupting the stability of bacterial cell membranes . Studies have also shown that bimetallic nanoparticles, such as combinations of two different metals, are more effective than their monometallic counterparts . They have better electron, optical, and catalytic properties, which translates into many times greater efficacy against MDR pathogens while reducing the required therapeutic dose The growing focus on alternatives to antibiotics in agriculture and animal husbandry is a response to the urgent need to combat AMR and reduce the environmental footprint of traditional farming practices. Probiotics, prebiotics, vaccines, phage therapy, medicinal plant extracts, enzymes, and antimicrobial peptides all represent promising tools in this effort. These strategies help maintain animal health, improve productivity, and reduce dependency on antibiotics, thus offering a sustainable path forward for the agricultural industry. Antimicrobial resistance in meat and meat products in Poland presents several challenges for public health, food safety, and environmental sustainability that require a more critical and coordinated approach. In Poland, the increasing prevalence of antibiotic-resistant bacteria in meat and meat products underscores the critical need for effective strategies to mitigate the spread of resistance. Microorganisms such as Campylobacter spp., Staphylococcus spp., Enterococcus spp., L. monocytogenes , and Enterobacterales (including Salmonella spp. and E. coli ) are commonly found in animal farming environments and food products, often exhibiting resistance to multiple classes of antibiotics. Current data on AMR are limited to isolated studies, with a lack of comprehensive nationwide surveillance, which hampers our understanding of resistance patterns across different regions and food products. The cited research results highlight the critical need for a multifaceted approach to antimicrobial resistance management in Poland, including stricter controls on antibiotic use in animal husbandry, improved monitoring of resistance patterns and the promotion of alternative strategies to reduce antibiotic dependence. Additionally, inconsistent application of monitoring systems and weak regulatory enforcement on antibiotic usage in livestock production contribute to the persistence of AMR. The environmental impact of farming practices, particularly the contamination of soil and water with resistant bacteria and genes, remains under-researched but is likely a significant pathway for the spread of AMR. To address these issues, future efforts must focus on establishing a standardized, nationwide surveillance system for monitoring both antibiotic usage and resistance in livestock. Moreover, further research is needed to understand the environmental persistence of AMR, particularly in regions with intensive farming operations. There is also a growing need for alternatives to antibiotics, such as probiotics, phage therapy, and antimicrobial peptides, to reduce dependency on traditional antibiotics in agriculture. Strengthening regulatory frameworks, improving compliance with EU standards, and raising awareness about the risks of AMR among farmers and veterinarians will be crucial. By focusing on these areas, Poland can make significant progress in controlling the spread of AMR in its food systems and protecting public health and the environment. |
A Systematic Review of Parkinson’s Disease Pharmacogenomics: Is There Time for Translation into the Clinics? | 501653ea-8ba6-4907-983b-a32a86395495 | 8268929 | Pharmacology[mh] | Parkinson’s disease (PD) is the second most common neurodegenerative disease present today. The incidence and prevalence are highest in the population aged ≥65 years old, making the disease a significant public health burden in the elderly . The clinical course of the disease is progressive and is defined by motor symptoms such as resting tremor, bradykinesia and rigidity, along with a wide variety of non-motor symptoms such as autonomic dysfunction, sleep disorders, cognitive deficits and behavioural changes . The first symptoms appear several years before the classic motor symptoms during the prodromal PD, which is marked by non-specific symptoms like constipation and insomnia . Our understanding of underlying mechanisms in PD has significantly increased over recent years. The main postulated pathological mechanisms in PD include the intracellular aggregation of α-synuclein, which form Lewy bodies , as well as the loss of dopaminergic neurons, which first happens in the substantia nigra but later becomes more widespread as the disease progresses . The landmark paper published by Braak et al. describes a gradually evolving pathological severity, starting from the lower brainstem, with a progression to the limbic and neocortical brain regions in the later stages of PD . The variation of clinical states between patients can be significant, even though the underlying mechanisms are similar. Efforts have been made to categorize the disease into varying subtypes. Seyed-Mohammad et al. propose three subtypes based predominantly on clinical characteristics: the mild motor, intermediate and diffuse malignant subtypes. Importantly, findings from the study indicated that neuroimaging correlated better with the subtypes than genetic information, even after incorporating a single “genetic risk score” that encompassed 30 specific PD-related mutations. However, this could also be a consequence of a lack of patients with particular variations in the population they studied . The need to categorize the disease comes from its variability in presentation, response to treatment and incidence of side-effects. Current treatment options for PD are plentiful, at least in comparison to other neurodegenerative diseases, and offer PD patients extended control of symptom severity as well as an improved quality of life. Unfortunately, no treatment halts the pathological mechanisms that drive disease progression, with most treatment being focused on replacing or enhancing dopamine availability. The golden standard in pharmacologic therapy is dopamine replacement therapy, mainly levodopa, used in synergy with dopamine receptor agonists, monoamine oxidase (MAO) inhibitors or catechol-O-methyltransferase (COMT) inhibitors . The challenge that stems from this type of therapy is the delicate balance between the beneficial and harmful effects that can arise . There is a significant variation in therapy response and side-effect incidence in treating PD, which can be linked to the varied subtypes mentioned earlier, along with increasing evidence of complex environmental and genetic factor interaction . The consequence of this is the need to fine-tune and personalize the therapy to each patient to account for the variability in drug response . As most treatment is focused on L-dopa, understanding the key players in its metabolism has put the research focus in pharmacogenomics on genes that influence the enzymes and receptors in this pathway . The general principles and goals of pharmacogenomics are to identify the genetic factors behind the varied drug response in individuals, thereby predicting response and paving the way for personalised medicine . The two main areas where the variability of drug response is studied are known as pharmacokinetics and pharmacodynamics. Pharmacokinetics incorporates all processes that affect drug absorption, distribution and metabolism in the body as well as its excretion, while pharmacodynamics focuses on the target actions of the drug. Current evidence suggests that genetic variability and its effects on drug characteristics are concentrated in three major steps: the initial pharmacokinetic processes that ultimately affect the plasma concentration, the capability of drugs in passing the blood-brain barrier (BBB) and finally, the modification of target pharmacodynamic properties of the drug . Expanding the knowledge of the variations that affect these three factors will pave the way for predicting drug response, thus furthering the benefit of a personalized medicine approach in all diseases. Unfortunately, there are currently no clinical guidelines regarding the use of pharmacogenomics in the clinical practice of treating PD, with sparse clinical annotations on relevant databases . Therefore, our aim is to assess the current state of knowledge in this field and the possibility of translation into the clinics.
Current treatment in PD is focused on alleviating the symptoms and does little to slow down the pathophysiological progression of the disease. As such, the therapy goal is to increase the amount of dopamine to compensate for the loss of dopaminergic neurons. The therapeutic of choice for this is levodopa (L-dopa), which relieves the motor symptoms by increasing the availability of dopamine in the central nervous system (CNS) . All the current pharmaceutical treatment options centre around the dopamine metabolic pathway, which encompasses many genetic pathways. However, there are specific pharmacogenomic properties for different treatment options, as well as differences in pharmacogenomic properties in genotype driven PD. 2.1. Drug Specific Pharmacogenomic Properties 2.1.1. Pharmacogenomics of the Therapeutic Response to L-dopa Clinically, L-dopa is always combined with dopa decarboxylase (DDC) inhibitors, which causes a switch in L-dopa metabolism to the COMT pathway, thereby increasing the bioavailability of L-dopa in the CNS . The genetic variability of several genes has been implicated in the varied response to L-dopa. COMT gene is a protein-coding gene that provides instructions for creating the COMT enzyme, and its polymorphisms are involved in the varied response to numerous CNS diseases and treatments . The most studied polymorphism of the COMT gene is rs4680 (G>A), which results in a valine to methionine substitution at codon 158 (Val158Met). Single nucleotide polymorphisms of the COMT gene form haplotypes that result in lower (A_C_C_G), medium (A_T_C_A) and higher (G_C_G_G) enzyme activity, which, in the case of higher activity, had an impact on the required dosage compared to noncarriers . Studies have shown that the higher dosage is required during chronic administration in patients with greater COMT activity, while acute L-dopa administration was unchanged . Similar changes were observed in a recent study by Sampaio et al., where higher COMT enzyme activity was linked to higher doses of L-dopa required, while no significant changes in dosage were found in lower COMT enzymatic activity compared to the control . Common characteristics of patients that required the higher L-dopa dosage in multiple studies were advanced PD and earlier onset. A contradicting result was published in patients of Korean origins, with no significant association between the rs4680 polymorphism and the response to L-dopa; however, the study population did not have a considerable number of patients with advanced PD . Higher L-dopa doses were needed for patients with Solute Carrier Family 22 Member 1 (SLC22A1) gene rs622342A>C polymorphism that encodes the Organic Cation Transporter 1, along with the patients having higher mortality than the control population . On the other hand, lower required doses of L-dopa were found in patients with Synaptic vesicle glycoprotein 2C (SV2C) rs30196 polymorphism, as well as in Solute Carrier Family 6 Member 3 (SLC6A3) polymorphism after multivariate analysis . 2.1.2. Pharmacogenomics of the Side-Effects to L-dopa Increased incidence of adverse events in L-dopa treatment has been linked with various gene polymorphisms. Although the variations in COMT enzymatic activity on the onset of adverse events is still under debate, several studies have linked the lower COMT enzymatic activity to the increased incidence of motor complications such as dyskinesia, especially in advanced PD . Hypothetically, more moderate COMT enzymatic activity could lead to inadequate dopamine inactivation and the accumulation of dopamine in the synaptic cleft, thereby causing the dyskinesias. The same result was not replicated in studies by Watanabe et al. and Contin et al. . There is some evidence that the activation of the Mechanistic target of rapamycin (mTOR) signaling pathway contributes to L-dopa induced dyskinesia. It was indicative of earlier animal studies that the inhibition of mTOR pathways reduces the L-dopa related dyskinesia, most likely due to impaired metabolic homeostasis . These findings were corroborated in a recent human study, by Martin-Flores et al., that found significant associations with several SNPs affecting the mTOR pathway, indicating that the mTOR pathway contributes genetically to L-dopa induced dyskinesia susceptibility . Similarly, a functional Brain derived neurotrophic factor (BDNF) Val66Met polymorphism can lead to aberrant synaptic plasticity, which has been associated with L-dopa induced dyskinesia in a single study by Foltynie et al. . Limited evidence has been found in favour of a protective function of the Dopamine receptor 1 (DRD1) (rs4532) SNP, shown in a single study by Dos Santos et al. . The effect of Dopamine receptor 2 (DRD2) SNP’s on dyskinesia is a point of contention in current literature, as some studies indicate an increased risk of developing dyskinesia , while others revealed a protective effect on the incidence of dyskinesia . Interestingly, both studies that show reduced dyskinesias were conducted in the Italian population with the polymorphism DRD2 CAn-STR. Increased risk for developing L-dopa induced dyskinesia was seen in the Dopamine receptor 3 (DRD3) rs6280 polymorphism in a Korean population . However, opposing results were found by three research groups, with no evidence of correlation between DRD3 genetic polymorphisms and incidence of dyskinesias . Lower risk of L-dopa-associated dyskinesias was found in patients with Homer protein homolog 1 (HOMER1 ) rs4704560 G allele polymorphism . Finally, incidence of L-dopa induced dyskinesias was studied for the dopamine transporter gene (DAT) , where the presence of two genotypes 10R/10R (rs28363170) and A carrier (rs393795) led to a reduced risk of dyskinesias in an Italian population . Hyperhomocysteinemia is a known complication of L-dopa treatment in PD. The potential dangers of elevated plasma homocysteine are systemic, and include cardiovascular risk, increased risk for dementia and impaired bone health . A SNP C667T (rs1801133) in the MTHFR gene is consistently being linked to hyperhomocysteinemia due to L-dopa treatment in several studies. The result of this mutation is a temperature-labile MTHFR enzyme, which ultimately leads to hyperhomocysteinemia . In addition, a study by Gorgone et al. showed that elevated homocysteine levels lead to systemic oxidative stress in patients with this polymorphism . A recent study by Yuan et al. further adds to the claim that homocysteine levels are affected by L-dopa administration, especially in 677C/T and T/T genotypes . A possible option for homocysteine level reduction and alleviation of systemic oxidative stress is the addition of COMT inhibitors to the therapy, which presents a clear possibility for translation of this knowledge into the treatment of patients . There is contradicting evidence regarding whether COMT polymorphisms can influence the incidence of daytime sleepiness in PD patients, with differing results of the pilot and follow-up studies conducted by the same authors . Two additional studies by the same primary author revealed an association between sudden-sleep onset and the polymorphisms in hypocretin and DRD2, which was unrelated to a specific drug . Furthermore, increased risk of sleep attacks was found in Dopamine receptor 4 (DRD4) 48-bp VNTR polymorphism in a German population . The L-dopa adverse effects affecting emetic activity are not uncommon in PD treatment. DRD2 and DRD3 polymorphisms both showed an association with an increased risk of developing gastrointestinal adverse effects that do not respond well to therapy in a Brazilian population . However, that has not been reproduced in a recent study in a Slovenian population by Redenšek et al. . Mental and cognitive adverse effects of L-dopa are common due to the shared physiological dopaminergic pathways. A significant interaction was found between L-dopa and the COMT gene polymorphism in causing a detrimental effect on the activity in task-specific regions of the pre-frontal cortex due to altered availability of dopamine . Interestingly, carriers of at least one COMT rs165815 C allele had a decreased risk of developing visual hallucinations . In the same study carriers of the DRD3 rs6280 C allele had higher odds of developing visual hallucinations , which is in line with a previous study published by Goetz et al. . Increased risk of developing hallucinations is seen in patients with polymorphisms in the DRD2 gene , cholecystokinin gene and HOMER1 rs4704559 A allele , which encodes a protein that possesses a vital function for synaptic plasticity and glutamate signaling. On the other hand, the HOMER 1 rs4704559 G allele appears to decrease the risk of visual hallucinations . Furthermore, several studies link BDN F Val66Met polymorphism to impaired cognitive functioning in PD, but it appears to be irrespective of dopamine replacement therapy and is a genotype-specific trait . Impulse control disorder (ICD) is a well-known complication that can occur in some PD patients after initiating dopamine replacement therapy by either L-dopa or dopamine agonists . Heritability of ICD in a cohort of PD patients has been estimated at 57%, particularly for Opioid Receptor Kappa 1 (OPRK1) , 5-Hydroxytryptamine Receptor 2A (HTR2a) and Dopa decarboxylase (DDC) genotypes . A recent study found a suggestive association for developing ICD in variants of the opioid receptor gene OPRM1 and the DAT gene . Furthermore, there is evidence that polymorphisms in DRD1 (rs4857798, rs4532, rs265981), DRD2/ANKK1 (rs1800497) and glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B) (rs7301328) bear an increased risk of developing ICD . The DRD3 (rs6280) mutation has also been linked with increased incidence of ICD with L-dopa therapy in studies by Lee et al. and Castro-Martinez et al. . On the other hand, there was no significant association found in COMT Val158Met and DRD2 Taq1A polymorphisms . Even though current data suggest high heritability for developing ICD after initiating dopamine replacement therapy, it should be noted that the effects of individual genes are small, and the development is most likely multigenic. 2.1.3. Dopamine Receptor Agonists Dopamine receptor agonists (DAs) are often the first therapies initiated in PD patients and are the main alternative to L-dopa . The effectiveness of DAs is lower than L-dopa, and most patients discontinue treatment within three years. Some significance has been found in polymorphisms of the DRD2 and DRD3 genes that could influence drug effectiveness and tolerability. A retrospective study by Arbouw et al. revealed that a DRD2 (CA)n-repeat polymorphism is linked with a decreased discontinuation of non-ergoline DA treatment, although the sample size in this study was small . A pilot study that included Chinese PD patients revealed that the DRD3 Ser9Gly (rs6280) polymorphism is associated with a varied response to pramipexole , which has since been confirmed in a recent study by Xu et al. . Interestingly, the same polymorphism has also been linked with depression severity in PD, indicating that in DRD3 Ser9Gly patients with Ser/Gly and Gly/Gly genotypes more care should be given to adjusting therapy and caring for non-motor complications . Furthermore, there is evidence from the aforementioned studies that DRD2 Taq1A polymorphism does not play a significant role in response to DA treatment . On the other hand, certain Taq1A polymorphisms (rs1800497) have been associated with differences in critical cognitive control processes depending on allele expression . As mentioned earlier, another crucial pharmacogenomic characteristic of DA to bear in mind when administering therapy is the possibility of genotype driven impulse control disorders, which is a problem, especially in de-novo PD patients starting DA therapy . Genetic model of polymorphisms in DRD1 (rs5326), OPRK1 (rs702764), OPRM1 (rs677830) and COMT (rs4646318) genes had a high prediction of ICD in patients of DA therapy (AUC of 0.70 (95% CI: 0.61–0.79) . 2.1.4. COMT Inhibitors COMT inhibitors are potent drugs that increase the bioavailability of L-dopa by stopping the physiological O-methylation of levodopa to its metabolite 3-O-methyldopa, and can work in tandem with DDC inhibitors . Similar to L-dopa, the presence of the previously mentioned rs4608 COMT gene polymorphism modified the motor response to COMT inhibitors entacapone in a small-sample study . Patients with higher COMT enzyme activity had greater response compared to patients with lower COMT enzyme activity during the acute challenge with entacapone . Subsequent studies have not found clinically significance in repeated administration of either entacapone or tolcapone , with the impact on opicapone still unknown, meriting further study. Increased doses of carbidopa combined with levodopa and entacapone can improve “off” times, which was shown in a recent randomized trial by Trenkwalder et al., with an even more pronounced effect in patients that had higher COMT enzymatic activity due to COMT gene polymorphisms . Pharmacokinetic studies have shown that COMT inhibitors are metabolized in the liver by glucuronidation, in particular by UDP-glucuronyltransferase UGT1A and UGT1A9 enzymes . Hepatotoxicity is a known rare side-effect of tolcapone , with only sparse reports of entacapone hepatotoxicity . Several studies indicate that SNPs in the UGT1A and UGT1A9 are responsible for these adverse events, which can cause inadequate metabolism and subsequent damage to the liver by the drugs . Interestingly, opicapone has not demonstrated evident hepatotoxicity related adverse events, while in-vitro studies show a favorable effect on hepatocytes when compared to entacapone and tolcapone . 2.1.5. MAO Inhibitors MAO inhibitors are used with L-dopa to extend its duration due to reduced degradation in the CNS. Most MAO inhibitors used today in PD treatment (e.g., selegiline, rasagiline) are focused on blocking the MAO-B enzyme that is the main isoform responsible for the degradation of dopamine . There have not been many studies performed to assess MAO inhibitor pharmacogenetic properties. Early clinical studies with rasagiline did reveal an inter-individual variation in the quality of response that could not be adequately explained at that time . Masellisi et al. conducted an extensive study using the ADAGIO study data to identify possible genetic determinants that can alter the response to rasagiline. They identified two SNPs on the DRD2 gene that were associated with statistically significant improvement of both motor and mental functions after 12 weeks of treatment . 2.2. Genotype Specific Treatment and Pharmacogenomic Properties Gene variations that influence pharmacogenomic properties and treatment in PD are not only focused on the metabolic and activity pathways of the drugs. There is a wide number of genes that are linked to monogenic PD, but only some had their association proven continuously in various research studies. Mutations in the genes coding α-Synuclein (SNCA) , Leucine-rich repeat kinase 2 (LRRK2) , vacuolar protein sorting-associated protein 35 (VPS35) , parkin RBR E3 ubiquitin-protein ligase (PRKN) , PTEN-induced putative kinase 1 (PINK1) , glucocerebrosidase (GBA) and oncogene DJ-1 have mostly been found before the onset of genome-wide association studies, while many candidate genes found after are yet to be definitively proven to cause a significant risk for PD. Importantly, the currently known candidate genes can explain only a small fraction of cases where there is a known higher familial incidence of PD . It is remarkable, however, that assessing polygenic risk scores and combining those with specific clinical parameters can yield impressive sensitivity of 83.4% and specificity of 90% . The unfortunate consequence of the rapid expansion of knowledge in the field and amount of target genes is that the studies assessing pharmacogenomics of these gene variants are not keeping up. 2.2.1. LRRK2 Current evidence, albeit limited, points to differences in treatment response between various genotypes of monogenic PD. Mutations in the LRRK2 gene are known to cause familial PD, especially in North African and Ashkenazi Jew populations . LRRK2 protein has a variety of physiological functions in intracellular trafficking and cytoskeleton dynamics, along with a substantial role in the cells of innate immunity. It is yet unclear how mutations in LRRK2 influence the pathogenesis of PD, but there is numerous evidence that links it to a disorder in cellular homeostasis and subsequent α-synuclein aggregation . Results in in vitro and in vivo animal model studies for inhibition of mutant LRRK2 are promising, and in most cases, confirm a reduced degeneration of dopaminergic neurons . The biggest challenge of human trials has been creating an LRRK2 inhibitor that can pass the blood-brain barrier, which was overcome by Denali Therapeutics, and the phase-1b trial for their novel LRRK2 inhibitor has been completed and is awaiting official results . Furthermore, LRRK2 -associated PD has a similar response to L-dopa compared to sporadic PD, with conflicting results for the possible earlier development of motor symptoms . Pharmacogenomics in LRRK2 associated PD are linked to specific genotype variants. G2019S and G2385R variants in LRRK2 have been linked as predictors of motor complications due to L-dopa treatment, along with requiring higher doses during treatment . On the other hand, G2019S carrier status did not influence the prevalence of L-dopa induced dyskinesias in a study by Yahalom et al. . Furthermore, a study covering the pharmacogenetics of Atremorine, a novel bioproduct with neuroprotective effects of dopaminergic neurons, found that LRRK2 associated PD patients had a more robust response to the compound, along with several genes that cover metabolic and detoxification pathways . 2.2.2. SNCA SNCA gene encodes the protein α-synuclein, now considered a central player in the pathogenesis of PD due to its aggregation into Lewy-bodies. SNP’s in the SNC A gene are consistently linked to an increased risk of developing PD in GWAS studies in both familial and even sporadic PD . In cases of autosomal dominant mutations, there is a solid L-dopa and classical PD treatment response, albeit with early cognitive and mental problems, akin to GBA mutations . There are several planned therapeutic approaches suited for SNCA polymorphism genotypes which include: targeted monoclonal antibody immunotherapy of α-synuclein , downregulation of SNCA expression by targeted DNA editing and RNA interference of SNCA . Roche Pharmaceuticals has developed an anti-α-synuclein monoclonal antibody which is in a currently ongoing phase two of clinical trials . Two other methods are still in preclinical testing, and their development shows promise for the future. 2.2.3. GBA Glucocerebrosidase mutations represent a known risk factor for developing PD. GBA mutation associated PD is characterized by the earlier onset of the disease, followed by a more pronounced cognitive deficit and a significantly higher risk of dementia . Gaucher’s disease (GD) is an autosomal recessive genetic disorder that also arises from mutations in the GBA gene. The current enzyme replacement and chaperone treatment options for systemic manifestations of GD are not effective enough in treating the neurological manifestations of the disease as they are not able to reach the CNS . Three genotype-specific therapies to address the cognitive decline are currently being tested with promising early results, with two focusing on the chaperones ambroxol and LTI-291 to increase glucocerebrosidase activity and the third focusing on reducing the levels of glucocerebrosidase with ibiglustat . There is growing evidence that GBA associated PD is often marked by rapid progression with many hallmarks of advanced PD, such as higher L-dopa daily dose required to control motor symptoms . However, current research does not show a significant influence of GBA mutations on L-dopa response properties with adequate motor symptom control . A single study by Lesage et al. in a population of European origin linked a higher incidence of L-dopa induced dyskinesias in GBA-PD patients , but that has not been replicated in a more recent study by Zhang et al. in a population of Chinese origin . 2.2.4. PRKN/PINK1/DJ1 Mutations in the PRKN gene can lead to early onset PD, characterized by a clinically typical form of PD that is often associated with dystonia and dyskinesia . Patients with PRKN mutations generally have excellent and sustained responses to L-dopa, even in lower doses than in sporadic PD . Dyskinesias can occur early on in the course of the disease with very low doses of L-dopa , while dystonia in these patients was not found to be linked to L-dopa treatment . Furthermore, patients with PINK1 mutations have a similar disease course as PRKN mutation carriers, with a good response to L-dopa treatment, but early dystonia and L-dopa induced dyskinesias . Pharmacogenomic properties and genotype-specific treatment of several other gene mutations in PD such as VPS35 and DJ1 have not yet been characterized fully due to the rarity of cases and are currently a focus of several studies that as of writing do not have preliminary results available .
2.1.1. Pharmacogenomics of the Therapeutic Response to L-dopa Clinically, L-dopa is always combined with dopa decarboxylase (DDC) inhibitors, which causes a switch in L-dopa metabolism to the COMT pathway, thereby increasing the bioavailability of L-dopa in the CNS . The genetic variability of several genes has been implicated in the varied response to L-dopa. COMT gene is a protein-coding gene that provides instructions for creating the COMT enzyme, and its polymorphisms are involved in the varied response to numerous CNS diseases and treatments . The most studied polymorphism of the COMT gene is rs4680 (G>A), which results in a valine to methionine substitution at codon 158 (Val158Met). Single nucleotide polymorphisms of the COMT gene form haplotypes that result in lower (A_C_C_G), medium (A_T_C_A) and higher (G_C_G_G) enzyme activity, which, in the case of higher activity, had an impact on the required dosage compared to noncarriers . Studies have shown that the higher dosage is required during chronic administration in patients with greater COMT activity, while acute L-dopa administration was unchanged . Similar changes were observed in a recent study by Sampaio et al., where higher COMT enzyme activity was linked to higher doses of L-dopa required, while no significant changes in dosage were found in lower COMT enzymatic activity compared to the control . Common characteristics of patients that required the higher L-dopa dosage in multiple studies were advanced PD and earlier onset. A contradicting result was published in patients of Korean origins, with no significant association between the rs4680 polymorphism and the response to L-dopa; however, the study population did not have a considerable number of patients with advanced PD . Higher L-dopa doses were needed for patients with Solute Carrier Family 22 Member 1 (SLC22A1) gene rs622342A>C polymorphism that encodes the Organic Cation Transporter 1, along with the patients having higher mortality than the control population . On the other hand, lower required doses of L-dopa were found in patients with Synaptic vesicle glycoprotein 2C (SV2C) rs30196 polymorphism, as well as in Solute Carrier Family 6 Member 3 (SLC6A3) polymorphism after multivariate analysis . 2.1.2. Pharmacogenomics of the Side-Effects to L-dopa Increased incidence of adverse events in L-dopa treatment has been linked with various gene polymorphisms. Although the variations in COMT enzymatic activity on the onset of adverse events is still under debate, several studies have linked the lower COMT enzymatic activity to the increased incidence of motor complications such as dyskinesia, especially in advanced PD . Hypothetically, more moderate COMT enzymatic activity could lead to inadequate dopamine inactivation and the accumulation of dopamine in the synaptic cleft, thereby causing the dyskinesias. The same result was not replicated in studies by Watanabe et al. and Contin et al. . There is some evidence that the activation of the Mechanistic target of rapamycin (mTOR) signaling pathway contributes to L-dopa induced dyskinesia. It was indicative of earlier animal studies that the inhibition of mTOR pathways reduces the L-dopa related dyskinesia, most likely due to impaired metabolic homeostasis . These findings were corroborated in a recent human study, by Martin-Flores et al., that found significant associations with several SNPs affecting the mTOR pathway, indicating that the mTOR pathway contributes genetically to L-dopa induced dyskinesia susceptibility . Similarly, a functional Brain derived neurotrophic factor (BDNF) Val66Met polymorphism can lead to aberrant synaptic plasticity, which has been associated with L-dopa induced dyskinesia in a single study by Foltynie et al. . Limited evidence has been found in favour of a protective function of the Dopamine receptor 1 (DRD1) (rs4532) SNP, shown in a single study by Dos Santos et al. . The effect of Dopamine receptor 2 (DRD2) SNP’s on dyskinesia is a point of contention in current literature, as some studies indicate an increased risk of developing dyskinesia , while others revealed a protective effect on the incidence of dyskinesia . Interestingly, both studies that show reduced dyskinesias were conducted in the Italian population with the polymorphism DRD2 CAn-STR. Increased risk for developing L-dopa induced dyskinesia was seen in the Dopamine receptor 3 (DRD3) rs6280 polymorphism in a Korean population . However, opposing results were found by three research groups, with no evidence of correlation between DRD3 genetic polymorphisms and incidence of dyskinesias . Lower risk of L-dopa-associated dyskinesias was found in patients with Homer protein homolog 1 (HOMER1 ) rs4704560 G allele polymorphism . Finally, incidence of L-dopa induced dyskinesias was studied for the dopamine transporter gene (DAT) , where the presence of two genotypes 10R/10R (rs28363170) and A carrier (rs393795) led to a reduced risk of dyskinesias in an Italian population . Hyperhomocysteinemia is a known complication of L-dopa treatment in PD. The potential dangers of elevated plasma homocysteine are systemic, and include cardiovascular risk, increased risk for dementia and impaired bone health . A SNP C667T (rs1801133) in the MTHFR gene is consistently being linked to hyperhomocysteinemia due to L-dopa treatment in several studies. The result of this mutation is a temperature-labile MTHFR enzyme, which ultimately leads to hyperhomocysteinemia . In addition, a study by Gorgone et al. showed that elevated homocysteine levels lead to systemic oxidative stress in patients with this polymorphism . A recent study by Yuan et al. further adds to the claim that homocysteine levels are affected by L-dopa administration, especially in 677C/T and T/T genotypes . A possible option for homocysteine level reduction and alleviation of systemic oxidative stress is the addition of COMT inhibitors to the therapy, which presents a clear possibility for translation of this knowledge into the treatment of patients . There is contradicting evidence regarding whether COMT polymorphisms can influence the incidence of daytime sleepiness in PD patients, with differing results of the pilot and follow-up studies conducted by the same authors . Two additional studies by the same primary author revealed an association between sudden-sleep onset and the polymorphisms in hypocretin and DRD2, which was unrelated to a specific drug . Furthermore, increased risk of sleep attacks was found in Dopamine receptor 4 (DRD4) 48-bp VNTR polymorphism in a German population . The L-dopa adverse effects affecting emetic activity are not uncommon in PD treatment. DRD2 and DRD3 polymorphisms both showed an association with an increased risk of developing gastrointestinal adverse effects that do not respond well to therapy in a Brazilian population . However, that has not been reproduced in a recent study in a Slovenian population by Redenšek et al. . Mental and cognitive adverse effects of L-dopa are common due to the shared physiological dopaminergic pathways. A significant interaction was found between L-dopa and the COMT gene polymorphism in causing a detrimental effect on the activity in task-specific regions of the pre-frontal cortex due to altered availability of dopamine . Interestingly, carriers of at least one COMT rs165815 C allele had a decreased risk of developing visual hallucinations . In the same study carriers of the DRD3 rs6280 C allele had higher odds of developing visual hallucinations , which is in line with a previous study published by Goetz et al. . Increased risk of developing hallucinations is seen in patients with polymorphisms in the DRD2 gene , cholecystokinin gene and HOMER1 rs4704559 A allele , which encodes a protein that possesses a vital function for synaptic plasticity and glutamate signaling. On the other hand, the HOMER 1 rs4704559 G allele appears to decrease the risk of visual hallucinations . Furthermore, several studies link BDN F Val66Met polymorphism to impaired cognitive functioning in PD, but it appears to be irrespective of dopamine replacement therapy and is a genotype-specific trait . Impulse control disorder (ICD) is a well-known complication that can occur in some PD patients after initiating dopamine replacement therapy by either L-dopa or dopamine agonists . Heritability of ICD in a cohort of PD patients has been estimated at 57%, particularly for Opioid Receptor Kappa 1 (OPRK1) , 5-Hydroxytryptamine Receptor 2A (HTR2a) and Dopa decarboxylase (DDC) genotypes . A recent study found a suggestive association for developing ICD in variants of the opioid receptor gene OPRM1 and the DAT gene . Furthermore, there is evidence that polymorphisms in DRD1 (rs4857798, rs4532, rs265981), DRD2/ANKK1 (rs1800497) and glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B) (rs7301328) bear an increased risk of developing ICD . The DRD3 (rs6280) mutation has also been linked with increased incidence of ICD with L-dopa therapy in studies by Lee et al. and Castro-Martinez et al. . On the other hand, there was no significant association found in COMT Val158Met and DRD2 Taq1A polymorphisms . Even though current data suggest high heritability for developing ICD after initiating dopamine replacement therapy, it should be noted that the effects of individual genes are small, and the development is most likely multigenic. 2.1.3. Dopamine Receptor Agonists Dopamine receptor agonists (DAs) are often the first therapies initiated in PD patients and are the main alternative to L-dopa . The effectiveness of DAs is lower than L-dopa, and most patients discontinue treatment within three years. Some significance has been found in polymorphisms of the DRD2 and DRD3 genes that could influence drug effectiveness and tolerability. A retrospective study by Arbouw et al. revealed that a DRD2 (CA)n-repeat polymorphism is linked with a decreased discontinuation of non-ergoline DA treatment, although the sample size in this study was small . A pilot study that included Chinese PD patients revealed that the DRD3 Ser9Gly (rs6280) polymorphism is associated with a varied response to pramipexole , which has since been confirmed in a recent study by Xu et al. . Interestingly, the same polymorphism has also been linked with depression severity in PD, indicating that in DRD3 Ser9Gly patients with Ser/Gly and Gly/Gly genotypes more care should be given to adjusting therapy and caring for non-motor complications . Furthermore, there is evidence from the aforementioned studies that DRD2 Taq1A polymorphism does not play a significant role in response to DA treatment . On the other hand, certain Taq1A polymorphisms (rs1800497) have been associated with differences in critical cognitive control processes depending on allele expression . As mentioned earlier, another crucial pharmacogenomic characteristic of DA to bear in mind when administering therapy is the possibility of genotype driven impulse control disorders, which is a problem, especially in de-novo PD patients starting DA therapy . Genetic model of polymorphisms in DRD1 (rs5326), OPRK1 (rs702764), OPRM1 (rs677830) and COMT (rs4646318) genes had a high prediction of ICD in patients of DA therapy (AUC of 0.70 (95% CI: 0.61–0.79) . 2.1.4. COMT Inhibitors COMT inhibitors are potent drugs that increase the bioavailability of L-dopa by stopping the physiological O-methylation of levodopa to its metabolite 3-O-methyldopa, and can work in tandem with DDC inhibitors . Similar to L-dopa, the presence of the previously mentioned rs4608 COMT gene polymorphism modified the motor response to COMT inhibitors entacapone in a small-sample study . Patients with higher COMT enzyme activity had greater response compared to patients with lower COMT enzyme activity during the acute challenge with entacapone . Subsequent studies have not found clinically significance in repeated administration of either entacapone or tolcapone , with the impact on opicapone still unknown, meriting further study. Increased doses of carbidopa combined with levodopa and entacapone can improve “off” times, which was shown in a recent randomized trial by Trenkwalder et al., with an even more pronounced effect in patients that had higher COMT enzymatic activity due to COMT gene polymorphisms . Pharmacokinetic studies have shown that COMT inhibitors are metabolized in the liver by glucuronidation, in particular by UDP-glucuronyltransferase UGT1A and UGT1A9 enzymes . Hepatotoxicity is a known rare side-effect of tolcapone , with only sparse reports of entacapone hepatotoxicity . Several studies indicate that SNPs in the UGT1A and UGT1A9 are responsible for these adverse events, which can cause inadequate metabolism and subsequent damage to the liver by the drugs . Interestingly, opicapone has not demonstrated evident hepatotoxicity related adverse events, while in-vitro studies show a favorable effect on hepatocytes when compared to entacapone and tolcapone . 2.1.5. MAO Inhibitors MAO inhibitors are used with L-dopa to extend its duration due to reduced degradation in the CNS. Most MAO inhibitors used today in PD treatment (e.g., selegiline, rasagiline) are focused on blocking the MAO-B enzyme that is the main isoform responsible for the degradation of dopamine . There have not been many studies performed to assess MAO inhibitor pharmacogenetic properties. Early clinical studies with rasagiline did reveal an inter-individual variation in the quality of response that could not be adequately explained at that time . Masellisi et al. conducted an extensive study using the ADAGIO study data to identify possible genetic determinants that can alter the response to rasagiline. They identified two SNPs on the DRD2 gene that were associated with statistically significant improvement of both motor and mental functions after 12 weeks of treatment .
Clinically, L-dopa is always combined with dopa decarboxylase (DDC) inhibitors, which causes a switch in L-dopa metabolism to the COMT pathway, thereby increasing the bioavailability of L-dopa in the CNS . The genetic variability of several genes has been implicated in the varied response to L-dopa. COMT gene is a protein-coding gene that provides instructions for creating the COMT enzyme, and its polymorphisms are involved in the varied response to numerous CNS diseases and treatments . The most studied polymorphism of the COMT gene is rs4680 (G>A), which results in a valine to methionine substitution at codon 158 (Val158Met). Single nucleotide polymorphisms of the COMT gene form haplotypes that result in lower (A_C_C_G), medium (A_T_C_A) and higher (G_C_G_G) enzyme activity, which, in the case of higher activity, had an impact on the required dosage compared to noncarriers . Studies have shown that the higher dosage is required during chronic administration in patients with greater COMT activity, while acute L-dopa administration was unchanged . Similar changes were observed in a recent study by Sampaio et al., where higher COMT enzyme activity was linked to higher doses of L-dopa required, while no significant changes in dosage were found in lower COMT enzymatic activity compared to the control . Common characteristics of patients that required the higher L-dopa dosage in multiple studies were advanced PD and earlier onset. A contradicting result was published in patients of Korean origins, with no significant association between the rs4680 polymorphism and the response to L-dopa; however, the study population did not have a considerable number of patients with advanced PD . Higher L-dopa doses were needed for patients with Solute Carrier Family 22 Member 1 (SLC22A1) gene rs622342A>C polymorphism that encodes the Organic Cation Transporter 1, along with the patients having higher mortality than the control population . On the other hand, lower required doses of L-dopa were found in patients with Synaptic vesicle glycoprotein 2C (SV2C) rs30196 polymorphism, as well as in Solute Carrier Family 6 Member 3 (SLC6A3) polymorphism after multivariate analysis .
Increased incidence of adverse events in L-dopa treatment has been linked with various gene polymorphisms. Although the variations in COMT enzymatic activity on the onset of adverse events is still under debate, several studies have linked the lower COMT enzymatic activity to the increased incidence of motor complications such as dyskinesia, especially in advanced PD . Hypothetically, more moderate COMT enzymatic activity could lead to inadequate dopamine inactivation and the accumulation of dopamine in the synaptic cleft, thereby causing the dyskinesias. The same result was not replicated in studies by Watanabe et al. and Contin et al. . There is some evidence that the activation of the Mechanistic target of rapamycin (mTOR) signaling pathway contributes to L-dopa induced dyskinesia. It was indicative of earlier animal studies that the inhibition of mTOR pathways reduces the L-dopa related dyskinesia, most likely due to impaired metabolic homeostasis . These findings were corroborated in a recent human study, by Martin-Flores et al., that found significant associations with several SNPs affecting the mTOR pathway, indicating that the mTOR pathway contributes genetically to L-dopa induced dyskinesia susceptibility . Similarly, a functional Brain derived neurotrophic factor (BDNF) Val66Met polymorphism can lead to aberrant synaptic plasticity, which has been associated with L-dopa induced dyskinesia in a single study by Foltynie et al. . Limited evidence has been found in favour of a protective function of the Dopamine receptor 1 (DRD1) (rs4532) SNP, shown in a single study by Dos Santos et al. . The effect of Dopamine receptor 2 (DRD2) SNP’s on dyskinesia is a point of contention in current literature, as some studies indicate an increased risk of developing dyskinesia , while others revealed a protective effect on the incidence of dyskinesia . Interestingly, both studies that show reduced dyskinesias were conducted in the Italian population with the polymorphism DRD2 CAn-STR. Increased risk for developing L-dopa induced dyskinesia was seen in the Dopamine receptor 3 (DRD3) rs6280 polymorphism in a Korean population . However, opposing results were found by three research groups, with no evidence of correlation between DRD3 genetic polymorphisms and incidence of dyskinesias . Lower risk of L-dopa-associated dyskinesias was found in patients with Homer protein homolog 1 (HOMER1 ) rs4704560 G allele polymorphism . Finally, incidence of L-dopa induced dyskinesias was studied for the dopamine transporter gene (DAT) , where the presence of two genotypes 10R/10R (rs28363170) and A carrier (rs393795) led to a reduced risk of dyskinesias in an Italian population . Hyperhomocysteinemia is a known complication of L-dopa treatment in PD. The potential dangers of elevated plasma homocysteine are systemic, and include cardiovascular risk, increased risk for dementia and impaired bone health . A SNP C667T (rs1801133) in the MTHFR gene is consistently being linked to hyperhomocysteinemia due to L-dopa treatment in several studies. The result of this mutation is a temperature-labile MTHFR enzyme, which ultimately leads to hyperhomocysteinemia . In addition, a study by Gorgone et al. showed that elevated homocysteine levels lead to systemic oxidative stress in patients with this polymorphism . A recent study by Yuan et al. further adds to the claim that homocysteine levels are affected by L-dopa administration, especially in 677C/T and T/T genotypes . A possible option for homocysteine level reduction and alleviation of systemic oxidative stress is the addition of COMT inhibitors to the therapy, which presents a clear possibility for translation of this knowledge into the treatment of patients . There is contradicting evidence regarding whether COMT polymorphisms can influence the incidence of daytime sleepiness in PD patients, with differing results of the pilot and follow-up studies conducted by the same authors . Two additional studies by the same primary author revealed an association between sudden-sleep onset and the polymorphisms in hypocretin and DRD2, which was unrelated to a specific drug . Furthermore, increased risk of sleep attacks was found in Dopamine receptor 4 (DRD4) 48-bp VNTR polymorphism in a German population . The L-dopa adverse effects affecting emetic activity are not uncommon in PD treatment. DRD2 and DRD3 polymorphisms both showed an association with an increased risk of developing gastrointestinal adverse effects that do not respond well to therapy in a Brazilian population . However, that has not been reproduced in a recent study in a Slovenian population by Redenšek et al. . Mental and cognitive adverse effects of L-dopa are common due to the shared physiological dopaminergic pathways. A significant interaction was found between L-dopa and the COMT gene polymorphism in causing a detrimental effect on the activity in task-specific regions of the pre-frontal cortex due to altered availability of dopamine . Interestingly, carriers of at least one COMT rs165815 C allele had a decreased risk of developing visual hallucinations . In the same study carriers of the DRD3 rs6280 C allele had higher odds of developing visual hallucinations , which is in line with a previous study published by Goetz et al. . Increased risk of developing hallucinations is seen in patients with polymorphisms in the DRD2 gene , cholecystokinin gene and HOMER1 rs4704559 A allele , which encodes a protein that possesses a vital function for synaptic plasticity and glutamate signaling. On the other hand, the HOMER 1 rs4704559 G allele appears to decrease the risk of visual hallucinations . Furthermore, several studies link BDN F Val66Met polymorphism to impaired cognitive functioning in PD, but it appears to be irrespective of dopamine replacement therapy and is a genotype-specific trait . Impulse control disorder (ICD) is a well-known complication that can occur in some PD patients after initiating dopamine replacement therapy by either L-dopa or dopamine agonists . Heritability of ICD in a cohort of PD patients has been estimated at 57%, particularly for Opioid Receptor Kappa 1 (OPRK1) , 5-Hydroxytryptamine Receptor 2A (HTR2a) and Dopa decarboxylase (DDC) genotypes . A recent study found a suggestive association for developing ICD in variants of the opioid receptor gene OPRM1 and the DAT gene . Furthermore, there is evidence that polymorphisms in DRD1 (rs4857798, rs4532, rs265981), DRD2/ANKK1 (rs1800497) and glutamate ionotropic receptor NMDA type subunit 2B (GRIN2B) (rs7301328) bear an increased risk of developing ICD . The DRD3 (rs6280) mutation has also been linked with increased incidence of ICD with L-dopa therapy in studies by Lee et al. and Castro-Martinez et al. . On the other hand, there was no significant association found in COMT Val158Met and DRD2 Taq1A polymorphisms . Even though current data suggest high heritability for developing ICD after initiating dopamine replacement therapy, it should be noted that the effects of individual genes are small, and the development is most likely multigenic.
Dopamine receptor agonists (DAs) are often the first therapies initiated in PD patients and are the main alternative to L-dopa . The effectiveness of DAs is lower than L-dopa, and most patients discontinue treatment within three years. Some significance has been found in polymorphisms of the DRD2 and DRD3 genes that could influence drug effectiveness and tolerability. A retrospective study by Arbouw et al. revealed that a DRD2 (CA)n-repeat polymorphism is linked with a decreased discontinuation of non-ergoline DA treatment, although the sample size in this study was small . A pilot study that included Chinese PD patients revealed that the DRD3 Ser9Gly (rs6280) polymorphism is associated with a varied response to pramipexole , which has since been confirmed in a recent study by Xu et al. . Interestingly, the same polymorphism has also been linked with depression severity in PD, indicating that in DRD3 Ser9Gly patients with Ser/Gly and Gly/Gly genotypes more care should be given to adjusting therapy and caring for non-motor complications . Furthermore, there is evidence from the aforementioned studies that DRD2 Taq1A polymorphism does not play a significant role in response to DA treatment . On the other hand, certain Taq1A polymorphisms (rs1800497) have been associated with differences in critical cognitive control processes depending on allele expression . As mentioned earlier, another crucial pharmacogenomic characteristic of DA to bear in mind when administering therapy is the possibility of genotype driven impulse control disorders, which is a problem, especially in de-novo PD patients starting DA therapy . Genetic model of polymorphisms in DRD1 (rs5326), OPRK1 (rs702764), OPRM1 (rs677830) and COMT (rs4646318) genes had a high prediction of ICD in patients of DA therapy (AUC of 0.70 (95% CI: 0.61–0.79) .
COMT inhibitors are potent drugs that increase the bioavailability of L-dopa by stopping the physiological O-methylation of levodopa to its metabolite 3-O-methyldopa, and can work in tandem with DDC inhibitors . Similar to L-dopa, the presence of the previously mentioned rs4608 COMT gene polymorphism modified the motor response to COMT inhibitors entacapone in a small-sample study . Patients with higher COMT enzyme activity had greater response compared to patients with lower COMT enzyme activity during the acute challenge with entacapone . Subsequent studies have not found clinically significance in repeated administration of either entacapone or tolcapone , with the impact on opicapone still unknown, meriting further study. Increased doses of carbidopa combined with levodopa and entacapone can improve “off” times, which was shown in a recent randomized trial by Trenkwalder et al., with an even more pronounced effect in patients that had higher COMT enzymatic activity due to COMT gene polymorphisms . Pharmacokinetic studies have shown that COMT inhibitors are metabolized in the liver by glucuronidation, in particular by UDP-glucuronyltransferase UGT1A and UGT1A9 enzymes . Hepatotoxicity is a known rare side-effect of tolcapone , with only sparse reports of entacapone hepatotoxicity . Several studies indicate that SNPs in the UGT1A and UGT1A9 are responsible for these adverse events, which can cause inadequate metabolism and subsequent damage to the liver by the drugs . Interestingly, opicapone has not demonstrated evident hepatotoxicity related adverse events, while in-vitro studies show a favorable effect on hepatocytes when compared to entacapone and tolcapone .
MAO inhibitors are used with L-dopa to extend its duration due to reduced degradation in the CNS. Most MAO inhibitors used today in PD treatment (e.g., selegiline, rasagiline) are focused on blocking the MAO-B enzyme that is the main isoform responsible for the degradation of dopamine . There have not been many studies performed to assess MAO inhibitor pharmacogenetic properties. Early clinical studies with rasagiline did reveal an inter-individual variation in the quality of response that could not be adequately explained at that time . Masellisi et al. conducted an extensive study using the ADAGIO study data to identify possible genetic determinants that can alter the response to rasagiline. They identified two SNPs on the DRD2 gene that were associated with statistically significant improvement of both motor and mental functions after 12 weeks of treatment .
Gene variations that influence pharmacogenomic properties and treatment in PD are not only focused on the metabolic and activity pathways of the drugs. There is a wide number of genes that are linked to monogenic PD, but only some had their association proven continuously in various research studies. Mutations in the genes coding α-Synuclein (SNCA) , Leucine-rich repeat kinase 2 (LRRK2) , vacuolar protein sorting-associated protein 35 (VPS35) , parkin RBR E3 ubiquitin-protein ligase (PRKN) , PTEN-induced putative kinase 1 (PINK1) , glucocerebrosidase (GBA) and oncogene DJ-1 have mostly been found before the onset of genome-wide association studies, while many candidate genes found after are yet to be definitively proven to cause a significant risk for PD. Importantly, the currently known candidate genes can explain only a small fraction of cases where there is a known higher familial incidence of PD . It is remarkable, however, that assessing polygenic risk scores and combining those with specific clinical parameters can yield impressive sensitivity of 83.4% and specificity of 90% . The unfortunate consequence of the rapid expansion of knowledge in the field and amount of target genes is that the studies assessing pharmacogenomics of these gene variants are not keeping up. 2.2.1. LRRK2 Current evidence, albeit limited, points to differences in treatment response between various genotypes of monogenic PD. Mutations in the LRRK2 gene are known to cause familial PD, especially in North African and Ashkenazi Jew populations . LRRK2 protein has a variety of physiological functions in intracellular trafficking and cytoskeleton dynamics, along with a substantial role in the cells of innate immunity. It is yet unclear how mutations in LRRK2 influence the pathogenesis of PD, but there is numerous evidence that links it to a disorder in cellular homeostasis and subsequent α-synuclein aggregation . Results in in vitro and in vivo animal model studies for inhibition of mutant LRRK2 are promising, and in most cases, confirm a reduced degeneration of dopaminergic neurons . The biggest challenge of human trials has been creating an LRRK2 inhibitor that can pass the blood-brain barrier, which was overcome by Denali Therapeutics, and the phase-1b trial for their novel LRRK2 inhibitor has been completed and is awaiting official results . Furthermore, LRRK2 -associated PD has a similar response to L-dopa compared to sporadic PD, with conflicting results for the possible earlier development of motor symptoms . Pharmacogenomics in LRRK2 associated PD are linked to specific genotype variants. G2019S and G2385R variants in LRRK2 have been linked as predictors of motor complications due to L-dopa treatment, along with requiring higher doses during treatment . On the other hand, G2019S carrier status did not influence the prevalence of L-dopa induced dyskinesias in a study by Yahalom et al. . Furthermore, a study covering the pharmacogenetics of Atremorine, a novel bioproduct with neuroprotective effects of dopaminergic neurons, found that LRRK2 associated PD patients had a more robust response to the compound, along with several genes that cover metabolic and detoxification pathways . 2.2.2. SNCA SNCA gene encodes the protein α-synuclein, now considered a central player in the pathogenesis of PD due to its aggregation into Lewy-bodies. SNP’s in the SNC A gene are consistently linked to an increased risk of developing PD in GWAS studies in both familial and even sporadic PD . In cases of autosomal dominant mutations, there is a solid L-dopa and classical PD treatment response, albeit with early cognitive and mental problems, akin to GBA mutations . There are several planned therapeutic approaches suited for SNCA polymorphism genotypes which include: targeted monoclonal antibody immunotherapy of α-synuclein , downregulation of SNCA expression by targeted DNA editing and RNA interference of SNCA . Roche Pharmaceuticals has developed an anti-α-synuclein monoclonal antibody which is in a currently ongoing phase two of clinical trials . Two other methods are still in preclinical testing, and their development shows promise for the future. 2.2.3. GBA Glucocerebrosidase mutations represent a known risk factor for developing PD. GBA mutation associated PD is characterized by the earlier onset of the disease, followed by a more pronounced cognitive deficit and a significantly higher risk of dementia . Gaucher’s disease (GD) is an autosomal recessive genetic disorder that also arises from mutations in the GBA gene. The current enzyme replacement and chaperone treatment options for systemic manifestations of GD are not effective enough in treating the neurological manifestations of the disease as they are not able to reach the CNS . Three genotype-specific therapies to address the cognitive decline are currently being tested with promising early results, with two focusing on the chaperones ambroxol and LTI-291 to increase glucocerebrosidase activity and the third focusing on reducing the levels of glucocerebrosidase with ibiglustat . There is growing evidence that GBA associated PD is often marked by rapid progression with many hallmarks of advanced PD, such as higher L-dopa daily dose required to control motor symptoms . However, current research does not show a significant influence of GBA mutations on L-dopa response properties with adequate motor symptom control . A single study by Lesage et al. in a population of European origin linked a higher incidence of L-dopa induced dyskinesias in GBA-PD patients , but that has not been replicated in a more recent study by Zhang et al. in a population of Chinese origin . 2.2.4. PRKN/PINK1/DJ1 Mutations in the PRKN gene can lead to early onset PD, characterized by a clinically typical form of PD that is often associated with dystonia and dyskinesia . Patients with PRKN mutations generally have excellent and sustained responses to L-dopa, even in lower doses than in sporadic PD . Dyskinesias can occur early on in the course of the disease with very low doses of L-dopa , while dystonia in these patients was not found to be linked to L-dopa treatment . Furthermore, patients with PINK1 mutations have a similar disease course as PRKN mutation carriers, with a good response to L-dopa treatment, but early dystonia and L-dopa induced dyskinesias . Pharmacogenomic properties and genotype-specific treatment of several other gene mutations in PD such as VPS35 and DJ1 have not yet been characterized fully due to the rarity of cases and are currently a focus of several studies that as of writing do not have preliminary results available .
Current evidence, albeit limited, points to differences in treatment response between various genotypes of monogenic PD. Mutations in the LRRK2 gene are known to cause familial PD, especially in North African and Ashkenazi Jew populations . LRRK2 protein has a variety of physiological functions in intracellular trafficking and cytoskeleton dynamics, along with a substantial role in the cells of innate immunity. It is yet unclear how mutations in LRRK2 influence the pathogenesis of PD, but there is numerous evidence that links it to a disorder in cellular homeostasis and subsequent α-synuclein aggregation . Results in in vitro and in vivo animal model studies for inhibition of mutant LRRK2 are promising, and in most cases, confirm a reduced degeneration of dopaminergic neurons . The biggest challenge of human trials has been creating an LRRK2 inhibitor that can pass the blood-brain barrier, which was overcome by Denali Therapeutics, and the phase-1b trial for their novel LRRK2 inhibitor has been completed and is awaiting official results . Furthermore, LRRK2 -associated PD has a similar response to L-dopa compared to sporadic PD, with conflicting results for the possible earlier development of motor symptoms . Pharmacogenomics in LRRK2 associated PD are linked to specific genotype variants. G2019S and G2385R variants in LRRK2 have been linked as predictors of motor complications due to L-dopa treatment, along with requiring higher doses during treatment . On the other hand, G2019S carrier status did not influence the prevalence of L-dopa induced dyskinesias in a study by Yahalom et al. . Furthermore, a study covering the pharmacogenetics of Atremorine, a novel bioproduct with neuroprotective effects of dopaminergic neurons, found that LRRK2 associated PD patients had a more robust response to the compound, along with several genes that cover metabolic and detoxification pathways .
SNCA gene encodes the protein α-synuclein, now considered a central player in the pathogenesis of PD due to its aggregation into Lewy-bodies. SNP’s in the SNC A gene are consistently linked to an increased risk of developing PD in GWAS studies in both familial and even sporadic PD . In cases of autosomal dominant mutations, there is a solid L-dopa and classical PD treatment response, albeit with early cognitive and mental problems, akin to GBA mutations . There are several planned therapeutic approaches suited for SNCA polymorphism genotypes which include: targeted monoclonal antibody immunotherapy of α-synuclein , downregulation of SNCA expression by targeted DNA editing and RNA interference of SNCA . Roche Pharmaceuticals has developed an anti-α-synuclein monoclonal antibody which is in a currently ongoing phase two of clinical trials . Two other methods are still in preclinical testing, and their development shows promise for the future.
Glucocerebrosidase mutations represent a known risk factor for developing PD. GBA mutation associated PD is characterized by the earlier onset of the disease, followed by a more pronounced cognitive deficit and a significantly higher risk of dementia . Gaucher’s disease (GD) is an autosomal recessive genetic disorder that also arises from mutations in the GBA gene. The current enzyme replacement and chaperone treatment options for systemic manifestations of GD are not effective enough in treating the neurological manifestations of the disease as they are not able to reach the CNS . Three genotype-specific therapies to address the cognitive decline are currently being tested with promising early results, with two focusing on the chaperones ambroxol and LTI-291 to increase glucocerebrosidase activity and the third focusing on reducing the levels of glucocerebrosidase with ibiglustat . There is growing evidence that GBA associated PD is often marked by rapid progression with many hallmarks of advanced PD, such as higher L-dopa daily dose required to control motor symptoms . However, current research does not show a significant influence of GBA mutations on L-dopa response properties with adequate motor symptom control . A single study by Lesage et al. in a population of European origin linked a higher incidence of L-dopa induced dyskinesias in GBA-PD patients , but that has not been replicated in a more recent study by Zhang et al. in a population of Chinese origin .
Mutations in the PRKN gene can lead to early onset PD, characterized by a clinically typical form of PD that is often associated with dystonia and dyskinesia . Patients with PRKN mutations generally have excellent and sustained responses to L-dopa, even in lower doses than in sporadic PD . Dyskinesias can occur early on in the course of the disease with very low doses of L-dopa , while dystonia in these patients was not found to be linked to L-dopa treatment . Furthermore, patients with PINK1 mutations have a similar disease course as PRKN mutation carriers, with a good response to L-dopa treatment, but early dystonia and L-dopa induced dyskinesias . Pharmacogenomic properties and genotype-specific treatment of several other gene mutations in PD such as VPS35 and DJ1 have not yet been characterized fully due to the rarity of cases and are currently a focus of several studies that as of writing do not have preliminary results available .
There has been considerable progress in the field of pharmacogenomics in Parkinson’s disease. The main question in the field is whether we can use the current knowledge in clinical practice to benefit the patients. The data on Parkinson’s disease in PharmGKB, a pharmacogenomics database, are sparse, with only ten clinical annotations with most being supported by a rather low level of evidence, which is clear from this systematic review as well . Most of the pharmacogenomic studies that focus on antiparkinsonian drugs are highly centered on L-dopa and its metabolism. The current evidence on the pharmacogenomics of therapeutic response to L-dopa is contradictory, with most studies focusing on the COMT gene polymorphisms. The differences between studies limit the potential for clinical use. However, there is potential to clarify the effects of COMT gene polymorphisms by further studies analyzing the enzymatic activity in various genotypes and the L-dopa dosage and therapeutic response. More robust evidence is present for the pharmacogenomics of side-effects in L-dopa or dopaminergic therapy. The most studied motor complication of L-dopa therapy is treatment-induced dyskinesias. Looking at the evidence, we can see that there are numerous reports focusing on various genes, although often with contradictory results in COMT , DRD2 and DRD3 genes. On the other hand, SNPs in the mTOR pathway genes, BDNF , HOMER1 and DAT have been implicated in either increased or reduced risk for dyskinesias, but with single studies that are yet to be corroborated in larger cohorts. Other side-effects such as cognitive decline, visual hallucinations and daytime sleepiness have been implicated in various polymorphisms of the COMT, DRD2, DRD3, HOMER1 and BDNF genes, but lack consistency in the results to consider current clinical implementations. Hyperhomocysteinemia and ICD are known complications of dopaminergic therapy, and both have been consistently linked with genetic factors . Specifically, mutations in the MTHFR gene can increase the incidence of hyperhomocysteinemia, which could be ameliorated by the addition of COMT inhibitors to therapy, presenting a possibility for clinical interventions based on pharmacogenomic testing. The same can be said about ICD, where genetic models are gaining accuracy with each new study in the field . Potential for clinical use can especially be seen in younger patients which are only starting dopamine agonist therapy, as polymorphisms in DRD1 (rs5326), OPRK1 (rs702764), OPRM1 (rs677830) and COMT (rs4646318) genes showed a high prediction rate of ICD . There is evidence that polymorphisms in DRD2 and DRD3 gene could also cause these side-effects, leading to earlier discontinuation of DA therapy in patients. There is clear potential for clinical implementation in this area, and future goal should be to establish studies with larger cohorts in order to improve the genetic prediction models. There is lacking evidence regarding the pharmacogenomic properties of other drugs used in PD, such as COMT and MAO inhibitors. However, there is some evidence that mutations leading to varied COMT enzyme activity could have an influence on the potency of COMT inhibitors, but the results are not consistent . More consistent results have been found regarding entacapone hepatotoxicity, with several studies indicating that SNP’s in the UGT1A and UGT1A9 could lead to this adverse effect . MAO inhibitors are known to have inter-individual variation, which is still not explained in current studies, with a single study reporting improved motor and mental functions in DRD2 gene SNP. Taken together, the pharmacogenomic data regarding COMT and MAO inhibitors are still not strong enough to make any recommendations for clinical implementation. Finally, pharmacogenomics in PD also encompasses changes that occur in specific differences in genotype-associated PD. Three of the most studied single gene mutations are the LRRK2, GBA and SNCA gene mutations. Published studies covering L-dopa treatment with these mutations have contradicting results depending on the populations studied, which makes it difficult to give any firm recommendations regarding treatment optimization . The current evidence for PRKN, PINK1 and DJ1 point to a sustained L-dopa response with lower doses, albeit with early motor complications that include dyskinesias and dystonia . Therefore, this clinical phenotype can raise suspicions of these mutations and lead to earlier genetic testing and treatment optimization. However, the number of cases analyzed is low due to the rarity of these mutations, and further studies are required to confirm these early findings.
We have done a systematic search of articles indexed in Medline and Embase from its inception to July of 2020 focused on the pharmacogenomics in Parkinson’s disease using a strategy similar to what was described by Corvol et al. . The search terms included: Genetic Variation (MeSH), Genotype (MeSH), Genes (MeSH), Polymorphism, Allele, Mutation, Treatment outcome (MeSH), Therapeutics (MeSH), Pharmacogenomic (MeSH), Pharmacogenetics (MeSH), Adverse effects (MeSH Subheading), Toxicogenetics (MeSH) and Parkinson’s disease (MeSH). The articles included in the search were clinical trials, meta-analysis, and randomized controlled trial, with excluding case reports and reviews, with additional filters of human studies and English language. We included studies that had a clear methodology regarding study population and main findings. Exclusion criteria were articles not written in English, lacking study population information and findings not relevant to the theme of pharmacogenomics in PD. Several reviews were added into the overall analyzed papers using manual searches through websites and citation searching. PharmGKB database was accessed as well using the search parameter “Parkinson’s disease” to view current clinical annotations present for PD . The systematic literature search in Medline and Embase revealed 15,778 potential publications, which were first automatically and then manually filtered to exclude studies that do not fit the inclusion criteria . We included 75 studies, with the final count being 116 after adding publications found through manual search that include reviews covering this topic, along with studies focused on genotype specific PD forms .
Most pharmacogenomic data for PD treatment present today are still not consistent enough to be entered into clinical practice, and further studies are required to enable a more personalized approach to therapy for each patient. The main findings can be summarized as follows: Most evidence from the analyzed studies is found via secondary endpoints, which limits their power, with small sample size also being a diminishing factor. Conflicting reports between varied populations could be a consequence of low sample sizes and unaccounted interactions, which ultimately leads to low confidence in the data currently available. The most promising avenues for clinical implementation of pharmacogenetics lie in the current findings of impulse control disorders and hyperhomocysteinemia, where the available data are more consistent. Most of the studies focus on L-dopa and DA, and greater focus should also be given to other PD treatment options such as MAO-B and COMT inhibitors. Even though the wealth of knowledge is rapidly increasing, there are still not enough consistent data to make quality choices in the clinical treatment of patients. Studies that have a clear focus on pharmacogenomic properties of antiparkinsonian drugs are key for consolidating the current information and for the translation into clinical practice.
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Evaluation of the impact of alveolar bone graft surgery on the nasal cavity of individuals with cleft lip and palate | ee6ce037-1c2c-4511-b0c1-3e325861db75 | 11643102 | Dentistry[mh] | Cleft lip and palate (CL/P) are the most common congenital malformations of the craniofacial region, occurring in Brazil at a rate of 1 in 700 births. , The rehabilitation of these patients requires a multidisciplinary approach with a specialized and integrated team and involves complex treatments to achieve satisfactory outcomes for both patients and the healthcare team. , Secondary alveolar bone grafting (SABG) plays a crucial role in the rehabilitation process of patients with CL/P. This procedure stabilizes the maxillary bone structure, the upper dental arch, and periodontium, while also promoting the development of permanent teeth in the cleft region and enabling orthodontic movement. Additionally, it allows for the placement of endosseous implants, when necessary, closes oronasal fistulas, and provides bone support for the nasal alar base. Overall, SABG enhances the patient's aesthetic harmony by improving nasal symmetry. – SABG using autologous iliac crest cancellous bone is a standard procedure for patients with CL/P during the mixed dentition phase. It addresses both functional and aesthetic outcomes, correlating with improvements in patient quality of life, satisfaction and high surgical success rates. During surgery, the nasal floor, which is invaginated into the cleft region and often associated with an oronasal fistula, is repositioned upwards and sutured, effectively reconstructing the nasal fossa anatomy. This procedure reshapes the nasal base and wing through by grafting bone tissue into the affected area. – The presence of the cleft itself impairs the development of the nasomaxillary complex, causing a deviated septum, nostril atresia, and hypertrophy of the nasal turbinates on the contralateral side. These alterations reduce the internal dimensions of the nasal cavity (NC) and increase resistance to respiratory airflow, often leading to mouth breathing , which can impact craniofacial development and compromise lower airway function. – Considering the frequent complaints of nasal obstruction by patients in the early postoperative period of SABG, it is important to assess the impact of this procedure on internal nasal dimensions. Therefore, this study aimed to determine the effect of SABG surgery on nasal volume and the cross-sectional areas of the nasal valve in patients with respiratory complaints two months after the procedure. We hypothesized that SABG surgery reduces nasal cavity dimensions, potentially explaining these respiratory complaints.
Study group, sample size, design and settings To determine whether patients’ complaints were directly related to the SABG procedure, which has been shown to alter nasal morphology in patients with complete unilateral cleft (UCL/P) (Lee, et al. (2013)), we conducted a comparative evaluation of the CBCT scans taken before and after surgery for clinical purposes. This was essential to assess any changes in the upper airway, particularly in the nostril region. The study protocol was approved by the Institutional Review Board (institution name and protocol number omitted for peer review). A total of 15 patients were enrolled in the study, and their pre- and postoperative CBCT scans were selected to evaluate possible morphological changes in the airways of patients with complete UCL/P shortly after SABG. A convenience sampling method was used, in accordance with the eligibility criteria. The study included both male and female patients aged 10 to 16 years with complete unilateral clefts undergoing routine orthodontic treatment, with indication for SABG. All participants were submitted to primary plastic surgeries in early childhood. Patients undergoing re-grafting, as well as those with genetic syndromes, other craniofacial anomalies or inflammatory diseases of the upper airway at the time of CBCT were excluded. All patients attended a 60-day postoperative follow-up and reported nasal complaints after surgery. SABG technique and CBCT characteristics The SABG procedure was performed by a single oral and maxillofacial surgeon using the surgical technique described by Boyne and Sands (1972), which is widely used in our institution. , The surgery involves making an oblique buccal incision reaching the central portion of the first molar and meeting an intra-sulcular incision extending up to the lateral cleft margin. The gingival boundary is then contoured, reaching the opposite segment of the maxilla and ending in the intra-sulcular region of the central incisors. From this incision, the buccal mucosa was divided, creating a full-thickness flap. The palatal mucosa was separated and sutured. The nasal floor mucosa was then repositioned superiorly and sutured to close fistulas, creating a space where the bone graft from the iliac crest was carefully placed. Finally, the buccal flap was repositioned over the bone graft. The entire divided bone extension was covered, and the incisions were sutured with simple stitches. Cone beam computed tomography scans were acquired using the i-CAT Next Generation CT scanner (ISI-iCAT Imaging System - cone beam, Next Generation i-CAT ® ), with the following specifications: field of view (FOV) of at least 13cm, allowing visualization of the upper airway, an exposure time of 26.9 seconds, 120 Kv, 37.07 mA and resolution of 0.25 voxels. The images were imported in DICOM (Digital Imaging and Communications in Medicine). – Morphometric analysis of the nasal cavity To evaluate the NC volume, the Mimics™ software (Materialise, Belgium) was used. First, the CBCT scan files were opened, and a mask with a threshold range of −1024 to −500 Hounsfield units, consistent with air density, was created. This tool allows the NC to be filled in, distinguishing it from other structures such as soft and hard tissues. Using the coronal plane, a section was selected to provide the best visualization of thresholds for the creation of the initial mask, with the following anatomical boundaries: the anterior limit of the nasal valve, the posterior limit of the choanae, the lower and upper limits of the nasal floor, and the turbinates and middle meatus, related to the respiratory portion. After creation of the first mask, areas not of interest, such as the paranasal sinuses, ethmoidal cells, and regions of artifact, were excluded from the tomographic images using the Multiple Slice Edit. Additional structures that were not initially selected were added, considering different tomographic planes, until the NC was filled by the mask according to the predefined limits. Once the necessary edits were made, the mask was converted into a 3D object. The final step involved polishing and removing any spicules, after which the 3D reconstruction of the NC was complete, allowing volume measurements to be obtained. To find the CSAs of the internal nasal valve (cleft and non-cleft sides), a coronal section was used. The first section anterior to the inferior nasal turbinate was defined as the most posterior reference point. A polygon was then outlined over the internal nasal valve region, and the area was calculated. The creation of 3D models enabled the measurement of total nasal volumes, right NC volumes, left NC volumes, and the CSAs of internal nasal valves. All reconstructions were performed by two trained and calibrated examiners, who obtained different nasal measurements. To assess intra- and interexaminer reproducibility, examiner 1 performed reconstructions on all 15 preoperative and 15 postoperative scans twice, while examiner 2 conducted reconstructions on 50% of the postoperative scans, also twice. Both examiners repeated their initial measurement after a 30-day interval (T1 and T2). The mean values from both examiners across the two measurements were used for statistical analysis. Intra- and interexaminer reproducibility for volumes and CSAs showed an intraexaminer ICC > 0.80 for both examiners, while the interexaminer ICC was 0.80, confirming the high reproducibility of measurements for both CSAs and volumes. Analysis of results The Kolmogorov-Smirnov test was used to assess the normality of the data. For comparison of quantitative variables, data with normal distribution were presented as mean ± standard deviation and compared by the paired Student's t-test. A pvalue ≤ 0.05 was considered significant. The power to detect mean differences between pre- and postoperative total NC volumes and cross-sectional areas of internal nasal valves (R and L), at a 95% confidence interval was 44.67%.
To determine whether patients’ complaints were directly related to the SABG procedure, which has been shown to alter nasal morphology in patients with complete unilateral cleft (UCL/P) (Lee, et al. (2013)), we conducted a comparative evaluation of the CBCT scans taken before and after surgery for clinical purposes. This was essential to assess any changes in the upper airway, particularly in the nostril region. The study protocol was approved by the Institutional Review Board (institution name and protocol number omitted for peer review). A total of 15 patients were enrolled in the study, and their pre- and postoperative CBCT scans were selected to evaluate possible morphological changes in the airways of patients with complete UCL/P shortly after SABG. A convenience sampling method was used, in accordance with the eligibility criteria. The study included both male and female patients aged 10 to 16 years with complete unilateral clefts undergoing routine orthodontic treatment, with indication for SABG. All participants were submitted to primary plastic surgeries in early childhood. Patients undergoing re-grafting, as well as those with genetic syndromes, other craniofacial anomalies or inflammatory diseases of the upper airway at the time of CBCT were excluded. All patients attended a 60-day postoperative follow-up and reported nasal complaints after surgery.
The SABG procedure was performed by a single oral and maxillofacial surgeon using the surgical technique described by Boyne and Sands (1972), which is widely used in our institution. , The surgery involves making an oblique buccal incision reaching the central portion of the first molar and meeting an intra-sulcular incision extending up to the lateral cleft margin. The gingival boundary is then contoured, reaching the opposite segment of the maxilla and ending in the intra-sulcular region of the central incisors. From this incision, the buccal mucosa was divided, creating a full-thickness flap. The palatal mucosa was separated and sutured. The nasal floor mucosa was then repositioned superiorly and sutured to close fistulas, creating a space where the bone graft from the iliac crest was carefully placed. Finally, the buccal flap was repositioned over the bone graft. The entire divided bone extension was covered, and the incisions were sutured with simple stitches. Cone beam computed tomography scans were acquired using the i-CAT Next Generation CT scanner (ISI-iCAT Imaging System - cone beam, Next Generation i-CAT ® ), with the following specifications: field of view (FOV) of at least 13cm, allowing visualization of the upper airway, an exposure time of 26.9 seconds, 120 Kv, 37.07 mA and resolution of 0.25 voxels. The images were imported in DICOM (Digital Imaging and Communications in Medicine). –
To evaluate the NC volume, the Mimics™ software (Materialise, Belgium) was used. First, the CBCT scan files were opened, and a mask with a threshold range of −1024 to −500 Hounsfield units, consistent with air density, was created. This tool allows the NC to be filled in, distinguishing it from other structures such as soft and hard tissues. Using the coronal plane, a section was selected to provide the best visualization of thresholds for the creation of the initial mask, with the following anatomical boundaries: the anterior limit of the nasal valve, the posterior limit of the choanae, the lower and upper limits of the nasal floor, and the turbinates and middle meatus, related to the respiratory portion. After creation of the first mask, areas not of interest, such as the paranasal sinuses, ethmoidal cells, and regions of artifact, were excluded from the tomographic images using the Multiple Slice Edit. Additional structures that were not initially selected were added, considering different tomographic planes, until the NC was filled by the mask according to the predefined limits. Once the necessary edits were made, the mask was converted into a 3D object. The final step involved polishing and removing any spicules, after which the 3D reconstruction of the NC was complete, allowing volume measurements to be obtained. To find the CSAs of the internal nasal valve (cleft and non-cleft sides), a coronal section was used. The first section anterior to the inferior nasal turbinate was defined as the most posterior reference point. A polygon was then outlined over the internal nasal valve region, and the area was calculated. The creation of 3D models enabled the measurement of total nasal volumes, right NC volumes, left NC volumes, and the CSAs of internal nasal valves. All reconstructions were performed by two trained and calibrated examiners, who obtained different nasal measurements. To assess intra- and interexaminer reproducibility, examiner 1 performed reconstructions on all 15 preoperative and 15 postoperative scans twice, while examiner 2 conducted reconstructions on 50% of the postoperative scans, also twice. Both examiners repeated their initial measurement after a 30-day interval (T1 and T2). The mean values from both examiners across the two measurements were used for statistical analysis. Intra- and interexaminer reproducibility for volumes and CSAs showed an intraexaminer ICC > 0.80 for both examiners, while the interexaminer ICC was 0.80, confirming the high reproducibility of measurements for both CSAs and volumes.
The Kolmogorov-Smirnov test was used to assess the normality of the data. For comparison of quantitative variables, data with normal distribution were presented as mean ± standard deviation and compared by the paired Student's t-test. A pvalue ≤ 0.05 was considered significant. The power to detect mean differences between pre- and postoperative total NC volumes and cross-sectional areas of internal nasal valves (R and L), at a 95% confidence interval was 44.67%.
Sample characterization The study sample included 15 individuals aged 10 to 16 years (13.00±1.96) with indication for SABG surgery and complete unilateral cleft lip and palate. Of the 15 participants, six had right-sided clefts and nine had left-sided clefts. The sample included 11 males (63.63%) and 4 females (36.36%). Volumes and cross-sectional areas summarizes the decrease in the nasal cavity volume and cross-sectional areas as a whole in the postoperative period for the 15 patients with unilateral clefts, both on the right and left sides. The mean total cavity volume decreased from 15,194 mm³ preoperatively to 13,409 mm³ postoperatively (p≤0.0001). The volume of the right cavity decreased from 9,219 mm³ preoperatively to 8,354 mm³ postoperatively (p≤0.0115), while the left cavity volume decreased from 7,974 mm to 6674 mm³ (p≤0.0024). Thus, when the 15 patients were analyzed without separation by cleft laterality, there was a statistically significant decrease in total nasal volume, as well as in the volumes of both the right and left cavities. The CSA of the right NV decreased from 106.20 mm 2 to 90.78 mm 2 after surgery, while the CSA of the left NV decreased from 102.50 mm 2 to 84.61 mm 2 . There was a statistically significant reduction in the cross-sectional areas of the right and left nasal valves (p≤0.05). The pre- and postoperative NC volumes (mm³) and CSAs of individuals with unilateral cleft lip and palate (UCL/P) were evaluated according to cleft laterality corresponding to the side where the grafted material was placed . The analysis revealed that patients with left-sided UCL/P showed a significant decrease in total nasal cavity volume, from 14,583 mm 3 to 12,712 mm 3 after surgery (p≤0.001). On the side contralateral to the cleft, the volume decreased from 9,202 mm 3 to 7,867 mm 3 after surgery (p≤0.0001). On the left side, corresponding to the cleft side, the volume was reduced from 7,429 mm 3 to 6,375 mm 3 after the procedure (p≤0.0275). Additionally, the nasal valve CSAs on the cleft side decreased from 95.21 mm 2 to 74.25 mm 2 (p≤0.0020), and on the non-cleft side from 118.70mm 2 to 101.20mm 2 (p≤0.0020). All showed statistically significant differences. For patients with right-sided UCL/P, a reduction in total nasal cavity volume was also observed, with a preoperative volume of 16,110 cm 3 , which decreased to 14,456 cm 3 postoperatively (p≤0.0123). The left contralateral cavity volume decreased from 8,792 mm 3 to 7,121 mm 3 after the procedure (p≤0.0135). However, on the right cleft side that received the graft, no statistically significant difference in volume was noted, with only a numerical decrease from 9,244 mm³ to 9,085 mm³ postoperatively (p≤0.4041). In terms of the cross-sectional areas of the internal nasal valve, the CSA on the cleft side decreased from 87.59 mm 2 to 75.18 mm 2 postoperatively (p≤0.0312). The CSA also decreased on the non-cleft side, from 113.40 mm 2 to 99.03 mm 2 (p≤0.0156). Three-dimensional CAD models of the nasal cavities of all study participants are shown in preoperatively and postoperatively. Qualitatively, the postoperative nasal cavities were smaller, especially in the internal nasal valve.
The study sample included 15 individuals aged 10 to 16 years (13.00±1.96) with indication for SABG surgery and complete unilateral cleft lip and palate. Of the 15 participants, six had right-sided clefts and nine had left-sided clefts. The sample included 11 males (63.63%) and 4 females (36.36%).
summarizes the decrease in the nasal cavity volume and cross-sectional areas as a whole in the postoperative period for the 15 patients with unilateral clefts, both on the right and left sides. The mean total cavity volume decreased from 15,194 mm³ preoperatively to 13,409 mm³ postoperatively (p≤0.0001). The volume of the right cavity decreased from 9,219 mm³ preoperatively to 8,354 mm³ postoperatively (p≤0.0115), while the left cavity volume decreased from 7,974 mm to 6674 mm³ (p≤0.0024). Thus, when the 15 patients were analyzed without separation by cleft laterality, there was a statistically significant decrease in total nasal volume, as well as in the volumes of both the right and left cavities. The CSA of the right NV decreased from 106.20 mm 2 to 90.78 mm 2 after surgery, while the CSA of the left NV decreased from 102.50 mm 2 to 84.61 mm 2 . There was a statistically significant reduction in the cross-sectional areas of the right and left nasal valves (p≤0.05). The pre- and postoperative NC volumes (mm³) and CSAs of individuals with unilateral cleft lip and palate (UCL/P) were evaluated according to cleft laterality corresponding to the side where the grafted material was placed . The analysis revealed that patients with left-sided UCL/P showed a significant decrease in total nasal cavity volume, from 14,583 mm 3 to 12,712 mm 3 after surgery (p≤0.001). On the side contralateral to the cleft, the volume decreased from 9,202 mm 3 to 7,867 mm 3 after surgery (p≤0.0001). On the left side, corresponding to the cleft side, the volume was reduced from 7,429 mm 3 to 6,375 mm 3 after the procedure (p≤0.0275). Additionally, the nasal valve CSAs on the cleft side decreased from 95.21 mm 2 to 74.25 mm 2 (p≤0.0020), and on the non-cleft side from 118.70mm 2 to 101.20mm 2 (p≤0.0020). All showed statistically significant differences. For patients with right-sided UCL/P, a reduction in total nasal cavity volume was also observed, with a preoperative volume of 16,110 cm 3 , which decreased to 14,456 cm 3 postoperatively (p≤0.0123). The left contralateral cavity volume decreased from 8,792 mm 3 to 7,121 mm 3 after the procedure (p≤0.0135). However, on the right cleft side that received the graft, no statistically significant difference in volume was noted, with only a numerical decrease from 9,244 mm³ to 9,085 mm³ postoperatively (p≤0.4041). In terms of the cross-sectional areas of the internal nasal valve, the CSA on the cleft side decreased from 87.59 mm 2 to 75.18 mm 2 postoperatively (p≤0.0312). The CSA also decreased on the non-cleft side, from 113.40 mm 2 to 99.03 mm 2 (p≤0.0156). Three-dimensional CAD models of the nasal cavities of all study participants are shown in preoperatively and postoperatively. Qualitatively, the postoperative nasal cavities were smaller, especially in the internal nasal valve.
Patients in this study reported nasal obstruction after undergoing SABG surgery. Chang, et al. (2017) found that children who underwent SABG surgery were more likely to report nasal obstruction than those who did not. Similarly, Lee, et al. (2013) identified morphological changes at the base of the nostrils in children who underwent SABG. Our study aimed to examine the effects of SABG on NC volumes and CSAs in patients with UCL/P, seeking to elucidate the breathing difficulties reported by these patients. While a direct cause and effect cannot be confirmed, the morphological changes in the nasal cavity after SABG may be related to nasal obstruction, as other conditions linked to respiratory symptoms were ruled out. Despite being able to reject the null hypothesis, the study results should be interpreted with caution due to certain limitations. The small, heterogeneous sample size and power values below 80% may limit generalizations (Crutzen and Peters, 2017; Serdar, et al. (2021)). However, as the sampling was based on patients with a common post-SABG complaint, altering these parameters might raise ethical concerns. Since this is a before-and-after study, comparisons within the same patient reduce possible biases. The absence of a validated respiratory symptoms questionnaire also represents a limitation. Our study demonstrated a reduction in total NC volume in patients with UCL/P. For those with left-sided UCL/P, reductions were observed on both the cleft side and the contralateral side. In patients with right-sided CL/P, the volume decreased on the contralateral side, with no statistically significant reduction on the cleft side, likely due to a smaller sample size. Conversely, the reduction in the contralateral NC volume in rightsided CL/P suggests that SABG affects not only the cleft side. Reductions in the CSA of the internal nasal valve were seen in both right and left UCL/P patients, with the region closest to the graft site being the most affected. This suggests that SABG reduces the internal nasal dimensions, due to elevation of the floor into the nasal cavity, which was previously invaginated into the cleft area. Additionally, CL/P can affect maxillary sinus development in the cleft side. Kiaee, et al. (2021) found that children with operated unilateral complete cleft, both with and without palatal fistula, had smaller maxillary sinuses on the fistula side. This reduction may increase the risk of sinus disease. Their study closely aligns with ours in terms of age group, cleft type, and choice of software to measure the volume of the tomographic images. Our findings point to a reduction in the total nasal cavity volume and the CSAs of the nasal valve regions, which could further reduce the maxillary sinus volume on the grafted side and constitute a risk factor for sinus diseases. Additionally, another study from Kiaee, et al. (2021) showed that the maxillary sinus volume was smaller on the cleft side, suggesting that surgeries in the nasal cavities and the maxillary sinus floor could impact both respiratory and sinusal physiology. Sijmons, et al. (2023), in the Netherlands, also investigated the impact of alveolar bone grafting through tomographic analysis. While their findings differ from ours (showing no reduction in internal nasal dimensions a year after surgery), their study used a different software, only assessed total nasal cavity volume, and had a different postoperative timespan than ours. This supports our hypothesis that changes may be less significant in the long term. The SABG is generally performed during mixed dentition, before the eruption of the permanent canine adjacent to the cleft. Thus, the procedure is performed on growing patients, which may induce changes in nasal volume Analyzing each nasal cavity individually must account for the "nasal cycle", a physiological process in which congestion and decongestion affect both sides. , This means that the decrease in volume and cross-sectional areas of the nasal valve on the non-cleft side may not be related to anatomical causes, but rather result from the nasal cycle itself. However, differences between the cleft and non-cleft sides were consistently observed in most cases analyzed, as reported by Kunkel, Wahlman and Wagner , (1997, 1999), who found a 35% smaller nasal volume on the cleft side. Cone beam computed tomography is the gold standard for assessing upper airway morphology and internal geometry in various patient groups. – As such, we used the Mimics Research ® software, which has good accuracy for reconstructing the nasal cavity and was already used in the research laboratory at (institution name omitted for peer review). – This software offers the possibility of creating a mask only in the region of interest, and the Multiple Slice Edit tool allows easy and accurate exclusion of structures not suitable for the group, such as ethmoid cells and paranasal sinuses. If necessary, structures can also be added to certain sections that were not considered when creating the mask. Comparing our results with previous studies is challenging due to limited research in this field. However, Kiaee, et al. , (2021) highlighted smaller sinus dimensions on the cleft and palatal fistula sides, suggesting that ABG may reduce sinus volumes on the grafted side, thus increasing the risk of future sinus diseases. As such, patients and clinicians should be aware that sinusal symptoms may occur after surgery. From a clinical point of view, aside from the possible higher risk of sinusitis, it should be noted that patients may experience transient symptoms of nasal obstruction shortly after surgery. Sijmons, et al. (2023) report that these symptoms tend to diminish over time. Our study consistently showed a significant reduction in total nasal volume and CSAs within the first two months after surgery. Unilaterally, there was a decrease in patients with left CLP on both sides of the nasal cavity, and in patients with right CLP there was a statistically significant decrease on the side contralateral to the cleft. This supports our hypothesis that the internal nasal valve region is the area most affected by SABG in the short term. Further research, including our ongoing study on ABG's effects on sinus morphology, will help clarify its long-term impacts on nasal dimensions and symptoms.
The analysis of internal nasal dimensions in patients with UCLP confirmed the hypothesis that SABG reduces nasal cavity dimensions, which would explain the respiratory complaints of patients. Alveolar bone grafting induces short-term morphophysiological changes, decreasing both the volume of the nasal cavities and the cross-sectional areas of the internal nasal valves on both sides, rather than only on the cleft area where the graft material was placed. These reductions in the internal dimensions of the nasal valve region may be linked to nasal obstruction symptoms shortly after surgery.
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Gastric Carcinogenesis and Potential Role of the Transient Receptor Potential Vanilloid 1 (TRPV1) Receptor: An Observational Histopathological Study | a95ae75a-ddeb-4d50-a9f3-3fb3a0e488e6 | 11312730 | Anatomy[mh] | Gastric cancer (GC) is the fifth most common cancer worldwide and is associated with significant cancer-related mortality . Once GC has metastasized, the patient’s prognosis is poor. However, early diagnosis and treatment significantly increase patient survival . Detection of early-stage GC bares difficulties due to a complex interaction of pathophysiological pathways and endo- and exogenous factors . Chronic inflammation of the gastric mucosa can lead to the development of chronic atrophic gastritis (CAG), characterized by loss of specialized gastric glands, mucosal fibrosis and gastric intestinal metaplasia (GIM), a recognized precancerous lesion . A major contributing factor is inflammation caused by Helicobacter pylori ( H. pylori ), especially when left untreated. In large epidemiologic studies, up to 3.0% of patients suffering from H. pylori -associated gastritis developed gastric carcinoma . The potential role of dietary capsaicin (the bioactive pungent component of chili peppers) in GC development has long been subject to scientific debate , with no convincing evidence linking habitual capsaicin consumption to GC. However, some studies have suggested that chronic exposure or single high-dose capsaicin (30–60 milligrams per day) can induce gastric mucosal injury and (chronic) inflammation , whereas other studies suggested that capsaicin (particularly in lower doses corresponding to daily use) and its natural homologs and analogs (capsaicinoids) can prevent gastric mucosal damage related to alcohol and non-steroidal anti-inflammatory drugs and, therefore, may prevent gastric carcinogenesis . Given the potential role of capsaicin in gastric carcinogenesis, specific interest has been directed in recent studies toward its target, the transient receptor potential Vanilloid 1 (TRPV1) receptor , although non-TRPV1-mediated effects of capsaicin have also been described . The TRPV1 receptor is a calcium-permeable non-selective cation channel belonging to the transient receptor potential (TRP) cation channel family and is predominantly localized in extrinsic sensory fibers of the gastrointestinal tract and non-neuronal cells such as gastric epithelial cells . TRPV1 receptor activation leads to the alterations of intracellular calcium concentrations, inducing the release of several neuropeptides from sensory nerve endings, exerting vascular smooth muscle action, inflammatory cell proliferation and plasma protein extravasation, which suppress gastric acid production and may prevent apoptosis and oxidative stress . Regarding carcinogenesis, the involvement of TRPV1 as a tumor suppressor has been described in various carcinogenic pathways, including breast cancer, urothelial cell carcinoma and thyroid cancer . However, the upregulation of TRPV1 in colonic cancer and esophageal squamous cancer correlates with tumor progression, migration, and poor survival . In contrast, in vitro (over)expression of TRPV1 in mouse models of GC resulted in the inhibition of tumor proliferation, migration, tissue invasion and smaller tumor size. Others have found less peritoneal dissemination in TRPV1-depleted mice . In human GC cells, a significant decrease in TRPV1 expression was described, suggesting TRPV1 to be a potential marker for the prognosis of GC due to its correlation with GC progression . Considering the current literature, the role of TRPV1 expression in gastric carcinogenesis remains unclear. The main objective of this observational study was to assess TRPV1 expression in the gastric mucosa in patients with H. pylori -associated gastritis with and without GIM, CAG and intestinal-type adenocarcinoma. 2.1. Study Population and Samples Fifty-five patients were included for analysis, of whom 31 (65.4%) were females. The median age was 60.4 (±16.3) years, and 58.2% had an age over 60 years. Patients were distributed into five groups: five patients were labeled as controls with normal stomach mucosa, 12 patients with H. pylori -associated gastritis with GIM, 13 patients with CAG with GIM, 19 patients with H. pylori -associated gastritis without GIM and six patients with gastric adenocarcinoma. In all patients, at least one stomach tissue sample was retrieved during biopsy for analysis and immunohistochemical staining. In most patients, gastric biopsies were retrieved from the antral and body region of the stomach (n = 52, 94.5% of total). In three patients, only cardia (n = 2) or angulus (n = 1) were sampled. All patient characteristics are provided in . 2.2. TRPV1 Expression Is Lost in Gastric Adenocarcinoma After initial pathological examination, tissue samples underwent immunohistochemical staining for the assessment of TRPV1 immunopositivity ( A–D). In all tissue samples, the median immunoreactive score (IRS, paragraph 4.3 of the materials and methods section) was calculated to quantify TRPV1 expression, as outlined in . Additionally, a median IRS was calculated for each group of all cells combined (foveolar cells, parietal cells and chief cells). In parietal cells, the TRPV1 expression was generally higher in all groups. In foveolar cells of gastric tissue retrieved from controls, there was no TRPV1 expression; therefore, no median IRS could be calculated. In tissue samples identified as gastric adenocarcinoma, there was no TRPV1 expression in either foveolar cells, parietal cells or chief cells. 2.3. TRPV1 Expression Significantly Higher in GIM Compared with No GIM or Controls Between all groups, there were significant differences in TRPV1 expression, in which a significantly greater TRPV1-immunopositivity was found in patients with GIM compared with patients without GIM and controls . Similar results were seen when all cells were combined to calculate a mean IRS for each group ( A). This significant difference was confirmed using post hoc analysis, except for the inter-group difference of H. pylori versus GIM and CAG versus GIM ( p = 0.13). 2.4. Significant Differences TRPV1 Expression within All Groups according to Cell Type In controls, TRPV1 expression was significantly higher in parietal cells, followed by the TRPV1 expression in chief cells, and was the lowest in foveolar cells (F = 92.250, p < 0.002). Similar results were conducted within other groups, all statistically significant: H. pylori -associated gastritis with GIM (F = 12.123, p = 0.002), CAG with GIM (F = 10.583, p = 0.003), and H. pylori -associated gastritis without GIM (F = 9.534, p = 0.002). Post hoc analysis revealed the highest TRPV1 expression in parietal cells and the lowest in foveolar cells in all groups. Fifty-five patients were included for analysis, of whom 31 (65.4%) were females. The median age was 60.4 (±16.3) years, and 58.2% had an age over 60 years. Patients were distributed into five groups: five patients were labeled as controls with normal stomach mucosa, 12 patients with H. pylori -associated gastritis with GIM, 13 patients with CAG with GIM, 19 patients with H. pylori -associated gastritis without GIM and six patients with gastric adenocarcinoma. In all patients, at least one stomach tissue sample was retrieved during biopsy for analysis and immunohistochemical staining. In most patients, gastric biopsies were retrieved from the antral and body region of the stomach (n = 52, 94.5% of total). In three patients, only cardia (n = 2) or angulus (n = 1) were sampled. All patient characteristics are provided in . After initial pathological examination, tissue samples underwent immunohistochemical staining for the assessment of TRPV1 immunopositivity ( A–D). In all tissue samples, the median immunoreactive score (IRS, paragraph 4.3 of the materials and methods section) was calculated to quantify TRPV1 expression, as outlined in . Additionally, a median IRS was calculated for each group of all cells combined (foveolar cells, parietal cells and chief cells). In parietal cells, the TRPV1 expression was generally higher in all groups. In foveolar cells of gastric tissue retrieved from controls, there was no TRPV1 expression; therefore, no median IRS could be calculated. In tissue samples identified as gastric adenocarcinoma, there was no TRPV1 expression in either foveolar cells, parietal cells or chief cells. Between all groups, there were significant differences in TRPV1 expression, in which a significantly greater TRPV1-immunopositivity was found in patients with GIM compared with patients without GIM and controls . Similar results were seen when all cells were combined to calculate a mean IRS for each group ( A). This significant difference was confirmed using post hoc analysis, except for the inter-group difference of H. pylori versus GIM and CAG versus GIM ( p = 0.13). In controls, TRPV1 expression was significantly higher in parietal cells, followed by the TRPV1 expression in chief cells, and was the lowest in foveolar cells (F = 92.250, p < 0.002). Similar results were conducted within other groups, all statistically significant: H. pylori -associated gastritis with GIM (F = 12.123, p = 0.002), CAG with GIM (F = 10.583, p = 0.003), and H. pylori -associated gastritis without GIM (F = 9.534, p = 0.002). Post hoc analysis revealed the highest TRPV1 expression in parietal cells and the lowest in foveolar cells in all groups. In this observational histopathological study, TRPV1 expression was significantly higher in patients with H. pylori -associated gastritis compared with controls. When GIM was present, TRPV1 expression was even higher compared with patients without GIM, particularly in parietal cells. TRPV1 expression was completely absent in gastric adenocarcinoma. The role of TRPV1 in various inflammatory and carcinogenic pathways has been previously studied with contradictory results, revealing both pro- and anti-inflammatory and tumor-promoting and -suppressing effects. Several studies have demonstrated an increase in TRPV1 expression in various inflammatory processes, in which downregulating the TRPV1 receptor by genetic manipulation or inhibiting with an antagonist contributed to alterations in disease activity and severity . This effect was shown in animal studies addressing inflammatory bowel disease, demonstrating decreased inflammation and disease severity in TRPV1-depleted mice . In the gastric mucosa, the tachykinin substance P and CGRP are released in response to TRPV1 activation, which triggers neurogenic inflammatory pathways with consecutive inflammatory cell activation . H. pylori -induced gastric inflammation is associated with the upregulation of pro-inflammatory cytokines such as IL-6 and IFN-Ƴ, pathways in which the TRPV1 receptor activation can have a facilitating role . On the other hand, other studies have shown that a nontoxic dose of capsaicin inhibited the H. pylori -induced IL-8 production by gastric epithelial cells through the modulation of I-κB-, NF-κB- and IL-8 pathways . H. pylori -associated gastritis is known as an individual risk factor for the development of GC, especially when untreated . The co-administration of high-dose capsaicin (30–60 milligrams/day) has shown a synergistic contribution to accelerated loss of differentiated gastric epithelial cell types, leading to precancerous conditions such as GIM and CAG . The significant increase in TRPV1 expression in patients with H. pylori -associated gastritis compared with controls might be due to the pro-inflammatory roles of TRPV1. A pending knowledge gap remains: it is unclear whether H. pylori -associated gastritis leads to TRPV1 overexpression, thereby increasing the risk of gastric cancer, or if the secondary epithelial changes associated with TRPV1 expression result in (pre)malignant transformation. In addition, it remains to be established whether TRPV1-induced immune activation contributes to the further aggravation of H. pylori -gastritis or rather has mitigating effects. Future preclinical functional and prospective clinical research investigating the specific correlations of TRPV1 expression in H. pylori -associated gastritis and gastric carcinogenesis is needed. A complete loss of TRPV1 expression in gastric adenocarcinoma was found in our study population. This is largely in line with findings as described by Gao et al., in which a decreased TRPV1 expression in human GC was seen compared with tumor-adjacent tissue . This decrease was associated with tumor size, metastases and poor prognosis, suggesting a tumor suppressant role of TRPV1. The complete loss of TRPV1 in gastric carcinoma, as observed here, may imply a tumor suppressor role. Our study also showed a significantly higher TRPV1 expression in patients with GIM and CAG, both known as precancerous conditions . The number of reports underlining the involvement of calcium-permeable TRP channels in GC development is increasing, showing either aberrant receptor expression or function leading to alterations in intracellular calcium levels . Over the past two decades, several members of the TRP channel family besides TRPV1 have been identified in gastric carcinogenesis, including TRPV2/4/6, TRP Melastatin (TRPM) 2/5/7/8 and TRP Canonical (TRPC) 1/3/6 . However, most of these receptors are associated with upregulation or overexpression in gastric cancer and have been suggested as oncogene and tumor promotors in GC. Furthermore, the expression of TRPV2, TRPV4 and TRPV6 was found to increase according to the tumor stage with an association with poor prognosis, particularly in advanced stages . Additionally, the inhibition of various TRP channels, including TRPM2/8 and TRPV2/4, may suppress the progress of GC development. With regard to TRPV1, its activation leads to intracellular calcium increase and the activation of anti-oncogenic pathways, resulting in decreased expression of cyclin D1 and MMP2, among others. In line with this concept, the downregulation of TRPV1 expression in mice promoted GC cell proliferation, invasion and dissemination, suggesting a tumor suppressant role of TRPV1 . In contrast, another study found that the upregulation of TRPV1 expression after the administration of a high dose of (dietary) capsaicin (30–60 milligrams/day) can accelerate GC metastasis . Since there is significantly higher TRPV1 expression in patients with GIM or CAG compared with controls, the question arises whether this is due to a tumor-promoting effect eventually resulting in GC or a counterbalancing tumor-suppressant mechanism directed at mitigating the pro-cancerous processes. The eventual loss of TRPV1 expression is supportive of the latter notion. Hypothetically, TRPV1 expression could be considered a marker for precancerous conditions. Future longitudinal studies with serial assessment of TRPV1 staining as a part of surveillance endoscopies for gastric precancerous conditions could further clarify this issue. Moreover, it warrants further investigation to determine whether there is a relationship between capsaicin dose and its potential pro- or anti-carcinogenic effects and whether these effects are mediated by TRPV1-dependent mechanisms. Due to the retrospective nature of this observational immunopathological study with a small sample size, there are several limitations to be noted. Since this study had a purely observational nature, no longitudinal patient follow-up was performed. Therefore, it remains uncertain whether patients with precursor stages of gastric cancer did or did not develop malignant neoplasms. Additional verification of the staining of the immonohistochemistry of the pathological preparations would clarify this further. In addition, no functional readouts were conducted. Although errors in the immunohistochemical staining process could have occurred, mostly leading to underestimating TRPV1 immunopositivity, a significant increase in TRPV1 expression was found. This effect could, therefore, be even more apparent when correcting for this bias. In summary, this observational histopathological study is the first to address TRPV1 expression in precursor stages of GC and H. pylori -associated gastritis, which is an individual risk for GC development. Significantly increased TRPV1 expression was demonstrated in H. pylori -associated gastritis and was even greater in patients with GIM and CAG, but its complete loss was seen in GC. These findings point to a potential tumor-suppressive role of TRPV1 and suggest that TRPV1 expression is a potential biomarker for precancerous conditions and a putative novel target for individualized treatment. Future longitudinal clinical studies with follow-up of precursor stages of GC and those addressing the impact of TRPV1 agonists (e.g., capsaicin) should provide more insight into the exact role of TRPV1 in gastric carcinogenesis. 4.1. Study Design and Patient Selection In this observational study, samples were selected based on a retrospective review of the pathology records of patients who underwent upper gastrointestinal (GI) endoscopy at Maastricht University Medical Center+ (MUMC+) in Maastricht, the Netherlands, between 2009 and 2017. Patient inclusion was based on a histopathological diagnosis, which was confirmed independently by two pathologists. Patients were subdivided into five groups based on pathologic diagnosis: H. pylori -associated gastritis without GIM, H. pylori infection-associated gastritis with GIM, CAG, adenocarcinoma (intestinal type carcinoma) and controls. In all patients, multiple biopsies were taken from the stomach according to the Sydney protocol, using standard biopsy forceps with a diameter of 2.8 mm (Boston Scientific, Marlborough, MA, USA). The initial indication for performing an upper GI endoscopy included upper GI symptoms (p.e. regurgitation, upper stomach pain), iron deficiency and anemia. Controls were selected from the pathological records of patients who underwent upper GI endoscopy to exclude celiac disease, in which multiple biopsies were taken in the stomach and duodenum. After excluding celiac disease and other gastric pathological conditions using histopathological evaluation as described earlier, patients were assigned to the control group. 4.2. Ethical Statement and Tissue Sampling The study was approved by the Local Ethic Committee (METC number 16-4-012) of the Maastricht University Medical Center+ (MUMC+). After initial histopathological examination in MUMC+, human tissue samples were anonymized for secondary immunohistochemical assessment and securely shipped to the laboratory of the University of Pécs/Szentágothai Research Center in Pécs, Hungary. Tissue samples were digitalized after immunohistochemical staining in an anonymized electronic database. 4.3. TRPV1 Immunohistochemical Staining Tissue samples were formalin-fixed and paraffin-embedded, and 5 µm sections were cut as part of a routine pathological specimen work-up. For secondary analysis of TRPV1 expression, tissue samples were deparaffinized, rehydrated and incubated in an acidic citrate buffer (pH = 6) in a microwave oven for antigen recovery. Endogenous peroxidase activity was quenched using 3% hydrogen peroxide. After sections were washed and incubated in a blocking solution, anti-TRPV1 antibodies were applied (GP14100; Neuromics, Edina, MN, USA). Slides were then incubated with an anti-rabbit antibody conjugated with the EnVision system with horse radish peroxidase (DakoCytomation, Carpinteria, CA, USA). To visualize the reaction, 3,3-diaminobenzide tetrachloride was used, followed by counterstaining with hematoxylin . Validation of antibody selectivity was validated by the lack of immunopositivity after the application of the blocking peptide (Neuromics, Edina, MN, USA) based on previous studies . 4.4. Quantification of TRPV1 Expression The quantitative assessment of TRPV1 immunopositivity was performed in every tissue sample in the three main stomach cells: foveolar cells, parietal cells and chief cells. This quantitative assessment was based on the intensity of the immunohistochemical staining and the proportion of immunopositive cells on 10 fields of vision/slide/biopsy by an expert pathologist (A.S.) blinded to the clinical results of the initial pathology analysis (performed by H.G. and I.S.). Only the results of the quantitative assessment are reported in this study. Immunohistochemical staining density was scored on a four-point scale: no immunoreactivity (0), weak staining (1), moderate staining (2) and strong staining (3) ( , A). The proportion of immunopositive cells was scored as none (0), less than 25% of the area (1), 25–49% of the area (2), 50–74% of the area (3) and more than 75% of the area (4) ( , B). To summarize the quantification of TRPV1 expression in biopsies, the IRS was calculated as follows: Intensity scale (A) X proportion of positive staining (B). Scores were subsequently grouped to form the IRS (scale 1–12). In addition, the IRS provides quantitative TRPV1 expression on a four-point scale: negative (0–1), slightly positive (2–3), moderately positive (4–8) and strongly positive (9–12) ( , C) . Tissue samples were digitalized for evaluation using a Pannoramic Digital Slide Scanner with CaseViewer software version 2.4 (3D HISTECH Ltd., Budapest, Hungary). 4.5. Data and Statistical Analysis Statistical analysis was performed using SPSS statistics 28.0 (IBM, Armonk, NY, USA) and R version 4.4.0 (R Core Team, 2024. R: A language and environment for statistical computing. Vienna, Austria). Continuous data were presented as medians and interquartile ranges (IQRs) and categorical data as proportions . To compare (non-parametric) continuous data between subgroups, the Kruskal–Wallis test and post hoc Tukey’s test were conducted. To compare (non-parametric) continuous data within subgroups, a repeated measures ANOVA was conducted, including Mauchly’s Test of Sphericity, to assess the assumption of sphericity. Greenhouse–Geisser corrections were applied where necessary. Post hoc comparisons were conducted by using a paired sample t-test with Bonferroni correction for multiple testing. A P value of <0.05 was deemed statistically significant. Considering the exploratory nature of the study, no formal sample size calculation was performed. In this observational study, samples were selected based on a retrospective review of the pathology records of patients who underwent upper gastrointestinal (GI) endoscopy at Maastricht University Medical Center+ (MUMC+) in Maastricht, the Netherlands, between 2009 and 2017. Patient inclusion was based on a histopathological diagnosis, which was confirmed independently by two pathologists. Patients were subdivided into five groups based on pathologic diagnosis: H. pylori -associated gastritis without GIM, H. pylori infection-associated gastritis with GIM, CAG, adenocarcinoma (intestinal type carcinoma) and controls. In all patients, multiple biopsies were taken from the stomach according to the Sydney protocol, using standard biopsy forceps with a diameter of 2.8 mm (Boston Scientific, Marlborough, MA, USA). The initial indication for performing an upper GI endoscopy included upper GI symptoms (p.e. regurgitation, upper stomach pain), iron deficiency and anemia. Controls were selected from the pathological records of patients who underwent upper GI endoscopy to exclude celiac disease, in which multiple biopsies were taken in the stomach and duodenum. After excluding celiac disease and other gastric pathological conditions using histopathological evaluation as described earlier, patients were assigned to the control group. The study was approved by the Local Ethic Committee (METC number 16-4-012) of the Maastricht University Medical Center+ (MUMC+). After initial histopathological examination in MUMC+, human tissue samples were anonymized for secondary immunohistochemical assessment and securely shipped to the laboratory of the University of Pécs/Szentágothai Research Center in Pécs, Hungary. Tissue samples were digitalized after immunohistochemical staining in an anonymized electronic database. Tissue samples were formalin-fixed and paraffin-embedded, and 5 µm sections were cut as part of a routine pathological specimen work-up. For secondary analysis of TRPV1 expression, tissue samples were deparaffinized, rehydrated and incubated in an acidic citrate buffer (pH = 6) in a microwave oven for antigen recovery. Endogenous peroxidase activity was quenched using 3% hydrogen peroxide. After sections were washed and incubated in a blocking solution, anti-TRPV1 antibodies were applied (GP14100; Neuromics, Edina, MN, USA). Slides were then incubated with an anti-rabbit antibody conjugated with the EnVision system with horse radish peroxidase (DakoCytomation, Carpinteria, CA, USA). To visualize the reaction, 3,3-diaminobenzide tetrachloride was used, followed by counterstaining with hematoxylin . Validation of antibody selectivity was validated by the lack of immunopositivity after the application of the blocking peptide (Neuromics, Edina, MN, USA) based on previous studies . The quantitative assessment of TRPV1 immunopositivity was performed in every tissue sample in the three main stomach cells: foveolar cells, parietal cells and chief cells. This quantitative assessment was based on the intensity of the immunohistochemical staining and the proportion of immunopositive cells on 10 fields of vision/slide/biopsy by an expert pathologist (A.S.) blinded to the clinical results of the initial pathology analysis (performed by H.G. and I.S.). Only the results of the quantitative assessment are reported in this study. Immunohistochemical staining density was scored on a four-point scale: no immunoreactivity (0), weak staining (1), moderate staining (2) and strong staining (3) ( , A). The proportion of immunopositive cells was scored as none (0), less than 25% of the area (1), 25–49% of the area (2), 50–74% of the area (3) and more than 75% of the area (4) ( , B). To summarize the quantification of TRPV1 expression in biopsies, the IRS was calculated as follows: Intensity scale (A) X proportion of positive staining (B). Scores were subsequently grouped to form the IRS (scale 1–12). In addition, the IRS provides quantitative TRPV1 expression on a four-point scale: negative (0–1), slightly positive (2–3), moderately positive (4–8) and strongly positive (9–12) ( , C) . Tissue samples were digitalized for evaluation using a Pannoramic Digital Slide Scanner with CaseViewer software version 2.4 (3D HISTECH Ltd., Budapest, Hungary). Statistical analysis was performed using SPSS statistics 28.0 (IBM, Armonk, NY, USA) and R version 4.4.0 (R Core Team, 2024. R: A language and environment for statistical computing. Vienna, Austria). Continuous data were presented as medians and interquartile ranges (IQRs) and categorical data as proportions . To compare (non-parametric) continuous data between subgroups, the Kruskal–Wallis test and post hoc Tukey’s test were conducted. To compare (non-parametric) continuous data within subgroups, a repeated measures ANOVA was conducted, including Mauchly’s Test of Sphericity, to assess the assumption of sphericity. Greenhouse–Geisser corrections were applied where necessary. Post hoc comparisons were conducted by using a paired sample t-test with Bonferroni correction for multiple testing. A P value of <0.05 was deemed statistically significant. Considering the exploratory nature of the study, no formal sample size calculation was performed. |
Positive family history of colorectal cancer in a general practice setting [FRIDA.Frankfurt]: study protocol of a of a cross-sectional study | 28f992c7-db43-4a27-8806-5bf3b9a7215e | 4552264 | Preventive Medicine[mh] | The risk of developing colorectal cancer (CRC) is 2–4 times higher in case of a family predisposition . A repeat occurrence within a family can be noted in around 30 % of all cases of CRC, whereby around 5 % of these are associated with hereditary types of CRC. The family predisposition for the remaining ~25 % of cases has not yet been properly explained . The different constellations of risk are currently not taken into account in the directives of the German Federal Joint Committee on cancer screening . In 2013, the usefulness of colorectal cancer screening for persons under 55 years of age with a family predisposition was declared by the IQWIG to be uncertain, as no high quality studies could be identified in which comprehensive screening strategies in the general population had been analyzed using anamnestic instruments . The “Network against colorectal cancer” questionnaire has shown that information on a positive family history is partly overstated when patients fill in questionnaires themselves, as opposed to when they are personally interviewed, and that when findings are positive, only 40 % of those concerned inform their GP or gastroenterologist . In two current reviews, the role of the GP and other medical personnel is described as being the most important factor influencing the decision to participate in screening examinations , and as having a greater influence than written invitations . As around 92 % of the German general population have a GP and around 89 % annually make use of outpatient services , screening participation rates are expected to be high. The “European Guideline for Quality Assurance in CRC screening and diagnosis” recommends that patients should be spoken to personally . This is easy for the GP to do on account of the trusting relationship he has with his patients. In view of the new law on the further development of cancer screening, as well as further clarification demanded by the German Federal Joint Committee, the proposed project could raise the awareness of the importance of family predisposition for future CRC screening programs . Research questions The following primary research question will be addressed: What is the frequency of positive family history of CRC (1 st degree relatives with CRC) among 40–54 year old persons in a German GP setting? Secondary research questions are: What is the frequency of colorectal neoplasms (CRC and advanced adenomas) in 1 st degree relatives of CRC patients in a German GP setting? What variables (e.g., demographic, genetic, epigenetic and proteomic characteristics) are associated with an increased risk of CRC? How can evidence-based information contribute to informed decisions with respect to screening? How does screening participation correlate with anxiety and regret? Study design and setting FRIDA.Frankfurt is a cross-sectional study in a general practice setting. Prior to the beginning of the study, the practice team (GP and one health care assistant (HCA)) will be briefly trained by study personnel in how to conduct the study in their practices. Before this session, a list of all 40–54 year old patients who have attended the practice within the last twelve months will be compiled by means of the practice software. Afterwards the HCA will contact eligible patients and complete the “Network against colorectal cancer” questionnaire (see screening list, Additional file ) during a routine practice visit, or per telephone. Those who have a positive family history will then be invited to participate in the study and to give their informed consent to do so. With the help of study materials that are presented clearly and informatively (both graphic and text based), the GP is expected to be able to provide family members related to CRC patients with adequate evidence-based information and to describe prevention strategies. During this first practice visit we plan to examine the participant’s family history of (colorectal-) cancer in further detail, collect information on previous CRC-screening tests, and gather information on other variables (e.g. demographics) associated with an increased risk of CRC (see questionnaire 1, Additional file ). Study participants with a hereditary risk of CRC (suspected or already known) will be documented and excluded from subsequent study-phases. In a second practice visit within two weeks of the first, details on anxiety, anticipated regret and reasons for or against participation with respect to screening will be collected before the study participants inform their GP about their decision. Furthermore, informed decision will be assessed using the validated instrument from Steckelberg et al. . The selected screening test (colonoscopy, fecal occult blood test) will be documented (see questionnaire 2, Additional file ). If study participants are willing to undergo a colonoscopy, the GP will schedule an appointment with the gastroenterologist, and ask the participant for a blood- and stool-sample and to fill in an additional questionnaire (see questionnaire 3, Additional file ). The results of the colonoscopy will be documented from the gastroenterologist’s report for the GP. We will also collect information on study participants who are not willing to participate in CRC-screening (e.g. colonoscopy before study participation due to a known positive family history of CRC). Twelve weeks after the first practice visit, questionnaires asking about anxiety and regret will be sent out by post to all persons who participate in the study (see questionnaire 4, Additional file ). For further details see flow chart (Fig. ). Details on methods and design are laid down in the original study protocol, which can be provided by the corresponding author on demand. Main practice and patient in- and exclusion criteria Doctors at participating trial sites must work as a general practitioner (GP or specialist in internal medicine), provide health services to persons with German statutory health insurance, have software which is capable of detecting potentially eligible patients, and work in a practice located in the German state of Hesse. Participating GPs and Health Care Assistants must also agree to the contractual obligations of the trial. Patients must be 40–54 years of age, regularly attend the GP’s practice (at least one contact in the last 12 months) and sign an informed consent form. A lack of German language skills and gravidity are exclusion criteria for patients. Sample size calculation As of August 2013, the “Forschungsnetzwerk Allgemeinmedizin Frankfurt” (ForN) database contained approximately 100 general practices. An average-sized practice treats about 1000 patients/quarter of which about 25 % are 40–54 years of age. Over the course of a year, about 250 eligible patients will attend any one practice. It is to be expected that at least 50 % of practices (50) will participate in the study and at least 70 % of patients will complete the questionnaire (175/practice). The expected sample size is at least 8,750 of which about 875 (10 %) are expected to have a positive family history of colorectal cancer . Of these, we expect around 350 (40 %) persons to follow the invitation to have a colonoscopy. Recruitment, study timeline and reimbursement The trial will be primarily conducted in general practices in the state of Hesse. Eligible practices will be recruited mainly through the “Forschungsnetzwerk Allgemeinmedizin Frankfurt” (ForN) which is a network of general practices that have successfully conducted research projects with our Institute . During an approximately eight-month period beginning in September, 2014, about 8,750 persons attending the general practices will be asked about their family history (see Fig. ). As compensation, recruitment practices will receive €2 per individual that is interviewed by the HCA on the basis of the “network against colorectal cancer questionnaire” / screening list, and €10 per individual that is counselled by a GP, provided with the evidence-based decision aid, and completed all questionnaires on risk-factors, anxiety, (anticipated) regret and informed decision. Data collection and quality assurance/avoidance of biases and monitoring At the practices, the HCA will contact eligible patients and complete the “Network against colorectal cancer” questionnaire in a screening list with them (see screening list, Additional file ). Every document includes information on how to fill in the form. The informed consent forms are sent to the Institute of General Practice (IGP) via fax on the day of the participant’s visit to the practice, and the questionnaires will later be collected from the practice by a member of the study team. Questionnaire 4 will be send to the study-participants by post. If necessary, the IGP will send out a reminder to participants after 2 weeks. All questionnaires are shown in Additional files , , and . The IGP study team will ensure that all processes in the trial comply with Good Clinical Practice (GCP) guidelines, the legal requirements and the standard operating procedures (SOPs) of the IGP. The patient questionnaires, patient information brochure and informed consent form will be piloted to check their comprehensibility and applicability. During the first visit, participating GPs and the HCA will be thoroughly trained and provided with the information required to conduct all steps in the study. Amongst other things, this will include the identification of suitable patients, help for patients in filling out the questionnaire on socio-demographic data, and the collection of data on those that are not willing to participate. All information from forms (e.g. CRFs) will be transferred to the clinical study database (IBM SPSS Statistics). A data check of this database will take place according to pre-defined trial rules (range-, validity-, and consistency- checks according to defined SOPs developed during the course of the trial and documented in the trial master file). Follow-up enquiries resulting from the data plausibility check will be resolved with the help of the GP or HCA concerned. The collection and processing of patient data will always be conducted using the patient identification number (Pat.-ID) pseudonym from the GP’s practice software. To ensure high-quality data, all pseudonymization will be conducted by the trained HCA in the GP’s practice. For the future investigation of genetic, epigenetic and proteomic biomarkers associated with CRC-risk, a blood and stool sample will be taken from study-participants that have decided to undergo a colonoscopy. The blood and stool samples and data from questionnaires about other risk-factors will be transferred to the German Cancer Research Center (DKFZ) in pseudonymized form and stored there. In addition, a qualitative and a quantitative fecal occult blood test will be performed at the DKFZ. All blood and stool samples, as well as further data, will be anonymized at the DKFZ and stored in the central biorepository. Study members of the IGP will perform on-site monitoring visits as frequently as necessary and record the dates of their visits in a database (Access®). At the visits, a study member will check the completeness and accuracy of the data, and, if necessary, compare the data entered into the CRFs with clinical records (source documents). Direct access to source documents must be permitted in order to verify that the data recorded in the CRF and other forms are consistent with the original source data. Findings from this review will be discussed with the GP and HCA. The study members will stay in regular contact with the GP and HCA and provide feedback on the course of the study. Data collection is scheduled to be completed by June 30, 2015. Analysis The data collected in this study will be described in terms of mean, standard deviation, median, minimum, maximum and quartiles for continuous variables, while absolute and relative frequencies will be computed for categorical variables. Scores on the applied standardized questionnaires will be calculated according to the user manuals. Frequencies of positive family histories will be reported in combination with confidence intervals. Exploration of associated variables and group comparisons, e.g. in patients that have undergone or not undergone a colonoscopy, will be performed using logistic or linear regression models as appropriate. All models will be adjusted for relevant confounders. Mixed linear models will be applied in case of paired data or repeated measures. A detailed description of the statistical methods used in this study will be provided in a Statistical Analysis Plan (SAP) which will be finished before database closure. Ethical approval and study registration Ethical approval for the study was obtained from the leading Ethics Committee at the Frankfurt University Hospital on July 8, 2014. Once the ethical approval has been given by one ethical council in Germany, it applies to all participating sites in the same federal state. The study has been registered in the German Clinical Trials Register; DRKS00006277 . The following primary research question will be addressed: What is the frequency of positive family history of CRC (1 st degree relatives with CRC) among 40–54 year old persons in a German GP setting? Secondary research questions are: What is the frequency of colorectal neoplasms (CRC and advanced adenomas) in 1 st degree relatives of CRC patients in a German GP setting? What variables (e.g., demographic, genetic, epigenetic and proteomic characteristics) are associated with an increased risk of CRC? How can evidence-based information contribute to informed decisions with respect to screening? How does screening participation correlate with anxiety and regret? FRIDA.Frankfurt is a cross-sectional study in a general practice setting. Prior to the beginning of the study, the practice team (GP and one health care assistant (HCA)) will be briefly trained by study personnel in how to conduct the study in their practices. Before this session, a list of all 40–54 year old patients who have attended the practice within the last twelve months will be compiled by means of the practice software. Afterwards the HCA will contact eligible patients and complete the “Network against colorectal cancer” questionnaire (see screening list, Additional file ) during a routine practice visit, or per telephone. Those who have a positive family history will then be invited to participate in the study and to give their informed consent to do so. With the help of study materials that are presented clearly and informatively (both graphic and text based), the GP is expected to be able to provide family members related to CRC patients with adequate evidence-based information and to describe prevention strategies. During this first practice visit we plan to examine the participant’s family history of (colorectal-) cancer in further detail, collect information on previous CRC-screening tests, and gather information on other variables (e.g. demographics) associated with an increased risk of CRC (see questionnaire 1, Additional file ). Study participants with a hereditary risk of CRC (suspected or already known) will be documented and excluded from subsequent study-phases. In a second practice visit within two weeks of the first, details on anxiety, anticipated regret and reasons for or against participation with respect to screening will be collected before the study participants inform their GP about their decision. Furthermore, informed decision will be assessed using the validated instrument from Steckelberg et al. . The selected screening test (colonoscopy, fecal occult blood test) will be documented (see questionnaire 2, Additional file ). If study participants are willing to undergo a colonoscopy, the GP will schedule an appointment with the gastroenterologist, and ask the participant for a blood- and stool-sample and to fill in an additional questionnaire (see questionnaire 3, Additional file ). The results of the colonoscopy will be documented from the gastroenterologist’s report for the GP. We will also collect information on study participants who are not willing to participate in CRC-screening (e.g. colonoscopy before study participation due to a known positive family history of CRC). Twelve weeks after the first practice visit, questionnaires asking about anxiety and regret will be sent out by post to all persons who participate in the study (see questionnaire 4, Additional file ). For further details see flow chart (Fig. ). Details on methods and design are laid down in the original study protocol, which can be provided by the corresponding author on demand. Doctors at participating trial sites must work as a general practitioner (GP or specialist in internal medicine), provide health services to persons with German statutory health insurance, have software which is capable of detecting potentially eligible patients, and work in a practice located in the German state of Hesse. Participating GPs and Health Care Assistants must also agree to the contractual obligations of the trial. Patients must be 40–54 years of age, regularly attend the GP’s practice (at least one contact in the last 12 months) and sign an informed consent form. A lack of German language skills and gravidity are exclusion criteria for patients. As of August 2013, the “Forschungsnetzwerk Allgemeinmedizin Frankfurt” (ForN) database contained approximately 100 general practices. An average-sized practice treats about 1000 patients/quarter of which about 25 % are 40–54 years of age. Over the course of a year, about 250 eligible patients will attend any one practice. It is to be expected that at least 50 % of practices (50) will participate in the study and at least 70 % of patients will complete the questionnaire (175/practice). The expected sample size is at least 8,750 of which about 875 (10 %) are expected to have a positive family history of colorectal cancer . Of these, we expect around 350 (40 %) persons to follow the invitation to have a colonoscopy. The trial will be primarily conducted in general practices in the state of Hesse. Eligible practices will be recruited mainly through the “Forschungsnetzwerk Allgemeinmedizin Frankfurt” (ForN) which is a network of general practices that have successfully conducted research projects with our Institute . During an approximately eight-month period beginning in September, 2014, about 8,750 persons attending the general practices will be asked about their family history (see Fig. ). As compensation, recruitment practices will receive €2 per individual that is interviewed by the HCA on the basis of the “network against colorectal cancer questionnaire” / screening list, and €10 per individual that is counselled by a GP, provided with the evidence-based decision aid, and completed all questionnaires on risk-factors, anxiety, (anticipated) regret and informed decision. At the practices, the HCA will contact eligible patients and complete the “Network against colorectal cancer” questionnaire in a screening list with them (see screening list, Additional file ). Every document includes information on how to fill in the form. The informed consent forms are sent to the Institute of General Practice (IGP) via fax on the day of the participant’s visit to the practice, and the questionnaires will later be collected from the practice by a member of the study team. Questionnaire 4 will be send to the study-participants by post. If necessary, the IGP will send out a reminder to participants after 2 weeks. All questionnaires are shown in Additional files , , and . The IGP study team will ensure that all processes in the trial comply with Good Clinical Practice (GCP) guidelines, the legal requirements and the standard operating procedures (SOPs) of the IGP. The patient questionnaires, patient information brochure and informed consent form will be piloted to check their comprehensibility and applicability. During the first visit, participating GPs and the HCA will be thoroughly trained and provided with the information required to conduct all steps in the study. Amongst other things, this will include the identification of suitable patients, help for patients in filling out the questionnaire on socio-demographic data, and the collection of data on those that are not willing to participate. All information from forms (e.g. CRFs) will be transferred to the clinical study database (IBM SPSS Statistics). A data check of this database will take place according to pre-defined trial rules (range-, validity-, and consistency- checks according to defined SOPs developed during the course of the trial and documented in the trial master file). Follow-up enquiries resulting from the data plausibility check will be resolved with the help of the GP or HCA concerned. The collection and processing of patient data will always be conducted using the patient identification number (Pat.-ID) pseudonym from the GP’s practice software. To ensure high-quality data, all pseudonymization will be conducted by the trained HCA in the GP’s practice. For the future investigation of genetic, epigenetic and proteomic biomarkers associated with CRC-risk, a blood and stool sample will be taken from study-participants that have decided to undergo a colonoscopy. The blood and stool samples and data from questionnaires about other risk-factors will be transferred to the German Cancer Research Center (DKFZ) in pseudonymized form and stored there. In addition, a qualitative and a quantitative fecal occult blood test will be performed at the DKFZ. All blood and stool samples, as well as further data, will be anonymized at the DKFZ and stored in the central biorepository. Study members of the IGP will perform on-site monitoring visits as frequently as necessary and record the dates of their visits in a database (Access®). At the visits, a study member will check the completeness and accuracy of the data, and, if necessary, compare the data entered into the CRFs with clinical records (source documents). Direct access to source documents must be permitted in order to verify that the data recorded in the CRF and other forms are consistent with the original source data. Findings from this review will be discussed with the GP and HCA. The study members will stay in regular contact with the GP and HCA and provide feedback on the course of the study. Data collection is scheduled to be completed by June 30, 2015. The data collected in this study will be described in terms of mean, standard deviation, median, minimum, maximum and quartiles for continuous variables, while absolute and relative frequencies will be computed for categorical variables. Scores on the applied standardized questionnaires will be calculated according to the user manuals. Frequencies of positive family histories will be reported in combination with confidence intervals. Exploration of associated variables and group comparisons, e.g. in patients that have undergone or not undergone a colonoscopy, will be performed using logistic or linear regression models as appropriate. All models will be adjusted for relevant confounders. Mixed linear models will be applied in case of paired data or repeated measures. A detailed description of the statistical methods used in this study will be provided in a Statistical Analysis Plan (SAP) which will be finished before database closure. Ethical approval for the study was obtained from the leading Ethics Committee at the Frankfurt University Hospital on July 8, 2014. Once the ethical approval has been given by one ethical council in Germany, it applies to all participating sites in the same federal state. The study has been registered in the German Clinical Trials Register; DRKS00006277 . In this cross-sectional study we primarily want to investigate the frequency of positive family history of CRC (1 st degree relatives with CRC) among 40–54 year old persons in a German GP setting. Further outcomes are to detect the frequency of colorectal neoplasms (CRC and advanced adenomas) in 1 st degree relatives of CRC patients and the kinds of variables that are associated with an increased risk of CRC. In addition, one major objective will be to measure how evidence-based information contributes to making informed decisions with respect to screening and how participation in screening correlates with anxiety and (anticipated) regret. The role of the GP is an important factor towards screening examinations . It would therefore appear reasonable to expect data that is collected by a specially trained and therefore highly motivated general practice team to be of significantly higher quality. It can further be expected that when professional advice is provided by such a general practice team, colonoscopy participation rates will be higher than otherwise , and that this, in turn, will result in an increase in the size of the cohort available to collect information on variables (both demographic variables and biomarkers) for further identification of persons with a positive medical family history. The absence of standardized colonoscopy reports from different gastroenterologists is a potential limitation of this study. Further, variables associated with an increased risk of CRC will be analyzed only among 1 st degree relatives of CRC patients. However, this study provides a strong translational context as it involves the creation of new collaborations and synergies involving GPs, clinical epidemiologists and gastroenterologists. |
Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives | c3ad9db4-4987-40c7-877f-d325e6151576 | 10977610 | Pharmacology[mh] | Pharmacogenomics (PGx) is a rapidly growing field of medicine that focuses on the relationship between an individual’s genetic makeup and their response to medications. This field is a prominent example of precision medicine, as it enables the prediction of medication effectiveness, potential toxicity, and the most appropriate dosage . The utilization of PGx testing in clinical setting has the potential to significantly transform healthcare delivery. By incorporating genetic information to tailor treatment plans, healthcare providers can improve patient outcomes and lower healthcare costs . However, the implementation of pharmacogenomics in clinical practice has been a slow process. Historically, there have been challenges associated with the interpretation of genetic data and the integration of this information into clinical decision-making . The primary objective of this paper is to shed light on the critical role of PGx in the field of precision medicine and its potential impact on healthcare delivery. Specifically, we aim to explore the current state of PGx research and implementation in Qatar and its relevance in the global context. Qatar, with its rapidly advancing healthcare infrastructure and diverse population, serves as an ideal case study for understanding the challenges and opportunities associated with integrating PGx into clinical practice in the Middle East . By focusing on Qatar, we hope to provide insights that can be valuable not only to the local healthcare system but also to the broader international community interested in the advancements of PGx. First, we will provide an overview of the current landscape of PGx in Qatar in the wider global context, emphasizing the ongoing research initiatives. Recognizing that education and awareness are pivotal for realizing PGx’s full potential in healthcare, we will then emphasize the value of educational efforts and other initiatives in Qatar that support the implementation of PGx. Finally, we will address challenges associated with implementation and outline future directions for the field. The global context Globally, research has helped in identifying several genetic variants that are associated with response and potential adverse effects to various drugs . Often such research involves a small number of patients from a specific population and hence generalizability and statistical significance are not achieved. At times, results from multiple studies are discordant for the same drug-gene pairs and unable to provide conclusive evidence in support of involvement of the genetic variant in drug response. Despite these issues, systematic efforts in mining the literature have identified a number of genes with enough evidence to be implicated in response. For example, the pharmacogenomics knowledgebase (PharmGKB) has extensively curated information about the impact of genetic variation on drug response. Such information is organized under various categories, such as prescribing information, drug label annotations, curated pathways, clinical annotations and variant annotations . While the variant annotation section provides information on the association between a genetic variant and a medication from a single publication, the clinical annotations section summarizes all such published evidence. The provision of a score and assigning a level of evidence to each genetic variant-drug combination based on all the evidence help in prioritizing which genes should be tested as priority. The sections on drug label annotations and prescribing information further help in understanding the practical requirements of genetic testing and how the test results should be interpreted. Drug regulatory agencies in several countries specify drug labels. Moreover, agencies including the US Food and Drug Administration (FDA), Swissmedic, Japanese Pharmaceutical and Medical Devices Agency (PMDA) and the European Medicines Agency (EMA) in their labels provide information on genetic variants affecting the medication and also at times on the requirement of genetic testing prior to prescription of the drug . Further support for the interpretation of PGx test results and how to incorporate these in the electronic medical records system are provided through guidelines by efforts such as the US-based Clinical Pharmacogenetic Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG) founded by the Royal Dutch Pharmacists Association (KNMP) in the Netherlands, Canadian Pharmacogenomics Network for Drug Safety (CPNDS) and the French National Network of Pharmacogenetics (RNPGx) . The CPIC has developed guidelines close to 100 genes – drugs pair . Similarly, the DPWG has so far developed 86 evidence-based gene-drug pair guidelines, of which close to 47 guidelines provide therapeutic recommendations for aberrant phenotypes that have been fully integrated into the electronic health records for clinical decision support . Several large studies are currently underway in different parts of the world to evaluate the use of gene panel based PGx approaches. Examples of studies from the USA include CLIPMERGE PGx, eMERGE-PGx, PG4KDS, IGNITE, INGENIOUS PGx, RIGHT 10 K, and the 1,200 Patients Project . For example, the “RIGHT 10 K” study is a collaborative effort between Mayo Clinic and Baylor College of Medicine, aimed at utilizing genomic data to personalize medical treatment for patients. The primary goal was to integrate preemptive, sequence-based PGx into routine clinical care practices. This involved proactively utilizing genetic information to guide drug prescribing decisions for patients. This study involves more than 10,000 patients at Mayo Clinic, who have had their pharmacogenes sequenced using samples from the Mayo Clinic Biobank. The study worked on developing the necessary tools and resources required to implement clinical pharmacogenomics effectively, including the creation of databases, algorithms, and reporting systems. Additionally, it conducted assessments to determine the prevalence of both well-documented common genetic variations, for which clinical guidelines are already established, and rare genetic variations that could be identified through DNA sequencing as opposed to traditional genotyping methods . In Europe, recently a randomized controlled trial (RCT) (PREPARE) was conducted in 8,100 patients as part of the U-PGx project to investigate the impact of pre-emptive PGx testing of a panel of 13 pharmacogenes. The study showed the viability and advantages of applying PGx decision assistance in a variety of European healthcare settings, including better prescribing practices and patient outcomes . PGx research in Africa is also gaining traction, with a focus on addressing health disparities and improving drug access. The Human Heredity and Health in Africa (H3Africa) initiative is a prime example, involving multiple African countries. The African Pharmacogenomics Consortium (APC) was launched in 2018 to initiate PGx characterization of African diverse population when Caucasian and Asian population-based algorithms failed for the African population . PGx diversity was assessed among 64 countries across Asia from the GenomeAsia 100 K Project pilot using a whole-genome sequencing dataset of 1,739 individuals of 219 population groups. This study predicted adverse drug reactions (ADRs) due to carbamazepine, clopidogrel, peginterferon and warfarin to vary between populations widely from zero to hundred percent . The Southeast Asian Pharmacogenomics Research Network (SEAPharm) was formed to enhance the understanding of PGx specifically in the region . The IndiGen national genome sequencing initiative in India analyzed 1,029 whole genomes and unveiled key PGx variants in Indians. Findings indicate notable disparities in clinically actionable PGx variant frequencies compared to global populations. A total of 134 common, potentially deleterious PGx variants affecting 102 pharmacogenes were identified. On average, each Indian individual carried eight PGx variants that can directly impact treatment choices or drug dosing . Findings from further analysis focusing on kinase-coding genes, a prominent category of drug targets, emphasized the importance of identifying and addressing ADRs unique to the Indian population. These insights hold the potential to advance the development of pre-clinical and post-market screening techniques specifically tailored for monitoring ADRs in India . Due to the high genetic variability of the populations in lower and middle income countries (LMICs), genotyping is necessary before PGx clinical use . However, recent surveys showed that limited PGx research in LMICs has resulted in lower adoption of PGx testing . PGx research in Qatar and the Middle East region PGx research in the Middle East has gained prominence due to the region’s distinctive genetic diversity, historical population movements and cultural interactions. This unique genetic makeup has significant implications for drug response variability among individuals. Researchers are actively investigating genetic factors influencing drug metabolism and responses, aiming to personalize treatments, improve drug effectiveness, and reduce adverse reactions. This research has the potential to improve healthcare outcomes, especially in populations with diverse genetic backgrounds like those found in the Middle East. Qatar has been in the forefront of PGx research among the countries in the Middle East region . This region is characterized by a high genetic diversity and admixture due to historical migrations and cultural exchanges. Therefore, it is possible that there are unique genetic variants or haplotypes in this region that affect response to drugs such as warfarin. To explore this possibility, a study was conducted on warfarin dosage requirement in patients. The study included 132 Qatari (discovery) and 50 Egyptian (replication) patients who were genotyped using Illumina Multi-Ethnic Global BeadChip Array. This study performed a meta-analysis, combining the Qatari and Egyptian cohorts, and a gene-based analysis to identify genes associated with warfarin dose variability. The results showed that the most significant genetic variants associated with warfarin dose requirements were located in chromosome 16, near the VKORC1 gene. The lead genome wide signal was VKORC1 rs9934438 (β = −0.17, p = 6 × 10 −15 ), which is a well-known variant that has been previously reported in other populations. The study also identified other SNPs in chromosome 10 at a p value less than 1 × 10 −5 , but these SNPs did not reach genome wide significance. The genetic variants within VKORC1 rs9934438 and CYP2C9 rs4086116 explained 39 and 27% of the variability in the weekly warfarin dose requirement in the Qatari and Egyptians, respectively. These results are consistent with previous studies that have shown that VKORC1 and CYP2C9 are the main genetic factors influencing warfarin dose response . Another study was conducted aimed at evaluating the economic benefit of using a genotype-guided approach to determine the optimal number of days to interrupt warfarin before a surgical procedure, compared to the standard of care, in Hamad Medical Corporation (HMC), Qatar. The study used a cost–benefit analysis based on a 1-year decision-analytic model. The study reported that the genotype-guided approach would reduce the risk of bleeding and thrombotic events, as well as the number of canceled procedures, by optimizing the preoperative INR level according to the patient’s genetic variants in CYP2C9 genes, which affect warfarin sensitivity and metabolism. It was estimated that the genotype-guided approach would result in a benefit to cost ratio of 4.0. On average, the genetic-guided approach resulted in a cost saving of USD 573.72 (QAR 2,094.07) per patient compared to the standard of care. This study provides strong evidence that implementing a pharmacogenetic-guided approach for pre-operative warfarin management is cost-beneficial in the Qatari healthcare setting . One of Qatar’s significant achievements in the field of precision medicine and PGx is the launch of its own large-scale national genome project in 2015, the Qatar Genome Program (QGP). This ambitious project is generating an extensive database combining whole genome sequencing, other omics data, along with phenotypic data, following recruitment and sample collection through the Qatar Biobank (QBB) . QBB supports biomedical research in Qatar by collecting and storing biological samples and health data from the Qatari and other resident population. By collecting and analyzing genetic data specific to the Qatari population, researchers can better understand genetic markers that indicate an individual’s risk of developing certain diseases . This data provides a valuable genetic reference point for Qataris, enabling earlier diagnoses and tailored management of diseases. Furthermore, it facilitates the development of predictors of response to drugs that account for the unique genetic variations present in the Qatari population . The Qatar Precision Health Institute (QPHI) is a pioneering institution dedicated to advancing precision healthcare practices in Qatar. Established under the auspices of Qatar Foundation, QPHI focuses on research and implementation of precision medicine, aiming to enhance healthcare quality through the comprehensive study of genomics and multi-omics data. Leveraging over a decade’s worth of valuable research and data collection from initiatives like Qatar Biobank and Qatar Genome, QPHI strives to pioneer personalized approaches to prevent and treat health issues. This institute stands at the forefront of empowering communities by facilitating precision health practices, ultimately fostering the development of healthier and more vibrant societies. This transformative initiative embodies a paradigm shift in healthcare, emphasizing individualized treatments and prevention strategies . QGP established a research consortium involving scientists from several institutions in Qatar to address challenging questions in population genomics, and one of the streams of the research was on PGx . This led to the publication of one of the most comprehensive studies in the field of PGx in Qatar involving 6,045 whole genomes from the pilot phase of QGP . The goal was to understand the distribution of genetic variation affecting drug responses in Qatar and analyzed 2,629 variants across 1,026 genes that impact 559 different drugs or classes of drugs. The key findings indicate a notable divergence in the allele frequencies of 1,320 variants found in 703 genes associated with 299 drugs, in comparison to other global populations. Additionally, the study specifically focused on 15 genes related to 46 drugs with established clinical implementation guidelines, predicting their potential phenotypic impact. On average, individuals in Qatar carry 3.6 actionable genotypes/diplotypes, which influence the use of 13 drugs for which clinical guidelines exist. Almost 99.5% of the individuals possessed at least one clinically actionable genotype/diplotype. One of the significant results from the study was the increased risk of simvastatin-induced myopathy in approximately 32% of Qataris. This prevalence is higher than observed in many other populations. Conversely, fewer Qataris are expected to require dosage adjustments for the immunosuppressant drug tacrolimus, based on their CYP3A5 genotypes, compared to populations elsewhere. Importantly, the study also revealed distinct distributions of actionable PGx variations within different Qatari subpopulations . Furthermore, a focused study on the psychotropic PGx landscape identified that approximately 2 to 51% of the population studied had actionable genetic variants for serotonin reuptake inhibitors. More than half (52%) of Qatari individuals have actionable metabolizer phenotypes related to CYP2D6 , CYP2C19 and CYP2B6 genes, which can influence their response to tricyclic antidepressants. Also, and for antipsychotics, it ranged from 0.1 to 32%, based on genetic variations in CYP3A4 and CYP2D6 . The results of these studies have profound implications for the preemptive implementation of PGx, not only in Qatar but also in the broader Middle Eastern region. By understanding the unique genetic landscape affecting drug responses in this population, healthcare providers can better tailor medication regimens to individual patients. This personalization of drug prescriptions has the potential to significantly reduce the personal and financial burden associated with drug inefficacy and adverse reactions, ultimately improving patient care and outcomes . Similar efforts from other countries in the region will enhance our knowledge of genetic variants affecting response to drugs and expedite the clinical implementation in the region. A recent study from Saudi Arabia as part of the Saudi Human Genome Project using next generation sequencing data from close to 12,000 participants identified that 99.2% of individuals from the Saudi population carry at least an actionable PGx variant . Studies in a healthy Emirati cohort also identified diverse allele frequencies of several pharmacogenetic variants in the UAE . Further studies in cardiovascular patients led to the identification of high frequency of patients treated with suboptimal drug regimens, reiterating the need for implementing PGx testing . The Emirati Genome Program in the UAE for mapping the genetic diversity of over 400,000 Emirati citizens, will empower healthcare professionals to personalize medical interventions and preventive measures . Globally, research has helped in identifying several genetic variants that are associated with response and potential adverse effects to various drugs . Often such research involves a small number of patients from a specific population and hence generalizability and statistical significance are not achieved. At times, results from multiple studies are discordant for the same drug-gene pairs and unable to provide conclusive evidence in support of involvement of the genetic variant in drug response. Despite these issues, systematic efforts in mining the literature have identified a number of genes with enough evidence to be implicated in response. For example, the pharmacogenomics knowledgebase (PharmGKB) has extensively curated information about the impact of genetic variation on drug response. Such information is organized under various categories, such as prescribing information, drug label annotations, curated pathways, clinical annotations and variant annotations . While the variant annotation section provides information on the association between a genetic variant and a medication from a single publication, the clinical annotations section summarizes all such published evidence. The provision of a score and assigning a level of evidence to each genetic variant-drug combination based on all the evidence help in prioritizing which genes should be tested as priority. The sections on drug label annotations and prescribing information further help in understanding the practical requirements of genetic testing and how the test results should be interpreted. Drug regulatory agencies in several countries specify drug labels. Moreover, agencies including the US Food and Drug Administration (FDA), Swissmedic, Japanese Pharmaceutical and Medical Devices Agency (PMDA) and the European Medicines Agency (EMA) in their labels provide information on genetic variants affecting the medication and also at times on the requirement of genetic testing prior to prescription of the drug . Further support for the interpretation of PGx test results and how to incorporate these in the electronic medical records system are provided through guidelines by efforts such as the US-based Clinical Pharmacogenetic Implementation Consortium (CPIC), the Dutch Pharmacogenetics Working Group (DPWG) founded by the Royal Dutch Pharmacists Association (KNMP) in the Netherlands, Canadian Pharmacogenomics Network for Drug Safety (CPNDS) and the French National Network of Pharmacogenetics (RNPGx) . The CPIC has developed guidelines close to 100 genes – drugs pair . Similarly, the DPWG has so far developed 86 evidence-based gene-drug pair guidelines, of which close to 47 guidelines provide therapeutic recommendations for aberrant phenotypes that have been fully integrated into the electronic health records for clinical decision support . Several large studies are currently underway in different parts of the world to evaluate the use of gene panel based PGx approaches. Examples of studies from the USA include CLIPMERGE PGx, eMERGE-PGx, PG4KDS, IGNITE, INGENIOUS PGx, RIGHT 10 K, and the 1,200 Patients Project . For example, the “RIGHT 10 K” study is a collaborative effort between Mayo Clinic and Baylor College of Medicine, aimed at utilizing genomic data to personalize medical treatment for patients. The primary goal was to integrate preemptive, sequence-based PGx into routine clinical care practices. This involved proactively utilizing genetic information to guide drug prescribing decisions for patients. This study involves more than 10,000 patients at Mayo Clinic, who have had their pharmacogenes sequenced using samples from the Mayo Clinic Biobank. The study worked on developing the necessary tools and resources required to implement clinical pharmacogenomics effectively, including the creation of databases, algorithms, and reporting systems. Additionally, it conducted assessments to determine the prevalence of both well-documented common genetic variations, for which clinical guidelines are already established, and rare genetic variations that could be identified through DNA sequencing as opposed to traditional genotyping methods . In Europe, recently a randomized controlled trial (RCT) (PREPARE) was conducted in 8,100 patients as part of the U-PGx project to investigate the impact of pre-emptive PGx testing of a panel of 13 pharmacogenes. The study showed the viability and advantages of applying PGx decision assistance in a variety of European healthcare settings, including better prescribing practices and patient outcomes . PGx research in Africa is also gaining traction, with a focus on addressing health disparities and improving drug access. The Human Heredity and Health in Africa (H3Africa) initiative is a prime example, involving multiple African countries. The African Pharmacogenomics Consortium (APC) was launched in 2018 to initiate PGx characterization of African diverse population when Caucasian and Asian population-based algorithms failed for the African population . PGx diversity was assessed among 64 countries across Asia from the GenomeAsia 100 K Project pilot using a whole-genome sequencing dataset of 1,739 individuals of 219 population groups. This study predicted adverse drug reactions (ADRs) due to carbamazepine, clopidogrel, peginterferon and warfarin to vary between populations widely from zero to hundred percent . The Southeast Asian Pharmacogenomics Research Network (SEAPharm) was formed to enhance the understanding of PGx specifically in the region . The IndiGen national genome sequencing initiative in India analyzed 1,029 whole genomes and unveiled key PGx variants in Indians. Findings indicate notable disparities in clinically actionable PGx variant frequencies compared to global populations. A total of 134 common, potentially deleterious PGx variants affecting 102 pharmacogenes were identified. On average, each Indian individual carried eight PGx variants that can directly impact treatment choices or drug dosing . Findings from further analysis focusing on kinase-coding genes, a prominent category of drug targets, emphasized the importance of identifying and addressing ADRs unique to the Indian population. These insights hold the potential to advance the development of pre-clinical and post-market screening techniques specifically tailored for monitoring ADRs in India . Due to the high genetic variability of the populations in lower and middle income countries (LMICs), genotyping is necessary before PGx clinical use . However, recent surveys showed that limited PGx research in LMICs has resulted in lower adoption of PGx testing . PGx research in the Middle East has gained prominence due to the region’s distinctive genetic diversity, historical population movements and cultural interactions. This unique genetic makeup has significant implications for drug response variability among individuals. Researchers are actively investigating genetic factors influencing drug metabolism and responses, aiming to personalize treatments, improve drug effectiveness, and reduce adverse reactions. This research has the potential to improve healthcare outcomes, especially in populations with diverse genetic backgrounds like those found in the Middle East. Qatar has been in the forefront of PGx research among the countries in the Middle East region . This region is characterized by a high genetic diversity and admixture due to historical migrations and cultural exchanges. Therefore, it is possible that there are unique genetic variants or haplotypes in this region that affect response to drugs such as warfarin. To explore this possibility, a study was conducted on warfarin dosage requirement in patients. The study included 132 Qatari (discovery) and 50 Egyptian (replication) patients who were genotyped using Illumina Multi-Ethnic Global BeadChip Array. This study performed a meta-analysis, combining the Qatari and Egyptian cohorts, and a gene-based analysis to identify genes associated with warfarin dose variability. The results showed that the most significant genetic variants associated with warfarin dose requirements were located in chromosome 16, near the VKORC1 gene. The lead genome wide signal was VKORC1 rs9934438 (β = −0.17, p = 6 × 10 −15 ), which is a well-known variant that has been previously reported in other populations. The study also identified other SNPs in chromosome 10 at a p value less than 1 × 10 −5 , but these SNPs did not reach genome wide significance. The genetic variants within VKORC1 rs9934438 and CYP2C9 rs4086116 explained 39 and 27% of the variability in the weekly warfarin dose requirement in the Qatari and Egyptians, respectively. These results are consistent with previous studies that have shown that VKORC1 and CYP2C9 are the main genetic factors influencing warfarin dose response . Another study was conducted aimed at evaluating the economic benefit of using a genotype-guided approach to determine the optimal number of days to interrupt warfarin before a surgical procedure, compared to the standard of care, in Hamad Medical Corporation (HMC), Qatar. The study used a cost–benefit analysis based on a 1-year decision-analytic model. The study reported that the genotype-guided approach would reduce the risk of bleeding and thrombotic events, as well as the number of canceled procedures, by optimizing the preoperative INR level according to the patient’s genetic variants in CYP2C9 genes, which affect warfarin sensitivity and metabolism. It was estimated that the genotype-guided approach would result in a benefit to cost ratio of 4.0. On average, the genetic-guided approach resulted in a cost saving of USD 573.72 (QAR 2,094.07) per patient compared to the standard of care. This study provides strong evidence that implementing a pharmacogenetic-guided approach for pre-operative warfarin management is cost-beneficial in the Qatari healthcare setting . One of Qatar’s significant achievements in the field of precision medicine and PGx is the launch of its own large-scale national genome project in 2015, the Qatar Genome Program (QGP). This ambitious project is generating an extensive database combining whole genome sequencing, other omics data, along with phenotypic data, following recruitment and sample collection through the Qatar Biobank (QBB) . QBB supports biomedical research in Qatar by collecting and storing biological samples and health data from the Qatari and other resident population. By collecting and analyzing genetic data specific to the Qatari population, researchers can better understand genetic markers that indicate an individual’s risk of developing certain diseases . This data provides a valuable genetic reference point for Qataris, enabling earlier diagnoses and tailored management of diseases. Furthermore, it facilitates the development of predictors of response to drugs that account for the unique genetic variations present in the Qatari population . The Qatar Precision Health Institute (QPHI) is a pioneering institution dedicated to advancing precision healthcare practices in Qatar. Established under the auspices of Qatar Foundation, QPHI focuses on research and implementation of precision medicine, aiming to enhance healthcare quality through the comprehensive study of genomics and multi-omics data. Leveraging over a decade’s worth of valuable research and data collection from initiatives like Qatar Biobank and Qatar Genome, QPHI strives to pioneer personalized approaches to prevent and treat health issues. This institute stands at the forefront of empowering communities by facilitating precision health practices, ultimately fostering the development of healthier and more vibrant societies. This transformative initiative embodies a paradigm shift in healthcare, emphasizing individualized treatments and prevention strategies . QGP established a research consortium involving scientists from several institutions in Qatar to address challenging questions in population genomics, and one of the streams of the research was on PGx . This led to the publication of one of the most comprehensive studies in the field of PGx in Qatar involving 6,045 whole genomes from the pilot phase of QGP . The goal was to understand the distribution of genetic variation affecting drug responses in Qatar and analyzed 2,629 variants across 1,026 genes that impact 559 different drugs or classes of drugs. The key findings indicate a notable divergence in the allele frequencies of 1,320 variants found in 703 genes associated with 299 drugs, in comparison to other global populations. Additionally, the study specifically focused on 15 genes related to 46 drugs with established clinical implementation guidelines, predicting their potential phenotypic impact. On average, individuals in Qatar carry 3.6 actionable genotypes/diplotypes, which influence the use of 13 drugs for which clinical guidelines exist. Almost 99.5% of the individuals possessed at least one clinically actionable genotype/diplotype. One of the significant results from the study was the increased risk of simvastatin-induced myopathy in approximately 32% of Qataris. This prevalence is higher than observed in many other populations. Conversely, fewer Qataris are expected to require dosage adjustments for the immunosuppressant drug tacrolimus, based on their CYP3A5 genotypes, compared to populations elsewhere. Importantly, the study also revealed distinct distributions of actionable PGx variations within different Qatari subpopulations . Furthermore, a focused study on the psychotropic PGx landscape identified that approximately 2 to 51% of the population studied had actionable genetic variants for serotonin reuptake inhibitors. More than half (52%) of Qatari individuals have actionable metabolizer phenotypes related to CYP2D6 , CYP2C19 and CYP2B6 genes, which can influence their response to tricyclic antidepressants. Also, and for antipsychotics, it ranged from 0.1 to 32%, based on genetic variations in CYP3A4 and CYP2D6 . The results of these studies have profound implications for the preemptive implementation of PGx, not only in Qatar but also in the broader Middle Eastern region. By understanding the unique genetic landscape affecting drug responses in this population, healthcare providers can better tailor medication regimens to individual patients. This personalization of drug prescriptions has the potential to significantly reduce the personal and financial burden associated with drug inefficacy and adverse reactions, ultimately improving patient care and outcomes . Similar efforts from other countries in the region will enhance our knowledge of genetic variants affecting response to drugs and expedite the clinical implementation in the region. A recent study from Saudi Arabia as part of the Saudi Human Genome Project using next generation sequencing data from close to 12,000 participants identified that 99.2% of individuals from the Saudi population carry at least an actionable PGx variant . Studies in a healthy Emirati cohort also identified diverse allele frequencies of several pharmacogenetic variants in the UAE . Further studies in cardiovascular patients led to the identification of high frequency of patients treated with suboptimal drug regimens, reiterating the need for implementing PGx testing . The Emirati Genome Program in the UAE for mapping the genetic diversity of over 400,000 Emirati citizens, will empower healthcare professionals to personalize medical interventions and preventive measures . For PGx to advance and be implemented in clinical settings, awareness plays a crucial role. In 2004, the International Society of Pharmacogenomics (ISP) held a Pharmacogenomics Education Forum at Santorini, Greece. The forum participants discussed the importance of pharmacogenomics education and proposed a document of “Background Statement” and “Recommendations and Call for Action” for deans of education at medical, pharmaceutical, and health schools globally . Additionally, the CPNDS has educated the public and several healthcare professionals on the use of PGx and trained hundreds of healthcare professionals in this area . The University of Florida conducted a survey to determine the impact of PGx on students’ practical knowledge, which revealed that students who had greater PGx training and practical knowledge performed better on the post-course exam than those who lacked these skills . A survey in Japan showed that only 0.4% pharmacists were able to ask for PGx testing based on patient’s PGx before prescribing a drug . Similar study in Kingdom of Saudi Arabia showed that only 16% of the students could identify drugs that require PGx testing, but 36% students were willing to use PGx testing before prescribing drug . Surprisingly, a recent survey in China showed that 99.1% of pharmacists participated in the study knew about PGx testing and 59% had been involved in PGx testing related services . Similarly, with increased awareness and support, it is likely that PGx will be widely adopted in clinical practice in India in the future . Despite the low awareness of PGx implementation among physicians and pharmacists in Qatar, they had a positive attitude towards practicing PGx in the clinical setting . Qatar, with its commitment to advance the healthcare system, has recognized the importance of PGx implementation to enhance patient care. To support this endeavor, several educational activities have been organized in the country, targeting healthcare providers and students. This section explores the value of these educational initiatives and highlights the significant steps taken towards incorporating PGx into Qatar’s healthcare landscape . Healthcare provider workshops and courses Recognizing the need to enhance healthcare providers’ knowledge and understanding of PGx, various institutions in Qatar have organized workshops and courses. These educational activities aim to provide healthcare professionals with the necessary skills to effectively implement PGx in their practice. By staying up-to-date with the latest research and advancements in the field, healthcare providers can make informed decisions when prescribing medications, thereby improving patient outcomes. These workshops and courses cover a range of topics, including the basics of PGx, resources and evidence, the important pharmacogenes, methods to evaluate PGx evidence and identify important pharmacogenes, PGx guidelines and informatics. Furthermore, genotyping techniques, interpretation of genetic test results, and the clinical application of PGx in different medical specialties are also covered. Moreover, these courses have shed light on how PGx is relevant across various medical specialties, allowing healthcare providers to appreciate its clinical applications in different contexts. To ensure a well-rounded learning experience, these educational activities combine theoretical knowledge with hands-on training, empowering healthcare professionals to gain practical expertise in utilizing PGx tools and resources . Precision medicine conferences Hamad Bin Khalifa University (HBKU) hosted the Advances in Precision Medicine (APM2021) conference, with the specific focus on the theme “Epigenetics and Precision Medicine.” This conference showcased the latest and most exciting advancements in the field of epigenetics, especially concerning their implications for clinical decision-making, diagnostic approaches, and treatment strategies . Sidra Medicine, along with other institutional partners in Qatar, conducts the annual Precision Medicine and Functional Genomics (PMFG) Symposium, which brings a large number of experts to Qatar. This acts as a recurring platform that brings together researchers, healthcare professionals, policymakers, and community members from around the world. The Hamad Medical Corporation (HMC) has been promoting personalized medicine and PGx implementation, especially in cardiology and oncology. HMC has organized conferences, providing a platform for healthcare professionals, researchers, and stakeholders to share knowledge, experiences, and best practices in the field . Besides this, the World Innovation Summit for Health (WISH) conferences in Qatar have been at the forefront of discussions and advancements in the field of personalized medicine. WISH is a global initiative that convenes healthcare professionals, policymakers, researchers, and experts from various disciplines to address pressing healthcare challenges and drive innovation in healthcare delivery. WISH conferences have highlighted the following key aspects related to personalized medicine: Genomic Medicine: the importance of genomics and genetic testing in understanding disease susceptibility and designing targeted therapies. The conferences have showcased breakthroughs in genomics research and their potential applications in clinical practice. Patient-Centered Care: personalized medicine places patients at the center of their healthcare journey. Discussion on strategies for involving patients in decision-making, ensuring their preferences are considered, and improving overall healthcare outcomes happens during the conference. Data and Technology: the conferences have explored the critical role of data analytics, artificial intelligence, and digital health technologies in advancing personalized medicine. Global Collaborations: it has encouraged international collaboration and partnerships to advance research and implementation of personalized medicine. Ethical and Regulatory Considerations: it also delved into the ethical, legal, and regulatory aspects of personalized medicine, addressing issues such as data privacy, consent, and equitable access to advanced treatments . These themes are from various WISH conferences and the readers are referred to the reports from WISH conferences over the years for more details: https://wish.org.qa/reports/ . These conferences provide a valuable chance to learn from experts in personalized medicine, stay updated on cutting-edge research and technology, and discuss challenges and solutions. Sharing knowledge and experiences among professionals enhances our understanding of personalized medicine’s potential and fosters collaboration between different disciplines. These interactions contribute to innovative strategies for implementing precision medicine and PGx effectively in Qatar. Inclusion of PGx in the university curricula Recognizing the potential impact of PGx on future healthcare professionals, colleges and universities in Qatar have taken proactive steps to include PGx in their health sciences curricula. By integrating this emerging field into the coursework, students are exposed to the fundamental concepts of PGx, its clinical implications, and the role it plays in personalized medicine. In 2017, Hamad Bin Khalifa University (HBKU), in collaboration with the QGP, launched a comprehensive program offering Master of Science and Ph.D. degrees in Genomics and Precision Medicine. This program not only emphasizes the study of precision medicine through various relevant topics, but also sheds light on the significant role of PGx. A full course on PGx is available to the students, which has a focus on clinical implementation and includes problem-based learning exercises. As research-oriented degrees, these programs equip the students to be aware of various facets of precision medicine, while making them expert in the chosen field of research. Through this initiative, HBKU aims to advance research and education in these fields, raising a deeper understanding of how genomics and precision medicine can revolutionize healthcare practices, including the critical insights provided by PGx . On the other hand, Qatar University is providing a Master of Science program in Genetic Counseling, which trains students who can contribute greatly to precision medicine field through the development of expertise in risk assessment and psychosocial counseling. As genomic medicine generally involves sensitive genetic information, the genetic counselors can assist in the adoption of genetic testing, providing essential psychosocial support to patients and family members, addressing the emotional and psychological aspects of their genetic condition. Given the diverse ethnicities in the Middle East region, understanding unique issues and challenges related to genetics within these populations will help in delivering personalized healthcare. Lastly, it will provide them with ethical principles that can guide genetic counseling practice, such as the interpretation and applying genetic counseling skills in relation to Sharia and local laws . By integrating PGx knowledge into students’ education early on, Qatar is raising a new generation of healthcare professionals who are highly skilled in this field, aiming to facilitate a smooth transition towards personalized medicine approaches. Establishment of committees Development of institutional and national level committees provide momentum to implement precision medicine across the nation. For example, the Hamad Medical Corporation (HMC) has established a precision medicine committee (PMC) responsible for overseeing and advancing precision medicine initiatives. This committee comprises representatives from various healthcare departments within the hospital, including but not limited to cardiology, oncology, and other specialties. One of the primary objectives of this committee is to collaborate with healthcare providers to smoothly incorporate PGx information into the clinical decision-making process . To advance the field of PGx, international collaboration is crucial. Qatar is actively encouraging global engagement with its data, and the findings from the research initiatives are publicly accessible for specialists and researchers worldwide . Collaborations with institutions like Genomics England allow for cross-analysis with national datasets, contributing to a broader understanding of genetic variations across populations. QGP and QBB also contributed to the large international consortia on COVID-19 and the Global Biobank Meta-analysis Initiative (GBMI) . As Qatar’s PGx initiatives progress, the hope is to foster greater collaboration among pharmaceutical companies and researchers worldwide. By leveraging international expertise and conducting comparative studies, Qatar aims to advance the implementation of PGx on a global scale. These research efforts will undoubtedly shape the future of personalized medicine and improve healthcare outcomes not only in Qatar but also in Arab populations and beyond. Recognizing the need to enhance healthcare providers’ knowledge and understanding of PGx, various institutions in Qatar have organized workshops and courses. These educational activities aim to provide healthcare professionals with the necessary skills to effectively implement PGx in their practice. By staying up-to-date with the latest research and advancements in the field, healthcare providers can make informed decisions when prescribing medications, thereby improving patient outcomes. These workshops and courses cover a range of topics, including the basics of PGx, resources and evidence, the important pharmacogenes, methods to evaluate PGx evidence and identify important pharmacogenes, PGx guidelines and informatics. Furthermore, genotyping techniques, interpretation of genetic test results, and the clinical application of PGx in different medical specialties are also covered. Moreover, these courses have shed light on how PGx is relevant across various medical specialties, allowing healthcare providers to appreciate its clinical applications in different contexts. To ensure a well-rounded learning experience, these educational activities combine theoretical knowledge with hands-on training, empowering healthcare professionals to gain practical expertise in utilizing PGx tools and resources . Hamad Bin Khalifa University (HBKU) hosted the Advances in Precision Medicine (APM2021) conference, with the specific focus on the theme “Epigenetics and Precision Medicine.” This conference showcased the latest and most exciting advancements in the field of epigenetics, especially concerning their implications for clinical decision-making, diagnostic approaches, and treatment strategies . Sidra Medicine, along with other institutional partners in Qatar, conducts the annual Precision Medicine and Functional Genomics (PMFG) Symposium, which brings a large number of experts to Qatar. This acts as a recurring platform that brings together researchers, healthcare professionals, policymakers, and community members from around the world. The Hamad Medical Corporation (HMC) has been promoting personalized medicine and PGx implementation, especially in cardiology and oncology. HMC has organized conferences, providing a platform for healthcare professionals, researchers, and stakeholders to share knowledge, experiences, and best practices in the field . Besides this, the World Innovation Summit for Health (WISH) conferences in Qatar have been at the forefront of discussions and advancements in the field of personalized medicine. WISH is a global initiative that convenes healthcare professionals, policymakers, researchers, and experts from various disciplines to address pressing healthcare challenges and drive innovation in healthcare delivery. WISH conferences have highlighted the following key aspects related to personalized medicine: Genomic Medicine: the importance of genomics and genetic testing in understanding disease susceptibility and designing targeted therapies. The conferences have showcased breakthroughs in genomics research and their potential applications in clinical practice. Patient-Centered Care: personalized medicine places patients at the center of their healthcare journey. Discussion on strategies for involving patients in decision-making, ensuring their preferences are considered, and improving overall healthcare outcomes happens during the conference. Data and Technology: the conferences have explored the critical role of data analytics, artificial intelligence, and digital health technologies in advancing personalized medicine. Global Collaborations: it has encouraged international collaboration and partnerships to advance research and implementation of personalized medicine. Ethical and Regulatory Considerations: it also delved into the ethical, legal, and regulatory aspects of personalized medicine, addressing issues such as data privacy, consent, and equitable access to advanced treatments . These themes are from various WISH conferences and the readers are referred to the reports from WISH conferences over the years for more details: https://wish.org.qa/reports/ . These conferences provide a valuable chance to learn from experts in personalized medicine, stay updated on cutting-edge research and technology, and discuss challenges and solutions. Sharing knowledge and experiences among professionals enhances our understanding of personalized medicine’s potential and fosters collaboration between different disciplines. These interactions contribute to innovative strategies for implementing precision medicine and PGx effectively in Qatar. Recognizing the potential impact of PGx on future healthcare professionals, colleges and universities in Qatar have taken proactive steps to include PGx in their health sciences curricula. By integrating this emerging field into the coursework, students are exposed to the fundamental concepts of PGx, its clinical implications, and the role it plays in personalized medicine. In 2017, Hamad Bin Khalifa University (HBKU), in collaboration with the QGP, launched a comprehensive program offering Master of Science and Ph.D. degrees in Genomics and Precision Medicine. This program not only emphasizes the study of precision medicine through various relevant topics, but also sheds light on the significant role of PGx. A full course on PGx is available to the students, which has a focus on clinical implementation and includes problem-based learning exercises. As research-oriented degrees, these programs equip the students to be aware of various facets of precision medicine, while making them expert in the chosen field of research. Through this initiative, HBKU aims to advance research and education in these fields, raising a deeper understanding of how genomics and precision medicine can revolutionize healthcare practices, including the critical insights provided by PGx . On the other hand, Qatar University is providing a Master of Science program in Genetic Counseling, which trains students who can contribute greatly to precision medicine field through the development of expertise in risk assessment and psychosocial counseling. As genomic medicine generally involves sensitive genetic information, the genetic counselors can assist in the adoption of genetic testing, providing essential psychosocial support to patients and family members, addressing the emotional and psychological aspects of their genetic condition. Given the diverse ethnicities in the Middle East region, understanding unique issues and challenges related to genetics within these populations will help in delivering personalized healthcare. Lastly, it will provide them with ethical principles that can guide genetic counseling practice, such as the interpretation and applying genetic counseling skills in relation to Sharia and local laws . By integrating PGx knowledge into students’ education early on, Qatar is raising a new generation of healthcare professionals who are highly skilled in this field, aiming to facilitate a smooth transition towards personalized medicine approaches. Development of institutional and national level committees provide momentum to implement precision medicine across the nation. For example, the Hamad Medical Corporation (HMC) has established a precision medicine committee (PMC) responsible for overseeing and advancing precision medicine initiatives. This committee comprises representatives from various healthcare departments within the hospital, including but not limited to cardiology, oncology, and other specialties. One of the primary objectives of this committee is to collaborate with healthcare providers to smoothly incorporate PGx information into the clinical decision-making process . To advance the field of PGx, international collaboration is crucial. Qatar is actively encouraging global engagement with its data, and the findings from the research initiatives are publicly accessible for specialists and researchers worldwide . Collaborations with institutions like Genomics England allow for cross-analysis with national datasets, contributing to a broader understanding of genetic variations across populations. QGP and QBB also contributed to the large international consortia on COVID-19 and the Global Biobank Meta-analysis Initiative (GBMI) . As Qatar’s PGx initiatives progress, the hope is to foster greater collaboration among pharmaceutical companies and researchers worldwide. By leveraging international expertise and conducting comparative studies, Qatar aims to advance the implementation of PGx on a global scale. These research efforts will undoubtedly shape the future of personalized medicine and improve healthcare outcomes not only in Qatar but also in Arab populations and beyond. Challenges and barriers Despite the recent innovations in PGx, the field has yet to be broadly adopted in clinical practice worldwide. There are several reasons for this slow adoption. One of the main obstacles to implementing PGx is the fact that data obtained have limited cost effectiveness . The cost of genome sequencing has decreased dramatically in recent years; however, it is still seen as relatively expensive. As such tests are not part of the standard care, it is not expected to be covered by insurance companies. This makes it difficult for some patients to access genetic testing. The implementation of PGx is expensive and difficult to apply even in high income countries. Therefore, health care systems in less developed countries, who are expected to be low income as well, find it even more challenging . The PGx testing results are often complex and can be difficult to interpret. There are minor inter- individual variation in genetic makeup, and it is not something easy to identify. It is very clear that there are several diverse disease alleles that lead to various disorders (allelic heterogeneity), and multiple enzymes are involved in drug metabolism following different pathways . The fact that more than a single gene could be involved in a drug mechanism of action makes it challenging for healthcare providers to use the information to guide treatment decisions. Not only that, but the deficiency and inconsistency of guidelines for clinical practice and the very few recommendations on how to incorporate genetic testing into routine care makes it even more difficult for clinicians to interpret genetic test results and to use the information to advise treatment decisions . The fact that majority of PGx studies have been conducted in populations of European descent, may limit the generalizability of the findings of these studies to other populations . This highlights the need for diversity in research population and testing. Another obstacle is the insufficiency of validation of study results. Many PGx tests are not standardized. Different labs use disparate methods and report results in different ways . Furthermore, patients need to be willing to participate in genomic medicine projects, which can be influenced by public policy debates on social and political barriers. These include concerns about medical ethics, confidentiality of genetic records, and potential abuses of genetic information . Finally, there are limited knowledge and awareness regarding PGx among both clinicians and patients. Senior physicians may not have studied PGx in medical school or during their training, thus they lack the familiarity needed to implement it routinely or appropriately advise patients . Many healthcare providers may not be familiar with genetic testing and how to use these results to make treatment decisions. Thus, implementing PGx involves several social, ethical and legal challenges, including those related to population structure and religious biases . Overcoming these barriers will be essential for the successful integration of PGx and personalized medicine in the clinical field. Addressing the challenges and promoting inclusivity in PGx As discussed, PGx holds great promise in advancing precision medicine worldwide, but it faces several challenges, including limited diversity in genomic research and the lack of extensive infrastructure for implementation. shows some of the challenges and potential solutions in PGx implementation. To ensure that progress in PGx benefits all, it’s vital to address the challenges and promote inclusivity in research and clinical settings . Sufficient training of Medical Genetics specialists: More specialists must be trained to effectively apply genetic testing results in clinical settings. Infrastructure for medical ethics should be established to incorporate medical ethics into clinical trials that use personalized genetic data. Robust measures are required to ensure the confidentiality and security of genetic records to build public trust. Developing a regulatory oversight infrastructure is crucial to safeguard the public from potential misuse or mishandling of genetic information. Enhancing diversity in genomic research: To overcome the issue of predominantly studying populations of European ancestry, efforts must be made to include diverse ethnic groups in genomic research. Efforts like the QGP are working towards such inclusivity. Collaborative initiatives like the “All of Us” project in the US, which aims to recruit a million citizens from diverse backgrounds, can be replicated globally. By including individuals from various ethnicities and minorities, researchers can gain a comprehensive understanding of how genetic variations impact drug responses across populations, thus advancing the field of PGx. Improving infrastructure for PGx implementation: Many healthcare systems lack the infrastructure to implement widespread PGx screening. To overcome this, investments should be made in developing efficient PGx testing processes and integrating genetic data with electronic health records (EHRs). This would allow clinicians to access relevant genetic information at the point of care, facilitating personalized medication decisions and refining prescription guidelines. Encouraging robust relations between investigators and participants in research: By building trust and collaborative relationships, this can support knowledge exchange, and mutually benefits for both parties. Researchers can share insights associated with PGx findings and its implications. This will empower participants to gain a better understanding of their genetic makeup and potential tailored treatment decisions. Promoting genetically guided prescription (GGP): As patients’ health outcomes and genetic data both are recorded in the EHRs, researchers can analyze the impact of genetic variations on drug responses/ adverse effects, which will lead to improved medication selections and enhanced overall patient care. Building mechanistic understanding of PGx: Increasing diversity in both research and clinical settings will enrich the pool of genetic variation data. To unlock the complete potential of PGx, it is vital to tackle the challenges of limited diversity in research and the lack of infrastructure for implementation. By making genomic research more inclusive, strengthening participant-researcher connections, and investing in PGx infrastructure, we can move forward for precise medicine, ensuring that PGx-guided treatments benefit more diverse population. Despite the recent innovations in PGx, the field has yet to be broadly adopted in clinical practice worldwide. There are several reasons for this slow adoption. One of the main obstacles to implementing PGx is the fact that data obtained have limited cost effectiveness . The cost of genome sequencing has decreased dramatically in recent years; however, it is still seen as relatively expensive. As such tests are not part of the standard care, it is not expected to be covered by insurance companies. This makes it difficult for some patients to access genetic testing. The implementation of PGx is expensive and difficult to apply even in high income countries. Therefore, health care systems in less developed countries, who are expected to be low income as well, find it even more challenging . The PGx testing results are often complex and can be difficult to interpret. There are minor inter- individual variation in genetic makeup, and it is not something easy to identify. It is very clear that there are several diverse disease alleles that lead to various disorders (allelic heterogeneity), and multiple enzymes are involved in drug metabolism following different pathways . The fact that more than a single gene could be involved in a drug mechanism of action makes it challenging for healthcare providers to use the information to guide treatment decisions. Not only that, but the deficiency and inconsistency of guidelines for clinical practice and the very few recommendations on how to incorporate genetic testing into routine care makes it even more difficult for clinicians to interpret genetic test results and to use the information to advise treatment decisions . The fact that majority of PGx studies have been conducted in populations of European descent, may limit the generalizability of the findings of these studies to other populations . This highlights the need for diversity in research population and testing. Another obstacle is the insufficiency of validation of study results. Many PGx tests are not standardized. Different labs use disparate methods and report results in different ways . Furthermore, patients need to be willing to participate in genomic medicine projects, which can be influenced by public policy debates on social and political barriers. These include concerns about medical ethics, confidentiality of genetic records, and potential abuses of genetic information . Finally, there are limited knowledge and awareness regarding PGx among both clinicians and patients. Senior physicians may not have studied PGx in medical school or during their training, thus they lack the familiarity needed to implement it routinely or appropriately advise patients . Many healthcare providers may not be familiar with genetic testing and how to use these results to make treatment decisions. Thus, implementing PGx involves several social, ethical and legal challenges, including those related to population structure and religious biases . Overcoming these barriers will be essential for the successful integration of PGx and personalized medicine in the clinical field. As discussed, PGx holds great promise in advancing precision medicine worldwide, but it faces several challenges, including limited diversity in genomic research and the lack of extensive infrastructure for implementation. shows some of the challenges and potential solutions in PGx implementation. To ensure that progress in PGx benefits all, it’s vital to address the challenges and promote inclusivity in research and clinical settings . Sufficient training of Medical Genetics specialists: More specialists must be trained to effectively apply genetic testing results in clinical settings. Infrastructure for medical ethics should be established to incorporate medical ethics into clinical trials that use personalized genetic data. Robust measures are required to ensure the confidentiality and security of genetic records to build public trust. Developing a regulatory oversight infrastructure is crucial to safeguard the public from potential misuse or mishandling of genetic information. Enhancing diversity in genomic research: To overcome the issue of predominantly studying populations of European ancestry, efforts must be made to include diverse ethnic groups in genomic research. Efforts like the QGP are working towards such inclusivity. Collaborative initiatives like the “All of Us” project in the US, which aims to recruit a million citizens from diverse backgrounds, can be replicated globally. By including individuals from various ethnicities and minorities, researchers can gain a comprehensive understanding of how genetic variations impact drug responses across populations, thus advancing the field of PGx. Improving infrastructure for PGx implementation: Many healthcare systems lack the infrastructure to implement widespread PGx screening. To overcome this, investments should be made in developing efficient PGx testing processes and integrating genetic data with electronic health records (EHRs). This would allow clinicians to access relevant genetic information at the point of care, facilitating personalized medication decisions and refining prescription guidelines. Encouraging robust relations between investigators and participants in research: By building trust and collaborative relationships, this can support knowledge exchange, and mutually benefits for both parties. Researchers can share insights associated with PGx findings and its implications. This will empower participants to gain a better understanding of their genetic makeup and potential tailored treatment decisions. Promoting genetically guided prescription (GGP): As patients’ health outcomes and genetic data both are recorded in the EHRs, researchers can analyze the impact of genetic variations on drug responses/ adverse effects, which will lead to improved medication selections and enhanced overall patient care. Building mechanistic understanding of PGx: Increasing diversity in both research and clinical settings will enrich the pool of genetic variation data. To unlock the complete potential of PGx, it is vital to tackle the challenges of limited diversity in research and the lack of infrastructure for implementation. By making genomic research more inclusive, strengthening participant-researcher connections, and investing in PGx infrastructure, we can move forward for precise medicine, ensuring that PGx-guided treatments benefit more diverse population. Over the past several decades, PGx has evolved from an emerging science into a vital interdisciplinary field crucial for personalized medicine. It began as pharmacogenetics, which showed how some genes influence our response to drugs. Randomized Controlled Trials (RCTs) confirmed these genetic discoveries. Advances in genomics has then taken the field to the next level . As we conclude this exploration of the current landscape, it is imperative to consider the future directions and offer recommendations to propel PGx into mainstream clinical practice . Efforts required worldwide Continued investment in research and education: The foundation of successful PGx implementation lies in robust research and education efforts. Governments, research institutions, and pharmaceutical companies should continue to invest in PGx studies to expand our knowledge of genetic variation and drug responses. Concurrently, healthcare professionals should receive training to effectively interpret and apply PGx data in clinical decision-making. Ethical considerations and inclusivity: As PGx advances, ethical considerations become more significant. Policy makers, researchers, and healthcare providers should emphasize on the ethical use of genetic information, ensuring privacy and non-discrimination. Additionally, joint efforts should be made to include underrepresented populations in PGx research, to create guidelines that consider genetic diversity. Innovations in PGx technology: As technology continues to progress, there will be more efficient and cost-effective methods for conducting PGx testing. Advances in high-throughput sequencing, microarrays, data analysis and computation tools will facilitate widespread implementation of PGx testing, making it more accessible to healthcare providers. Integration PGx with EHRs: The integration of PGx data into EHRs will be important for its effective utilization in clinical decision-making. This integration will enable healthcare providers to access and interpret genetic information at the point of care, leading to more precise treatment selection. Global Collaborations and Data Sharing: PGx research relies heavily on large-scale datasets to identify significant genetic associations. Global collaborations and data sharing initiatives will become increasingly important to pool resources, accelerate research, and improve the understanding of how genetic variations impact drug responses across diverse populations. Conducting standardized randomized clinical trials (RCTs) holds paramount significance in advancing the field of PGx and helping its implementation. While there are contrasting perspectives suggesting potential delays , rigorous cross-country RCTs are essential for robust scientific validation and informed decision-making regarding PGx integration into clinical practice. Standardized RCTs are important for several reasons, including that they provide a rigorous and unbiased evaluation of the effectiveness of PGx testing in clinical practice. Also, it helps to identify the most effective testing strategies and inform policy decisions regarding the implementation of PGx in healthcare systems worldwide. Additionally, it addresses concerns about the cost-effectiveness of PGx testing. PGx in public health initiatives: PGx can contribute significantly to public health initiatives by optimizing drug treatment in populations with specific genetic characteristics. This approach can help reduce healthcare costs and improve overall health outcomes. Cost-Effective implementation: PGx testing should not be cost-prohibitive. Efforts should be directed towards reducing the cost of genetic testing and medications informed by PGx. Future directions for PGx in Qatar In addition to the points mentioned above, here we present some recommendations for Qatar to embrace PGx implementation seamlessly. Preemptive PGx testing implementation: Qatar’s vision for the future of PGx involves incorporating preemptive PGx testing into routine clinical practice. By proactively testing individuals for genetic variations relevant to drug response, healthcare providers can make more informed treatment decisions and personalize medication regimens for better patient outcomes. Well-designed RCTs to prove the significance of pharmacogenomics: Incorporating RCTs ensures evidence-based practices and strengthens the foundation of PGx implementation in clinical settings. Rigorous experimental designs and concurrent comparison groups are required, as majority of the existing studies were conducted as single arm trials without control groups. Long-term follow-up studies are also required to check whether PGx and personalized medicine improve patient outcomes, adherence, satisfaction, and cost effectiveness. Another requirement is for bigger sample size, which will give sufficient power for the primary outcome. These comprehensive efforts collectively pave the way for a future where precision medicine based on genetic information becomes an integral part of healthcare. Patient-centered care model: Qatar’s healthcare transformation efforts emphasize a patient-centered approach to care. PGx aligns perfectly with this model, as it empowers patients to be active participants in their treatment plans, leading to greater patient satisfaction and improved treatment adherence. Building infrastructure and informatics capacity: To fully realize the benefits of PGx, Qatar should aim to develop the necessary infrastructure for efficient PGx testing, data storage, and analysis. Building bioinformatics capacity will enable the accurate interpretation of genomic sequences and the production of clinical-grade reports for actionable medications, as recommended by the clinical implementation consortia. Collaborations with international PGx initiatives: Qatar’s participation in global PGx collaborations will foster knowledge exchange and ensure that the country remains up-to-date with the latest advancements in the field. Collaborating with international experts will also aid in establishing best practices for PGx testing and implementation. Public awareness and education: As PGx becomes an integral part of healthcare in Qatar, public awareness and education will be crucial. Initiatives to inform both healthcare professionals and the general population about the benefits and implications of PGx testing will promote its acceptance and utilization. Continued investment in research and education: The foundation of successful PGx implementation lies in robust research and education efforts. Governments, research institutions, and pharmaceutical companies should continue to invest in PGx studies to expand our knowledge of genetic variation and drug responses. Concurrently, healthcare professionals should receive training to effectively interpret and apply PGx data in clinical decision-making. Ethical considerations and inclusivity: As PGx advances, ethical considerations become more significant. Policy makers, researchers, and healthcare providers should emphasize on the ethical use of genetic information, ensuring privacy and non-discrimination. Additionally, joint efforts should be made to include underrepresented populations in PGx research, to create guidelines that consider genetic diversity. Innovations in PGx technology: As technology continues to progress, there will be more efficient and cost-effective methods for conducting PGx testing. Advances in high-throughput sequencing, microarrays, data analysis and computation tools will facilitate widespread implementation of PGx testing, making it more accessible to healthcare providers. Integration PGx with EHRs: The integration of PGx data into EHRs will be important for its effective utilization in clinical decision-making. This integration will enable healthcare providers to access and interpret genetic information at the point of care, leading to more precise treatment selection. Global Collaborations and Data Sharing: PGx research relies heavily on large-scale datasets to identify significant genetic associations. Global collaborations and data sharing initiatives will become increasingly important to pool resources, accelerate research, and improve the understanding of how genetic variations impact drug responses across diverse populations. Conducting standardized randomized clinical trials (RCTs) holds paramount significance in advancing the field of PGx and helping its implementation. While there are contrasting perspectives suggesting potential delays , rigorous cross-country RCTs are essential for robust scientific validation and informed decision-making regarding PGx integration into clinical practice. Standardized RCTs are important for several reasons, including that they provide a rigorous and unbiased evaluation of the effectiveness of PGx testing in clinical practice. Also, it helps to identify the most effective testing strategies and inform policy decisions regarding the implementation of PGx in healthcare systems worldwide. Additionally, it addresses concerns about the cost-effectiveness of PGx testing. PGx in public health initiatives: PGx can contribute significantly to public health initiatives by optimizing drug treatment in populations with specific genetic characteristics. This approach can help reduce healthcare costs and improve overall health outcomes. Cost-Effective implementation: PGx testing should not be cost-prohibitive. Efforts should be directed towards reducing the cost of genetic testing and medications informed by PGx. In addition to the points mentioned above, here we present some recommendations for Qatar to embrace PGx implementation seamlessly. Preemptive PGx testing implementation: Qatar’s vision for the future of PGx involves incorporating preemptive PGx testing into routine clinical practice. By proactively testing individuals for genetic variations relevant to drug response, healthcare providers can make more informed treatment decisions and personalize medication regimens for better patient outcomes. Well-designed RCTs to prove the significance of pharmacogenomics: Incorporating RCTs ensures evidence-based practices and strengthens the foundation of PGx implementation in clinical settings. Rigorous experimental designs and concurrent comparison groups are required, as majority of the existing studies were conducted as single arm trials without control groups. Long-term follow-up studies are also required to check whether PGx and personalized medicine improve patient outcomes, adherence, satisfaction, and cost effectiveness. Another requirement is for bigger sample size, which will give sufficient power for the primary outcome. These comprehensive efforts collectively pave the way for a future where precision medicine based on genetic information becomes an integral part of healthcare. Patient-centered care model: Qatar’s healthcare transformation efforts emphasize a patient-centered approach to care. PGx aligns perfectly with this model, as it empowers patients to be active participants in their treatment plans, leading to greater patient satisfaction and improved treatment adherence. Building infrastructure and informatics capacity: To fully realize the benefits of PGx, Qatar should aim to develop the necessary infrastructure for efficient PGx testing, data storage, and analysis. Building bioinformatics capacity will enable the accurate interpretation of genomic sequences and the production of clinical-grade reports for actionable medications, as recommended by the clinical implementation consortia. Collaborations with international PGx initiatives: Qatar’s participation in global PGx collaborations will foster knowledge exchange and ensure that the country remains up-to-date with the latest advancements in the field. Collaborating with international experts will also aid in establishing best practices for PGx testing and implementation. Public awareness and education: As PGx becomes an integral part of healthcare in Qatar, public awareness and education will be crucial. Initiatives to inform both healthcare professionals and the general population about the benefits and implications of PGx testing will promote its acceptance and utilization. The future of PGx worldwide and in Qatar is promising, with advancements in technology, increased data sharing, and precision drug development driving personalized medicine to new heights. Qatar’s vision to implement preemptive PGx testing aligns perfectly with its patient-centered care model and healthcare reform efforts. By building the necessary infrastructure, bioinformatics capacity, and collaborating with international PGx initiatives, Qatar aims to leverage PGx to optimize medication therapy and improve patient outcomes, as well as decrease side effects. KB: Conceptualization, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing. DV: Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing. AI: Formal analysis, Investigation, Writing – original draft, Writing – review & editing. MA: Formal analysis, Investigation, Writing – original draft, Writing – review & editing. SM: Investigation, Writing – original draft, Writing – review & editing. HM: Investigation, Writing – original draft, Writing – review & editing. MQ: Investigation, Supervision, Writing – original draft, Writing – review & editing. PJ: Conceptualization, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing. |
Study protocol OKRA: orientation compass for the preparing, delivering and following up on breaking bad news conversations in paediatric oncology | 9ab9d4d2-9e8f-44fb-92f9-6955801dde96 | 11149114 | Internal Medicine[mh] | Although breaking bad news (BBN) in paediatric oncology is considered challenging, little is known about the specific needs of the transmitters or receivers during the trialogue, and age-specific protocols are lacking. A multiperspective understanding of the perceived needs and wishes for BBN will be generated. Based on these findings, an ‘orientation compass’ for BBN will be designed and consecutively matured in practical application. This final product will be accessible to all paediatric oncology departments in Germany. The compass, which was designed through a participative approach, may be considered a needs-driven instrument, which assists health professionals to prepare, guide and follow-up BBN processes in a systematic manner. It may improve the BBN processes’ quality and help children and parents to better cope with the situation. Particularly in the training of healthcare professionals, the compass may sensitise to the BBN implications, provide guidance and reduce emotional stress. In Germany, around 2200 children and adolescents (under the age of 18) are newly diagnosed with cancer every year. The cure rates for paediatric cancer have improved significantly in recent decades so that the average 15-year survival rate in Germany is 82%. Nevertheless, there are still around 410 deaths per year within 15 years of cancer diagnosis. Breaking bad news (BBN) refers to those conversations that may change the patient’s view of their future in a drastic, negative way. BBN comprises different types of information, for example, the diagnosis of cancer, the progression or recurrence of the disease. BBN plays a central role in the routine of clinical oncology. Meanwhile, due to its complex requirements, BBN is considered a major communicative challenge. The quality of the BBN conversation is considered crucial, which influences the patient’s course of treatment, including adherence to treatment or the ability to deal with challenges in therapy and cancer-related self-efficacy to cope with emotional distress. In adult oncology, various communication trainings and ‘protocols for BBN’ (eg, SPIKES, ABCDE; BREAKS) exist. The transferability of these protocols to the paediatric setting remains unsearched. Breaking and receiving bad news in paediatric oncology In contrast to adult oncology for adults, for paediatric oncology, a comprehensive understanding of experiences and the needs from multiple perspectives (eg, from the perspective of the BBN transmitter and receiver) are missing. In this setting, a trialogue communication between the multidisciplinary paediatric oncology team, patients and their parents is obligatory. Therefore, BBN transmitters often perceive this task as even more stressful than in adult oncology. Nevertheless, international publications on BBN transmitters’ experiences, needs and perceived bottlenecks related to BBN in paediatric oncology are rare and context-specific knowledge from Germany is missing. Paediatric oncology studies from Canada and Sweden indicate that many BBN transmitters (eg, physicians, psychologists and nurses) perceive it as ‘a challenge’ and often feel ‘uncomfortable’, ‘vulnerable’ or ‘insufficiently prepared’. Paediatricians in outpatient care declare a lack of knowledge, experience and/or communication skills to ‘successfully’ and ‘appropriately’ manage the BBN trialogue. Cancer in children affects the entire family system. The BBN process might have a negative impact on its receivers’ treatment adherence, quality of life, symptom reduction or emotional health. However, only a few studies explored the BBN experiences of children and their families, whether in an ambulatory or inpatient setting. Adolescents and young adults of a cancer self-help group designate BBN as a ‘biographical turning point’, which may trigger a range of emotional complaints (eg, depression) that was even aggravated by social isolation caused by the treatment trajectory. Likewise, little is known about parents of children with cancer BBN experiences. Some parents describe strong emotional outbursts and even physical breakdowns during or after the counselling session. BBN support needs and guidance in paediatric oncology Adolescents with cancer emphasised that providing understandable information, establishing a stable and trustful relationship and applying the principles of participatory (ie, shared) decision-making are important for BBN. A systematic, paediatric-specific and evidence-based guidance is missing. The extent to which support protocols from oncology (eg, SPIKES might be transferred to paediatric oncology (doctor/child as patient/parent trialogue) remains insufficiently investigated. Family-centred communication, which includes complex family dynamics, is considered promising for BBN in paediatric oncology. For this type of communication, we consider the BUSTER protocol, with its systemic approach, as particularly suitable for the paediatric context. Finally, it remains unclear to what extent the BBN protocols for adults are applied in Germany in the paediatric setting and what experiences have been made with them. Given the specific challenges of BBN processes in paediatric oncology, combined with the lack of existing protocols for the given context, the necessity for the development of a context-specific, needs-driven and practice-based instrument becomes evident. Objective Within the research project OKRA (German acronym for Orientierungskompass zur Übermittlung schwerwiegender Nachrichten in der Kinderonkologie), a tailored support instrument—the so-called ‘orientation compass’ for health professionals in paediatric oncology should be systematically designed and matured in practice. This compass aims to (1) comprehensively prepare professionals for the BBN trialogue (eg, with children with cancer and their parents), (2) guide them through the BBN conversation itself and (3) offer follow-up impulses for both BBN transmitters and receivers. In contrast to adult oncology for adults, for paediatric oncology, a comprehensive understanding of experiences and the needs from multiple perspectives (eg, from the perspective of the BBN transmitter and receiver) are missing. In this setting, a trialogue communication between the multidisciplinary paediatric oncology team, patients and their parents is obligatory. Therefore, BBN transmitters often perceive this task as even more stressful than in adult oncology. Nevertheless, international publications on BBN transmitters’ experiences, needs and perceived bottlenecks related to BBN in paediatric oncology are rare and context-specific knowledge from Germany is missing. Paediatric oncology studies from Canada and Sweden indicate that many BBN transmitters (eg, physicians, psychologists and nurses) perceive it as ‘a challenge’ and often feel ‘uncomfortable’, ‘vulnerable’ or ‘insufficiently prepared’. Paediatricians in outpatient care declare a lack of knowledge, experience and/or communication skills to ‘successfully’ and ‘appropriately’ manage the BBN trialogue. Cancer in children affects the entire family system. The BBN process might have a negative impact on its receivers’ treatment adherence, quality of life, symptom reduction or emotional health. However, only a few studies explored the BBN experiences of children and their families, whether in an ambulatory or inpatient setting. Adolescents and young adults of a cancer self-help group designate BBN as a ‘biographical turning point’, which may trigger a range of emotional complaints (eg, depression) that was even aggravated by social isolation caused by the treatment trajectory. Likewise, little is known about parents of children with cancer BBN experiences. Some parents describe strong emotional outbursts and even physical breakdowns during or after the counselling session. Adolescents with cancer emphasised that providing understandable information, establishing a stable and trustful relationship and applying the principles of participatory (ie, shared) decision-making are important for BBN. A systematic, paediatric-specific and evidence-based guidance is missing. The extent to which support protocols from oncology (eg, SPIKES might be transferred to paediatric oncology (doctor/child as patient/parent trialogue) remains insufficiently investigated. Family-centred communication, which includes complex family dynamics, is considered promising for BBN in paediatric oncology. For this type of communication, we consider the BUSTER protocol, with its systemic approach, as particularly suitable for the paediatric context. Finally, it remains unclear to what extent the BBN protocols for adults are applied in Germany in the paediatric setting and what experiences have been made with them. Given the specific challenges of BBN processes in paediatric oncology, combined with the lack of existing protocols for the given context, the necessity for the development of a context-specific, needs-driven and practice-based instrument becomes evident. Within the research project OKRA (German acronym for Orientierungskompass zur Übermittlung schwerwiegender Nachrichten in der Kinderonkologie), a tailored support instrument—the so-called ‘orientation compass’ for health professionals in paediatric oncology should be systematically designed and matured in practice. This compass aims to (1) comprehensively prepare professionals for the BBN trialogue (eg, with children with cancer and their parents), (2) guide them through the BBN conversation itself and (3) offer follow-up impulses for both BBN transmitters and receivers. Research team The research team consists of five professionals with experiences in psychology, psychosomatic and general medicine, healthcare development, nursing sciences and public health. They are affiliated with the University of Cologne and Robert-Bosch Hospital Stuttgart; none of them is or has been employed by any of the organisations involved in the study. Study design OKRA has an explorative and participatory character. It follows a QUAL-quant mixed-methods research approach, which is suitable for considering the various perspectives on the complex issue of BBN. QUAL indicates that different qualitative methods will be applied in both phases (eg, interviews or focus group discussions), whereas the quant indicates that only a small part of the study includes quantitative measures (phase 1). Emphasises are given to qualitative methods and the Consolidated criteria for Reporting Qualitative research criteria are applied to this study protocol. By applying the participatory approach, participants are constantly empowered to incorporate their perspective, which may lead to a contextualised, needs-driven and comprehensible outcome—the OKRA compass. illustrates the OKRA design, which consists of two consecutive phases. The corresponding data collection methods, participating groups, outputs and study outcomes are highlighted in the following text. Phase 1: participatory group Delphi: generating multiperspective knowledge OKRA starts with a participatory group Delphi (PGD) ( , left side). PGD is a discursive method with several consensus rounds that are considered as appropriate when aiming to design knowledge-based guidelines or checklists while considering multiple perspectives (eg, those receiving and transmitting BBN). PGDs permit an open, equal and constructive dialogue between the different participants and lead to a broad generation of knowledge. Participants have the opportunity to reconsider and revise their statements or assessments at any time. The OKRA PGD consists of six consecutive rounds, as described in . When calculating the number of organisations needed to fully understand the BBN issues in paediatric oncology, we understood that there are basically four groups involved in the BBN issue. They are 14 dedicated representatives of the cooperation and belong to four expert groups: (1) ‘experts through personal experience’ (representatives of children receiving BBN and their parents), (2) medical care providers and representatives of national medical societies, (3) outpatient psychosocial support providers and (4) researchers ( , left side). Four experts from each group participated, except for the group of external researchers, which has only two. The number of members in each group should be balanced and large enough to outline the perspective. We decided that four originators would be appropriate for groups 1–3. In group 4 (researchers), only two organisations are involved because the OKRA research team is also part of this group and it includes two organisational perspectives. In the end, 14 external organisations contributed as coresearchers. It is also important to recognise that the participants do not speak for themselves but present the perspective of their organisation. Participants are located throughout Germany and are continuously engaged. In order to augment the scope, for the 2 written surveys, these 14 participants may select three other persons from their own organisation with expertise in the subject matter, so that a maximum of 56 participants can be expected in the PGD, thereby meeting the recommended group size. In round 1, items will be generated for each subject through one individual expert interview with one person from each organisation (N=14) . Theses will then be generated and prioritised based on this knowledge through focus group discussions (rounds 2 and 4) with the same participants of round 1. In round 3, a survey with open text option and in round 5, a survey with a 5-point Likert scale will be offered. This process results in the joint formulation of final theses (output phase 1) which serve as the base for the development of the pilot orientation compass (phase 2). Phase 2: participatory action research: designing and maturing of the orientation compass in the clinical routine Second, the pilot orientation compass is designed and refined in clinical reality using the participatory action research (PAR) method ( , right side). PAR is used to improve practice (eg, BBN transfer) through the simultaneous process of action and research and the non-linear, iterative process of learning by doing. PAR combines collective reasoning with evidence-based learning that is embedded in active collaboration (eg, BBN transmitters and researchers) and includes the following three elements: (1) participation (eg, active engagement and codesigning of those involved in the process, (2) action and (3) research. The compass will be matured in five different federal states through the participation of multidisciplinary team members (eg, physicians, nurses and psychosocial support) in paediatric oncology. During this phase, participants from phase 1 will be invited to participate intentionally. A maximum of 30 BBN transmitters, belonging to the multidisciplinary paediatric oncology team from five study sites, are expected to participate ( , right side). Based on PAR experiences, 2–3 maturation loops are appropriate. Based on the outputs of phase 1 (final theses for a high-quality BBN process), the research team started to design a pilot orientation compass for BBN in paediatric oncology ( , right side). Its maturation is achieved through iterative PAR learning and a total of three optimisation cycles in practice within three paediatric oncology clinics. Each of our PAR cycles includes four steps: plan, act, observe and reflect. specifics this maturation process. Inclusion criteria and participants The study will include only adult participants with an extensive content-specific expertise. The first group, known as ‘experts through personal experience’, also represents the perspective of children receiving BBN. However, these individuals are part of a self-help group organisation comprised adults who were affected by cancer during childhood. Further inclusion criteria are (1) ability to actively participate in online data collection, (2) unrestricted or adequately corrected vision and hearing (3) and very good German language skills. Data collection and analysis For reasons of feasibility (geographical distribution of participants), all data collection during the PGD will be conducted online . Participants must have a computer with a good internet connection and a camera to make the study technically feasible. Interactive whiteboards will be used for focus group discussions. According to the German General Data Protection Regulation (GDPR), a protected ZOOM access and LIME Survey version, offered by the University of Cologne, is used for data collection. Participant’s metadata (eg, age, setting, profession and specific skills) are gathered via a short questionnaire and analysed descriptively via SPSS. Box 1 Strengths and limitations of this study Given the paucity of evidence, the mixed-methods approach (participatory group Delphi (PGD) and participatory action research) permits gaining a comprehensive understanding, as well as developing, piloting and maturing a needs-driven breaking bad news (BBN) support instrument for paediatric oncology. Applying a participatory approach continuously, helps to adequately incorporate the needs of the BBN transmitters (health professionals) and receivers (paediatric cancer patients and their parents) in the instrument, which improves its quality, understandability and acceptance (compass). By enabling a collaboration between a multidisciplinary research team, content-specific experts and healthcare providers, it is ensured, that a wide range of perspectives is taken into consideration. The PGD methodology represents a method to achieve expert consensus via comprehensive synthesis of essential factors in a specific context. Transnational transferability needs to be tested. Replication by other researchers is possible when aiming to explore needs-tailored and design-tailored interventions in the clinical setting. Collecting data online has both limitations and advantages. It is considered the gold standard to conduct focus groups face to face. However, even before the Corona crisis, studies looking at the differences between online and face to face did not find significant differences. Other research highlights the superficiality of the responses, which lack contextual details produced in the online environment and a question-answer to the detriment and not a spontaneous conversational between participants. Researchers should be aware that technology and digital literacy, recruitment, group size, level of prior knowledge, the role of the interviewer, the participants’ media environment and data management may affect the quality of online data collection. However, the availability of the experts and geographical distances can be overcome by using online formats. It would not have been reasonable for most experts to attend four face-to-face meetings in the given time planned for that activity. They offer an opportunity to reduce the amount of travel required by researchers and participants to and from focus group locations and can be time-saving and cost-effective. When online focus groups provide a practical and convenient communication space for both participants and researchers, they also facilitate the inclusion of geographically dispersed participants and provide an opportunity to study hard-to-reach populations. As all participants had the technical skills and experience of online meetings, and the research team had been trained in the specific challenges of online data collection, it was decided to conduct the interviews and focus groups online. In summary, the online approach has strengths and limitations. Phase 1: PGD Semistructured interview guidelines (see ) are developed for qualitative data collection. The instrument will be piloted by a professional of the paediatric oncology team of the University Hospital Cologne and a member of the Foundation for Children with Cancer with affiliated Parent-House (‘Elternhaus e.V.’, Cologne). Subsequently, the piloting individuals are not included in the study. During all qualitative data collection, audio recordings are conducted and supplemented by short written memos of the researchers. During the focus group discussions, speaker turnover is documented. All audio recordings are then transcribed and pseudonymised. The transcripts are coded independently by two researchers (inter-rater reliability), using the software MAXQDA (V.24). The method of thematic analysis is applied, including six steps: (1) familiarisation with the data material, (2) development of initial codes, (3) search for topics, (4) examination of topics, (5) specification and naming of topics and (6) preparation of the analysis results. 10.1136/bmjpo-2023-002473.supp1 Supplementary data The items for the two Delphi questionnaires (quantitative) in rounds 3 and 5 are identified through the previous individual interviews and focus group discussions. The results are converted into theses for the OKRA Delphi questionnaire and presented to the respondents via LIME Survey for standardised assessment. The surveys are carried out pseudonymously by assigning codes so that the code can also be assigned to the respective participant in the second survey. Participants are asked to appraise each thesis from different perspectives (eg, time of realisation, obstacles to realisation or importance of the thesis). During round 3, survey participants were given the option to include or exclude the theses that were formulated in the previous sessions (open text option). In addition, participants can make additions by using open-ended questions with a free text option. If a thesis reaches a consensus of over 95% in round 3 (survey), it will be considered accepted. Theses rated between 80% and 95% will require optimisation while those that receive less than 80% will be withdrawn. During round 5, a unidimensional 5-point Likert scale questionnaire will be used to weigh the theses. The scale ranges from ‘very important’ to ‘not important at all’. The statistical analysis of the OKRA surveys is descriptive, with means and SDs calculated from the answers to the questionnaire. The final theses will be presented as follows: ‘very important’ with a percentage greater than 90% (indicated by ↑↑), ‘important’ with a percentage between 70% and 90% (indicated by ↑) and ‘wishful’ with a percentage less than 70% (indicated by ↔). The statistical analysis of the OKRA surveys is descriptive. Means and SDs are calculated from the answers to the questionnaires. Phase 2: PAR In phase 2, the respective maturity level of the pilot orientation compass is assessed through oral (via focus group discussions) or written reflection loops (eg, via text comment function). This is accompanied by an user-friendly optimisation tool (UPIM check) with a traffic light system that considers ‘green’ items as mature whereas ‘yellow’ and ‘red’ require optimisation impulses. This instrument offers a systematic examination and maturation of the compass regarding four items: (1) content correctness and validity, (2) content readability, (3) structural readability and (4) graphical readability. Patient and public involvement In OKRA, children’s and parents’ self-help as well as ambulant support organisations were selected to ensure a high level of public involvement ( , left side). Due to the chosen methodology (PGD and PAR), paediatric patients themselves are not involved. All participants of the BBN trialogue (transmitters and receivers) are engaged in order to design a comprehensive, appropriate and accepted support instrument for the German paediatric oncology. OKRA-participants are constantly empowered to participate in cocreative learning and codesigning processes with the research team. The research team consists of five professionals with experiences in psychology, psychosomatic and general medicine, healthcare development, nursing sciences and public health. They are affiliated with the University of Cologne and Robert-Bosch Hospital Stuttgart; none of them is or has been employed by any of the organisations involved in the study. OKRA has an explorative and participatory character. It follows a QUAL-quant mixed-methods research approach, which is suitable for considering the various perspectives on the complex issue of BBN. QUAL indicates that different qualitative methods will be applied in both phases (eg, interviews or focus group discussions), whereas the quant indicates that only a small part of the study includes quantitative measures (phase 1). Emphasises are given to qualitative methods and the Consolidated criteria for Reporting Qualitative research criteria are applied to this study protocol. By applying the participatory approach, participants are constantly empowered to incorporate their perspective, which may lead to a contextualised, needs-driven and comprehensible outcome—the OKRA compass. illustrates the OKRA design, which consists of two consecutive phases. The corresponding data collection methods, participating groups, outputs and study outcomes are highlighted in the following text. Phase 1: participatory group Delphi: generating multiperspective knowledge OKRA starts with a participatory group Delphi (PGD) ( , left side). PGD is a discursive method with several consensus rounds that are considered as appropriate when aiming to design knowledge-based guidelines or checklists while considering multiple perspectives (eg, those receiving and transmitting BBN). PGDs permit an open, equal and constructive dialogue between the different participants and lead to a broad generation of knowledge. Participants have the opportunity to reconsider and revise their statements or assessments at any time. The OKRA PGD consists of six consecutive rounds, as described in . When calculating the number of organisations needed to fully understand the BBN issues in paediatric oncology, we understood that there are basically four groups involved in the BBN issue. They are 14 dedicated representatives of the cooperation and belong to four expert groups: (1) ‘experts through personal experience’ (representatives of children receiving BBN and their parents), (2) medical care providers and representatives of national medical societies, (3) outpatient psychosocial support providers and (4) researchers ( , left side). Four experts from each group participated, except for the group of external researchers, which has only two. The number of members in each group should be balanced and large enough to outline the perspective. We decided that four originators would be appropriate for groups 1–3. In group 4 (researchers), only two organisations are involved because the OKRA research team is also part of this group and it includes two organisational perspectives. In the end, 14 external organisations contributed as coresearchers. It is also important to recognise that the participants do not speak for themselves but present the perspective of their organisation. Participants are located throughout Germany and are continuously engaged. In order to augment the scope, for the 2 written surveys, these 14 participants may select three other persons from their own organisation with expertise in the subject matter, so that a maximum of 56 participants can be expected in the PGD, thereby meeting the recommended group size. In round 1, items will be generated for each subject through one individual expert interview with one person from each organisation (N=14) . Theses will then be generated and prioritised based on this knowledge through focus group discussions (rounds 2 and 4) with the same participants of round 1. In round 3, a survey with open text option and in round 5, a survey with a 5-point Likert scale will be offered. This process results in the joint formulation of final theses (output phase 1) which serve as the base for the development of the pilot orientation compass (phase 2). Phase 2: participatory action research: designing and maturing of the orientation compass in the clinical routine Second, the pilot orientation compass is designed and refined in clinical reality using the participatory action research (PAR) method ( , right side). PAR is used to improve practice (eg, BBN transfer) through the simultaneous process of action and research and the non-linear, iterative process of learning by doing. PAR combines collective reasoning with evidence-based learning that is embedded in active collaboration (eg, BBN transmitters and researchers) and includes the following three elements: (1) participation (eg, active engagement and codesigning of those involved in the process, (2) action and (3) research. The compass will be matured in five different federal states through the participation of multidisciplinary team members (eg, physicians, nurses and psychosocial support) in paediatric oncology. During this phase, participants from phase 1 will be invited to participate intentionally. A maximum of 30 BBN transmitters, belonging to the multidisciplinary paediatric oncology team from five study sites, are expected to participate ( , right side). Based on PAR experiences, 2–3 maturation loops are appropriate. Based on the outputs of phase 1 (final theses for a high-quality BBN process), the research team started to design a pilot orientation compass for BBN in paediatric oncology ( , right side). Its maturation is achieved through iterative PAR learning and a total of three optimisation cycles in practice within three paediatric oncology clinics. Each of our PAR cycles includes four steps: plan, act, observe and reflect. specifics this maturation process. OKRA starts with a participatory group Delphi (PGD) ( , left side). PGD is a discursive method with several consensus rounds that are considered as appropriate when aiming to design knowledge-based guidelines or checklists while considering multiple perspectives (eg, those receiving and transmitting BBN). PGDs permit an open, equal and constructive dialogue between the different participants and lead to a broad generation of knowledge. Participants have the opportunity to reconsider and revise their statements or assessments at any time. The OKRA PGD consists of six consecutive rounds, as described in . When calculating the number of organisations needed to fully understand the BBN issues in paediatric oncology, we understood that there are basically four groups involved in the BBN issue. They are 14 dedicated representatives of the cooperation and belong to four expert groups: (1) ‘experts through personal experience’ (representatives of children receiving BBN and their parents), (2) medical care providers and representatives of national medical societies, (3) outpatient psychosocial support providers and (4) researchers ( , left side). Four experts from each group participated, except for the group of external researchers, which has only two. The number of members in each group should be balanced and large enough to outline the perspective. We decided that four originators would be appropriate for groups 1–3. In group 4 (researchers), only two organisations are involved because the OKRA research team is also part of this group and it includes two organisational perspectives. In the end, 14 external organisations contributed as coresearchers. It is also important to recognise that the participants do not speak for themselves but present the perspective of their organisation. Participants are located throughout Germany and are continuously engaged. In order to augment the scope, for the 2 written surveys, these 14 participants may select three other persons from their own organisation with expertise in the subject matter, so that a maximum of 56 participants can be expected in the PGD, thereby meeting the recommended group size. In round 1, items will be generated for each subject through one individual expert interview with one person from each organisation (N=14) . Theses will then be generated and prioritised based on this knowledge through focus group discussions (rounds 2 and 4) with the same participants of round 1. In round 3, a survey with open text option and in round 5, a survey with a 5-point Likert scale will be offered. This process results in the joint formulation of final theses (output phase 1) which serve as the base for the development of the pilot orientation compass (phase 2). Second, the pilot orientation compass is designed and refined in clinical reality using the participatory action research (PAR) method ( , right side). PAR is used to improve practice (eg, BBN transfer) through the simultaneous process of action and research and the non-linear, iterative process of learning by doing. PAR combines collective reasoning with evidence-based learning that is embedded in active collaboration (eg, BBN transmitters and researchers) and includes the following three elements: (1) participation (eg, active engagement and codesigning of those involved in the process, (2) action and (3) research. The compass will be matured in five different federal states through the participation of multidisciplinary team members (eg, physicians, nurses and psychosocial support) in paediatric oncology. During this phase, participants from phase 1 will be invited to participate intentionally. A maximum of 30 BBN transmitters, belonging to the multidisciplinary paediatric oncology team from five study sites, are expected to participate ( , right side). Based on PAR experiences, 2–3 maturation loops are appropriate. Based on the outputs of phase 1 (final theses for a high-quality BBN process), the research team started to design a pilot orientation compass for BBN in paediatric oncology ( , right side). Its maturation is achieved through iterative PAR learning and a total of three optimisation cycles in practice within three paediatric oncology clinics. Each of our PAR cycles includes four steps: plan, act, observe and reflect. specifics this maturation process. The study will include only adult participants with an extensive content-specific expertise. The first group, known as ‘experts through personal experience’, also represents the perspective of children receiving BBN. However, these individuals are part of a self-help group organisation comprised adults who were affected by cancer during childhood. Further inclusion criteria are (1) ability to actively participate in online data collection, (2) unrestricted or adequately corrected vision and hearing (3) and very good German language skills. For reasons of feasibility (geographical distribution of participants), all data collection during the PGD will be conducted online . Participants must have a computer with a good internet connection and a camera to make the study technically feasible. Interactive whiteboards will be used for focus group discussions. According to the German General Data Protection Regulation (GDPR), a protected ZOOM access and LIME Survey version, offered by the University of Cologne, is used for data collection. Participant’s metadata (eg, age, setting, profession and specific skills) are gathered via a short questionnaire and analysed descriptively via SPSS. Box 1 Strengths and limitations of this study Given the paucity of evidence, the mixed-methods approach (participatory group Delphi (PGD) and participatory action research) permits gaining a comprehensive understanding, as well as developing, piloting and maturing a needs-driven breaking bad news (BBN) support instrument for paediatric oncology. Applying a participatory approach continuously, helps to adequately incorporate the needs of the BBN transmitters (health professionals) and receivers (paediatric cancer patients and their parents) in the instrument, which improves its quality, understandability and acceptance (compass). By enabling a collaboration between a multidisciplinary research team, content-specific experts and healthcare providers, it is ensured, that a wide range of perspectives is taken into consideration. The PGD methodology represents a method to achieve expert consensus via comprehensive synthesis of essential factors in a specific context. Transnational transferability needs to be tested. Replication by other researchers is possible when aiming to explore needs-tailored and design-tailored interventions in the clinical setting. Collecting data online has both limitations and advantages. It is considered the gold standard to conduct focus groups face to face. However, even before the Corona crisis, studies looking at the differences between online and face to face did not find significant differences. Other research highlights the superficiality of the responses, which lack contextual details produced in the online environment and a question-answer to the detriment and not a spontaneous conversational between participants. Researchers should be aware that technology and digital literacy, recruitment, group size, level of prior knowledge, the role of the interviewer, the participants’ media environment and data management may affect the quality of online data collection. However, the availability of the experts and geographical distances can be overcome by using online formats. It would not have been reasonable for most experts to attend four face-to-face meetings in the given time planned for that activity. They offer an opportunity to reduce the amount of travel required by researchers and participants to and from focus group locations and can be time-saving and cost-effective. When online focus groups provide a practical and convenient communication space for both participants and researchers, they also facilitate the inclusion of geographically dispersed participants and provide an opportunity to study hard-to-reach populations. As all participants had the technical skills and experience of online meetings, and the research team had been trained in the specific challenges of online data collection, it was decided to conduct the interviews and focus groups online. In summary, the online approach has strengths and limitations. Phase 1: PGD Semistructured interview guidelines (see ) are developed for qualitative data collection. The instrument will be piloted by a professional of the paediatric oncology team of the University Hospital Cologne and a member of the Foundation for Children with Cancer with affiliated Parent-House (‘Elternhaus e.V.’, Cologne). Subsequently, the piloting individuals are not included in the study. During all qualitative data collection, audio recordings are conducted and supplemented by short written memos of the researchers. During the focus group discussions, speaker turnover is documented. All audio recordings are then transcribed and pseudonymised. The transcripts are coded independently by two researchers (inter-rater reliability), using the software MAXQDA (V.24). The method of thematic analysis is applied, including six steps: (1) familiarisation with the data material, (2) development of initial codes, (3) search for topics, (4) examination of topics, (5) specification and naming of topics and (6) preparation of the analysis results. 10.1136/bmjpo-2023-002473.supp1 Supplementary data The items for the two Delphi questionnaires (quantitative) in rounds 3 and 5 are identified through the previous individual interviews and focus group discussions. The results are converted into theses for the OKRA Delphi questionnaire and presented to the respondents via LIME Survey for standardised assessment. The surveys are carried out pseudonymously by assigning codes so that the code can also be assigned to the respective participant in the second survey. Participants are asked to appraise each thesis from different perspectives (eg, time of realisation, obstacles to realisation or importance of the thesis). During round 3, survey participants were given the option to include or exclude the theses that were formulated in the previous sessions (open text option). In addition, participants can make additions by using open-ended questions with a free text option. If a thesis reaches a consensus of over 95% in round 3 (survey), it will be considered accepted. Theses rated between 80% and 95% will require optimisation while those that receive less than 80% will be withdrawn. During round 5, a unidimensional 5-point Likert scale questionnaire will be used to weigh the theses. The scale ranges from ‘very important’ to ‘not important at all’. The statistical analysis of the OKRA surveys is descriptive, with means and SDs calculated from the answers to the questionnaire. The final theses will be presented as follows: ‘very important’ with a percentage greater than 90% (indicated by ↑↑), ‘important’ with a percentage between 70% and 90% (indicated by ↑) and ‘wishful’ with a percentage less than 70% (indicated by ↔). The statistical analysis of the OKRA surveys is descriptive. Means and SDs are calculated from the answers to the questionnaires. Phase 2: PAR In phase 2, the respective maturity level of the pilot orientation compass is assessed through oral (via focus group discussions) or written reflection loops (eg, via text comment function). This is accompanied by an user-friendly optimisation tool (UPIM check) with a traffic light system that considers ‘green’ items as mature whereas ‘yellow’ and ‘red’ require optimisation impulses. This instrument offers a systematic examination and maturation of the compass regarding four items: (1) content correctness and validity, (2) content readability, (3) structural readability and (4) graphical readability. Semistructured interview guidelines (see ) are developed for qualitative data collection. The instrument will be piloted by a professional of the paediatric oncology team of the University Hospital Cologne and a member of the Foundation for Children with Cancer with affiliated Parent-House (‘Elternhaus e.V.’, Cologne). Subsequently, the piloting individuals are not included in the study. During all qualitative data collection, audio recordings are conducted and supplemented by short written memos of the researchers. During the focus group discussions, speaker turnover is documented. All audio recordings are then transcribed and pseudonymised. The transcripts are coded independently by two researchers (inter-rater reliability), using the software MAXQDA (V.24). The method of thematic analysis is applied, including six steps: (1) familiarisation with the data material, (2) development of initial codes, (3) search for topics, (4) examination of topics, (5) specification and naming of topics and (6) preparation of the analysis results. 10.1136/bmjpo-2023-002473.supp1 Supplementary data The items for the two Delphi questionnaires (quantitative) in rounds 3 and 5 are identified through the previous individual interviews and focus group discussions. The results are converted into theses for the OKRA Delphi questionnaire and presented to the respondents via LIME Survey for standardised assessment. The surveys are carried out pseudonymously by assigning codes so that the code can also be assigned to the respective participant in the second survey. Participants are asked to appraise each thesis from different perspectives (eg, time of realisation, obstacles to realisation or importance of the thesis). During round 3, survey participants were given the option to include or exclude the theses that were formulated in the previous sessions (open text option). In addition, participants can make additions by using open-ended questions with a free text option. If a thesis reaches a consensus of over 95% in round 3 (survey), it will be considered accepted. Theses rated between 80% and 95% will require optimisation while those that receive less than 80% will be withdrawn. During round 5, a unidimensional 5-point Likert scale questionnaire will be used to weigh the theses. The scale ranges from ‘very important’ to ‘not important at all’. The statistical analysis of the OKRA surveys is descriptive, with means and SDs calculated from the answers to the questionnaire. The final theses will be presented as follows: ‘very important’ with a percentage greater than 90% (indicated by ↑↑), ‘important’ with a percentage between 70% and 90% (indicated by ↑) and ‘wishful’ with a percentage less than 70% (indicated by ↔). The statistical analysis of the OKRA surveys is descriptive. Means and SDs are calculated from the answers to the questionnaires. In phase 2, the respective maturity level of the pilot orientation compass is assessed through oral (via focus group discussions) or written reflection loops (eg, via text comment function). This is accompanied by an user-friendly optimisation tool (UPIM check) with a traffic light system that considers ‘green’ items as mature whereas ‘yellow’ and ‘red’ require optimisation impulses. This instrument offers a systematic examination and maturation of the compass regarding four items: (1) content correctness and validity, (2) content readability, (3) structural readability and (4) graphical readability. In OKRA, children’s and parents’ self-help as well as ambulant support organisations were selected to ensure a high level of public involvement ( , left side). Due to the chosen methodology (PGD and PAR), paediatric patients themselves are not involved. All participants of the BBN trialogue (transmitters and receivers) are engaged in order to design a comprehensive, appropriate and accepted support instrument for the German paediatric oncology. OKRA-participants are constantly empowered to participate in cocreative learning and codesigning processes with the research team. Our study results will be published in a peer-reviewed journal based on recognised reporting statements and in grey literature (eg, self-help journals). The criteria of the International Committee of Medical Journal Editors are binding for the authors. Reviewer comments Author's manuscript |
Assessing the competitiveness of medical humanities research on psychiatry, otolaryngology, and ophthalmology residency program applications | 50946f92-af8f-4b6c-af16-26ab7b50eeab | 10177745 | Ophthalmology[mh] | Research in the medical humanities investigates the connection between medicine and humanities fields like philosophy, history, literature, anthropology, law, music, and art. The scholarly pursuit of medical humanities can take many forms beyond the standard scientific paper, including essays, poems, visual art, music compositions, and workshops. In general, medical humanities as an academic discipline has become an increasingly important part of medical school education . In many cases, it is now a required component of the curriculum . Some have even argued that undergraduate humanities majors are the ideal candidates for medical school admissions because they may possess a more compassionate and nuanced understanding of the human condition . Early medical school admission programs, such as the Flexmed program at the Icahn School of Medicine at Mount Sinai, relieve accepted undergraduate students of premedical requirements so they may pursue humanities interests, reflecting a shift towards person-centered care and a holistic application review process. Along the same line, the Medical College Admission Test (MCAT) as of 2015 has put a stronger emphasis on humanities and social sciences . Although residency programs have begun incorporating elements of narrative medicine and storytelling into their education, it remains to be seen whether the residency admissions process embraces medical humanities on the same level as medical schools and undergraduate institutions . As residency placement becomes more competitive each year and traditional metrics, such as the United States Medical Licensing Exam (USMLE) Step 1 and pre-clinical course performance, switch to pass/fail grading systems, medical students are concerned with what residency programs want to see in their applicants. Previous studies have attempted to tease out the importance of research on residency applications with varying results. While research consistently ranks among one of the most important factors on an application , it has been shown that research quantity beyond one first author publication is not a significant factor in matching . However, the high number of students who misrepresent their research output combined with the large increase in medical student research activity in the last decade suggests that students consider it a top priority . One of the key questions students are faced with in medical school is what type of research they want to pursue. The cultural shift away from objective scores and metrics towards holistic application review raises important questions about the perception of non-clinical research, including the medical humanities. While the medical humanities are solidly embraced on the university level and increasingly so on the medical school level, residency programs have been slow to adopt them . Furthermore, researchers are still searching for a truly effective, quantitative method of measuring the impact of medical humanities on students . As a result, students may express concern that pursuing medical humanities activities detracts from their competitiveness in residency, especially if it is at the cost of not pursuing clinical research. To our knowledge, no prior study exists that directly asks residency program directors (PDs) for their perception of medical humanities research on program applications. We used a mixed methods approach to both satisfy the current lack of quantitative data existing on medical humanities and to capture the nuances that the humanities requires. We hypothesize that doing medical humanities research will not preclude students from being seriously considered for residency programs in either surgical and medicine fields, and may even help students stand out among their peers. It is our hope that this study alleviates hesitations that students may feel about pursuing medical humanities research during medical school. Our study surveyed residency PDs across New York State in both surgical and medicine fields (otolaryngology, ophthalmology, and psychiatry) about their opinion on the relative competitiveness of residency program applicants who completed medical humanities research as opposed to clinical research. Additionally, we probed what directors perceived to be the benefits, if any, of medical humanities in being a better doctor in residency and beyond. Ophthalmology and otolaryngology were selected because of their perceived competitiveness and limited residency spots. Psychiatry was chosen as a contrast to these two fields as it is known to attract more open-minded and humanities-inclined applicants . We completed this descriptive study via administration of a 5-question online survey on Google Forms (Google LLC) to residency PDs of the 2022–2023 academic year. All PDs of New York State residency programs were identified using residency program websites. A total of 64 PDs were emailed with an invitation to the survey, with two subsequent follow-up reminder emails. There was a total of 37 psychiatry PDs, 16 ophthalmology PDs, and 11 otolaryngology PDs. Compensation was not provided, and participation was voluntary. Neither patients nor the public were involved in the design, conduct, reporting, or dissemination plans of our research. The surveys were composed of four multiple choice response questions and one open-ended response question. An optional question was left for additional comments. Questions were designed to optimize ease of completion for the residency PDs and utility for potential residency program applicants in determining the positive, neutral, or negative effect of medical humanities research on residency application competitiveness. Three types of questions, dichotomous, Likert scale, and open-ended, were incorporated to maximize efficiency as well as leave space for optional expression. No names or demographic variables were recorded. All questions are included in the Results section verbatim. All questions, both quantitative and qualitative, were recorded and analyzed based on number and sentiment by the authors using Google Sheets (Google LLC). For the open-ended questions, the authors categorized the responses based on perceived sentiment (positive, neutral, or negative) on the effect of humanities research on residency applicant competitiveness. A total of 20 PDs completed the survey (31.3%). Of these, ten (27.0%) were from psychiatry, six (37.5%) from ophthalmology, and four (36.3%) from otolaryngology. The responses to the first four questions are graphically represented in . The fifth question, ‘How do you think medical humanities research and/or coursework affects an individual’s performance in residency and beyond?’ yielded a variety of responses. All are included in based on perceived positive, neutral, or negative sentiment on the effect of humanities research on residency applications. Notable positive responses included ‘Possibly that resident is more compassionate or takes in effect the psychosocial impact on healthcare’ and ‘Yes I think it can inform a better understanding of the humanistic aspects of being a doctor and psychiatrist.’ Notable neutral responses included ‘No effect’ and ‘Very little. It may make the individual more interesting, but unlikely to improve their mastery of diagnosis and treatment.’ Significantly, no responses were identified to express that medical humanities research would negatively affect a residency applicant’s competitiveness. Question 6 offered PDs a space to expound upon question 5. A total of six PDs (6/20, 30%) filled out this optional question. Of these three (3/10, 30%) psychiatry, two (2/6, 33%) ophthalmology, and one (1/4, 25%) otolaryngology PD submitted responses. One psychiatry PD noted that ‘one type of research does not weigh more strongly than another.’ One ophthalmology PD echoed this sentiment, writing that ‘on some level, research is research.’ Moreover, they added that they ‘especially enjoy talking to the students about their research in these domains.’ Conversely, a second ophthalmology PD wrote that while humanities research is a ‘nice addition,’ it was not as important as ‘basic science coursework or research.’ All responses are presented in separated based on positive, neutral, or negative sentiment. Our results support that applicants with only medical humanities research background may be seriously considered for psychiatry, ophthalmology, and otolaryngology residency programs . We conclude that students participating in medical humanities research should not be concerned about their relative competitiveness compared to their clinical research peers. In fact, the survey suggests that medical humanities research in addition to clinical research may actually give an edge to applicants . Many residency PDs expressed value in the medical humanities, saying that they encouraged more open-mindedness and empathy (‘resident is more compassionate,’ ‘increases empathy’; ). Studies about the effect of medical humanities education on medical school students have also echoed the same findings . For example, one study found that students perceived value in learning clinical communications skills after taking a medical drawing course . Other students have reported that medical humanities projects provide important self-reflection time and joy outside of their typical coursework . Some PDs were less confident in whether the medical humanities influenced performance in residency (‘No effect,’ ‘unlikely to improve their mastery of diagnosis and treatment’; ). The study of medical humanities has long carried the burden of quantitatively proving its worthiness in medical training. This has proven to be a challenge given that the emotional impact of the humanities is difficult to capture with a numerical analysis . However, the strong support (95%) of medical humanities research displayed in Question 1 of our survey indicates that it may not prevent a student from being seriously considered in both surgical and medicine residency programs . Surprisingly, the sole respondent that answered ‘No’ to Question 1 was from psychiatry, a specialty that has historically attracted humanities-minded students . Impressively, a majority of PDs (65%) said that doing medical humanities in addition to clinical research increased an applicant’s chance of being accepted . This implies that programs may be increasingly seeking well-rounded applicants with diverse interests. This sentiment was further emphasized in qualitative responses. Responses included that the medical humanities ‘helps with … understanding of diversity,’ ‘broadens the view of the individual,’ and ‘may make the individual more interesting’ . Not only may students stand out from their peers if they participate in humanities-based projects, but they could also have a broader, person-centered outlook on clinical care. Because of its inherent capability to promote self-reflection and critical thinking, the arts and humanities are considered an essential vehicle for delivering content related to diversity, equity, inclusion, and disability justice, which are topics increasingly emphasized in medical school curricula, admissions, and standardized testing . PDs were split on whether medical humanities research should pertain to their specialty of interest or not, with most saying that they did not have a preference . Rather than having projects that were in the relevant field, one psychiatry PD expressed that ‘[taking] a project from concept to publication’ was a more important marker of a good applicant . Another psychiatry PD even emphasized that these projects did not need to take the form of a published article, saying ‘we would value the work of someone who published a personal essay as much as someone who did medical humanities research’ . Different modalities of projects can be equally as valid as long as the student rigorously engages with the process. Though the survey results demonstrated that medical humanities research may be a valid and potentially advantageous experience for an applicant, PDs were still hesitant to say that the medical humanities were an important selection criterion for their program overall . However, 25% (1) of otolaryngology PDs, 17% (1) of ophthalmology PDs, and 40% (4) of psychiatry PDs agreed or strongly agreed that it was . This is a high percentage of programs (25%) given that residency programs have only sparsely adopted the medical humanities into their actual curricula. It is possible that this number foreshadows a growing importance and prevalence of the medical humanities in residency programming. Applicants with medical humanities experience may be actively sought out for their skills in the coming years as programs seek to ramp up humanities integration into the clinical space. Our study was limited by the small sample size ( n = 20) and number of specialties. The response rate of 31% could potentially be a sign of selection bias among PDs. Future studies should pursue more specialties on a larger scale. It would also be beneficial to survey PDs beyond New York State. Programs in different states and settings (e.g., rural) may have different priorities for their applicants. Though our questions were designed to be as concise and clear as possible, there is always the possibility that participants misinterpreted or misread questions. Several studies have investigated the otolaryngology and ophthalmology residency application process from the perspective of logistical and financial barriers to students . We are not aware of a previous study that has directly asked residency PDs what they are looking for in applicants. As a consequence, students are often left wondering what they need to do to be a good applicant. This results in students defaulting to what they perceive to be safe areas of research (i.e., clinical). This study was conducted in the hopes that students will read this and feel more assured in the decision to pursue medical humanities research on its own or in additional to clinical research. They should feel empowered in this choice whether they want to enter a competitive surgical field like otolaryngology and ophthalmology or a medical field like psychiatry. Doing so may even confer an advantage to individuals in the application process and in their residency and career performance. |
What Can Be Learned by Knowing Only the Amino Acid Composition of Proteins? | 145a3213-6a24-431f-b8c7-651ba3fcb15e | 11676433 | Biochemistry[mh] | The goal of recent works has been to find and define the structural and sequence features that are common to some class of proteins, for example, disordered or amyloidogenic regions . Thanks to the wealth of data available in the Protein Data Bank, most analyses try and are able to discover common structural and chemical properties. AlphaFold has achieved the greatest success in this area . It is reasonable to suppose that proteins grouped together on the basis of common architecture would reveal some commonality on the level of primary structure as well. The amino acid composition of proteins is one of the most important parameters for determining the structure and function of proteins. It would seem to be a rather crude characteristic, but a large number of cysteines most likely indicate that these are keratins or keratin-associated proteins. Mucin-2 contains an abnormally large number of threonines (32%) and prolines (16%). Histone H1.5 consists of more than half alanines (27%) and prolines (29%). Even such a familiar protein as human beta-hemoglobin contains many histidines (12%) and valines (6%). The amino acid composition depends on the structure and function of the protein, as well as on the position of the organism on the evolutionary tree. We will consider this issue in more detail later. Many protein structure prediction programs, both those with artificial intelligence and those using parameters/scales derived from the physical properties of amino acids, use the amino acid composition as one of the most important parameters . Recently, we have developed a method that allows us to best separate peptides/proteins belonging to two different groups based only on their amino acid composition . We have previously shown that this method can be used to predict antibacterial peptides, and this simple method works at the level of deep learning methods. We have learned to separate the amyloidogenic peptides from the non-amyloidogenic ones (the work has not been published yet). We want to extend our approach to whole proteins and observe what can be achieved using only amino acid composition without additional information. The goal of this work is to understand what features of proteins can be identified based only on their amino acid composition, and what is the scale of this tool in relation to such data sets as the proteome, individual protein sets such as ribosomal proteins, and proteins from different structural classes (α, β, α/β, α + β). In this article, we will not study the question of the evolution of amino acids, although several interesting works are devoted to this matter . By studying the evolution of some important protein folds, one can also follow changes in amino acid composition, and this was also the subject of many works . Thus, it was shown that c class of proteins (α/β) is one of the most ancient and more designable folds . Statistical analysis shows that the four major structural classes of proteins (all-α, all-β, α/β, α + β) differ from each other in a statistically significant way in the number of rotatable angles φ, ψ, and χ, and the average number of contacts per residue. In general, among proteins of the same size, α/β proteins were shown to have, on average, a higher number of contacts per residue due to their more compact structure . Studying the occurrence of homo-repeats for 20 amino acids, we realized that each proteome has its own prevailing type of homo-repeats ; for example, in humans, these are homo-repeats from prolines and glutamic acid . In this paper, we want to understand what features of proteins can be identified taking into account only their amino acid composition. To see in which cases our approach allows us to predict something, and in which cases it does not. The latter is also interesting because it indicates the direction of the natural selection of amino acid composition for different tasks . So far, we have been the first to consider the division of two sets of proteins according to their amino acid composition.
2.1. Features of Amino Acid Distribution in Proteins from Different Organisms Each protein has its own ensemble of amino acid residues; some residues prevail in each protein compared to the proteomic values, and a set of amino acid residues that, in contrast, are few when compared again with the proteomic data. Usually, when comparing with proteomic values, the frequencies of occurrence for 20 amino acid residues are divided by the frequencies of occurrence in the proteome. These frequencies are called normalized frequencies, with the reference level being 1. Thus, for human myoglobin, the normalized frequencies for histidine and lysine are 2.2. times higher than in the proteomic data, and there is very little cysteine and arginine in this protein . At the same time, for such a common protein in the human body as actin, isoleucine and methionine prevail, at twice the level than in the proteome; also threonine and tyrosine, which are 1.5 times more in quantity. In human lysozyme, there are completely different amino acids: tryptophan (3 times more compared to the proteomic values), arginine (2 times more), cysteine (2.7 times more), and asparagine (2.2 times more). All this is encouraging, as it may be possible to separate two sets of proteins with different structures or functions, and also belonging to different organisms. We selected seven proteomes with the highest percentage of reviewed proteins from different forms of life. For each proteome, we calculated the frequency of occurrence and the observed probability density for 20 amino acid residues. We introduced the concept of the observed probability density: n /( N ∆). Here, n is the number of proteins in the selected range of amino acid frequencies, N is the total number of proteins in the proteome, and Δ is the interval width, which we considered as 0.01. With this width, the distribution looks smooth and without fluctuations. We showed that the distributions of 20 amino acid residues varied among organisms ( and ). A very common question is whether the occurrence of amino acids in proteins can be considered as a normal distribution. Here, we will analyze the distribution of amino acid frequencies in the human proteome. The proteome itself was taken from the UniProt database (only reviewed proteins were taken). A total of 20,360 proteins were analyzed. First of all, we would like to note the proteins that sharply stand out in amino acid frequencies. The Q156A1 or Ataxin-8 protein is remarkable in that it consists of only glutamines (79) and methionine at the N-terminus. F7VJQ1 or alternative prion protein contains 18 tryptophans with a protein size of only 73 amino acid residues. There are many keratin-binding proteins enriched with cysteine, tyrosine, and glycine. There are also other proteins that sharply stand out in frequencies. On the other hand, there are quite a few proteins that lack one or more amino acids . 1343, or 6.6%, of proteins do not contain tryptophan at all. Only 19, or 0.09%, of proteins do not contain serine, which emphasizes the importance of this amino acid for the formation of protein sequences. This distribution pattern is observed not only for the human proteome, but also for the other six proteomes we considered (see ). The proteins with the highest frequencies were analyzed above. Now let us analyze the typical pattern of amino acid occurrence in the human proteome . The highest average frequency is for leucine (10.0%), while the lowest is for tryptophan (1.3%). The average frequency of 20 amino acids for seven proteomes is given in the . It is important to note that for some amino acids, the average value is close to the standard deviation. This indicates the asymmetry of the frequency distribution. Let us examine the frequency distribution of specific amino acids and compare it with the normal distribution with the same average and standard deviation (SD). For glycine, the mean is 0.067, and the standard deviation is 0.030 . Interestingly, the normal distribution does not fall to zero at zero frequency, although the mean is approximately twice the standard deviation. The maximum frequency of glycine is 0.55 for the protein-small cysteine and glycine repeat-containing protein 10 (A0A286YEX9 number in UniProtKB reviewed, MGCCGCGGCGGRCSGGCGGGCGGGCGGGCGGCGGGCGSYTTCR). However, the frequency distribution of valine is practically no different from the normal one (the average is 0.060, the standard deviation is 0.020) . The example is also remarkable in that the average values for glycine and valine are close, but the distributions differ greatly. The distributions for all amino acids in comparison with the normal distribution are presented in . For some amino acids, the distributions are almost identical, while for others they are far from ideal. Thus, three groups can be distinguished. The first group is where the two distributions are almost identical. Such a distribution is typical for the following amino acids: I, V, L, N, and D. The second group includes those amino acids where the frequency at zero is visibly greater than zero: C, V, F, W, Y, N, H, and K. And finally, the third group is where there is obvious asymmetry: C, A, G, S, Q, E, R, H, K, and P. Let us consider non-specific reasons why the distribution of amino acid frequencies differs from the normal distribution. First of all, it should be noted that it does not have to resemble the normal distribution. Firstly, we see asymmetry. This is due to the fact that the mean and standard deviation are close in magnitude. This means that the normal distribution inevitably goes beyond zero, while the frequency is by definition distributed from zero to one. The asymmetry coefficient is calculated using Equation (1). (1) A = x − x ¯ 3 σ 3 Here, x is the variable parameter (in our case, the frequency of amino acid residues in proteins), and σ is the standard deviation. In this case, the maximum value of asymmetry (A) 6.69 is observed for cysteine (C) and the minimum of 0.25 for valine (V) for human proteome (for others, see the ). The average value of asymmetry is 1.6 for the human proteome. Such residues as L, V, N, and D have the lowest asymmetry (0.29, 0.25, 0.41, and 0.58, respectively) and a distribution close to the normal, for which the asymmetry is 0. Another reason is related to the sizes of proteins, which vary within a very wide range . Let us assume that proteins do not differ in composition from random copolymers with amino acid residues. In this case, at a fixed size, we will observe a distribution close to normal. Let us consider an amino acid residue with a frequency of 0.05 = 1/20 and distributions for proteins of 100 and 400 amino acid residues . For different protein sizes, different normal distributions will ensue, and the combination of these distributions will differ from the normal distribution. 2.2. Separating Proteomes Using Amino Acid Composition Alone As shown above, the frequencies of amino acids in proteins from different organisms vary greatly. This gives a reason to hope that by relying only on the amino acid composition, it will be possible to separate proteins from different organisms. We performed calculations for all possible pairs, and for each pair, we obtained a set of R-values for amino acid residues at which we can maximally separate proteins of these proteomes. The set of these R-values can be found in the . The prediction accuracy and Z-score are presented in . It should be noted that the average protein size does not influence the performance of the method illustrated in . As we see from , the method can separate all pairs of organisms except humans and mice, which belong to the class of mammals. Most likely, the amino acid composition of proteins is too similar within the classes. However, in other cases, we correctly predict the separation of two sets of 74% to 88% of proteins. The quality of separation of human and mouse proteomes is shown in a. At Z = 0.14, there is practically no separation of sets. The r distributions are too similar to each other although we tried to make them as divergent as possible. If we exclude the human–mouse pair when comparing proteomes, Z varies from 0.81 to 1.53. Accordingly, balance accuracy (BA) varies from 74% to 88%. Interestingly, pairs of proteomes within the mammalian class are poorly separated, while eukaryotes with different bacteria are well separated. Moreover, the level of separation between bacteria is high and amounts to 84%. How well can we separate proteomes in general? The answer to this question is given in a. Each protein is predicted to belong to its own set or to another. Since we have seven proteomes, we can correctly predict the membership in six cases or none. All intermediate variants are also possible. For all but humans and mice, we can correctly assign a protein to its proteome in 60% of cases. As it is easy to understand, random guessing would work in only (1/2) 6 cases, or 1.6%. Another interesting set is ribosome proteins in bacterial proteomes. We selected four bacteria: Thermus thermophilus ( T. thermophilus ), Staphylococcus aureus ( S. aureus ), Pseudomonas aeruginosa ( P. aeruginosa ), and Escherichia coli ( E. coli ). We again considered all possible pairs and ran calculations using our method to find such R-values that separated the two sets as much as possible. Five pairs were separated with an accuracy from 87% to 94% or Z from 1.5 to 2.0 . The exception was one pair, P. aeruginosa and E. coli , with BA = 68% and Z = 0.42. Characteristically, this pair belongs to one class, Gammaproteobacteria, while all other pairs diverge at the level following the superkingdom of bacteria: P. aeruginosa and E. coli belong to the kingdom Pseudomonadati, S. aureus —to the kingdom Bacillati, for T. thermophilus there is no kingdom, and the phylum Deinococcota is immediately after the superkingdom. As can be seen, the general principle is also preserved for bacteria: the greater the taxonomic relationship, the worse the protein sets are separated. However, what happens if we try to separate the proteomes of whole bacteria? Calculations were made for pairs of proteomes, and R-values were again obtained (see ). Considering all proteins in the proteome leads to better separation of the protein sets from different organisms than when only ribosomal proteins are considered . The pair P. aeruginosa and E. coli was still separated the worst, but already at the level of Z = 1.2 and BA = 82%. In the pair T. thermophilus and S. aureus , Z reached 3.2 and BA 99%. The quality of recognition of these protein sets is presented in c,d. From 60% to 80% of proteins confidently correspond to their set. We compared the R-values of these proteomes that separate the proteomes and those that separate only ribosomal proteins . The R-values are similar, but for some amino acids, they have different signs, such as threonine in the pair T. thermophilus and P. aeruginosa . For separating ribosomal proteins, the R-value of threonine is −1.77, and for whole proteomes it is 0.41. In different pairs, the correlation between R-values ranges from 28% to 61% . In this regard, the question arose whether it was possible to separate ribosomal proteins using the R-values obtained for whole proteomes. As it turned out, they are separated quite well, but worse than using the R-values optimal for separating ribosomal proteins. If we exclude the pair P. aeruginosa and E. coli , then BA varies from 69% to 80% and Z from 0.7 to 1.3. 2.3. Separation of Proteins with Different Gene Ontology Annotations Any protein has a function and a localization in the cell and the body, and participates in various processes. This information is collected in Gene Ontology (GO) annotations for all well-studied proteins . Is it possible to separate proteins with different cellular localization and different functions? To answer this question, we took proteins with five different GO annotations from the human proteome. We created a set of GO annotations so that no protein contained two annotations from our set. It should be noted that this is not the only possible set of non-overlapping GO annotations, but we left one as an example. The sets of proteins with different GO annotations were separated well. Z varied from 1.4 to 7.2, respectively, and BA from 89% to 100%, i.e., complete separation was achieved. The quality of recognition of its own set was above 80% ( b). d shows an example of the separation of two sets. 2.4. Separation of Proteins into Structural Classes Using Only Amino Acid Composition Above, we have shown that it is possible to separate proteomes if organisms belong to different classes. We have also shown that it is possible to separate proteins with different functions or localizations. Is it possible to separate sets that differ in protein structure? To answer this question, we took proteins belonging to different structural classes according to the SCOP 1.65 nomenclature: a—all α proteins, b—all β proteins, c—α/β proteins, and d—α + β proteins. The last two classes were separated with the greatest difficulty: Z = 0.5 and BA = 65%. This is not surprising, because the secondary structure in these classes is the same; it is just folded differently. For the remaining pairs, Z varied from 0.8 to 1.4, and BA from 71% to 85%. The quality of recognition of own class was at the level of 50% ( e). Note that random recognition would work at a level of 6%. For α helical proteins, such amino acids as M, K, A, L, C, R, Q, E, and N are important for class separation. For β proteins—V, P, W, T, G, S, and N; for the c class of proteins—I, L, M, A, F, G, V, and Y; and for the d class of proteins—I, F, G, A, M, L, V, H, and Y. As we know, α helical proteins are enriched with such amino acids as hydrophobic and positively and negatively charged amino acids, which stabilize the dipole structure of the helix with their charges. Lysine, arginine, cysteine, and glutamine with positive R-values are important only for the a class of proteins. For the b class of proteins, these are aromatic and polar amino acids for hydrogen bonding in β-sheets. Serine, threonine, and proline are important only for the b class of proteins. Isoleucine, phenylalanine, and tyrosine are important for c and d classes of proteins. Histidine is important for the d class of proteins.
Each protein has its own ensemble of amino acid residues; some residues prevail in each protein compared to the proteomic values, and a set of amino acid residues that, in contrast, are few when compared again with the proteomic data. Usually, when comparing with proteomic values, the frequencies of occurrence for 20 amino acid residues are divided by the frequencies of occurrence in the proteome. These frequencies are called normalized frequencies, with the reference level being 1. Thus, for human myoglobin, the normalized frequencies for histidine and lysine are 2.2. times higher than in the proteomic data, and there is very little cysteine and arginine in this protein . At the same time, for such a common protein in the human body as actin, isoleucine and methionine prevail, at twice the level than in the proteome; also threonine and tyrosine, which are 1.5 times more in quantity. In human lysozyme, there are completely different amino acids: tryptophan (3 times more compared to the proteomic values), arginine (2 times more), cysteine (2.7 times more), and asparagine (2.2 times more). All this is encouraging, as it may be possible to separate two sets of proteins with different structures or functions, and also belonging to different organisms. We selected seven proteomes with the highest percentage of reviewed proteins from different forms of life. For each proteome, we calculated the frequency of occurrence and the observed probability density for 20 amino acid residues. We introduced the concept of the observed probability density: n /( N ∆). Here, n is the number of proteins in the selected range of amino acid frequencies, N is the total number of proteins in the proteome, and Δ is the interval width, which we considered as 0.01. With this width, the distribution looks smooth and without fluctuations. We showed that the distributions of 20 amino acid residues varied among organisms ( and ). A very common question is whether the occurrence of amino acids in proteins can be considered as a normal distribution. Here, we will analyze the distribution of amino acid frequencies in the human proteome. The proteome itself was taken from the UniProt database (only reviewed proteins were taken). A total of 20,360 proteins were analyzed. First of all, we would like to note the proteins that sharply stand out in amino acid frequencies. The Q156A1 or Ataxin-8 protein is remarkable in that it consists of only glutamines (79) and methionine at the N-terminus. F7VJQ1 or alternative prion protein contains 18 tryptophans with a protein size of only 73 amino acid residues. There are many keratin-binding proteins enriched with cysteine, tyrosine, and glycine. There are also other proteins that sharply stand out in frequencies. On the other hand, there are quite a few proteins that lack one or more amino acids . 1343, or 6.6%, of proteins do not contain tryptophan at all. Only 19, or 0.09%, of proteins do not contain serine, which emphasizes the importance of this amino acid for the formation of protein sequences. This distribution pattern is observed not only for the human proteome, but also for the other six proteomes we considered (see ). The proteins with the highest frequencies were analyzed above. Now let us analyze the typical pattern of amino acid occurrence in the human proteome . The highest average frequency is for leucine (10.0%), while the lowest is for tryptophan (1.3%). The average frequency of 20 amino acids for seven proteomes is given in the . It is important to note that for some amino acids, the average value is close to the standard deviation. This indicates the asymmetry of the frequency distribution. Let us examine the frequency distribution of specific amino acids and compare it with the normal distribution with the same average and standard deviation (SD). For glycine, the mean is 0.067, and the standard deviation is 0.030 . Interestingly, the normal distribution does not fall to zero at zero frequency, although the mean is approximately twice the standard deviation. The maximum frequency of glycine is 0.55 for the protein-small cysteine and glycine repeat-containing protein 10 (A0A286YEX9 number in UniProtKB reviewed, MGCCGCGGCGGRCSGGCGGGCGGGCGGGCGGCGGGCGSYTTCR). However, the frequency distribution of valine is practically no different from the normal one (the average is 0.060, the standard deviation is 0.020) . The example is also remarkable in that the average values for glycine and valine are close, but the distributions differ greatly. The distributions for all amino acids in comparison with the normal distribution are presented in . For some amino acids, the distributions are almost identical, while for others they are far from ideal. Thus, three groups can be distinguished. The first group is where the two distributions are almost identical. Such a distribution is typical for the following amino acids: I, V, L, N, and D. The second group includes those amino acids where the frequency at zero is visibly greater than zero: C, V, F, W, Y, N, H, and K. And finally, the third group is where there is obvious asymmetry: C, A, G, S, Q, E, R, H, K, and P. Let us consider non-specific reasons why the distribution of amino acid frequencies differs from the normal distribution. First of all, it should be noted that it does not have to resemble the normal distribution. Firstly, we see asymmetry. This is due to the fact that the mean and standard deviation are close in magnitude. This means that the normal distribution inevitably goes beyond zero, while the frequency is by definition distributed from zero to one. The asymmetry coefficient is calculated using Equation (1). (1) A = x − x ¯ 3 σ 3 Here, x is the variable parameter (in our case, the frequency of amino acid residues in proteins), and σ is the standard deviation. In this case, the maximum value of asymmetry (A) 6.69 is observed for cysteine (C) and the minimum of 0.25 for valine (V) for human proteome (for others, see the ). The average value of asymmetry is 1.6 for the human proteome. Such residues as L, V, N, and D have the lowest asymmetry (0.29, 0.25, 0.41, and 0.58, respectively) and a distribution close to the normal, for which the asymmetry is 0. Another reason is related to the sizes of proteins, which vary within a very wide range . Let us assume that proteins do not differ in composition from random copolymers with amino acid residues. In this case, at a fixed size, we will observe a distribution close to normal. Let us consider an amino acid residue with a frequency of 0.05 = 1/20 and distributions for proteins of 100 and 400 amino acid residues . For different protein sizes, different normal distributions will ensue, and the combination of these distributions will differ from the normal distribution.
As shown above, the frequencies of amino acids in proteins from different organisms vary greatly. This gives a reason to hope that by relying only on the amino acid composition, it will be possible to separate proteins from different organisms. We performed calculations for all possible pairs, and for each pair, we obtained a set of R-values for amino acid residues at which we can maximally separate proteins of these proteomes. The set of these R-values can be found in the . The prediction accuracy and Z-score are presented in . It should be noted that the average protein size does not influence the performance of the method illustrated in . As we see from , the method can separate all pairs of organisms except humans and mice, which belong to the class of mammals. Most likely, the amino acid composition of proteins is too similar within the classes. However, in other cases, we correctly predict the separation of two sets of 74% to 88% of proteins. The quality of separation of human and mouse proteomes is shown in a. At Z = 0.14, there is practically no separation of sets. The r distributions are too similar to each other although we tried to make them as divergent as possible. If we exclude the human–mouse pair when comparing proteomes, Z varies from 0.81 to 1.53. Accordingly, balance accuracy (BA) varies from 74% to 88%. Interestingly, pairs of proteomes within the mammalian class are poorly separated, while eukaryotes with different bacteria are well separated. Moreover, the level of separation between bacteria is high and amounts to 84%. How well can we separate proteomes in general? The answer to this question is given in a. Each protein is predicted to belong to its own set or to another. Since we have seven proteomes, we can correctly predict the membership in six cases or none. All intermediate variants are also possible. For all but humans and mice, we can correctly assign a protein to its proteome in 60% of cases. As it is easy to understand, random guessing would work in only (1/2) 6 cases, or 1.6%. Another interesting set is ribosome proteins in bacterial proteomes. We selected four bacteria: Thermus thermophilus ( T. thermophilus ), Staphylococcus aureus ( S. aureus ), Pseudomonas aeruginosa ( P. aeruginosa ), and Escherichia coli ( E. coli ). We again considered all possible pairs and ran calculations using our method to find such R-values that separated the two sets as much as possible. Five pairs were separated with an accuracy from 87% to 94% or Z from 1.5 to 2.0 . The exception was one pair, P. aeruginosa and E. coli , with BA = 68% and Z = 0.42. Characteristically, this pair belongs to one class, Gammaproteobacteria, while all other pairs diverge at the level following the superkingdom of bacteria: P. aeruginosa and E. coli belong to the kingdom Pseudomonadati, S. aureus —to the kingdom Bacillati, for T. thermophilus there is no kingdom, and the phylum Deinococcota is immediately after the superkingdom. As can be seen, the general principle is also preserved for bacteria: the greater the taxonomic relationship, the worse the protein sets are separated. However, what happens if we try to separate the proteomes of whole bacteria? Calculations were made for pairs of proteomes, and R-values were again obtained (see ). Considering all proteins in the proteome leads to better separation of the protein sets from different organisms than when only ribosomal proteins are considered . The pair P. aeruginosa and E. coli was still separated the worst, but already at the level of Z = 1.2 and BA = 82%. In the pair T. thermophilus and S. aureus , Z reached 3.2 and BA 99%. The quality of recognition of these protein sets is presented in c,d. From 60% to 80% of proteins confidently correspond to their set. We compared the R-values of these proteomes that separate the proteomes and those that separate only ribosomal proteins . The R-values are similar, but for some amino acids, they have different signs, such as threonine in the pair T. thermophilus and P. aeruginosa . For separating ribosomal proteins, the R-value of threonine is −1.77, and for whole proteomes it is 0.41. In different pairs, the correlation between R-values ranges from 28% to 61% . In this regard, the question arose whether it was possible to separate ribosomal proteins using the R-values obtained for whole proteomes. As it turned out, they are separated quite well, but worse than using the R-values optimal for separating ribosomal proteins. If we exclude the pair P. aeruginosa and E. coli , then BA varies from 69% to 80% and Z from 0.7 to 1.3.
Any protein has a function and a localization in the cell and the body, and participates in various processes. This information is collected in Gene Ontology (GO) annotations for all well-studied proteins . Is it possible to separate proteins with different cellular localization and different functions? To answer this question, we took proteins with five different GO annotations from the human proteome. We created a set of GO annotations so that no protein contained two annotations from our set. It should be noted that this is not the only possible set of non-overlapping GO annotations, but we left one as an example. The sets of proteins with different GO annotations were separated well. Z varied from 1.4 to 7.2, respectively, and BA from 89% to 100%, i.e., complete separation was achieved. The quality of recognition of its own set was above 80% ( b). d shows an example of the separation of two sets.
Above, we have shown that it is possible to separate proteomes if organisms belong to different classes. We have also shown that it is possible to separate proteins with different functions or localizations. Is it possible to separate sets that differ in protein structure? To answer this question, we took proteins belonging to different structural classes according to the SCOP 1.65 nomenclature: a—all α proteins, b—all β proteins, c—α/β proteins, and d—α + β proteins. The last two classes were separated with the greatest difficulty: Z = 0.5 and BA = 65%. This is not surprising, because the secondary structure in these classes is the same; it is just folded differently. For the remaining pairs, Z varied from 0.8 to 1.4, and BA from 71% to 85%. The quality of recognition of own class was at the level of 50% ( e). Note that random recognition would work at a level of 6%. For α helical proteins, such amino acids as M, K, A, L, C, R, Q, E, and N are important for class separation. For β proteins—V, P, W, T, G, S, and N; for the c class of proteins—I, L, M, A, F, G, V, and Y; and for the d class of proteins—I, F, G, A, M, L, V, H, and Y. As we know, α helical proteins are enriched with such amino acids as hydrophobic and positively and negatively charged amino acids, which stabilize the dipole structure of the helix with their charges. Lysine, arginine, cysteine, and glutamine with positive R-values are important only for the a class of proteins. For the b class of proteins, these are aromatic and polar amino acids for hydrogen bonding in β-sheets. Serine, threonine, and proline are important only for the b class of proteins. Isoleucine, phenylalanine, and tyrosine are important for c and d classes of proteins. Histidine is important for the d class of proteins.
3.1. Dataset of Proteomes Seven proteomes with a high fraction of reviewed (Swiss-Prot) proteins: Homo sapiens (UP000005640, 20,360 proteins), Mus musculus (UP000000589, 17,179 proteins), Drosophila melanogaster (UP000000803, 3708 proteins), Arabidopsis thaliana (UP000006548, 16,298 proteins), Bacillus subtilis (UP000001570, 4191 proteins), Escherichia coli (UP000000625, 4401 proteins), Thermus thermophilus (UP000000532, 2227 proteins), Staphylococcus aureus (UP000008816, 2889 proteins), and Pseudomonas aeruginosa (UP000002438, 5563 proteins). Proteomes were taken from the UniProt database in December 2023. 3.2. Dataset of Proteins Four sets of ribosomal proteins were taken from the proteomes: Thermus thermophilus , Staphylococcus aureus , Pseudomonas aeruginosa , and Escherichia coli . We used 53 proteins for T. thermophilus and 54 for the rest. Whole proteomes of these bacteria were also used (2227, 2889, 5563, and 4401 proteins, respectively; see dataset of proteomes). Proteins from 4 main structural classes of SCOP 1.65 were as follows: class a (all-α proteins, 794 proteins), class b (all-β proteins, 928 proteins), class c (α/β proteins, 1089 proteins), and class d (958 proteins) . Proteins were filtered to exclude those with identity greater than 25%. We created five sets of proteins from the human proteome with different Gene Ontology (GO) annotations. The GO annotations themselves were selected according to the following principles: at least 100 proteins should have these annotations, and no protein should be included in two sets. It should be noted that by using these criteria, it was possible to select other sets of proteins with other annotations. Our method for generating a set of GO annotations was simple. We took one annotation and searched for all annotations that did not intersect with this one in the human proteome. If the selected annotation occurred in any protein with any of the previously selected ones, we discarded it. We considered annotations from the most common to the rarer ones. The information is summarized in . 3.3. The Algorithm of the Program for Separation The algorithm for separating two sets of sequences consists of selecting 20 parameters (R-values) assigned to each amino acid. Knowing the amino acid composition of a protein or peptide, we can calculate the average value (r). If r > 0, we predict the protein as belonging to the first set; otherwise to the second. The algorithm itself is implemented on the website http://bioproteom.protres.ru/prod_scale/ (accessed on 1 November 2024) and is described in the paper . When we have more than two sets of proteins, we consider M = N × ( N − 1)/2 pairs of sets, where N is the number of sets. Accordingly, we get 20 × M R-values. For any protein from any set, we can make N − 1 predictions with our set and others. The results are shown in , and and the . 3.4. An Evaluation of the Quality of Prediction As the main criterion for assessing the quality of prediction, we use balanced accuracy (BA). We have two sets of proteins, A and B. Within each set, there is a proportion of correctly predicted proteins T ; then, (2) B A = T A + T B / 2 The main value to be maximized in our algorithm is Z: (3) Z = R A − R B S A 2 + S B 2 1 / 2 Here, R is the average r for the set, and S is the standard deviation. As is easy to see, Z will not change if we add any number to all R-values, nor if we multiply all R-values by any positive number. It is important to note that if the sets contain several thousand proteins, then at Z > 5 our BA becomes indistinguishable from 1; that is, the prediction becomes absolutely accurate. If the sets contain several hundred proteins, the prediction becomes absolutely accurate at Z > 4. 3.5. Parameters Used We introduce the concept of the observed probability density: n /( N ∆). Here, n is the number of proteins in the selected range of amino acid frequencies, N is the total number of proteins in the proteome, and Δ is the interval width. Normalized frequency is the frequency of occurrence of an amino acid residue in a protein divided by the average frequency of occurrence in the proteome.
Seven proteomes with a high fraction of reviewed (Swiss-Prot) proteins: Homo sapiens (UP000005640, 20,360 proteins), Mus musculus (UP000000589, 17,179 proteins), Drosophila melanogaster (UP000000803, 3708 proteins), Arabidopsis thaliana (UP000006548, 16,298 proteins), Bacillus subtilis (UP000001570, 4191 proteins), Escherichia coli (UP000000625, 4401 proteins), Thermus thermophilus (UP000000532, 2227 proteins), Staphylococcus aureus (UP000008816, 2889 proteins), and Pseudomonas aeruginosa (UP000002438, 5563 proteins). Proteomes were taken from the UniProt database in December 2023.
Four sets of ribosomal proteins were taken from the proteomes: Thermus thermophilus , Staphylococcus aureus , Pseudomonas aeruginosa , and Escherichia coli . We used 53 proteins for T. thermophilus and 54 for the rest. Whole proteomes of these bacteria were also used (2227, 2889, 5563, and 4401 proteins, respectively; see dataset of proteomes). Proteins from 4 main structural classes of SCOP 1.65 were as follows: class a (all-α proteins, 794 proteins), class b (all-β proteins, 928 proteins), class c (α/β proteins, 1089 proteins), and class d (958 proteins) . Proteins were filtered to exclude those with identity greater than 25%. We created five sets of proteins from the human proteome with different Gene Ontology (GO) annotations. The GO annotations themselves were selected according to the following principles: at least 100 proteins should have these annotations, and no protein should be included in two sets. It should be noted that by using these criteria, it was possible to select other sets of proteins with other annotations. Our method for generating a set of GO annotations was simple. We took one annotation and searched for all annotations that did not intersect with this one in the human proteome. If the selected annotation occurred in any protein with any of the previously selected ones, we discarded it. We considered annotations from the most common to the rarer ones. The information is summarized in .
The algorithm for separating two sets of sequences consists of selecting 20 parameters (R-values) assigned to each amino acid. Knowing the amino acid composition of a protein or peptide, we can calculate the average value (r). If r > 0, we predict the protein as belonging to the first set; otherwise to the second. The algorithm itself is implemented on the website http://bioproteom.protres.ru/prod_scale/ (accessed on 1 November 2024) and is described in the paper . When we have more than two sets of proteins, we consider M = N × ( N − 1)/2 pairs of sets, where N is the number of sets. Accordingly, we get 20 × M R-values. For any protein from any set, we can make N − 1 predictions with our set and others. The results are shown in , and and the .
As the main criterion for assessing the quality of prediction, we use balanced accuracy (BA). We have two sets of proteins, A and B. Within each set, there is a proportion of correctly predicted proteins T ; then, (2) B A = T A + T B / 2 The main value to be maximized in our algorithm is Z: (3) Z = R A − R B S A 2 + S B 2 1 / 2 Here, R is the average r for the set, and S is the standard deviation. As is easy to see, Z will not change if we add any number to all R-values, nor if we multiply all R-values by any positive number. It is important to note that if the sets contain several thousand proteins, then at Z > 5 our BA becomes indistinguishable from 1; that is, the prediction becomes absolutely accurate. If the sets contain several hundred proteins, the prediction becomes absolutely accurate at Z > 4.
We introduce the concept of the observed probability density: n /( N ∆). Here, n is the number of proteins in the selected range of amino acid frequencies, N is the total number of proteins in the proteome, and Δ is the interval width. Normalized frequency is the frequency of occurrence of an amino acid residue in a protein divided by the average frequency of occurrence in the proteome.
As can be seen from this work, our method allows both to estimate the degree of similarity of different sets of proteins and to predict their belonging to a particular set. It turned out that there are practically indistinguishable sets of proteins (human and mouse proteomes), and those separated quite confidently (GO:0004984 and GO:0019814 in the human proteome). The proposed method cannot separate sets of proteins with the same amino acid frequencies; that is, in closely related species, the frequencies are practically the same. We evaluated the results of applying our method to different pairs of protein sets. Our method gives a line of divergence of two protein sets by amino acid composition and allows to separate protein sets by organisms, structure, position, and function of proteins. At 0.5 < Z < 1.5, the quality of separation increases linearly: balance accuracy reaches 90%, after which it very smoothly reaches 100%. Our method detects the difference in amino acid frequencies. If the frequencies are the same in the two sets, then theoretically it should give Z = 0. In practice, it can catch and amplify the influence of fluctuations or random differences. Naturally, the larger the size of the proteins, the smaller the R fluctuation for protein sequences. The fewer protein sequences, the more fluctuations or random differences can be caught by our method. However, if the difference in frequencies is real, we will see it even on a small set of proteins. Theoretically, our method works if we have more than 19 sequences in both sets. The main task that we want to address in the future is protein clustering. Usually, proteins are clustered using the alignment method, which clusters proteins by degree of relatedness. Our approach allows us to group non-homologous proteins into one group. With a high degree of probability, the localization and function of proteins should determine the general characteristics of the protein composition, even if they have different origins. The results of the work will allow us to annotate proteins for proteomes for which such a problem exists.
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Impact of the COVID-19 Pandemic on Admissions to the Pediatric Emergency Department in a Tertiary Care Hospital | 8ec801d0-1ba0-43f9-aa65-7f66aa8ed662 | 7609824 | Pediatrics[mh] | |
Investigation of the metabolic and endocrinological differences between daily and weekly growth hormone replacement therapy, somapacitan, in patients with adult growth hormone deficiency: A real-world pilot study | 586fc2f9-71b7-4b63-ae94-c992518e2440 | 10519569 | Physiology[mh] | Adult growth hormone deficiency (AGHD) is one of the anterior pituitary hormonal deficiencies. Growth hormone (GH) plays important roles not only in childhood but also in adulthood. Patients with severe AGHD have fatty liver/nonalcoholic steatohepatitis (NASH)/nonalcoholic fatty liver disease (NAFLD), increased visceral adiposity, osteoporosis, poor concentration/inattention, impaired quality of life, coronary artery disease, and heart failure. Moreover, Pappachan et al reported that AGHD can lead to increased mortality. Hence, GH replacement therapy is essential for patients with AGHD. For a long time, daily GH replacement therapy was the only treatment available for patients with AGHD. Recently, patients with AGHD have had the opportunity to receive weekly GH replacement therapy (long-acting GH: somapacitan). The efficacy and safety of somapacitan have been revealed in some phase 3 trials, however, no real-world study has been reported. Thus, we report the first investigation of the clinical, metabolic, and endocrinological differences between daily GH replacement therapy and weekly GH replacement therapy with somapacitan in patients with AGHD in the real world. 2.1. Ethical approval of the study protocol The study protocol was approved by the ethics review committees of Fukuoka University (Fukuoka, Japan). Written informed consent was obtained from all patients for participation in the study. The study was conducted in accordance with the principles of the Declaration of Helsinki. 2.2. Study participants We investigated 11 individuals with AGHD previously diagnosed with no or inadequate changes in GH levels after a GH-releasing peptide-2 test/insulin tolerance test/arginine test at Fukuoka University Chikushi Hospital and Nagasaki Prefecture Iki Hospital. All patients had received daily GH replacement therapy for over 2 years and switched from daily GH replacement therapy to weekly GH replacement therapy with somapacitan between January 2022 and June 2022. 2.3. Methods and disease definitions We administered and continued treatment with somapacitan for 6 months in patients with AGHD previously receiving daily GH replacement therapy. Starting doses of somapacitan were 1.5 mg/week for adults 18 to 60 years of age and 1.0 mg/week for patients aged >60 years, referring to the recommendation based on phase 3 trial in Japan (REAL Japan). Dose titration was performed according to the value. Dose titration of somapacitan was performed according to the value of insulin-like growth factor 1 (IGF1) which was checked monthly after switching to somapacitan. The IGF1 value was basically checked at the morning 7 days after the injection of somapacitan (the next somapacitan injection was performed at night on the day), when the IGF1 value was assumed to be bottom in the week. If the IGF1 value was lower than −1 standard deviation score (SDS), the dose of somapacitan was increased (+0.5 mg/week). If the IGF1 value was higher than +1 standard deviation score (SDS), the dose of somapacitan was increased (−0.5 mg/week). In addition, to avoid overdose, the IGF1 value was also sometimes checked in the morning 2 to 3 days after the injection of somapacitan, when the IGF1 value was assumed to peak in the week. The following variables were examined at switching and 6 months after switching to somapacitan: parameters of glucose control (glycated hemoglobin [HbA1c], fasting plasma glucose [FPG], homeostasis model assessment of insulin resistance [HOMA-IR], and homeostasis model assessment of β-cell function [HOMA-β]), markers of lipid metabolism (low-density lipoprotein-cholesterol, high-density lipoprotein cholesterol, and triglycerides), liver functions (aspartate transaminase [AST], alanine transaminase [ALT], and gamma-glutamyl transferase [γ-GTP]), estimated glomerular filtration rate, and body mass index (BMI). Blood samples were obtained after overnight fasting, and HOMA-IR was calculated using the following formula: HOMA-IR = FPG × fasting insulin/405 HOMA-β was calculated using the following formula: HOMA-β = 360 × fasting insulin/(FPG − 63) Endocrinologically, anterior pituitary hormones and related hormones (adrenocorticotropic hormone [ACTH], cortisol, TSH, free T4, luteinizing hormone [LH], follicle-stimulating hormone [FSH], and testosterone [male]/estradiol [female]) were measured at switching and 6 months after switching to somapacitan. ACTH deficiency was diagnosed by a combination of reduced ACTH and cortisol levels in the morning, and no or inadequate changes in ACTH or cortisol levels after a corticotropin-releasing hormone test. TSH deficiency was diagnosed based on a combination of reduced TSH levels, no or inadequate changes in TSH levels after a thyrotropin-releasing hormone test, and existing secondary hypothyroidism. Deficiency in LH or FSH was diagnosed by a combination of reduced LH or FSH levels, no or inadequate changes in LH or FSH levels after an LH-releasing hormone test, and existing secondary hypogonadism. Central diabetes insipidus was diagnosed by a combination of increased urinary volume; low urinary osmolarity; low antidiuretic hormone (ADH) levels compared with serum osmolarity; no or inadequate changes in ADH levels after a water restriction test/5% NaCl loading test; and increased ADH levels and decreased urinary volume after 1-desamino-8-D-arginine vasopressin administration. Medical treatment aside from GH replacement therapy did not change in any of the patients for the duration of this study. 2.4. Statistical analyses Data are shown as the mean ± standard deviation (SD). Statistical analyses were performed using Stata SE version 16 (StataCorp.2019. Stata Statistical Software: Release 16. College Station, TX: Stata Corp LLC.). The Student t test was used to assess the significance of differences between mean values. This relationship was examined using univariate regression analysis (Fisher test). P value < .05 was considered significant. The study protocol was approved by the ethics review committees of Fukuoka University (Fukuoka, Japan). Written informed consent was obtained from all patients for participation in the study. The study was conducted in accordance with the principles of the Declaration of Helsinki. We investigated 11 individuals with AGHD previously diagnosed with no or inadequate changes in GH levels after a GH-releasing peptide-2 test/insulin tolerance test/arginine test at Fukuoka University Chikushi Hospital and Nagasaki Prefecture Iki Hospital. All patients had received daily GH replacement therapy for over 2 years and switched from daily GH replacement therapy to weekly GH replacement therapy with somapacitan between January 2022 and June 2022. We administered and continued treatment with somapacitan for 6 months in patients with AGHD previously receiving daily GH replacement therapy. Starting doses of somapacitan were 1.5 mg/week for adults 18 to 60 years of age and 1.0 mg/week for patients aged >60 years, referring to the recommendation based on phase 3 trial in Japan (REAL Japan). Dose titration was performed according to the value. Dose titration of somapacitan was performed according to the value of insulin-like growth factor 1 (IGF1) which was checked monthly after switching to somapacitan. The IGF1 value was basically checked at the morning 7 days after the injection of somapacitan (the next somapacitan injection was performed at night on the day), when the IGF1 value was assumed to be bottom in the week. If the IGF1 value was lower than −1 standard deviation score (SDS), the dose of somapacitan was increased (+0.5 mg/week). If the IGF1 value was higher than +1 standard deviation score (SDS), the dose of somapacitan was increased (−0.5 mg/week). In addition, to avoid overdose, the IGF1 value was also sometimes checked in the morning 2 to 3 days after the injection of somapacitan, when the IGF1 value was assumed to peak in the week. The following variables were examined at switching and 6 months after switching to somapacitan: parameters of glucose control (glycated hemoglobin [HbA1c], fasting plasma glucose [FPG], homeostasis model assessment of insulin resistance [HOMA-IR], and homeostasis model assessment of β-cell function [HOMA-β]), markers of lipid metabolism (low-density lipoprotein-cholesterol, high-density lipoprotein cholesterol, and triglycerides), liver functions (aspartate transaminase [AST], alanine transaminase [ALT], and gamma-glutamyl transferase [γ-GTP]), estimated glomerular filtration rate, and body mass index (BMI). Blood samples were obtained after overnight fasting, and HOMA-IR was calculated using the following formula: HOMA-IR = FPG × fasting insulin/405 HOMA-β was calculated using the following formula: HOMA-β = 360 × fasting insulin/(FPG − 63) Endocrinologically, anterior pituitary hormones and related hormones (adrenocorticotropic hormone [ACTH], cortisol, TSH, free T4, luteinizing hormone [LH], follicle-stimulating hormone [FSH], and testosterone [male]/estradiol [female]) were measured at switching and 6 months after switching to somapacitan. ACTH deficiency was diagnosed by a combination of reduced ACTH and cortisol levels in the morning, and no or inadequate changes in ACTH or cortisol levels after a corticotropin-releasing hormone test. TSH deficiency was diagnosed based on a combination of reduced TSH levels, no or inadequate changes in TSH levels after a thyrotropin-releasing hormone test, and existing secondary hypothyroidism. Deficiency in LH or FSH was diagnosed by a combination of reduced LH or FSH levels, no or inadequate changes in LH or FSH levels after an LH-releasing hormone test, and existing secondary hypogonadism. Central diabetes insipidus was diagnosed by a combination of increased urinary volume; low urinary osmolarity; low antidiuretic hormone (ADH) levels compared with serum osmolarity; no or inadequate changes in ADH levels after a water restriction test/5% NaCl loading test; and increased ADH levels and decreased urinary volume after 1-desamino-8-D-arginine vasopressin administration. Medical treatment aside from GH replacement therapy did not change in any of the patients for the duration of this study. Data are shown as the mean ± standard deviation (SD). Statistical analyses were performed using Stata SE version 16 (StataCorp.2019. Stata Statistical Software: Release 16. College Station, TX: Stata Corp LLC.). The Student t test was used to assess the significance of differences between mean values. This relationship was examined using univariate regression analysis (Fisher test). P value < .05 was considered significant. Table presents the patient characteristics in our study. All patients underwent AGHD and daily GH replacement therapy. The mean age was 61.9 ± 18.9 years, and 9 patients were female. The BMI was 26.7 ± 5.2. Endocrinologically, 54.5, 54.5, 45.5, and 45.5% of the patients had ACTH, TSH, LH, and FSH deficiencies, respectively. A total of 9.1% of patients had central diabetes insipidus. In addition, hydrocortisone, levothyroxine, human chorionic gonadotrophin/human menopausal gonadotropin (HCG/HMG), and testosterone/estrogen, and desmopressin replacement therapy were performed in 54.5, 63.6, 0.0, 0.0, and 9.1% of patients (one patient did not have TSH deficiency but rather primary hypothyroidism, and was administered levothyroxine). As a result of titration, IGF1 values 6 months after switching to somapacitan were almost the same as those at switching (100.2 ± 44.3 vs 98.3 ± 40.5 ng/mL, P = .316). The IGF1 values of all patients at switching and 6 months after switching to somapacitan were between −1SDS and +1SDS, and the value of IGF1 at 2–3 days after the injection of somapacitan were almost the same as the 7 days after injection, which indicated larger amount of somapacitan must not be injected. The mean dose of daily GH replacement at switching was 0.20 ± 0.07 mg/day, and the dose of somapacitan 6 months after switching was 1.45 ± 0.35 mg/week (Table ). Table shows the changes in clinical, metabolic, and endocrinological parameters. In terms of glucose tolerance, HOMA-IR and FPG were significantly improved 6 months after switching compared with those at switching (HOMA-IR: 3.1 ± 1.6 vs 2.3 ± 1.3, P = .022; FPG: 104.5 ± 19.6 vs 99.3 ± 16.9 mg/dL, P = .044). Meanwhile, HbA1c and HOMA-β did not improve from at switching to 6 months after switching (HbA1c: 6.3 ± 0.5 vs 6.2 ± 0.5%, P = .174, HOMA-β: 148.0 ± 138.3 vs 110.5 ± 78.0, P = .140). The markers of lipid metabolism, estimated glomerular filtration rate, and electrolyte levels did not change significantly from switching to 6 months after switching. In contrast, all measured liver functions improved significantly from at switching to 6 months after switching (AST: 23.4 ± 3.4 vs 19.8 ± 5.1 U/L, P = .001; ALT: 19.6 ± 5.6 vs 15.0 ± 4.4 U/L, P = .004; γ-GTP: 25.2 ± 16.4 vs 20.8 ± 11.1 U/L, P = .018, respectively). Regarding clinical parameters, BMI improved significantly from at switching to 6 months after switching (26.7 ± 5.2 vs 26.1 ± 5.3, P = .007, respectively). In addition, systolic/diastolic blood pressure improved from at switching to 6 months after switching, but not significantly (142.2 ± 14.9 vs 139.4 ± 10.8/81.6 ± 10.9 vs 79.3 ± 8.4 mm Hg, P = .253/0.182). Regarding endocrinological parameters, there were no differences between the values at switching and those 6 months after switching for all anterior pituitary hormones and related hormones (Table ). In addition, Fisher test showed that age, sex, improvement in BMI or liver functions, presence of any hormonal deficiency, and the existence of any hormonal replacement therapy were not associated with improvement in HOMA-IR. However, daily GH replacement therapy periods were significantly positively associated with improvements in HOMA-IR ( P = .048) (Table ). AGHD is one of the pituitary hormonal deficiencies (anterior pituitary hormonal deficiencies and diabetes insipidus); however, replacement therapy could not be performed before 2006 in Japan. Furthermore, daily GH replacement therapy has been the only available treatment since 2006. It is well known that GH concentrations in the blood are normally high at midnight and low in the daytime, whereas those in patients with AGHD are extremely low during the entire day. Hence, patients with AGHD commonly self-injected GH on a nightly basis (7:00 pm–8.00 pm). However, GH concentrations in the blood of patients with AGHD during the daytime would remain severely low compared to that in normal subjects because the prolonged duration of daily GH formulation was <12 hours. Recently, patients with AGHD have been able to use somapacitan, the only weekly GH formulation in Japan. Nevertheless, the prolonged duration of somapacitan is more than 1 week, and the effect of this formulation continues throughout the day. Thus, these differences in duration could affect metabolic and endocrinological parameters. Patients with severe AGHD have many kinds of metabolic disorders. AGHD must be similar to metabolic syndrome at the point of the association with obesity, insulin resistance, visceral fat, lipid profile, NASH/NAFLD, and the risk of coronary heart disease. In our study, BMI was lower 6 months after switching to somapacitan than at switching. Since the prevalence of obesity in patients with AGHD is well known, and GH replacement therapy has been reported to improve obesity, the results of our study indicate that weekly GH replacement therapy with somapacitan could be better than daily GH replacement therapy. Nevertheless, in our study, the comparison between somapacitan and the other long-acting GH formulations was not performed. Future studies could prove the existence of the difference among long-acting GH formulations. Regarding liver dysfunction, AST/ALT/γ-GTP was significantly improved by switching from daily GH replacement therapy to weekly GH replacement therapy with somapacitan. AGHD is well-known to cause NASH/NAFLD. In phase 3 trials of somapacitan, the analysis of liver functions was not performed. The results of our study indicate that weekly GH replacement therapy with somapacitan could be more effective than daily GH replacement therapy, probably because continuous GH replacement therapy by somapacitan could improve liver dysfunction, considering that the values of IGF1 at switching and 6 months after switching were equivalent. Similarly, HOMA-IR and FPG levels improved after switching from daily GH replacement therapy to somapacitan. Considering these data and the lack of change in HOMA-β, the improvement in FPG might be due to the improvement in insulin resistance. Recently, Takahashi et al reported that there were no significant differences between daily GH formulations and somapacitan, summarizing the data of phase 3 clinical trials (REAL 1 [NCT02229851], REAL 2 [NCT02382939], REAL Japan [NCT03075644]). The differences could be caused that the no medical treatment of all patients in our study changed during this period, aside from GH formulations, while it is quite possible that medical treatment, aside from GH formulations, may have been changed in some patients in phase 3 trials of somapacitan. Thus, the results of insulin tolerance in our real-world study could be different from those in the previous report by Takahashi et al. Interestingly, in the same report, they also showed that the post hoc analysis of one of the phase 3 studies (REAL 1 [NCT02229851]) indicated the group receiving somapacitan had significantly lower HOMA-IR and FPG levels than those receiving daily GH formulation at 32 weeks after beginning. Moreover, the analysis also showed there were no significant differences in HbA1c values between the group receiving somapacitan and those receiving daily GH formulation. In our study, there were also no significant differences between the HbA1c values at switching and 6 months after switching to somapacitan. These results were consistent with those of the present study. Several factors regulate insulin resistance. In our study, BMI was lower 6 months after switching to somapacitan than at the time of switching, but with a very slight difference (26.7 ± 5.2 vs 26.1 ± 5.3 kg/m 2 ), which was difficult to explain the differences in HOMA-IR. In addition, a previous clinical trial showed no differences in body composition between the daily GH formulation and somapacitan. Our study demonstrated an improvement in liver functions after switching to somapacitan, which might lead to an improvement in hepatic insulin resistance. Nonetheless, patients with AGHD may have excessive hepatic insulin resistance caused by fatty liver/NASH/NAFLD. Hence, somapacitan could have more beneficial effects on insulin resistance as well as liver dysfunctions in AGHD than the daily GH formulation. On the other hand, a significant association between the improvement in HOMA-IR and liver functions was not revealed by Fisher test, probably because our study cohort was small. Thus, future studies with larger cohorts are expected to confirm the results of our study. Meanwhile, Fisher test revealed that improvement in HOMA-IR was significantly associated with the period of daily GH replacement therapy before switching to somapacitan, even though our cohort was small. These findings suggest that daily GH replacement formulation could be less efficient, at least for glucose intolerance, than somapacitan, considering that the values of IGF1 at switching and 6 months after switching were equivalent and switching from daily GH formulation to somapacitan should be considered as soon as possible if patients with AGHD were treated with daily GH replacement therapy. We also demonstrated that switching to GH replacement therapy did not affect endocrinological parameters. Previously, it was reported that GH could have antagonistic effects against 11β-HSD1, which could lead to lower cortisol values and higher ACTH values. Our study showed that ACTH and cortisol levels did not change after switching from daily GH replacement therapy to weekly GH replacement therapy with somapacitan. There were no changes in other endocrinological parameters. Hence, somapacitan can be used without impairing the endocrinological condition of patients. Our study had some limitations. First, the sample size was small because AGHD is a rare and intractable disease; this study was a real-world pilot study; and we excluded the patients whose medical treatment, aside from GH replacement therapy, was changed during the study period. In addition, the period of our study was not so long. Hence, future studies with larger cohorts are longer observation periods are required to confirm the results of our study. Second, we used HOMA-IR and HOMA-β as surrogate markers of insulin resistance, and insulin secretion as a substitute for an oral glucose tolerance test or hyperglycemic/hyperinsulinemic-euglycemic clamps. In addition, our study could not reveal the mechanism of improvement of HOMA-IR and FPG adequately. Future studies are also required on this point. Third, our study is a real-world pilot study, and thus could not check the changes in visceral fat content, bone density, bone metabolism markers, and myocardial zymogram, which were complications of AGHD. Therefore, future studies will investigate the differences between the group receiving somapacitan and those receiving daily GH formulation regarding the complications of AGHD. Our study is the first investigation of the effects of somapacitan on metabolic and endocrinological parameters in patients with AGHD who previously received daily GH replacement therapy in a real-world pilot study and reveals that weekly GH replacement therapy with somapacitan could have more beneficial effects on liver functions than daily GH replacement therapy. Furthermore, it is possible that weekly GH replacement therapy with somapacitan could improve glucose intolerance by reducing insulin resistance compared with daily GH replacement therapy. Future studies are required to confirm and develop our study. We thank Ms. Yumi Iriguchi for her assistance in conducting our study. Conceptualization: Ichiro Abe, Kaori Takeshita, Hideaki Shimada, Shigeaki Mukoubara, Kunihisa Kobayashi. Data curation: Ichiro Abe, Kaori Takeshita, Mai Nagata, Yuya Fujita, Kentaro Ochi, Midori Koga, Tadachika Kudo, Makiko Abe. Formal analysis: Ichiro Abe, Makiko Abe. Investigation: Ichiro Abe, Kaori Takeshita, Mai Nagata, Yuya Fujita, Kentaro Ochi, Midori Koga, Tadachika Kudo, Makiko Abe, Shigeaki Mukoubara, Kunihisa Kobayashi. Methodology: Ichiro Abe, Hideaki Shimada. Project administration: Ichiro Abe, Shigeaki Mukoubara, Kunihisa Kobayashi. Resources: Ichiro Abe. Supervision: Ichiro Abe, Shigeaki Mukoubara, Kunihisa Kobayashi. Validation: Ichiro Abe. Writing – original draft: Ichiro Abe. Writing – review & editing: Kaori Takeshita, Mai Nagata, Yuya Fujita, Kentaro Ochi, Midori Koga, Tadachika Kudo, Hideaki Shimada, Makiko Abe, Shigeaki Mukoubara, Kunihisa Kobayashi. |
Comprehensive Evaluation of Advanced Imputation Methods for Proteomic Data Acquired via the Label-Free Approach | 3c292ebd-b007-49ad-8f37-5d14dddda7d8 | 11728106 | Biochemistry[mh] | One of the most widely used approaches in mass spectrometry-based proteomics is the ‘label-free’ strategy. This method is favored for its ability to identify a vast number of proteins in a single analysis, making it particularly well-suited for large-scale proteomic studies and the discovery of novel biomarkers . Unlike isotope labeling methods, which require additional sample preparation steps, the label-free approach is simpler and more cost-effective. Its versatility and high-throughput nature make it an indispensable tool in proteomic research, especially when dealing with complex biological samples or when a comprehensive overview of the proteome is needed. However, despite its advantages, the label-free strategy has some notable limitations. Compared to isotope labeling methods, it offers lower accuracy and reproducibility . This is largely due to the inherent variability in the data acquisition process and the reliance on indirect measures of protein abundance, such as spectral counts or ion intensities. As a result, achieving consistent and reliable quantification across multiple samples can be challenging. One of the most significant obstacles in using the label-free strategy is the prevalence of missing values, which can affect up to 50% of the dataset . These missing values, which often arise from technical and biological factors, represent a major barrier to robust data interpretation. They limit the ability to derive comprehensive and accurate insights into protein abundance, statistical relationships, and functional roles within the analyzed samples . The incomplete data can skew results, reduce statistical power, and complicate downstream analyses, making it critical to address these gaps effectively. Thus, while the label-free strategy is a powerful tool, overcoming its limitations—particularly those related to missing values—is essential for maximizing its potential in proteomic research. The causes of missing values are numerous and often challenging to pinpoint for any given protein. Missing values may arise from biological, instrumental, or sample preparation issues. Biological factors include the absence of a specific protein in the sample or its low concentration, which may fall below the detection limit of the instrument. Instrumental factors encompass issues such as ion competition, poor ionization efficiency, the selective fragmentation of only the most intense peptides during data-dependent acquisition (DDA), and errors in peptide identification . Sample preparation may also contribute to missing values due to protein losses or irregular cleavages during trypsin digestion. To better understand missing values, they are commonly categorized as missing at random (MAR) or missing not at random (MNAR) . The MAR values typically result from technical limitations and stochastic fluctuations, whereas MNAR values are directly correlated with the concentration of a specific protein or peptide in the sample . Experimentally derived datasets often contain a mixture of both MAR and MNAR values. Although the precise ratio of MAR to MNAR values is generally unknown, it is widely believed that MNAR values constitute the majority . Addressing missing values is crucial for ensuring the reliability of proteomic analyses. There are three main strategies to manage missing values. The first approach involves removing proteins that contain missing values in any sample. While straightforward, this method may result in the loss of valuable biological information. The second approach focuses on performing data analysis only on complete datasets with correctly identified values. However, this strategy significantly limits the use of many statistical methods, which require a complete dataset. The third and most commonly used approach is the imputation of missing values. This method replaces missing values with estimated values, allowing for the retention of valuable information and enabling robust data analysis while mitigating the impact of missing data on the overall dataset. Removing all proteins that contain any missing values for some samples can result in the loss of valuable biological information. This approach may seem straightforward, but it often disregards the underlying complexity of biological systems, leading to the exclusion of relevant proteins that may still provide critical insights. On the other hand, performing data analysis solely on correctly identified values severely limits the applicability of most statistical methods, as these techniques typically require a complete dataset to generate reliable and meaningful results. The inherent challenges of missing values in proteomics datasets necessitate alternative approaches to handle this issue effectively. One widely adopted solution is data imputation, which relies on the assumption that all samples have fundamentally similar protein compositions, with observed differences reflecting variations in the expression levels of individual proteins. By replacing missing values with estimated values, imputation minimizes the loss of information and allows for more robust statistical analyses. In proteomic datasets, a left-censored normal distribution is often observed, resulting from the non-random nature of missing values, which are often missing not at random (MNAR) . As a result, it is widely believed that imputation methods should be specifically designed to handle left-censored data, allowing for the effective approximation of small MNAR values . However, imputation is not without its challenges. As the number of missing values increases, the potential for distortion in the data grows, leading to increasingly biased or inaccurate estimates . For instance, assigning a constant value to a protein (such as the mean or median of non-missing values) can cause an underestimation of the variance, which in turn may result in false-positive findings. This highlights the importance of carefully selecting the most appropriate imputation strategy to avoid introducing systematic errors into the analysis. Imputation methods are generally classified into three main types: single-value imputation, local-similarity methods, and global-similarity methods. Each of these approaches has its own strengths and limitations, depending on the nature of the dataset and the specific goals of the analysis. Single-value imputation methods, for example, are typically simpler to implement but may introduce significant bias, especially when missing values are not randomly distributed. In contrast, local-similarity methods are based on the assumption that proteins with similar expression patterns can be used to predict missing values, making them more suited to datasets where proteins show strong interdependencies. On the other hand, global-similarity methods adopt a broader approach by using overall patterns across the entire dataset to reconstruct missing data, which can be particularly useful when dealing with complex proteomic data. The choice of imputation method depends on both the characteristics of the data and the underlying assumptions about the causes of missing values. Single-value imputation methods replace missing values with a constant or random value. This category includes LOD (imputation of lowest acquired intensity from entire dataset), SampMin (imputation of lowest acquired intensity for a given protein) and imputation of a random value from the left tail of the normal distribution (ND), also known as RTI (random tail imputation) . Local-similarity imputation methods are based on the assumption that protein behaviors and expression are interdependent and highly correlated . The fundamental idea behind these methods is to estimate missing values by leveraging the information from other proteins that exhibit similar intensity profiles. The process typically begins by identifying a set of proteins that closely resemble the imputed protein in terms of expression patterns. Then, the missing value is calculated as a weighted combination of the intensities of these similar proteins. Several algorithms fall under this category, including k-nearest neighbors (kNN), local least-squares (LLS), least-squares adaptive (LSA) and random forest (RF). Each of these methods utilizes different techniques to identify and combine information from similar proteins, allowing for more accurate imputation of missing data. Imputation methods based on global similarity use matrix reduction techniques to iteratively reconstruct missing values. Among such methods are SVD (single-value decomposition) and variations of the PCA method: PPCA (probabilistic principal component analysis), and BPCA (Bayesian principal component analysis). At this moment, there is no consensus in the field of proteomics on the best method for data imputation. Problems that lead to this situation include the lack of comparable, high-quality datasets, the use of different imputation methods depending on the publication, and the selection of criteria for assessing imputation efficiency. A reasonable approach seems to be a direct comparison of experimentally obtained values with the values imputed by the chosen algorithm. A popular strategy is to simulate missing values on the full dataset . This allows for the calculation of differences between real and imputed values, but studies on real missing values are still most desirable. This forces the definition of other evaluation criteria than a simple comparison, e.g., through statistical parameters . The studies conducted show that different imputation methods present different performances on MAR and MNAR values. Single-value imputation methods showed good performance on MNAR values in contrast to local-similarity methods, which performed well on MAR values. The opposite was the case for methods such as SVD, kNN, or REM . The conclusions suggested by Kong et al. indicate that the selection of the imputation method should depend on the characteristic and structure of the experimentally obtained data; while this is a very difficult task in itself, it is strongly desirable to find a universal way of proceeding and select the best imputation method regardless of the data. It is difficult to choose the best imputation method based on the available results. In the work carried out so far, the best methods have been identified as follows: SampMin , belonging to the single-value imputation group; REM, LSA , kNN , and RF from the family of methods based on local similarities; and BPCA , based on global similarities. The primary objective of this study is to systematically collect and evaluate imputation methods previously identified as highly effective in the scientific literature , applying them to a real proteomics dataset obtained through manual curation. The analysis encompasses widely utilized approaches for data handling and integrates representative methods from all major imputation categories: single-value, local-similarity, and global-similarity strategies. As single-value methods, two commonly used left-censored approaches, LOD and ND, were selected, as well as the SampMin method, which was characterized by high performance in other publications . As representatives of the local-similarity group, the kNN, LLS, LSA, and RF methods were selected, each of which was indicated as the most effective in individual works . Among the global-similarity methods, two methods representing different approaches to the principal component analysis (BPCA and PPCA) were selected, as well as the SVD method, which is not based on PCA analysis and uses matrix dimension reduction. Furthermore, this study examines the influence of key additional factors that may affect imputation performance, including the choice of protein identification algorithm and the application of logarithmization to the data as a preprocessing step. By addressing these aspects, the study provides a comprehensive framework for assessing the robustness and utility of imputation techniques in proteomic analyses, contributing to the advancement of reliable quantitative methodologies in the field. Protein identification and the handling of missing values are fundamental components in ensuring the reliability of quantitative proteomic analyses. In this study, we evaluated the performance of two widely used protein identification tools, FragPipe and MaxQuant, and assessed the efficacy of various imputation methods applied to the resulting datasets. This section presents the results of the comparative evaluation, highlighting the differences in protein identification between FragPipe and MaxQuant, as well as the corresponding imputation times. 2.1. Protein Identification FragPipe and MaxQuant identified 3508 and 4987 proteins, respectively. This result is 42% better for MaxQuant, but the identification time was almost 10 times faster for FragPipe (1693 min. for MaxQuant, 178 min. for FragPipe). However, the programs achieved very similar results both in terms of the share of missing values in the full dataset (ca. 51%) and the share of proteins containing all values correctly identified (ca. 27%). 2.2. Imputation Time The slowest imputation method is clearly the RF method, although it is worth noting that the method works faster with an increase in the MV share. The time differences between the other methods are negligible; only the kNN and BPCA methods require a few seconds more than the rest. 2.3. NRMSE The mean NRMSE values obtained for individual methods for FragPipe data and presented in may be interpreted as the absolute imputation error because they are calculated as the difference between the imputed value and the true value. Lower NRMSE values indicate a lower imputation error. For a better understanding of the behavior of individual methods, it is interesting to consider the extreme cases of the share of MNAR values, i.e., 0% MNAR and 100% MNAR. However, these are artificial cases; they do not apply to real data, which are a mixture of MNAR and MAR values. They specify the nature of individual imputation methods, but they should be interpreted separately from the rest of the cases. With a zero share of MNAR values, the best result in terms of imputation error expressed by NRMSE is obtained by the RF method, followed by LLS and kNN. The worst results are obtained by the LOD and ND methods, which is in line with expectations for left-censored methods. Global methods in these conditions obtain worse results with the increase in the MV share, while for the other methods it does not matter. At a 100% MNAR value share, the best results are achieved by the left-censored methods, i.e., LOD and SampMin, and the local-similarity methods: kNN and LLS. Again, the global-similarity methods improve with the increase in MV, an effect that is also observed for the ND, LLS, LSA, and RF. With the increase in the MV share, the imputation error increases for the LOD, SampMin, and BPCA methods, and decreases only for the RF method. For the kNN and LSA methods, it has a negligible effect. At a low share of the MNAR values for the SVD and PPCA methods, the imputation error initially increases, but when their share increases to 80%, we begin to observe the opposite trend. The increase in the share of MNAR values has a negative impact on the ND, LLS, LSA, and global-similarity methods, with the most significant effect observed for the LSA method. The opposite behavior is observed for the single-value methods LOD and SampMin. No significant impact is observed for the kNN and RF methods. shows the case that best reflects the conditions of the real experiment, i.e., MV = 50% and a high share of MNAR values = 80% for both identification programs, before and after logarithmization. The behavior of the individual imputation methods for data obtained using both programs with respect to increasing the share of MV and MNAR is the same. The imputation error for data from FragPipe and MaxQuant is comparable. In the case of FragPipe, the obtained NRMSE values are slightly better only for the LOD method. For MaxQuant, however, better results are obtained for the ND and global-similarity methods, which is probably due to more data being available. Carrying out the logarithmization process before imputation does not negatively affect the imputation error for any of the methods. For the LOD, SampMin, kNN, and RF methods, no significant effect is observed, while for the remaining methods (ND, LLS, LSA), the results are visibly improved, especially for the global-similarity methods (SVD, BPCA, PPCA), which achieve some of the best results in such conditions. 2.4. ROC Curve The ROC curve shows the relationship between the true-positive rate (TPR) and the false-positive rate (FPR) at different decision thresholds. It allows you to visualize the effects of changing the threshold (as an adjusted p -value) and allows you to choose it in such a way as to balance the need to minimize FPR with the need to maximize TPR. Another use of the ROC curve is to compare the performance of classification models, which, in the context of this experiment, means a measure of how well a given imputation method performs in reproducing the actual results. The area under the ROC curve (AUC) was used to compare the classification of proteins as true or false positives with respect to the actual data, which, as a single-number parameter, is easier to compare and visualize. An AUC value of 1 indicates excellent classification ability of the model, while a value of 0.5 indicates no discriminatory ability, comparable to random guessing. shows all the AUC values obtained for the FragPipe data, similarly to NRMSE. With a 0% share of MNAR values, the best result, similarly to NRMSE, was obtained by the RF and LLS methods. One of the single-value methods—SampMin—also obtained a high result for these conditions. All the methods achieve the highest results with all combinations of MV and MNAR when the share of MNAR values is 100%. The observed scatter of results is also significantly reduced for this condition. An increase in the number of missing values has a negative impact on all the tested imputation methods. However, with the increase in the share of MNAR values, the classification accuracy increases significantly for the LOD and ND methods. The SampMin, kNN, LSA, and PPCA methods also improve but to a lesser extent. The increase in the MNAR value share negatively affects only the LLS and RF methods. The RF and LLS methods achieve slightly better results, and the kNN method improves in the case of a low share of MNAR values. In the case of the LSA method, and especially the global methods, a clear improvement is visible, but in critical conditions, i.e., with a 100% share of the MNAR values, they perform worse than before logarithmization. Comparing the results for the FragPipe and MaxQuant data for real-experiment conditions in , the results obtained by the individual imputation methods are again very similar for both identification programs. In this case, kNN, SVD, and BPCA achieve slightly better AUC values for MaxQuant data, and for the other methods the differences are negligible. As in the case of NRMSE, prior logarithmization has a positive effect on the obtained results in most cases. Noticeably better AUC values can be observed for the kNN, LLS, and global-similarity methods. The greatest improvement due to logarithmization can be observed for the PPCA method. For the ND method, logarithmization resulted in worse results, contrary to NRMSE. The other methods behave the same regardless of the logarithmization conditions. 2.5. MV Imputation on Full Dataset In the second stage of the imputation method evaluation, the full datasets with naturally occurring MVs were used and the data were then filtered, retaining only those proteins that are present in at least 50% of the samples, which resulted in 1709 proteins for FragPipe and 2404 proteins for MaxQuant. This represented 48.7% and 48.2% of the total number of proteins initially identified, respectively. After data imputation, the t-Student test (FDR = 5%) was performed, and the adjusted p -value and fold change were calculated. shows the number of proteins identified as true positives by each imputation method for FragPipe and MaxQuant data before and after logarithmization. Without logarithmization, the highest number of proteins identified as true positives was observed for the RF, LLS, and BPCA methods in the case of FragPipe and for the SampMin, RF, and LLS methods in the case of MaxQuant. The worst results were obtained for the ND and LSA methods for both protein identification programs. The vast majority of the imputation methods achieved a better result for FragPipe despite a smaller total number of identified proteins. The largest differences in performance were observed for the LOD (ca. 20%) and BPCA (ca. 25%) methods, and the smallest for the LLS method (ca. 4%). For the MaxQuant program, only the SampMin method achieved a better result but by as much as 27%. Data logarithmization did not improve the results achieved only for the LOD and SampMin methods, and worsened the results only for the kNN method in the case of MaxQuant. For the other methods, the number of proteins identified as true positives increased, but the percentage scale of improvement differed depending on the identification program used. In this respect, the largest difference was noted for the PPCA method, which improved by as much as 32% for FragPipe and by only 2% for MaxQuant. Among the imputation methods that improved, the smallest differences can be observed for the RF method. Previous logarithmization once again had a very positive effect on global imputation methods, but in this test this tendency was more pronounced for the FragPipe program and it was the SVD method, next to LLS and RF, that achieved the best results under these conditions. For the MaxQuant program, the largest increase in TP value was noted for another global imputation method—BPCA–, but the best result was still achieved by the SampMin method. Including FC in the considerations, Volcano plots were drawn and the number of statistically significant proteins at FC = 2 and FDR = 5% was compared. The obtained results differ, sometimes significantly, depending on the logarithmization or its absence and the program used to identify proteins. Unfortunately, in this case there is no absolute reference point on the basis of which it is possible to state which imputation method gives better, more reliable results. Any overexpression in the case of this experiment can be expected to occur on the side of the 7- and 21-day groups, but this is not unambiguous. A larger number of statistically significant points also does not necessarily indicate better performance of a given imputation method, because despite performing a number of statistical tests, some overestimations may still occur, leading to later overinterpretations. For the FragPipe program, significantly more high points can be observed, which correspond to proteins with very low FDR. For the LOD method, overexpression occurs on the control group side for the FragPipe program, and for the MaxQuant program on the 7-day group side, and logarithmization of data does not affect the number of statistically significant points and their distribution in any way. This is in agreement with the results for TP similarly to the SampMin method, with the difference that overexpression for the 7-day group is observed here regardless of the program used. For the ND method, logarithmization causes a clear equalization of the number of significant points on both sides and an increase in their total number, and the results for both identification programs are relatively similar. The graphs for the methods that achieved the best results for tests on data with artificially implemented MV, i.e., RF and LLS, are quite similar. Logarithmization of data does not affect the number of statistically significant points and overexpression in this case, which occurs on the 7-day group side, although their total number is greater for the FragPipe program. In the case of the remaining methods, i.e., kNN, LSA, SVD, BPCA, and PPCA, there is a decrease in the number of statistically significant points for imputation performed after data normalization. This effect is greater for the MaxQuant program in the case of the LSA, SVD, and BPCA methods and especially for the PPCA method. In each of the mentioned cases, overexpression occurs on the side of the 7-day group both before and after logarithmization. For the mentioned methods, more statistically significant points are observed for the FragPipe program. The largest number of statistically significant points can be noted for the PPCA method for the FragPipe program before logarithmization. For the obtained imputation results, PCA analysis was also performed using only statistically significant proteins (FDR = 5% and FC = 2). Complete separation of the studied groups before and after logarithmization was observed for the LOD, ND, and LSA methods. For the PPCA method, complete separation was also noted before logarithmization, but for the logarithmized datasets, only partial separation of the groups occurred and this is the only imputation method for which a negative trend was observed. In the case of imputation methods for which the separation of the studied groups was minimal or only partial, after logarithmization the separation of groups increases for the SampMin, RF, SVD, and BPCA methods. No clear effect of logarithmization on the separation of the studied groups was noted for the kNN and LLS methods. FragPipe and MaxQuant identified 3508 and 4987 proteins, respectively. This result is 42% better for MaxQuant, but the identification time was almost 10 times faster for FragPipe (1693 min. for MaxQuant, 178 min. for FragPipe). However, the programs achieved very similar results both in terms of the share of missing values in the full dataset (ca. 51%) and the share of proteins containing all values correctly identified (ca. 27%). The slowest imputation method is clearly the RF method, although it is worth noting that the method works faster with an increase in the MV share. The time differences between the other methods are negligible; only the kNN and BPCA methods require a few seconds more than the rest. The mean NRMSE values obtained for individual methods for FragPipe data and presented in may be interpreted as the absolute imputation error because they are calculated as the difference between the imputed value and the true value. Lower NRMSE values indicate a lower imputation error. For a better understanding of the behavior of individual methods, it is interesting to consider the extreme cases of the share of MNAR values, i.e., 0% MNAR and 100% MNAR. However, these are artificial cases; they do not apply to real data, which are a mixture of MNAR and MAR values. They specify the nature of individual imputation methods, but they should be interpreted separately from the rest of the cases. With a zero share of MNAR values, the best result in terms of imputation error expressed by NRMSE is obtained by the RF method, followed by LLS and kNN. The worst results are obtained by the LOD and ND methods, which is in line with expectations for left-censored methods. Global methods in these conditions obtain worse results with the increase in the MV share, while for the other methods it does not matter. At a 100% MNAR value share, the best results are achieved by the left-censored methods, i.e., LOD and SampMin, and the local-similarity methods: kNN and LLS. Again, the global-similarity methods improve with the increase in MV, an effect that is also observed for the ND, LLS, LSA, and RF. With the increase in the MV share, the imputation error increases for the LOD, SampMin, and BPCA methods, and decreases only for the RF method. For the kNN and LSA methods, it has a negligible effect. At a low share of the MNAR values for the SVD and PPCA methods, the imputation error initially increases, but when their share increases to 80%, we begin to observe the opposite trend. The increase in the share of MNAR values has a negative impact on the ND, LLS, LSA, and global-similarity methods, with the most significant effect observed for the LSA method. The opposite behavior is observed for the single-value methods LOD and SampMin. No significant impact is observed for the kNN and RF methods. shows the case that best reflects the conditions of the real experiment, i.e., MV = 50% and a high share of MNAR values = 80% for both identification programs, before and after logarithmization. The behavior of the individual imputation methods for data obtained using both programs with respect to increasing the share of MV and MNAR is the same. The imputation error for data from FragPipe and MaxQuant is comparable. In the case of FragPipe, the obtained NRMSE values are slightly better only for the LOD method. For MaxQuant, however, better results are obtained for the ND and global-similarity methods, which is probably due to more data being available. Carrying out the logarithmization process before imputation does not negatively affect the imputation error for any of the methods. For the LOD, SampMin, kNN, and RF methods, no significant effect is observed, while for the remaining methods (ND, LLS, LSA), the results are visibly improved, especially for the global-similarity methods (SVD, BPCA, PPCA), which achieve some of the best results in such conditions. The ROC curve shows the relationship between the true-positive rate (TPR) and the false-positive rate (FPR) at different decision thresholds. It allows you to visualize the effects of changing the threshold (as an adjusted p -value) and allows you to choose it in such a way as to balance the need to minimize FPR with the need to maximize TPR. Another use of the ROC curve is to compare the performance of classification models, which, in the context of this experiment, means a measure of how well a given imputation method performs in reproducing the actual results. The area under the ROC curve (AUC) was used to compare the classification of proteins as true or false positives with respect to the actual data, which, as a single-number parameter, is easier to compare and visualize. An AUC value of 1 indicates excellent classification ability of the model, while a value of 0.5 indicates no discriminatory ability, comparable to random guessing. shows all the AUC values obtained for the FragPipe data, similarly to NRMSE. With a 0% share of MNAR values, the best result, similarly to NRMSE, was obtained by the RF and LLS methods. One of the single-value methods—SampMin—also obtained a high result for these conditions. All the methods achieve the highest results with all combinations of MV and MNAR when the share of MNAR values is 100%. The observed scatter of results is also significantly reduced for this condition. An increase in the number of missing values has a negative impact on all the tested imputation methods. However, with the increase in the share of MNAR values, the classification accuracy increases significantly for the LOD and ND methods. The SampMin, kNN, LSA, and PPCA methods also improve but to a lesser extent. The increase in the MNAR value share negatively affects only the LLS and RF methods. The RF and LLS methods achieve slightly better results, and the kNN method improves in the case of a low share of MNAR values. In the case of the LSA method, and especially the global methods, a clear improvement is visible, but in critical conditions, i.e., with a 100% share of the MNAR values, they perform worse than before logarithmization. Comparing the results for the FragPipe and MaxQuant data for real-experiment conditions in , the results obtained by the individual imputation methods are again very similar for both identification programs. In this case, kNN, SVD, and BPCA achieve slightly better AUC values for MaxQuant data, and for the other methods the differences are negligible. As in the case of NRMSE, prior logarithmization has a positive effect on the obtained results in most cases. Noticeably better AUC values can be observed for the kNN, LLS, and global-similarity methods. The greatest improvement due to logarithmization can be observed for the PPCA method. For the ND method, logarithmization resulted in worse results, contrary to NRMSE. The other methods behave the same regardless of the logarithmization conditions. In the second stage of the imputation method evaluation, the full datasets with naturally occurring MVs were used and the data were then filtered, retaining only those proteins that are present in at least 50% of the samples, which resulted in 1709 proteins for FragPipe and 2404 proteins for MaxQuant. This represented 48.7% and 48.2% of the total number of proteins initially identified, respectively. After data imputation, the t-Student test (FDR = 5%) was performed, and the adjusted p -value and fold change were calculated. shows the number of proteins identified as true positives by each imputation method for FragPipe and MaxQuant data before and after logarithmization. Without logarithmization, the highest number of proteins identified as true positives was observed for the RF, LLS, and BPCA methods in the case of FragPipe and for the SampMin, RF, and LLS methods in the case of MaxQuant. The worst results were obtained for the ND and LSA methods for both protein identification programs. The vast majority of the imputation methods achieved a better result for FragPipe despite a smaller total number of identified proteins. The largest differences in performance were observed for the LOD (ca. 20%) and BPCA (ca. 25%) methods, and the smallest for the LLS method (ca. 4%). For the MaxQuant program, only the SampMin method achieved a better result but by as much as 27%. Data logarithmization did not improve the results achieved only for the LOD and SampMin methods, and worsened the results only for the kNN method in the case of MaxQuant. For the other methods, the number of proteins identified as true positives increased, but the percentage scale of improvement differed depending on the identification program used. In this respect, the largest difference was noted for the PPCA method, which improved by as much as 32% for FragPipe and by only 2% for MaxQuant. Among the imputation methods that improved, the smallest differences can be observed for the RF method. Previous logarithmization once again had a very positive effect on global imputation methods, but in this test this tendency was more pronounced for the FragPipe program and it was the SVD method, next to LLS and RF, that achieved the best results under these conditions. For the MaxQuant program, the largest increase in TP value was noted for another global imputation method—BPCA–, but the best result was still achieved by the SampMin method. Including FC in the considerations, Volcano plots were drawn and the number of statistically significant proteins at FC = 2 and FDR = 5% was compared. The obtained results differ, sometimes significantly, depending on the logarithmization or its absence and the program used to identify proteins. Unfortunately, in this case there is no absolute reference point on the basis of which it is possible to state which imputation method gives better, more reliable results. Any overexpression in the case of this experiment can be expected to occur on the side of the 7- and 21-day groups, but this is not unambiguous. A larger number of statistically significant points also does not necessarily indicate better performance of a given imputation method, because despite performing a number of statistical tests, some overestimations may still occur, leading to later overinterpretations. For the FragPipe program, significantly more high points can be observed, which correspond to proteins with very low FDR. For the LOD method, overexpression occurs on the control group side for the FragPipe program, and for the MaxQuant program on the 7-day group side, and logarithmization of data does not affect the number of statistically significant points and their distribution in any way. This is in agreement with the results for TP similarly to the SampMin method, with the difference that overexpression for the 7-day group is observed here regardless of the program used. For the ND method, logarithmization causes a clear equalization of the number of significant points on both sides and an increase in their total number, and the results for both identification programs are relatively similar. The graphs for the methods that achieved the best results for tests on data with artificially implemented MV, i.e., RF and LLS, are quite similar. Logarithmization of data does not affect the number of statistically significant points and overexpression in this case, which occurs on the 7-day group side, although their total number is greater for the FragPipe program. In the case of the remaining methods, i.e., kNN, LSA, SVD, BPCA, and PPCA, there is a decrease in the number of statistically significant points for imputation performed after data normalization. This effect is greater for the MaxQuant program in the case of the LSA, SVD, and BPCA methods and especially for the PPCA method. In each of the mentioned cases, overexpression occurs on the side of the 7-day group both before and after logarithmization. For the mentioned methods, more statistically significant points are observed for the FragPipe program. The largest number of statistically significant points can be noted for the PPCA method for the FragPipe program before logarithmization. For the obtained imputation results, PCA analysis was also performed using only statistically significant proteins (FDR = 5% and FC = 2). Complete separation of the studied groups before and after logarithmization was observed for the LOD, ND, and LSA methods. For the PPCA method, complete separation was also noted before logarithmization, but for the logarithmized datasets, only partial separation of the groups occurred and this is the only imputation method for which a negative trend was observed. In the case of imputation methods for which the separation of the studied groups was minimal or only partial, after logarithmization the separation of groups increases for the SampMin, RF, SVD, and BPCA methods. No clear effect of logarithmization on the separation of the studied groups was noted for the kNN and LLS methods. The evaluation of extreme cases involving missing values, specifically with 0% and 100% of missing not at random (MNAR) values, was instrumental in understanding how individual imputation methods perform under conditions where missing data are either left-censored or completely random. These conditions allowed for an in-depth examination of the methods’ sensitivity to different types of missing data patterns, contributing valuable insights into their strengths and limitations. As expected, and consistent with findings from previous studies , single-value imputation methods, LOD, and SampMin demonstrated strong performance in scenarios with a high proportion of missing not at random (MNAR) values. These methods are particularly effective when the missing data exhibit systematic patterns or are subject to censoring, where imputation is required to approximate the true values. Even the ND method, despite exhibiting a higher imputation error (as measured by NRMSE) under these conditions, showed comparable classification efficiency (AUC) to the other methods. This highlights the nuanced nature of the ND method, which, while less precise in imputation, can still perform well in maintaining the integrity of the overall dataset classification. When all missing values were random (0% MNAR), none of the imputation methods showed significant improvements in performance, reinforcing the challenge of handling completely random missing values. However, in line with previous findings , the local-similarity methods, especially RF and LLS, emerged as the most effective approaches under these conditions, yielding the best results in terms of imputation accuracy and classification performance. This suggests that local-similarity methods are better equipped to deal with the inherent randomness of missing data, as they leverage the relationships and patterns within the available data to impute missing values more effectively. The SampMin method, which has previously been highlighted as one of the best imputation methods , also performed remarkably well in this context, further supporting its utility in dealing with missing data, particularly in cases where missing values exhibit a non-random pattern. Overall, most of the methods that have been identified as top performers in earlier studies—SampMin , kNN , RF , and BPCA —consistently delivered high-quality results, both in terms of imputation error and the identification of true positives. Among the methods that have not been very popular so far, but which achieved very high results in a given experiment, we can mention the LLS and SVD after log-normalization. Limitations of the methods described, depending on the case, may include imputation time, the need for optimization, or difficulty of implementation. The slowest process is definitely the RF method; it is counted in minutes and even took 30 times longer than the imputation time of the second-in-line method, kNN, proportional to the size of the data. An undoubted advantage is the lack of necessity of optimization, in contrast to kNN and LLS (k-nearest neighbors) and global-similarity methods (nPCs). Implementation of the above methods is slightly more difficult than in the case of single-value methods, which are often built into the software for processing proteomic data and require certain, at least minimal programming skills. Differences in the performance of individual methods were observed, which can largely be attributed to the experimental conditions, such as the choice of protein identification program (FragPipe vs. MaxQuant), as well as the impact of data preprocessing steps like logarithmization. The comparison of the results before and after logarithmization confirms the statement , according to which normalization should be performed immediately before data imputation, and some methods, especially global-similarity methods such as SVD , are particularly sensitive to this factor. These factors influenced the final imputation outcomes and highlighted the importance of optimizing both the choice of imputation method and the preprocessing pipeline to suit the specific characteristics of the dataset. The findings underscore that while there is no one-size-fits-all solution for imputation , certain methods, particularly local-similarity approaches, exhibit robust performance across various missing value scenarios, offering valuable tools for improving data quality in proteomics. The results of this study have significant implications for the reliability and accuracy of proteomic analyses, particularly in the context of large-scale quantitative studies where missing data are inevitable. The choice of imputation method can influence the overall dataset quality, and, thus, the interpretation of protein expression profiles, which are critical for downstream analysis and conclusions. By identifying the strengths and limitations of various imputation techniques, this study provides valuable guidance for optimizing proteomic workflows, ensuring that missing data do not compromise the validity of the findings. The improved performance of local-similarity methods like LLS and RF, particularly under random missing data conditions, highlights their potential for enhancing the robustness of proteomic datasets, which are often subject to high variability and incomplete data due to experimental constraints. In the context of medical diagnostics, these findings could have a profound impact on the interpretation of biomarker discovery and disease diagnostics. Proteomic data are increasingly used to identify disease-related biomarkers, monitor disease progression, and assess therapeutic efficacy. The ability to accurately impute missing values ensures that proteomic datasets remain consistent and reliable, even in the presence of incomplete data, which is common in clinical settings. For example, in diagnosing complex diseases, such as cancer or neurodegenerative disorders, where protein expression profiles play a key role, reliable imputation methods could improve the identification of disease-specific biomarkers and facilitate the development of personalized therapeutic strategies. The ability to accurately address missing values in proteomic data not only improves the quality of scientific analyses but also enhances the clinical applicability of proteomics. The results obtained for the volcano plots and PCA analysis show that the wrong choice of imputation method can lead to false conclusions about the biological functionality of selected proteins. For example, the use of methods such as LOD and ND in subsequent statistical tests led to obtaining a large number of statistically significant proteins and a good separation of the studied groups for these points. Considering the results from the first part of the experiment, where both methods showed very low imputation accuracy, it can be expected that such results result from the underestimation of certain values and, consequently, the overestimation of changes in expression. For studies on the border of medicine and biology, this could lead to indicating incorrect biomarkers or indicating incorrect factors influencing the development of the disease. Furthermore, the importance of assuring data validity in proteomics cannot be overstated, as it directly influences the reliability of diagnostic results. A recent publication on a standardized protocol for assuring the validity of proteomics results from liquid chromatography–high-resolution mass spectrometry outlines essential steps to ensure result integrity. This protocol, based on the ISO/IEC 17025:2017 and ISO 15189:2022 standards, provides a comprehensive approach to quality control in proteomic research, further emphasizing the need for stringent validation processes in mass spectrometry-based proteomics. From a metrological perspective, the evaluation of imputation methods ensures data quality and comparability across studies, which is essential for clinical diagnostics. Logarithmization and careful imputation can minimize biases and improve the reproducibility and accuracy of proteomic measurements, supporting more reliable diagnostic tools. These findings suggest that optimizing imputation strategies is key for advancing proteomics in both research and clinical settings. Future studies should focus on evaluating these methods across additional datasets and at the peptide level, further refining the utility of proteomics in precision medicine. By integrating robust quality control protocols, such as those outlined in recent standards, proteomic analyses can meet the high standards required for diagnostic applications, advancing the field of precision medicine. 4.1. Samples In this study, the most effective imputation methods identified in individual publications were curated and applied to data derived from a real experimental setting. The dataset originated from a study involving rat brain samples, analyzed in the context of fluorine-containing drug administration. A comprehensive description of the experimental results and the analytical procedures employed in this investigation has been detailed in our prior paper . A proteomics label-free approach was used to prepare and analyze the samples. Firstly, sample preparation was performed, which included protein extraction, reduction, alkylation, and in-solution digestion with tripsin. In the second step, chromatographic separation by liquid chromatography (nano-UHPLC, Thermo Scientific, Bartlesville, OK, USA) and analysis by high-resolution mass spectrometry (MS; Orbitrap; Thermo Scientific, Bartlesville, OK, USA) were used to obtain the data. The experimental workflow for this proteomics approach was also described previously . 4.2. Chemicals, Reagents, and Instrumentation Analytical grade chemicals and analytical standards were obtained from Merck (Darmstadt, Germany), Promega (Madison, WI, USA), Thermo Scientific (Bartlesville, OK, USA), and EMD Millipore (Darmstadt, Germany). Deionized water from the Milli-Q system (18.2 MΩ cm; EMD Millipore, Darmstadt, Germany) was used for samples and standard dilution. The instrumentation for extraction and sample preparation was as follows: mechanical homogenizer Ultra-Turrax (IKA, Königswinter, Germany), laboratory incubator CLN 240 (MultiSerw, Brzeźnica, Poland), vacuum centrifuge 5804/5804 R (Eppendorf, Enfield, CT, USA), vortex shaker (IKA, Königswinter, Germany), thermomixer Eppendorf Comfort (Eppendorf, Enfield, CT, USA), and vacuum concentrator SpeedVac Concentrator Plus (Eppendorf, Enfield, CT, USA). Reversed-phase capillary nano-UHPLC separations were performed using an UltiMate 3000 nano system (Dionex Ultimate Series UHPLC, Thermo Scientific, Bartlesville, OK, USA) equipped with in-house–packed capillary C-18 column (75 µm × 500 mm, particle size 1.9 µm) coupled on-line with a high-resolution tandem mass spectrometer (Orbitrap Fusion Tribrid™ Mass Spectrometer, Thermo Scientific, Bartlesville, OK, USA). 4.3. Protein Identification The recorded MS/MS spectra were used to identify the proteins using two different algorithms to compare their possible effects on the performance of the imputation methods. For this purpose, the FragPipe (v. 17.1) and MaxQuant (v. 2.0.3.0) programs were used using the MSFragger and Andromeda algorithms , respectively. The SwissProt database (accessed on 25 March 2022) was searched, with the specified taxonomy Rattus Norvegicus (Taxonomy ID: 10116). Proteins and peptides were identified using a target–decoy approach with a reversed database. As the fixed modification, propionamidation on cysteine (C) was set, which derived from using acrylamide as an alkylating agent. RAW files were used to identify proteins using the MaxQuant program. The mass tolerance was set to ±10.0 ppm for parent ion masses and ±0.6 Da for fragment ion masses. The false discovery rate for PSM and peptides was set at 1%. To perform identification using FragPipe, it was necessary to convert the raw data to the *.mzXML format with the Mass Converter (v. 1.0.3) R package . The precursor and fragment ion mass tolerance was set to ±10.0 ppm and a maximum isotope error option (0/1/2/3) was used. Only the MaxLFQ intensities calculated by both identification programs were used to test the imputation methods, which allowed for an optimal comparison of the obtained results. Additionally, to check the influence of the logarithmization process, an evaluation of the imputation methods was performed before and after the data logarithmization. 4.4. Imputation Methods The LOD, ND SampMin, and LSA algorithms were developed and implemented in-house. The LLS, SVD, BPCA, and PPCA methods were taken from the R package library pcaMethods (accessed on 10 June 2024). The kNN and RF algorithms were derived from the VIM (accessed on 10 June 2024) and missForest libraries (accessed on 10 June 2024), respectively. To test the individual imputation methods and analyze the results, a script in R (v. 4.4.0) was used. For the ND method, the mean value (µ) and standard deviation (σ) were assumed as µ i = µ m − 2.2σ m and σ i = 0.3σ m (where i = values for imputation, m = measured values) based on previous work . For the kNN and LLS methods, the number of nearest neighbors k, also understood as the number of similar proteins, was 6 and 150, respectively. For the RF method, standard parameters (ntree = 100) were used. For the global-similarity methods, the number of principal components (nPCs) was optimized and was set to 4 for the SVD and BPCA, and nPCs = 1 for the PPCA. The study of imputation methods consisted of two stages and the procedure is presented in . In the first, only those proteins for which all the values were correctly determined were listed from the obtained dataset. Missing values were implemented with variously defined ratios of the total MV and MNAR using the algorithm presented by Jin et al. . The MV ratios were 10%, 25%, and 50% and the MNAR ratios were 0%, 20%, 40%, 80%, and 100%, for a total of 15 combinations. The chosen scope of the MV ratios makes it possible to examine the behavior of individual imputation methods with a low, medium, and high share of missing values and to observe the trends with increasing MV. Extreme values of MNAR (0% and 100%) were used to verify the thesis about the effectiveness of left-censored methods for non-random missing values and to indicate the group of methods that performs best in the opposite case. The remaining MNAR ratios (20%, 40%, 80%), similarly to MV, were used to observe the behavior of imputation methods with an increasing share of MNAR, i.e., whether there are certain maxima for imputation accuracy or whether the trend is increasing or decreasing. The case that best reflects the conditions of a real experiment is the ratio MV = 50% and MNAR = 80% , i.e., when about half of the data consist of missing values and missing not at random values dominate in this set. Each combination was replicated 10 times, resulting in a total of 150 test data sets. In order to evaluate the performance of the imputation methods by comparing the imputed values with real data, normalized root mean square error (NRMSE) implemented from the missForest R package was used (accessed on 10 June 2024). NRMSE introduces normalization, making the result independent of the data scale, which facilitates the comparison of different models operating on different datasets and has been used to assess the imputation error in other works . Raw datasets before MV implementation were used to classify proteins as TP or FP using an adjusted p -value at 5%. Then, this classification was performed on each of the imputed datasets and the classification results were compared, which allowed for the plotting of the ROC curve and the calculation of the area under the curve (AUC). In the second stage, imputation by selected methods was carried out on the full datasets, and the evaluation of the imputation methods was based on the number of true-positive results, fold change (FC), and PCA. In this study, the most effective imputation methods identified in individual publications were curated and applied to data derived from a real experimental setting. The dataset originated from a study involving rat brain samples, analyzed in the context of fluorine-containing drug administration. A comprehensive description of the experimental results and the analytical procedures employed in this investigation has been detailed in our prior paper . A proteomics label-free approach was used to prepare and analyze the samples. Firstly, sample preparation was performed, which included protein extraction, reduction, alkylation, and in-solution digestion with tripsin. In the second step, chromatographic separation by liquid chromatography (nano-UHPLC, Thermo Scientific, Bartlesville, OK, USA) and analysis by high-resolution mass spectrometry (MS; Orbitrap; Thermo Scientific, Bartlesville, OK, USA) were used to obtain the data. The experimental workflow for this proteomics approach was also described previously . Analytical grade chemicals and analytical standards were obtained from Merck (Darmstadt, Germany), Promega (Madison, WI, USA), Thermo Scientific (Bartlesville, OK, USA), and EMD Millipore (Darmstadt, Germany). Deionized water from the Milli-Q system (18.2 MΩ cm; EMD Millipore, Darmstadt, Germany) was used for samples and standard dilution. The instrumentation for extraction and sample preparation was as follows: mechanical homogenizer Ultra-Turrax (IKA, Königswinter, Germany), laboratory incubator CLN 240 (MultiSerw, Brzeźnica, Poland), vacuum centrifuge 5804/5804 R (Eppendorf, Enfield, CT, USA), vortex shaker (IKA, Königswinter, Germany), thermomixer Eppendorf Comfort (Eppendorf, Enfield, CT, USA), and vacuum concentrator SpeedVac Concentrator Plus (Eppendorf, Enfield, CT, USA). Reversed-phase capillary nano-UHPLC separations were performed using an UltiMate 3000 nano system (Dionex Ultimate Series UHPLC, Thermo Scientific, Bartlesville, OK, USA) equipped with in-house–packed capillary C-18 column (75 µm × 500 mm, particle size 1.9 µm) coupled on-line with a high-resolution tandem mass spectrometer (Orbitrap Fusion Tribrid™ Mass Spectrometer, Thermo Scientific, Bartlesville, OK, USA). The recorded MS/MS spectra were used to identify the proteins using two different algorithms to compare their possible effects on the performance of the imputation methods. For this purpose, the FragPipe (v. 17.1) and MaxQuant (v. 2.0.3.0) programs were used using the MSFragger and Andromeda algorithms , respectively. The SwissProt database (accessed on 25 March 2022) was searched, with the specified taxonomy Rattus Norvegicus (Taxonomy ID: 10116). Proteins and peptides were identified using a target–decoy approach with a reversed database. As the fixed modification, propionamidation on cysteine (C) was set, which derived from using acrylamide as an alkylating agent. RAW files were used to identify proteins using the MaxQuant program. The mass tolerance was set to ±10.0 ppm for parent ion masses and ±0.6 Da for fragment ion masses. The false discovery rate for PSM and peptides was set at 1%. To perform identification using FragPipe, it was necessary to convert the raw data to the *.mzXML format with the Mass Converter (v. 1.0.3) R package . The precursor and fragment ion mass tolerance was set to ±10.0 ppm and a maximum isotope error option (0/1/2/3) was used. Only the MaxLFQ intensities calculated by both identification programs were used to test the imputation methods, which allowed for an optimal comparison of the obtained results. Additionally, to check the influence of the logarithmization process, an evaluation of the imputation methods was performed before and after the data logarithmization. The LOD, ND SampMin, and LSA algorithms were developed and implemented in-house. The LLS, SVD, BPCA, and PPCA methods were taken from the R package library pcaMethods (accessed on 10 June 2024). The kNN and RF algorithms were derived from the VIM (accessed on 10 June 2024) and missForest libraries (accessed on 10 June 2024), respectively. To test the individual imputation methods and analyze the results, a script in R (v. 4.4.0) was used. For the ND method, the mean value (µ) and standard deviation (σ) were assumed as µ i = µ m − 2.2σ m and σ i = 0.3σ m (where i = values for imputation, m = measured values) based on previous work . For the kNN and LLS methods, the number of nearest neighbors k, also understood as the number of similar proteins, was 6 and 150, respectively. For the RF method, standard parameters (ntree = 100) were used. For the global-similarity methods, the number of principal components (nPCs) was optimized and was set to 4 for the SVD and BPCA, and nPCs = 1 for the PPCA. The study of imputation methods consisted of two stages and the procedure is presented in . In the first, only those proteins for which all the values were correctly determined were listed from the obtained dataset. Missing values were implemented with variously defined ratios of the total MV and MNAR using the algorithm presented by Jin et al. . The MV ratios were 10%, 25%, and 50% and the MNAR ratios were 0%, 20%, 40%, 80%, and 100%, for a total of 15 combinations. The chosen scope of the MV ratios makes it possible to examine the behavior of individual imputation methods with a low, medium, and high share of missing values and to observe the trends with increasing MV. Extreme values of MNAR (0% and 100%) were used to verify the thesis about the effectiveness of left-censored methods for non-random missing values and to indicate the group of methods that performs best in the opposite case. The remaining MNAR ratios (20%, 40%, 80%), similarly to MV, were used to observe the behavior of imputation methods with an increasing share of MNAR, i.e., whether there are certain maxima for imputation accuracy or whether the trend is increasing or decreasing. The case that best reflects the conditions of a real experiment is the ratio MV = 50% and MNAR = 80% , i.e., when about half of the data consist of missing values and missing not at random values dominate in this set. Each combination was replicated 10 times, resulting in a total of 150 test data sets. In order to evaluate the performance of the imputation methods by comparing the imputed values with real data, normalized root mean square error (NRMSE) implemented from the missForest R package was used (accessed on 10 June 2024). NRMSE introduces normalization, making the result independent of the data scale, which facilitates the comparison of different models operating on different datasets and has been used to assess the imputation error in other works . Raw datasets before MV implementation were used to classify proteins as TP or FP using an adjusted p -value at 5%. Then, this classification was performed on each of the imputed datasets and the classification results were compared, which allowed for the plotting of the ROC curve and the calculation of the area under the curve (AUC). In the second stage, imputation by selected methods was carried out on the full datasets, and the evaluation of the imputation methods was based on the number of true-positive results, fold change (FC), and PCA. This study highlights the robustness and versatility of random forest and local least-squares imputation methods, which achieved the highest performance in terms of normalized root mean square error, area under the ROC curve, and the number of proteins accurately classified as true positives. Other methods, including SampMin, k-nearest neighbors, singular value decomposition, and Bayesian principal component analysis, also delivered commendable results, though their efficacy was often context-dependent. These findings underscore the importance of selecting imputation methods tailored to specific dataset characteristics and experimental conditions. Logarithmization emerged as a critical preprocessing step, particularly for global-similarity methods like singular value decomposition, improving data consistency and interpretability without negatively impacting imputation performance. Its consistent utility suggests that log-normalization should be a standard practice before data imputation in proteomics workflows. The study also noted algorithm-specific variability, such as the substantial differences observed in SampMin performance between datasets processed with MaxQuant and FragPipe, emphasizing the need to optimize imputation strategies for specific workflows. From a metrological perspective, the study highlights the critical role of robust imputation methods in ensuring data quality, reliability, and comparability across proteomic studies. Proteomic datasets are inherently prone to variability due to experimental constraints, and missing data further complicates result consistency. Methods like random forest and local least-squares minimize biases and maintain the integrity of quantitative analyses, which is vital for both research and clinical applications. Aligning imputation strategies with quality control standards, such as ISO/IEC 17025:2017 and ISO 15189:2022, enhances the reproducibility and reliability of protein quantification. Logarithmization further supports this goal by stabilizing variance and reducing biases, ensuring consistency in data interpretation. The integration of imputation methods with validated metrological frameworks is crucial for advancing biomarker discovery and diagnostic applications, particularly in clinical settings where data integrity directly impacts outcomes. These findings emphasize the role of optimized imputation strategies in achieving high standards of measurement reliability, fostering the development of robust proteomic workflows. Future research should explore the application of these methods across diverse datasets, including peptide-level analyses, while further integrating metrological frameworks to ensure data quality and comparability. This will advance the use of proteomics in precision medicine and diagnostics, ensuring robust and reliable analytical outcomes. |
A Rare Presentation of Aggressive Renal Cell Carcinoma and the Utility of Early Molecular Testing in Rapidly Progressing Malignancies: A Case Report | bb458050-ee0c-4865-a580-d1744c820357 | 10712707 | Anatomy[mh] | Cancer is the second-leading cause of death in the US, with the American Cancer Society projecting over 600 000 new cancer deaths in 2022. In rapidly progressing malignancies with poor prognoses, an accurate diagnosis is essential when selecting first-line palliative therapies and prolonging survival. Despite advances in diagnostic pathology, modern-day immunohistochemistry (IHC) remains limited, with various cancers exhibiting shared or ambiguous histomorphological properties. IHC alone provides insufficient coverage of genomic variants, which necessitates further molecular profiling to accurately characterize tumors. Among the most comprehensive molecular profiling assays are whole exome sequencing (WES/DNA) and whole transcriptome sequencing (WTS/RNA), which read out the entirety of the expressed human genome within a cell. In a study of 200 patients with cancer of unknown primary (CUP), Ross et. al found that 96% of cases had an actionable mutation detected via comprehensive genomic profiling, and 85% of these were determined to be an alteration that could potentially guide decisions for targeted treatment. Here, we present a fulminant case of clear cell renal cell carcinoma (ccRCC) with an atypical pattern of presentation, highlighting the importance of pursuing early whole exome and transcriptome sequencing in the setting of rapidly advancing cancers with complex diagnoses.
A 43-year-old man with no relevant medical history, who did not smoke and worked in insurance, presented to his local emergency department with cough and shortness of breath. He had been diagnosed with a diffuse bilateral pneumonia 1 week prior and was symptomatically worsening despite cefpodoxime, azithromycin, and prednisone. In the preceding weeks, he reported decreased appetite and oral intake, mild sinusitis, left lower extremity swelling, and purple discoloration of 2 toes. Upon presentation to the emergency department, he was hypertensive (145/94), tachycardic (118 bpm), tachypneic (est. 20-25 breaths per minute), and hypoxic requiring supplemental oxygen (91% on 2 L, improved on 4 L). Laboratory testing was notable for hyponatremia (125 mmol/L), hypoalbuminemia (2.9 g/L), thrombocytopenia (121 10 9 /L), mild leukocytosis (11.3 K/µL), and hyperglycemia (314 mg/dL). His liver function tests and creatinine were within normal limits, and viral testing, including influenza and SARS-CoV-2, was negative. An initial chest x-ray showed worsening bilateral pneumonia and pleural effusion but could not rule out an underlying mass. Fluid from a subsequent thoracentesis demonstrated atypical epithelioid cells. Most notably, radiologic workup (CT) revealed a 4.7 × 4.7 cm mass in the lower pole of the right kidney ( and ), which was entirely asymptomatic, along with enlarged retroperitoneal and mesenteric lymph nodes and masses in infracarinal and hilar lymph nodes, suspicious for metastases. A biopsy of a left retroperitoneal lymph node stained with synaptophysin (weakly), CD56, CAM 5.2, MNF 116, and MITF, and no significant staining was appreciated with chromogranin, HMB-45, S-100, Sox 10, cytokeratin AE1/AE3, CD3, CD20, PAX5, CD30, neurofilament, and CD15. Following interdepartmental consultation, although a ganglioneuroma was considered, the staining pattern, especially in the presence of a renal mass, seemed most consistent with epithelioid angiomyolipoma (eAML). A thoracentesis was performed for therapeutic and additional diagnostic purposes; however, cytology proved inconclusive. A consulting urologist noted that portions of the asymptomatic kidney mass likely contained fat cells, which would be consistent with angiomyolipoma, yet admitted that the diagnosis was “unusual.” In approximately 3 weeks at his local hospital, his hypoxia progressively worsened, eventually requiring high-flow oxygen. Imaging demonstrated that the long axis of the renal mass had grown to 6 cm ( and ), and several of his lymphatic metastases had enlarged. Given the aggressive nature of his cancer and the complexity surrounding the diagnostic process, he was transferred to a large academic hospital for further workup and management. He was admitted with worsening thrombocytopenia (85 × 10 9 /L) and hypoxia requiring high flow oxygen up to 10 L. He was treated for a pulmonary infection with a broad-spectrum antibiotic regimen, including IV cefepime, IV vancomycin, oral azithromycin, and oral metronidazole. On the third day after his transfer, he suffered cardiac arrest, attributed to respiratory causes, from which he was resuscitated and subsequently intubated. With his clinical status worsening, the decision was made on the third day post-transfer to commence urgent systemic anticancer therapy; he was started on temsirolimus, an mTOR inhibitor, as first-line therapy for presumed metastatic eAML. Concurrently, the antibiotic regimen was narrowed to IV ceftriaxone when sputum culture resulted positive for Klebsiella Pneumoniae . Ceftriaxone was continued until completion of the course on day 8 post-transfer. On day 5 post-transfer, a 4R lymph node was biopsied to confirm the diagnosis and identify genomic signatures for potential targeted therapy if mTOR inhibition proved inadequate. Tissue samples were sent to the pathology department for diagnosis and externally for whole exome and whole transcriptome sequencing. In the following days, while tumor analysis was pending, he began to clinically decline, with his ventilation settings and thrombocytopenia worsening. Ultimately, 10 days after transfer, due to worsening clinical status, his goals of care were shifted to comfort measures only, and he was soon extubated. He died 1 month after his initial cancer diagnosis and underwent an autopsy the following morning. The 4R lymph node pathology report, finalized after the patient’s passing, demonstrated a metastatic malignant epithelioid neoplasm with rhabdoid morphology; however, definitive classification of the tumor was deferred to autopsy. Meanwhile, the external molecular profiling report on the same sample resulted 12 days after the biopsy and 8 days post-mortem. Although the sample was collected and sent for sequencing with clinical intent, the patient had previously been consented via his healthcare proxy to IRB-approved protocol #13-416, under which the case could be carried to completion post-mortem for research purposes. The microscopic diagnosis was a malignant epithelioid neoplasm with clear cell and rhabdoid features, and molecular testing revealed pathogenic variants in BAP1 and VHL, resulting in a post-mortem diagnosis of metastatic clear cell renal cell carcinoma (mccRCC) . Post-mortem analysis confirmed these findings. Although partially necrotic, the renal mass and extensive metastases involving the retroperitoneum, thorax, and abdominal cavity were noted to have tumor cells with clear cytoplasm. The renal and lung blocks were positive for EMA and CA-IX. A cytology sample from his 4R lymph node biopsy was also reviewed at this time, from which lesional cells were positive for CA-IX and PAX8, with retained expression of FH and SDHB . These results were most consistent with mccRCC with rhabdoid differentiation. His cause of death was confirmed to be mccRCC, which included lung metastases up to 1.2 cm, complicated by acute pneumonia.
Remarkably, the autopsy results provided a definitive diagnosis and categorically resolved the discrepancy between ccRCC and eAML. Unfortunately, the definitive diagnosis resulted after the patient’s death. Given the extensive, aggressive nature of his disease, rhabdoid differentiation, and persistent pneumonia-related complications despite appropriate antibiotic coverage, his clinical decline may have been unavoidable regardless of therapeutic intervention. However, given that his cancer not only directly caused fatal respiratory failure but also may have inhibited his ability to clear a likely hospital-acquired pulmonary infection, it bears asking how his clinical course may have been different had he had a clear diagnosis and received optimal systemic therapy weeks earlier. Numerous studies have described the histologic and radiologic similarities between RCC and eAML, yet the management of these 2 cancers differs. While there is no consensus standard-of-care treatment for eAML, , it has been reported that abnormal activation of the mTOR pathway may contribute to renal eAML growth and progression, and there have been reports of sustained responses to mTOR inhibition in angiomyolipomas. , By contrast, although mTOR inhibitors are approved in RCC, they have limited activity, with an objective response rate (ORR) of 8.6%, median progression-free survival (PFS) of 3.8 months, and a modest overall survival (OS) benefit of 3.6 months (median OS 10.9 months) with first-line temsirolimus in patients with poor prognosis. In recent years, mTOR inhibition has been replaced by immune checkpoint inhibitors (ICI) or combination ICI and tyrosine kinase inhibitors (TKI) as first-line therapy for advanced RCC. Patients with mccRCC tend to respond significantly better to ICI/TKI combinations, with an ORR as high as 71%, a complete response rate as high as 16.1%, and a median PFS of 23.9 months with Pembrolizumab and Lenvatinib , What if molecular profiling had been performed at the time of the first biopsy? This patient’s diagnosis was, at minimum, complex. The initial biopsy required interdepartmental consultation, a consulting urologist admitted the diagnosis to be “unusual,” and the presumed diagnosis was a cancer known to “mimic” another. , Identifying molecular signatures was the key to confirming the diagnosis and selecting the most appropriate first-line therapy, and advanced molecular testing has demonstrated remarkable efficacy in predicting primary tumor of origin in CUP samples, with validation studies showing efficacy ranging from 75.7% (Zhao et al) to 94% (Abraham et al) to 98% accurate (Hainsworth et al). In addition, Ross et al (85% of 200 patients) and Cobain et al (80.5% of 1015) have found clinically relevant, potentially actionable mutations via molecular profiling in the vast majority of CUP patients. When the 4R lymph node biopsy was performed, WES/WTS was finalized in 12 days. Had this been sought from the initial biopsy, the BAP1 and VHL mutations, nearly pathognomonic for RCC in the setting of a kidney mass, would have been discovered weeks earlier. Post-mortem analysis revealing PAX8 and CA-IX may have confirmed the RCC diagnosis, , but molecular profiling identified markers that led to the same diagnosis in less than 2 weeks. This also underscores the imperative for future quality improvement efforts to reduce the turnaround time for genomic sequencing, as such cases necessitate results as quickly as possible. For this patient, rapid, precise diagnosis of mccRCC would likely have been quickly followed by the commencement of ICI/TKI combination, which, in mccRCC, has an objective response rate that is 8 to 9 times higher, and a median progression-free survival that is over 6 times longer than temsirolimus. , In addition, treatment would have commenced while he carried a lower tumor burden and a more stable hemodynamic and respiratory status. The potential impact of therapy would have been considerably higher. The stakes are now higher to get early and accurate diagnoses, as pursuing comprehensive molecular-based genomic testing has been shown to expand therapeutic options for patients with metastatic cancer, , including those in clinical trials. Although comprehensive sequencing is still relatively new, evidence demonstrates that there may be trends toward better survival, and future research is needed to more definitively quantify this effect. Genomic testing is not without its limitations. Whole exome and transcriptome sequencing does require more tissue than IHC alone, so having sufficient tumor is essential and may require additional cores to be taken at the time of biopsy. Although companies provide supplemental information regarding standard of care options and available clinical trials associated with biomarkers in their reports, it can be challenging to interpret complex genomic data and discern the difference between driver and passenger mutations. In addition, a single tumor site, which is often all that can be sampled during a routine core biopsy, may not capture the full complexity and heterogenous nature of the entire genomic landscape of a metastatic malignancy. However, outside the setting of autopsy, it is not feasible to sample every tumor in a widely metastatic cancer, so further investigation is needed to aid in selection of the most appropriate biopsy sites for comprehensive sequencing, or in non-invasive liquid biopsy options. Cost and access to sequencing also merits discussion. In 2018, it was estimated that the price range for a single whole exome test fell between $555 and $5,169. Genomic testing panels are becoming increasingly utilized, with multiple commercially available platforms appearing on the market. It has been shown that a substantial number of patients with undiagnosed diseases and financial barriers to WES have actionable molecular diagnoses, underscoring the need for both expanded insurance coverage and the utilization of patient-assistance programs to increase access. In addition, advocacy efforts should be targeted at expanding access to WES/WTS to the most vulnerable and underserved communities. The cost-effectiveness of implementing next generation sequencing on a larger scale reveals limited, mixed evidence and remains an active of research; investigations have focused on specific populations ranging from treatment refractory cancers to the screening of healthy individuals. A study from Tan et al did find that the early use of more comprehensive genomic sequencing has been shown to be a potentially cost-effective option when compared to sequential testing in lung cancer patients in Asia. However, no study has yet analyzed the cost-effectiveness of early molecular profiling on patient outcomes among those with aggressive cancer, ambiguous diagnoses, and atypical clinical presentations, and this patient’s case demonstrates that there is, at minimum, a subset of patients who may derive significant clinical benefit from its utilization.
This patient’s diagnosis was, at minimum, complex. The initial biopsy required interdepartmental consultation, a consulting urologist admitted the diagnosis to be “unusual,” and the presumed diagnosis was a cancer known to “mimic” another. , Identifying molecular signatures was the key to confirming the diagnosis and selecting the most appropriate first-line therapy, and advanced molecular testing has demonstrated remarkable efficacy in predicting primary tumor of origin in CUP samples, with validation studies showing efficacy ranging from 75.7% (Zhao et al) to 94% (Abraham et al) to 98% accurate (Hainsworth et al). In addition, Ross et al (85% of 200 patients) and Cobain et al (80.5% of 1015) have found clinically relevant, potentially actionable mutations via molecular profiling in the vast majority of CUP patients. When the 4R lymph node biopsy was performed, WES/WTS was finalized in 12 days. Had this been sought from the initial biopsy, the BAP1 and VHL mutations, nearly pathognomonic for RCC in the setting of a kidney mass, would have been discovered weeks earlier. Post-mortem analysis revealing PAX8 and CA-IX may have confirmed the RCC diagnosis, , but molecular profiling identified markers that led to the same diagnosis in less than 2 weeks. This also underscores the imperative for future quality improvement efforts to reduce the turnaround time for genomic sequencing, as such cases necessitate results as quickly as possible. For this patient, rapid, precise diagnosis of mccRCC would likely have been quickly followed by the commencement of ICI/TKI combination, which, in mccRCC, has an objective response rate that is 8 to 9 times higher, and a median progression-free survival that is over 6 times longer than temsirolimus. , In addition, treatment would have commenced while he carried a lower tumor burden and a more stable hemodynamic and respiratory status. The potential impact of therapy would have been considerably higher. The stakes are now higher to get early and accurate diagnoses, as pursuing comprehensive molecular-based genomic testing has been shown to expand therapeutic options for patients with metastatic cancer, , including those in clinical trials. Although comprehensive sequencing is still relatively new, evidence demonstrates that there may be trends toward better survival, and future research is needed to more definitively quantify this effect. Genomic testing is not without its limitations. Whole exome and transcriptome sequencing does require more tissue than IHC alone, so having sufficient tumor is essential and may require additional cores to be taken at the time of biopsy. Although companies provide supplemental information regarding standard of care options and available clinical trials associated with biomarkers in their reports, it can be challenging to interpret complex genomic data and discern the difference between driver and passenger mutations. In addition, a single tumor site, which is often all that can be sampled during a routine core biopsy, may not capture the full complexity and heterogenous nature of the entire genomic landscape of a metastatic malignancy. However, outside the setting of autopsy, it is not feasible to sample every tumor in a widely metastatic cancer, so further investigation is needed to aid in selection of the most appropriate biopsy sites for comprehensive sequencing, or in non-invasive liquid biopsy options. Cost and access to sequencing also merits discussion. In 2018, it was estimated that the price range for a single whole exome test fell between $555 and $5,169. Genomic testing panels are becoming increasingly utilized, with multiple commercially available platforms appearing on the market. It has been shown that a substantial number of patients with undiagnosed diseases and financial barriers to WES have actionable molecular diagnoses, underscoring the need for both expanded insurance coverage and the utilization of patient-assistance programs to increase access. In addition, advocacy efforts should be targeted at expanding access to WES/WTS to the most vulnerable and underserved communities. The cost-effectiveness of implementing next generation sequencing on a larger scale reveals limited, mixed evidence and remains an active of research; investigations have focused on specific populations ranging from treatment refractory cancers to the screening of healthy individuals. A study from Tan et al did find that the early use of more comprehensive genomic sequencing has been shown to be a potentially cost-effective option when compared to sequential testing in lung cancer patients in Asia. However, no study has yet analyzed the cost-effectiveness of early molecular profiling on patient outcomes among those with aggressive cancer, ambiguous diagnoses, and atypical clinical presentations, and this patient’s case demonstrates that there is, at minimum, a subset of patients who may derive significant clinical benefit from its utilization.
In cases of rapidly progressing malignancies, unknown or unclear diagnoses, or both, pursuing comprehensive, molecular-based genomic sequencing as early as possible in the patient’s disease course may be essential to selecting the therapy that provides the best opportunity for clinical benefit.
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Utility and limitations of exome sequencing as a genetic diagnostic tool for children with hearing loss | e9503b41-ad1d-4200-9c44-e3c64a88d871 | 6295269 | Pathology[mh] | Hearing loss (HL) affects nearly 1 in 500 infants. , More than half of the cases of congenital or early-onset bilateral sensorineural HL (BLSNHL) have a genetic cause, the remainder being either acquired or idiopathic. , Genetic etiologies can be further divided into isolated (nonsyndromic) HL or HL associated with dysmorphisms and/or additional medical problems (syndromic). Nonsyndromic HL comprises about 70% of genetic cases. With the recognition that early detection and diagnosis of HL improves health outcomes, hearing screenings have been implemented in the newborn period . However, molecular diagnostic ascertainment of the underlying cause to help guide counseling and management remains challenging. One of the challenges of molecular diagnostics for HL is the high Degree of genetic heterogeneity; approximately 1% (~250) of human genes are necessary for a functional auditory system. Over 70 genes are implicated in isolated BLSNHL, for which phenotypic clues are limited to the type and severity of HL without additional nonaudiological features to help guide a molecular workup. Syndromic cases can be just as challenging to diagnose, as neonates may not yet have developed additional clinical features to guide molecular diagnostics. Moreover, variants in genes known to cause syndromic HL have been identified in patients with nonsyndromic HL. Due to the high degree of genetic heterogeneity and phenotypic overlap, HL is well suited to the strengths of “next-generation sequencing” (NGS). NGS is the basis for a collection of clinical tests that allow rapid sequencing of genomic material using a common method. Multiple genes associated with a specific diagnosis may be targeted in “gene panels”, and with “exome sequencing” (ES) all protein-coding exons can be targeted. The increased scope of ES leads to additional challenges, including increased cost, lengthy turnaround time, analytic burden of variants of uncertain significance (VUSs) and identification of secondary findings unrelated to HL. ES covers a much larger portion of the genome than targeted panels. It allows for reanalysis of data for genes newly associated with HL that were not known initially. However, the coverage over any given set of genes may be inconsistent. ES was initially used in the research setting to identify new HL genes (reviewed in ), and now gene panels are the molecular diagnostic gold standard for HL if the etiology remains unknown after evaluation (history, physical examination, and testing for cytomegalovirus if appropriate). Diagnostic rates for these panels range from 16 to 42%, with greater success in nonsyndromic cases. – Targeted analysis of the exome to analyze 120 genes—a similar size to current HL panels—identified causative variants in 33.5% of patients. The strength of NGS genetic testing and potentially ES in contributing to the management and diagnostic yield for HL has led to recent recommendations for a “genetics-first” approach to the etiologic workup. We examined the efficacy of ES as a diagnostic tool in HL by evaluating the diagnostic yield in an expanded list of 247 genes associated with HL, and the capture and coverage across a broad spectrum of HL loci. We present clinical vignettes to highlight the strengths and limitations of this approach.
The Institutional Review Board at the Children’s Hospital of Philadelphia (CHOP) approved the Pediatric Sequencing (PediSeq) Project at the CHOP—part of the National Human Genome Research Institute Clinical Sequencing Exploratory Research Consortium. In total, 191 patients were enrolled and provided informed consent for research ES. Of these individuals, 43 had HL (the majority had BLSNHL). Individual patient information was de-identified. Patients with HL were recruited to the PediSeq project from the Genetics of Hearing Loss Clinic at the CHOP (Table ). Clinical information was based on the clinical documentation. The primary focus of the study was on BLSNHL, but a small number of probands with other forms of HL were also enrolled if a genetic etiology was suspected. Clinical testing (if approved by insurance) was performed in parallel to research exome. About one-quarter of the patients (27.9%) were diagnosed with congenital HL and another quarter (23.3%) were diagnosed with prelingual HL (defined as being identified at less than or equal to 1 year of age). The remainder had postlingual HL (defined as being identified after 1 year of age). Although there were a few cases of syndromic HL (9.3%), the majority of cases (90.7%) were nonsyndromic. Sensorineural HL (SNHL) was the major type (83.7%). There was one case of conductive HL (2.3%) and six cases of mixed (sensorineural and conductive) HL (14%). Two patients had unilateral HL (4.7%), while the majority had bilateral HL (95.3%). Almost half the patients had a family history of HL (46.5%) and approximately half did not (48.8%), although two patients (4.7%) were unsure whether there was a family history of HL. The demographics of the patient population are provided in Table . In parallel with research ES, 32 of 43 patients (74.4%) had gene panel and/or copy-number variant (CNV) analysis performed (Table ). Four of 43 patients (9.3%) had the HL panel available at the CHOP (Sanger sequencing of GJB2 (exons 1 and 2), GJB6 (deletion region), MTRNR1 (entire gene), and SLC26A4 (exons 6, 9, 10, and 19)). Nineteen of 43 patients (44.2%) had GJB2 sequencing with reflex testing on OtoGenome version 1 or 2 (71 or 70 genes, respectively; Partners HealthCare, Boston, MA). Five of 43 patients (11.6%) had targeted or single-gene testing performed, including single-gene tests for EYA1 , SIX1 , SHOX , and PAX3 , as well as Waardenburg syndrome and Usher Syndrome panel testing. One patient (2.3%) had clinical ES. Twenty-four of 43 patients (55.8%) had a chromosomal microarray. Multiple patients had more than one test sent. Other clinical tests included fragile X testing and distal motor neuropathy gene panel testing. Fragile X testing was excluded from the analysis as this has not been associated with HL. Peripheral blood was collected from patients and stored immediately at 4 °C. Genomic DNA was extracted manually by standard procedures using the Gentra Puregene Blood Kit Plus (158489; Qiagen, Germantown, MD) and 3–6 μg was used for further analysis. Exome capture was performed using the SureSelect version 4 capture kit (Agilent, Santa Clara, CA) and 100-base pair paired-end sequencing was performed on HiSeq 2500 sequencers (Illumina, San Diego, CA) at the Bejing Genomics Institute at the CHOP sequencing facility. The average depth of coverage was 100×. Sequencing reads were generated in FASTQ format and analyzed using the PediSeq ES pipeline. Sequences were mapped to human genome assembly GRCh37.p10. Novoalign (version 3.00.02; www.novocraft.com ) was used for optimal alignment. The GATK Variant Filtration tool was used to filter reads with low quality and strand bias. The GATK Depth of Coverage tool (version 2.2) was used to obtain capture and coverage statistics of exons and genomic positions. Quality control steps during variant calling included minBaseQuality 20/minMappingQuality 20 settings and exclusion of variants with a depth of coverage of fewer than 10 reads. CNVs were identified using the R package ExomeDepth. Each sample was compared with the entire PediSeq cohort. An average of 79 CNVs per individual were identified. Rare variants were filtered by comparing their frequency against the frequency within our internal cohort and the Database of Genomic Variants. Ten validation samples with previously identified causative HL pathogenic variants (PV), including three CNVs, were run through the pipeline blinded. Each of these diagnoses was captured and identified on ES (Supplementary Table ). A list of 247 genes related to HL was manually curated using information from the Gene List Automatically Derived For You gene list generator using the terms “hearing loss” and “deafness” and previously established HL gene panels (listed at genetests.org ) (Supplementary Table ). From reports in the literature, 72 genes had nonsyndromic presentations, 154 had syndromic phenotypes and 21 had syndromic and nonsyndromic phenotypes. This gene list was used as a primary filter to examine capture by the Agilent SureSelect version 4 kit and coverage of HL-associated genes. Exon coverage was defined by the percentage of the bases in the exon covered at 20× sequencing depth. Previous work suggested that 8× and 13× are the minimums for calling homozygous and heterozygous variants, respectively. At a level of 20× coverage, there is enough power to detect heterozygous variants with at least a 20% variant allele frequency. Some 14,598 variants were associated with the 247 HL genes in the Human Gene Mutation Database (HGMD)—a collection of genetic variants associated with human disease. For each gene, up to two variants within exon boundaries were randomly selected for coverage analysis using our ES platform. These variants were then manually curated to ensure each variant had been reported with a HL phenotype (as not all annotated variants in the HGMD may be truly associated with disease ), yielding 454 variants selected for capture and coverage analysis (Supplementary Table ). For primary analysis, variants were generated from the 247 genes in our HL gene list using the Exome Aggregation Consortium database (minor allele frequency (MAF) <0.05) and our internal cohort (MAF <5%) as filters. Variants were not limited to HGMD variants. Variants were analyzed according to American College of Medical Genetics and Genomics standards. Exome analysts were blinded to the clinical test results. The rare variants were manually assigned a pathogenicity call (benign, likely benign, VUS, likely pathogenic, or pathogenic). Similarly, for secondary findings, the variants were generated using the same filters (Exome Aggregation Consortium: MAF <0.05%; internal cohort: MAF <5%) from a set of 2,956 medically actionable genes developed from the Online Mendelian Inheritance in Man compendium, genetests.org and the HGMD. All rare missense variants were then filtered against the HGMD database, and only those reported in the HGMD were analyzed to determine pathogenicity. Frameshift, insertions/deletions, splice-site and nonsense variants were analyzed irrespective of whether or not they were reported in the HGMD. We categorized the results into immediately medically actionable, childhood- or adult-onset medically actionable, and carrier status. For the carrier status, we interpreted similar rare variants within 185 autosomal recessive disorder genes. Secondary findings were analyzed for all patients, although 7 of 43 probands (16.3%) opted out of specific secondary findings (Table ). A clinical laboratory director certified by the American Board of Medical Genetics and Genomics confirmed all variant calls. Parental studies were performed as required to verify inheritance. Clinical Sanger sequencing confirmed the variants identified by ES before the results were returned to the patient. After the initial analysis, we reviewed the literature and attempted to expand the gene list. No new pathogenic findings were reportable after re-running the samples. There were VUS in genes of limited clinical validity, which did not meet our reportable criteria. At the time of revision, updated clinical ES identified a likely pathogenic variant in AMMECR1 , which was not included in this analysis.
A genetic diagnosis for HL was identified in 17 of 43 probands (39.5%), with research ES identifying a diagnosis in 16 of 43 probands (37.2%) (Tables and ). CNVs were identified in three patients, although none definitively contributed to the patient's HL. One patient had a deletion on chr1q24.2 containing SLC19A2 , which causes autosomal recessive thiamine-responsive megaloblastic anemia syndrome, progressive SNHL, and diabetes mellitus, but sequencing of the other allele was normal. Another patient had a deletion on chr15q13.1, although this was also present in the patient’s son who did not have HL. The third patient had a small duplication on 22q11.2, which was called as a VUS. Three of 19 patients (15.8%) received a diagnosis by GJB2 sequencing with reflex testing on the OtoGenome panel. Neither the four patients with the CHOP HL panel nor the five patients with targeted testing received a genetic diagnosis through clinical testing. For the 17 diagnosed cases, the inheritance pattern was recessive for 11 cases (64.7%), dominant for 5 cases (29.4%), and X-linked for 1 case (5.9%) (Table ). Of the 11 recessive cases, 5 (29.4%) were homozygous and 6 (35.3%) were compound heterozygotes. Of the 5 dominant cases, 3 (17.6%) were inherited dominant PV and 2 (11.8%) were de novo dominant PV. ES did not identify a primary diagnosis for 26 out of 43 probands (60.5%). The majority of families in this cohort chose to be notified of secondary findings (Tables and ). Two probands (4.7%) had immediately medically actionable secondary findings in 3 genes associated with familial hypercholesterolemia, hypertrophic cardiomyopathy, and retinitis pigmentosa. One proband (2.3%) had an adult-onset medically actionable secondary finding in a gene associated with hereditary breast and ovarian cancer. Carrier status was identified in 27 patients (63%) during analysis for secondary findings. To further examine the diagnostic capabilities of ES for HL, capture and coverage analysis was performed for the 247 pathogenic HL genes (4,421 exons; Fig. ) and 454 variants (Fig. ), as described in the “Materials, patients and methods” section. The capture kit used for ES targeted 94.7% of the exons of the 247 HL genes and 89% of these variants for capture. Coverage of an exon was defined as at least 20×. In total, 81.7% of the captured exons had coverage over the entire exon. For 3.8% of captured exons, 90 to <100% coverage of the exon was seen. For 4.1% of captured exons, 70 to <90% coverage of the exon was seen. For 4.3% of captured exons, 40 to <70% coverage of the exon was seen. For 6.1% of captured exons, <40% coverage of the exon was seen. In total, 75.0% of variants were fully covered (defined as at least 20×), 17.6% had 10 to <20× coverage, 6.4% had 1 to <10× coverage, and the remainder had <1× coverage. The exons and variants that did not have at least 20× coverage in 50% of samples are identified in Supplementary Tables and . We assessed the capture and coverage by ES for three specific genes associated with HL: GJB2 , OTOA , and STRC (Fig. ) . GJB2 is the most common molecular cause of HL. OTOA and STRC were selected as they both have highly homologous pseudogenes that complicate molecular diagnostics. One out of two GJB2 exons was targeted for capture, and the targeted exon had poor coverage. For 3 differentially spliced OTOA transcripts, 70% of the 30 exons were targeted for capture. Experimentally, 70% of the OTOA exons had at least 90% of the sequence covered at 20×, while about 30% of the OTOA exons had less than 40% coverage at 20×. For STRC , 7 of 29 exons (24.1%) were targeted for capture. Of these exons, 13% were well covered (>90 to <100% at 20×), 3% were mostly covered (>70 to 90% at 20×), and the majority (83%) were not covered (<40% coverage at 20×). Illustrative case examples BRCA1 variant as an example of a medically actionable secondary finding A 4-month-old girl with history of nasolacrimal duct obstruction presented after failing her newborn hearing screen. Family history, including her three older siblings, was negative for HL but significant for a paternal aunt with ovarian cancer. Both research ES and clinical GJB2 sequencing identified homozygous PV in GJB2 (c.35delG; p.G12fs). ES also discovered a pathogenic variant (c.5503C>T; p.R1835*) in BRCA1 —a well-known tumor suppressor associated with autosomal dominant hereditary breast and ovarian cancer. This case demonstrates the importance of secondary findings from ES. This patient has a significantly increased cancer risk, and it is likely that other family members do as well. These results were returned with genetic counseling and the family was scheduled for follow-up in a cancer genetics clinic. ES identifies molecular etiology before clinical features are available to guide diagnostic testing A six-day-old boy was evaluated for dysmorphic features and mild to moderate BLSNHL, which was diagnosed after a failed newborn hearing screen. Physical examination revealed three fontanels, a sacral dimple, telecanthus, posteriorly rotated ears, and head lag. The family history was negative for both HL and dysmorphic features, including a healthy older brother. Given the combination of telecanthus and HL, targeted PAX3 gene testing to evaluate for Waardenburg syndrome type I and chromosomal microarray was requested. Both tests returned normal results. Research ES identified two PV in the PEX1 gene, consistent with Zellweger syndrome—a peroxisomal biogenesis disorder. Over the next few months, additional features of peroxisomal biogenesis disorders became evident, such as hypotonia, severe developmental delay, abnormal eye movements, and tapetoretinal degeneration identified by magnetic resonance imaging. A five-week-old newborn female presented for small size and conductive HL. Physical examination was notable for growth in the fifth to tenth percentile, a thin upper lip, and prominent maxilla. At 28 months, she had delayed expressive and receptive language and mild behavioral problems. Family history, including her two siblings, was negative for any hearing impairment or developmental delays. The results of a chromosomal microarray were normal. ES performed through the PediSeq research study identified a de novo frameshift variant in the EFTUD2 gene (c.764dup; p.Cys256Valfs*6) associated with autosomal dominant mandibulofacial dysostosis with microcephaly, which is associated with conductive HL and characteristic facial features. Although variants in PEX1 and EFTUD2 result in syndromic HL, these genes are not present on any HL gene panels in the United States. In both cases, ES was essential for early diagnosis before the additional syndromic features were present. ES identifies a diagnosis not present on standard clinical testing A 2-year-old male presented with language delay and progressive moderate to profound BLSNHL, necessitating hearing aids. The proband had three brothers with normal hearing. His mother had congenital progressive unilateral SNHL, also necessitating a hearing aid. The maternal grandfather had BLSNHL. The patient was consented for research ES in the PediSeq study while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel, Waardenburg syndrome testing, and chromosomal microarray analysis were requested. OtoGenome and research ES revealed three VUSs (one missense heterozygous variant each in DFNB31 , MYO15A, and USH2A ). Chromosomal microarray and Waardenburg syndrome testing returned normal results. ES also identified a maternally inherited pathogenic variant in the SMPX gene (c.133-1G>A). PV in SMPX cause X-linked dominant nonsyndromic HL, characterized by SNHL starting in the first decade of life for males. – This explains the family history of unilateral HL in the mother and BLSNHL in the grandfather, as the onset and severity of the condition are more variable for females. In this case, ES identified the genetic etiology, as the OtoGenome panel did not include SMPX . Clinical testing, but not ES, provides the diagnosis An 11-year-old female presented with mild to moderately severe BLSNHL. The proband had no family history of HL. The patient was consented for research ES while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel were requested. Research ES identified a single pathogenic variant in the GJB2 gene (c.71G>A; p.W24*). Clinical testing identified the same GJB2 pathogenic variant as ES and an additional pathogenic variant present in intron 1 (noncoding) of the GJB2 gene (c.-23+1G>A). This intronic variant was not identified using ES because the intron was not targeted by the capture kit. This case demonstrates a potential limitation of ES as a diagnostic tool, and the importance of carefully examining the coverage of any genes associated with the phenotype being evaluated.
BRCA1 variant as an example of a medically actionable secondary finding A 4-month-old girl with history of nasolacrimal duct obstruction presented after failing her newborn hearing screen. Family history, including her three older siblings, was negative for HL but significant for a paternal aunt with ovarian cancer. Both research ES and clinical GJB2 sequencing identified homozygous PV in GJB2 (c.35delG; p.G12fs). ES also discovered a pathogenic variant (c.5503C>T; p.R1835*) in BRCA1 —a well-known tumor suppressor associated with autosomal dominant hereditary breast and ovarian cancer. This case demonstrates the importance of secondary findings from ES. This patient has a significantly increased cancer risk, and it is likely that other family members do as well. These results were returned with genetic counseling and the family was scheduled for follow-up in a cancer genetics clinic. ES identifies molecular etiology before clinical features are available to guide diagnostic testing A six-day-old boy was evaluated for dysmorphic features and mild to moderate BLSNHL, which was diagnosed after a failed newborn hearing screen. Physical examination revealed three fontanels, a sacral dimple, telecanthus, posteriorly rotated ears, and head lag. The family history was negative for both HL and dysmorphic features, including a healthy older brother. Given the combination of telecanthus and HL, targeted PAX3 gene testing to evaluate for Waardenburg syndrome type I and chromosomal microarray was requested. Both tests returned normal results. Research ES identified two PV in the PEX1 gene, consistent with Zellweger syndrome—a peroxisomal biogenesis disorder. Over the next few months, additional features of peroxisomal biogenesis disorders became evident, such as hypotonia, severe developmental delay, abnormal eye movements, and tapetoretinal degeneration identified by magnetic resonance imaging. A five-week-old newborn female presented for small size and conductive HL. Physical examination was notable for growth in the fifth to tenth percentile, a thin upper lip, and prominent maxilla. At 28 months, she had delayed expressive and receptive language and mild behavioral problems. Family history, including her two siblings, was negative for any hearing impairment or developmental delays. The results of a chromosomal microarray were normal. ES performed through the PediSeq research study identified a de novo frameshift variant in the EFTUD2 gene (c.764dup; p.Cys256Valfs*6) associated with autosomal dominant mandibulofacial dysostosis with microcephaly, which is associated with conductive HL and characteristic facial features. Although variants in PEX1 and EFTUD2 result in syndromic HL, these genes are not present on any HL gene panels in the United States. In both cases, ES was essential for early diagnosis before the additional syndromic features were present. ES identifies a diagnosis not present on standard clinical testing A 2-year-old male presented with language delay and progressive moderate to profound BLSNHL, necessitating hearing aids. The proband had three brothers with normal hearing. His mother had congenital progressive unilateral SNHL, also necessitating a hearing aid. The maternal grandfather had BLSNHL. The patient was consented for research ES in the PediSeq study while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel, Waardenburg syndrome testing, and chromosomal microarray analysis were requested. OtoGenome and research ES revealed three VUSs (one missense heterozygous variant each in DFNB31 , MYO15A, and USH2A ). Chromosomal microarray and Waardenburg syndrome testing returned normal results. ES also identified a maternally inherited pathogenic variant in the SMPX gene (c.133-1G>A). PV in SMPX cause X-linked dominant nonsyndromic HL, characterized by SNHL starting in the first decade of life for males. – This explains the family history of unilateral HL in the mother and BLSNHL in the grandfather, as the onset and severity of the condition are more variable for females. In this case, ES identified the genetic etiology, as the OtoGenome panel did not include SMPX . Clinical testing, but not ES, provides the diagnosis An 11-year-old female presented with mild to moderately severe BLSNHL. The proband had no family history of HL. The patient was consented for research ES while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel were requested. Research ES identified a single pathogenic variant in the GJB2 gene (c.71G>A; p.W24*). Clinical testing identified the same GJB2 pathogenic variant as ES and an additional pathogenic variant present in intron 1 (noncoding) of the GJB2 gene (c.-23+1G>A). This intronic variant was not identified using ES because the intron was not targeted by the capture kit. This case demonstrates a potential limitation of ES as a diagnostic tool, and the importance of carefully examining the coverage of any genes associated with the phenotype being evaluated.
variant as an example of a medically actionable secondary finding A 4-month-old girl with history of nasolacrimal duct obstruction presented after failing her newborn hearing screen. Family history, including her three older siblings, was negative for HL but significant for a paternal aunt with ovarian cancer. Both research ES and clinical GJB2 sequencing identified homozygous PV in GJB2 (c.35delG; p.G12fs). ES also discovered a pathogenic variant (c.5503C>T; p.R1835*) in BRCA1 —a well-known tumor suppressor associated with autosomal dominant hereditary breast and ovarian cancer. This case demonstrates the importance of secondary findings from ES. This patient has a significantly increased cancer risk, and it is likely that other family members do as well. These results were returned with genetic counseling and the family was scheduled for follow-up in a cancer genetics clinic.
A six-day-old boy was evaluated for dysmorphic features and mild to moderate BLSNHL, which was diagnosed after a failed newborn hearing screen. Physical examination revealed three fontanels, a sacral dimple, telecanthus, posteriorly rotated ears, and head lag. The family history was negative for both HL and dysmorphic features, including a healthy older brother. Given the combination of telecanthus and HL, targeted PAX3 gene testing to evaluate for Waardenburg syndrome type I and chromosomal microarray was requested. Both tests returned normal results. Research ES identified two PV in the PEX1 gene, consistent with Zellweger syndrome—a peroxisomal biogenesis disorder. Over the next few months, additional features of peroxisomal biogenesis disorders became evident, such as hypotonia, severe developmental delay, abnormal eye movements, and tapetoretinal degeneration identified by magnetic resonance imaging. A five-week-old newborn female presented for small size and conductive HL. Physical examination was notable for growth in the fifth to tenth percentile, a thin upper lip, and prominent maxilla. At 28 months, she had delayed expressive and receptive language and mild behavioral problems. Family history, including her two siblings, was negative for any hearing impairment or developmental delays. The results of a chromosomal microarray were normal. ES performed through the PediSeq research study identified a de novo frameshift variant in the EFTUD2 gene (c.764dup; p.Cys256Valfs*6) associated with autosomal dominant mandibulofacial dysostosis with microcephaly, which is associated with conductive HL and characteristic facial features. Although variants in PEX1 and EFTUD2 result in syndromic HL, these genes are not present on any HL gene panels in the United States. In both cases, ES was essential for early diagnosis before the additional syndromic features were present.
A 2-year-old male presented with language delay and progressive moderate to profound BLSNHL, necessitating hearing aids. The proband had three brothers with normal hearing. His mother had congenital progressive unilateral SNHL, also necessitating a hearing aid. The maternal grandfather had BLSNHL. The patient was consented for research ES in the PediSeq study while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel, Waardenburg syndrome testing, and chromosomal microarray analysis were requested. OtoGenome and research ES revealed three VUSs (one missense heterozygous variant each in DFNB31 , MYO15A, and USH2A ). Chromosomal microarray and Waardenburg syndrome testing returned normal results. ES also identified a maternally inherited pathogenic variant in the SMPX gene (c.133-1G>A). PV in SMPX cause X-linked dominant nonsyndromic HL, characterized by SNHL starting in the first decade of life for males. – This explains the family history of unilateral HL in the mother and BLSNHL in the grandfather, as the onset and severity of the condition are more variable for females. In this case, ES identified the genetic etiology, as the OtoGenome panel did not include SMPX .
An 11-year-old female presented with mild to moderately severe BLSNHL. The proband had no family history of HL. The patient was consented for research ES while connexin 26 ( GJB2 ) sequencing with reflex testing on the OtoGenome panel were requested. Research ES identified a single pathogenic variant in the GJB2 gene (c.71G>A; p.W24*). Clinical testing identified the same GJB2 pathogenic variant as ES and an additional pathogenic variant present in intron 1 (noncoding) of the GJB2 gene (c.-23+1G>A). This intronic variant was not identified using ES because the intron was not targeted by the capture kit. This case demonstrates a potential limitation of ES as a diagnostic tool, and the importance of carefully examining the coverage of any genes associated with the phenotype being evaluated.
Research ES on a cohort of 43 patients with HL identified a molecular etiology in 37.2% of probands, similar to the 39% diagnostic rate reported for the OtoSCOPE HL gene panel. In comparison, 15.8% of the probands that had GJB2 sequencing with reflex testing on the OtoGenome panel received a diagnosis. Clinical testing was limited due to insurance, so we examined the variants for cases diagnosed by research ES. We estimate that 9 of 16 patients would receive a molecular etiology by OtoGenome testing, assuming that any variant in a covered region would be detected. Seven patients had variants in COCH , GJB2 , MYO15A, or EYA1 that would probably have been detected by OtoGenome testing. For five other cases, the causative gene was not included in the OtoGenome testing ( EFTUD2 , PEX1 , SMPX , SIX1 , and OTOG ), although SIX1 is included in the current OtoGenome test. For two cases, OtoGenome testing did not confirm both variants detected on ES. This study demonstrates that poor capture and coverage is a limitation of the use of ES in the genetic diagnosis of HL. Incomplete capture may lead to a failed diagnosis, such as the proband with an intronic GJB2 PV that was identified by clinical testing but not ES. ES may be limited due to poor sequencing coverage issues (e.g., homopolymeric regions or GC-rich regions) or mapping issues (e.g., pseudogenes or large deletions), as demonstrated by the coverage of STRC and OTOA . Improvements in capture technology and enrichment for known disease genes to optimize the capture and coverage of HL genes will improve the performance of ES in the future. Targeted Sanger sequencing can supplement consistently poorly covered regions in exome-based testing. This finding suggests that tiered clinical testing may be beneficial. Examples of tiered clinical testing for HL include GJB2 gene testing with reflex testing of smaller panels (some of which are now exome-based “slices”, in which ES is performed and a list of HL genes are analyzed first, and then reflex testing of the full ES is offered if desired) before ES. CNVs are implicated in 18.7% of HL cases with a genetic etiology, about 86% of which are CNVs in STRC and OTOA . Our validation cases showed that CNVs are detected by ES, but in our cohort, we did not find any pathogenic deletions or duplications in GJB2 , OTOA or STRC . Genes and pseudogenes with high homology can create ambiguity in mapping of the short reads. Thus, CNV calling using short-read ES in genes with pseudogenes, such as OTOA and STRC , is challenging. This is one of the shortcomings of the short-read sequencing technology. Supplementation of ES with array comparative genomic hybridization may be helpful in CNV detection. The use of ES for molecularly diagnosing HL provides some benefits over standard genetic diagnostic protocols. In cases of nonsyndromic HL, early diagnosis may help direct care for associated medical comorbidities (e.g., in patients with Usher, Pendred, Jervell, or Lange–Nielsen syndromes). Additionally, ES may identify novel candidate genes, diagnoses that would not be identified with targeted testing, or diagnoses associated with syndromic HL when the additional clinical features are not present to help guide testing, as seen in the above cases. If a primary diagnosis is not found initially, the diagnostic yield may be improved by reanalysis when additional genotype or phenotype information is available, such as the revised clinical ES report with a likely PV in AMMECR1 , which we are examining for clinical relevance. Another consideration is that ES has a high likelihood of identifying VUS, especially in under-represented minority populations for whom there are less robust control genomic data. This can complicate the counseling of affected families. As more patients undergo ES, there will be more opportunities to share data that will improve the identification of nonpathogenic variants compared with pathogenic variants, as well as the racial distribution of these variants, thereby decreasing the uncertainty associated with broad-scale genomic tests. Although our study did not examine cost and turnaround time (for both, the sequencing as well as the variant analysis), these will continue to decrease, making ES more competitive. The rate of secondary findings of almost 7% in our cohort is not much higher than the rate of 4.6% previously published by Yang et al. The BRCA1 case discussed above highlights the importance of informed consent for ES and the benefit that identifying secondary findings may have for the entire family. Additionally, in almost two-thirds of the patients, carrier status was identified that may alter future reproductive decisions. While the identification of medically actionable secondary findings may have the benefit of early diagnosis, counseling and management, this should be undertaken only if desired and consented by the families, as some may find this information overwhelming and undesirable. In summary, ES is a potentially powerful tool for the molecular diagnosis of HL. It has enabled the molecular identification of HL genes not present on gene panels and the identification of unsuspected molecular etiologies, and performed well for identifying common genetic causes of HL. Limitations and concerns remain around the ability of ES to provide adequate coverage for all genes, exons, and variants known to cause HL at the same rate as targeted gene tests or HL gene panels. Tiered genetic testing or exome “slices” may be a solution to address these issues. Additional considerations include the identification of VUSs and secondary unrelated findings, as these may complicate counseling for affected families, but may also lead to the identification of medically actionable variants.
Supplementary Table 1 Supplementary Table 2 Supplementary Table 3 Supplementary Table 4
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Bridging the communication gap between radiographers and patients to improve chest radiography image acquisition: A multilingual solution in the COVID-19 pandemic | 8f6c515b-ec65-409d-9cea-6cecf7a260af | 7885683 | Health Communication[mh] | The prevalence of the highly infectious coronavirus disease, COVID-19, has caused massive health and socio-economic upheavals worldwide. In the immensely overloaded medical infrastructures and healthcare systems, the devastating impacts of the COVID-19 pandemic , were highly evident. Being the nearest acute hospital to the largest cluster of COVID-19 cases arising from S11 dormitory @ Punggol, a foreign worker dormitory in Singapore, the Department of Radiology in Sengkang General Hospital (SKH) had to accommodate the increasing orders of CXR for these patients from the S11 dormitory. , CXR is widely used for the medical triaging of suspected COVID-19 patients presented with moderate to severe upper respiratory symptoms , and a fully-inspired CXR should be acquired to visualise small pulmonary abnormalities better. The diagnostic value of a chest radiograph can be affected if the CXR is acquired with suboptimal inspiratory effort by the patient. Poor inspiration may cause increased opacification of the lung bases and affect the presentation of multifocal peripheral lung changes of ground glass opacity, which is a key feature in CXR findings in COVID-19 cases. , During the start of the COVID-19 outbreak in the dormitory, radiographers realised that they were faced with many difficulties when delivering verbal instructions to non-local dormitory residents during their CXR examination. This was because there was a lack of common language as the dormitory residents were from other Southern Asian countries who came to work mainly in the construction sector. Majority of these dormitory residents do not speak or understand English, which is the common language in Singapore. The outbreak within the dormitory led to it becoming the largest COVID-19 cluster in Singapore , and without a common language, the process of image acquisition was hindered. Effective communication is important to ensure patients adhere to the breathing instructions given so as to acquire CXRs in full inspiration , , . When faced with a communication barrier, most radiographers made use of non-verbal cues to aid patients’ understanding. This included eliminating the usage of medical jargons and expressing instructions in simple English, coupled with body language such as mimicking the action of shirt removal and breath-holding motions. These non-verbal cues were often carried out and repeated when patients failed to understand instructions initially. Even then, the body language was limited by the donning of the full Personal Protective Equipment (PPE) gear which included a disposable hair cover, face shield or goggles, N95 mask and gloves. Consequently, patients were unable to visualise the breathing motion which was expressed through facial expressions and chest rise action demonstrated by the radiographers. This resulted in radiographers struggling to acquire CXR in full inspiration for dormitory residents as they were unable to understand the breathing instructions. To bridge the communication gap, a team of radiographers came up with audio recordings of simple instructions for performing a CXR, such as “Remove your shirt” and “Breathe in and hold your breath”, in 11 languages, native to the dormitory residents presented in the SKH Emergency Department (ED) Isolation zone. The X-ray procedure room at the intervention site was set up with a Bluetooth speaker and a playlist of all the instructions were downloaded onto a laptop. Radiographers could playback the recorded instructions for dormitory residents during their chest examinations. A set of translation manual was also made available in A5-size flip-card model enhanced with pictorial illustration. These cards were laminated to uphold high adherence to infection control standards. (Annex A: Translation Manual). This paper aims to explore the effectiveness of using pre-recorded audio instructions in bridging the communication gap between radiographers and the dormitory residents to achieve full inspiration CXR.
A survey was conducted between 25/05/2020 to 10/06/2020 to evaluate the radiographers’ perspective on the effectiveness of the audio recordings and Translation Manual. All radiographers working in the ED were invited to participate in the survey. Survey questions were specially crafted to investigate the challenges faced by radiographers when performing a CXR for the dormitory residents, and to gauge the radiographer's confidence level in terms of patient communication with the aid of the Translation Manual and audio recordings playback of breathing instructions in different languages. The survey consisted of 5 multiple-choice questions using a 5-point Likert scale. Reject rate analysis (RRA) in Digital Radiography aims to help radiographers identify educational gaps, and guide them to improve the workflow, hence increase department efficiency. A rejected image is defined as a radiograph that is deemed unacceptable by the radiographer, at the time of image acquisition. The radiographer makes the judgement to reject an image that does not fulfill stringent technical qualities to contribute to the medical diagnosis, and therefore performs a repeat radiograph. Data on the CXR taken for all dormitory residents in the ED since the beginning of the COVID-19 outbreak in S11 dormitory were collected by the department's RRA team. Data on CXR rejected under reject reason “Inadequate inspiration” between 06/04/2020 to 31/05/2020 were extracted for analysis.
Survey results A total of 22 radiographers participated in the survey. This translates to a participation rate of 55%. 49% of the participants found it a challenge to get the patient to follow the breathing instructions when using the Translation Manual and audio recordings of translated breathing instructions. 40.9% of the participants are confident that the patient can understand the breathing instructions when using the Translation Manual and audio recordings of translated breathing instructions. 54.5% of the participants agreed that they can acquire full inspiration CXR when using the Translation Manual and audio recordings of translated breathing instructions. 95.5% of the participants agreed that the Translation Manual and audio recordings of translated breathing instructions were useful. RRA results depicts the reject rate of all dormitory residents’ CXRs performed between the beginning of April (Week 1) to end May (Week 8) in the ED Isolation zone. A steep increase in reject rate for CXR due to inadequate inspiration was observed from week 3 to week 4, this was the point where there was an increase in the dormitory residents who sought medical treatment at the ED. The audio recordings were implemented on week 6 and a significant drop in reject rate was observed immediately, suggesting that the audio recordings playback had been effective in helping radiographers achieve full inspiration CXR. To eliminate confounding factors that might have caused the decrease in reject rate post-intervention (i.e. radiographers passing suboptimal images of inadequate inspiration), an image audit of all the CXRs done from Week 6–8 was conducted. All the CXRs were screened by two radiographers from the team. Based on the CXR audit, 92.3% of the CXRs fulfilled the criteria of at least 9 posterior ribs seen above the right hemi-diaphragm. This demonstrated that the quality of the CXR was maintained despite a drop in reject rate, indicating that radiographers were consistently acquiring CXR in full inspiration.
A total of 22 radiographers participated in the survey. This translates to a participation rate of 55%. 49% of the participants found it a challenge to get the patient to follow the breathing instructions when using the Translation Manual and audio recordings of translated breathing instructions. 40.9% of the participants are confident that the patient can understand the breathing instructions when using the Translation Manual and audio recordings of translated breathing instructions. 54.5% of the participants agreed that they can acquire full inspiration CXR when using the Translation Manual and audio recordings of translated breathing instructions. 95.5% of the participants agreed that the Translation Manual and audio recordings of translated breathing instructions were useful.
depicts the reject rate of all dormitory residents’ CXRs performed between the beginning of April (Week 1) to end May (Week 8) in the ED Isolation zone. A steep increase in reject rate for CXR due to inadequate inspiration was observed from week 3 to week 4, this was the point where there was an increase in the dormitory residents who sought medical treatment at the ED. The audio recordings were implemented on week 6 and a significant drop in reject rate was observed immediately, suggesting that the audio recordings playback had been effective in helping radiographers achieve full inspiration CXR. To eliminate confounding factors that might have caused the decrease in reject rate post-intervention (i.e. radiographers passing suboptimal images of inadequate inspiration), an image audit of all the CXRs done from Week 6–8 was conducted. All the CXRs were screened by two radiographers from the team. Based on the CXR audit, 92.3% of the CXRs fulfilled the criteria of at least 9 posterior ribs seen above the right hemi-diaphragm. This demonstrated that the quality of the CXR was maintained despite a drop in reject rate, indicating that radiographers were consistently acquiring CXR in full inspiration.
Language barriers can directly affect the radiographer's ability to achieve a CXR in full inspiration due to the lack of effective communication. With reference to survey results, it was evident that radiographers found it a challenge in getting patients to adhere to breathing instructions. As the pre-recorded audio instructions provide solution in only a one-way communication, radiographers were unable to prepare patients in anticipating some pre-recorded instructions during the procedure. The survey results revealed most of the participants were not confident that the patient can understand the breathing instructions when using the Translation Manual and audio recordings of translated breathing instructions. This could be due to the fact that there was no effective two-way communication between radiographers and patients; resulting in the radiographer's inability to check for the patient's understanding. This confidence level could be managed by rehearsing with the patient by playing the recording once to check for understanding before the procedure. The patient's inability to adhere to breathing instructions might be attributed to the stress and fear that they are experiencing during this period of uncertainty. This pre-recorded audio instructions is something new and foreign to the patient and they might need more time to be accustomed to such new practice. A majority of participants (95.5%) agreed that they will continue to use the pre-recorded audio instructions, indicating the sustainability of these methods in bridging the communication gap. This highlighted an opportunity for future studies to explore how the proposed intervention can be effectively integrated in other procedures in a hospital setting. From the RRA, the decreased reject rate percentage (26%–9%) in the last 3 weeks of the study reflected an increased department efficiency. It also translates into increased radiographer's confidence in acquiring optimal images. This meant that radiographers spent less time to complete a CXR examination, hence resulting in faster turnover rate. This remained especially crucial in the COVID-19 context as radiographers were expected to minimise contact time with suspected patients. In addition to faster turnover rate, patient dose was kept to the minimum, conforming to the guiding principle of radiation safety, the “ALARA” (“As Low As Reasonably Achievable”) principle. Limitations The main limitation of this study was a lack of control over the work processes in the ED Isolation X-ray room. For example when there was a change in the group of radiographers rostered to ED in the subsequent part of the study, the new group may be unaware of the presence of the pre-recorded audio instructions. Additionally, the research team was unable to fully ensure that all radiographers consistently utilise the proposed methods due to the segregation of employees, imposed by the hospital management as part of COVID-19 control measures. As such, the efficacy of proposed methods may not be accurately assessed. Despite the challenges associated with the research methods stated in this study, we posit that they are still valuable in understanding and assessing interventions for radiographers when performing CXRs for patients who do not share a common language. Overall, this would be beneficial in progressing towards establishing a common practice to employ effective methods that can be adopted in other departments or hospitals. In the long run, this reduces departmental expenses as radiographers do not repeat CXR as often as the pre-intervention period. The second limitation of this study was the short study period of one week for each proposed intervention. Due to the rapid development of COVID-19 in S11 dormitory, the team had to promptly review and adjust the implementation when the CXR reject rate percentage did not decrease after the first week post-intervention. In an ideal situation, each study period should be in place for at least 2 weeks before introducing any new changes. Assumptions Several assumptions were made in this study. In order for the efficacy of proposed methods to be accurately assessed, the study assumed that patients had no prior experience having a CXR taken. When sieving the appropriate target audience (i.e. S11 dormitory residents) for RRA, the study assumed that all Medical Record Number (MRN) that began with the letter “G” and “F” are foreigners living in the S11 dormitory.
The main limitation of this study was a lack of control over the work processes in the ED Isolation X-ray room. For example when there was a change in the group of radiographers rostered to ED in the subsequent part of the study, the new group may be unaware of the presence of the pre-recorded audio instructions. Additionally, the research team was unable to fully ensure that all radiographers consistently utilise the proposed methods due to the segregation of employees, imposed by the hospital management as part of COVID-19 control measures. As such, the efficacy of proposed methods may not be accurately assessed. Despite the challenges associated with the research methods stated in this study, we posit that they are still valuable in understanding and assessing interventions for radiographers when performing CXRs for patients who do not share a common language. Overall, this would be beneficial in progressing towards establishing a common practice to employ effective methods that can be adopted in other departments or hospitals. In the long run, this reduces departmental expenses as radiographers do not repeat CXR as often as the pre-intervention period. The second limitation of this study was the short study period of one week for each proposed intervention. Due to the rapid development of COVID-19 in S11 dormitory, the team had to promptly review and adjust the implementation when the CXR reject rate percentage did not decrease after the first week post-intervention. In an ideal situation, each study period should be in place for at least 2 weeks before introducing any new changes.
Several assumptions were made in this study. In order for the efficacy of proposed methods to be accurately assessed, the study assumed that patients had no prior experience having a CXR taken. When sieving the appropriate target audience (i.e. S11 dormitory residents) for RRA, the study assumed that all Medical Record Number (MRN) that began with the letter “G” and “F” are foreigners living in the S11 dormitory.
Translation manuals and pre-recorded audio instructions were explored and assessed in the study to address the issue of language barrier, as identified in the survey. They were utilised by radiographers to acquire CXRs in full inspiration, for dormitory residents who do not share a common language. After the implementation of pre-recorded audio instructions, radiographers have successfully achieved fully-inspired CXRs for 92.3% of suspected COVID-19 patients. This was evident by a decrease in the reject rate for CXR, coupled with an audit that proved that the quality of CXR remained. This confirmed that pre-recorded audio instructions was an efficient proposed intervention, despite serving as a form of one-way communication tool to the patients. Overall, these findings showed that better communication led to more accurate imaging results, corresponding to existing literature on communication experiences between healthcare professionals and patients. Moreover, the decreased rejection rate of CXRs had increased department efficiency and radiographers’ confidence, consequently reducing departmental expenses in the long run.
The positive results promoted the continued use of the translation manual and audio recordings. Given that Singapore has an ageing population and the vast majority of our elderly converse in their various dialects, this implementation has the potential to expand to include local native languages and dialects. These can be seamlessly integrated in CXR and other procedures in the hospital setting. To ensure that the translations are culturally sensitive, attention should be paid to the translation process of instructions into other languages and local dialects by enlisting the help of native speakers.
None.
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Contribution of rare and common variants to intellectual disability in a sub-isolate of Northern Finland | faf86f3a-fc3f-4342-a038-6c47968865e6 | 6345990 | Pathology[mh] | Intellectual disability (ID) is a relatively common disorder characterized by deficits in both intellectual and adaptive functioning in conceptual, social and practical domains. A diagnosis of ID requires deficits in a broad range of intellectual functions, deficits in adaptive functioning resulting in failure to meet developmental and sociocultural standards for personal independence and social responsibility, and an onset during the developmental period . The population prevalence estimates of ID varies between 1 and 3% and is clearly lower (<0.5%) for more severe forms of ID (IQ < 50) than for mild forms . While genome-wide studies using microarrays and exome sequencing have identified a prominent role of de novo copy number variations (CNVs), INDELs and single nucleotide variants in mostly severe ID with reported diagnostic yields of 13–42%, their role in mild ID is less studied but expected to have a less prominent role , . Intriguingly siblings of mild ID individuals have low IQ compared to the general population whereas the IQ of siblings of severe ID individuals do not differ from the general population . Reichenberger et al. conclude that mild ID represents a low extreme in a normal distribution of IQ, while severe ID is a distinct condition with different etiology . The observation that intellectual disability has a high co-morbidity with other neurodevelopmental and neuropsychiatric diseases such as autism, schizophrenia, and epilepsy has stimulated the hypothesis that these diseases might, in part, have shared genetic backgrounds and thus alterations in the same pathways . One strategy to shed light on the genetic background of diseases is to use populations where the incidence of the trait is higher, and/or where the population history provides benefits for variant identification. Finland is a well-characterized genetic isolate where the small size of the founder population, subsequent bottleneck effects, and genetic drift have caused an enrichment of some rare and low-frequency variants as compared to other European populations , . In a population with a recent bottleneck, such as Finland, variants conferring a high risk for a disease with reduced fecundity can exist at markedly higher frequencies than in older populations because negative selection has not had time to drive down the allele frequencies, and therefore these variants are easier to associate to a disease . Interestingly, ID (Fig. ) and other neurodevelopmental and neuropsychiatric diseases (NDD) like schizophrenia have a higher prevalence in North-Eastern Finland as compared to South-Western Finland , . It has been hypothesized that such a pattern is related to the recent bottlenecks of these regions. The Eastern and Northern parts of Finland were inhabited more permanently only after the internal migration of small groups in the 16th century while Southern coastal regions were already more populous (Fig. ) . The regional genetic differences between the early and late settlements (east-west and north-south) can be clearly recapitulated from genome-wide common SNP data – . The aforementioned Finnish population history and the observation of geographical differences in the prevalence of neurodevelopmental diseases in Finland motivated us to initiate the Northern Finland Intellectual Disability (NFID) study, a geographically based cohort of ID patients and their family members recruited from specialty clinics in the two most Northern provinces of Finland. The only study exclusion criterion was having a known or suspected genetic or environmental cause for the phenotype and therefore the majority of our patients have the most common mild form of ID. Here we describe a comprehensive genetic characterization of 442 independent NFID patients with unknown disease etiology, enriched for mild (51.4%) forms of ID. We then examined the genetic architecture of this ID cohort that has undergone a population bottleneck and has a high proportion of mild ID cases. We studied the contribution of rare variants using exome sequencing, common variant polygenic risk scores, and CNVs using genome-wide association study (GWAS) arrays, each for different ID severity categories. We then compared the common and rare variants observed in the ID cohort to a large collection of pre-existing Finnish exome ( n = 11,311) and GWAS array data ( n = 11,699). We also analyzed the geographical distribution of the polygenic risk variant load of educational attainment, IQ and schizophrenia across different parts of Finland. Finally, to explore the broader phenotypic impact of identified variant categories and individual variants in the NFID cohort, we compared the identified variants to 640 exome-sequenced individuals with cognitive impairment, schizophrenia (SCZ) or autism spectrum disorder (ASD). We show that damaging variants in known ID genes are more often identified in more severe ID than mild ID. We further show that polygenic common variant burden is associated with all severity forms of ID and the polygenic risk seems to act in additive manner with rare damaging variants in known ID genes.
Regional ID prevalence in Finland We first estimated the regional prevalence of ID in Finland using the social security disability benefits register. We observed a higher prevalence of individuals receiving disability benefits for ID in the Eastern and Northern parts of Finland as compared to Southern and Western Finland (Fig. ). The highest prevalence was observed in Kainuu and North-Ostrobothnia, two of the primary municipalities of the NFID patient collection (Fig. ). Mutations in known genes causing cognitive impairment After joint genotype calling and quality control, we analyzed the exomes of 442 independent ID patients (Tables and ) and 2206 genetically matched population controls. Out of the 442 independent patients we had exome data for 138 full trios, 133 duos and the remaining 171 patients were cases only. To identify individuals with a potential causative variant in the exome analysis, we first searched for damaging missense or protein truncating variants (PTV) in 818 known developmental delay genes (see Materials and Methods and gene list in Supplementary Data ). For genes where autosomal recessive inheritance has been reported, only homozygote variants were considered. Within these 818 genes we identified a Likely pathogenic mutation in 64 patients (Supplementary Data , see Supplementary Data for clinical details of each patient). For the subset of individuals for which we had parental exome available (138 trios and 133 duos), we further filtered the list of Likely pathogenic variants by not inherited from a parent without learning disability. This step filtered 5/24 likely pathogenic variants in trios and 0/15 in duos (Supplementary Data ). We also excluded 1 Likely diagnostic variants when the clinical phenotype was clearly different (assessed by clinical geneticist) than reported in the literature. After these filterings we identified Likely pathogenic diagnosis for 59/422 patients in exome sequencing. When comparing the rate of likely pathogenic variants to the 2206 genetically matched controls, we observed the strongest enrichment in PTV variants (OR: 10.94, 95% CI: 4.89–26.21, p : 2.7e−10, Fisher’s exact test) followed by dominant acting (OR: 5.47, 95% CI: 3.19–9.38, p : 7.5e−12, Fisher’s exact test) and recessive (OR: 1.83, 95% CI: 0.7–4.30, p : 1.4e−1, Fisher’s exact test) constrained/damaging missense variant classes (Fig. ). Variants in novel cognitive impairment genes Given that ~86% of our cases did not have a variant affecting a known NDD gene, we wanted to assess if there was a burden of rare variants outside of known genes. We performed an enrichment analysis of variants that were either PTV or constrained damaging missense (MPC > 2) variants and not observed in the non-Finnish GnomAD samples or in our internal Finnish controls (different controls used for filtering and enrichment, see Table ). First, we verified that there was no spurious enrichment of variants caused by stratification or batch effects by analyzing if there was an enrichment of synonymous variants (not observed in GnomAD or our Finnish controls) between cases and controls. No such enrichment was observed, suggesting that QC and case control matching were successful (Fig. ). Dominant PTVs in high pLI genes (OR: 2.65, 95% CI: 2.02–3.47, p : 2.2e−12, Fisher’s exact test) and constrained damaging missense variants not seen in GnomAD or Finnish controls within novel genes (OR: 1.64, 95% CI: 1.29–2.08, p : 5.9e−5, Fisher’s exact test) were significantly enriched in cases (Fig. ). The signal for PTV variants was almost exclusively in genes intolerant of PTV-mutations (pLI < 0.95, OR: 1.16, 95% CI: 0.94–1.44, 1.7e−1; Fig. ). Homozygous PTVs (likely complete knockout of a gene) in novel genes were over twofold enriched in cases, but were not statistically significant (OR 2.51, 95% CI: 0.40–11.78, p : 1.8e−1, Fisher’s exact test; Fig. ). Copy number variants After QC (see Methods), we assessed the contribution of likely diagnostic CNVs in 433 NFID patients and 1100 genetically matched controls. Deletions of any type (>100 kb) were observed slightly more often in cases than in controls (OR: 1.3 (CI 0.94–1.7) p : 0.098, Fig. : n cases = 85 (19.6%), n controls = 177 (16.1%)). However, large deletions (>500 kb) were more frequent in cases, regardless of chromosomal location (OR 4.4 (CI 2.4–8.3) p : 4.8e−7 (Fisher’s exact test), NFID: 31 individuals (7.2%), controls: 19 individuals (1.8%); Fig. ). CNVs that have previously been associated with syndromes, or deleted a known ID gene, were strongly enriched in cases (OR: 26.5 (CI 6.4–233.9), p : 4.4e−10, Fisher’s exact test) 20 patients (4.6%) vs. two population controls (0.02%); Fig. ). Using our classification algorithm, we identified a Likely pathogenic CNV in a total of 29 cases (Supplementary Data ). Large deletions (>1 Mb) were the most commonly identified likely pathogenic CNVs (21 cases, 4.9%; 7 controls 0.6%) (Fig. ). A total of 17 cases (3.9%) and two controls (0.2%) carried a CNV overlapping a region previously linked to syndromic ID (Fig. ). A single 4.7 Mb duplication meeting pathogenicity criteria was detected, overlapping the well-established Prader-Willi/Angelman syndrome region at 15q11-q13. The syndromic CNVs identified in controls were non-ID associated (12p13.33 deletion) and a region with known variable phenotype (22q11 duplication syndrome ). Known ID-associated gene was deleted in 14 cases (3.2%) and 0 controls (Fig. ). The distribution of duplication sizes is presented in Fig. . As a pathogenic CNV was observed in only 29 cases (6.7%), we analyzed if there was an excess of smaller deletions in genes intolerant of PTV variations not previously associated with cognitive phenotype. After removing likely pathogenic CNV types, we observed such deletions in 12 cases (2.8%) and 9 controls (0.8%) (OR (CI 1.3 - 9.3), p : 5.8e-3, Fisher’s exact test) (Fig. and Supplementary Figure ). Total genetic diagnosis rate After combining exome and CNV data, we identified a likely diagnosis for 80 (18.5%) patients (Fig. ) of the 433 patients with both exome and CNV data available). The strongest risk factor was having a PTV in a known neurodevelopmental disorder gene (OR 11.1, 95% CI: 4.1–38.1, p : 3.0e−8, Fisher’s exact test) followed by a likely pathogenic deletion (OR 8.7, 95% CI: 4.0–21.1, p : 6.5e−10, Fisher’s exact test) and a constrained missense variant in a known developmental disorder gene (OR 5.8, 95% CI: 3.0–11.6, p : 9.5e−9, Fisher’s exact test) (Fig. ). We then analyzed if there was a signal from damaging variants (PTVs, missenses MPC > 2 or CNVs) outside of known ID-associated genes (termed Other high impact variants). We observed a significant enrichment of Other high impact variants in cases vs. controls (Fig. ). PTVs (OR 3.0, 95% CI: 2.2–4.2, p : 1.7e−12, Fisher’s exact test) and deletions (OR 3.5, 95% CI: 1.3–9.4, p : 5.8e−3, Fisher’s exact test) in high pLI genes as well as constrained missense variants (OR 1.7, 95% CI: 1.3–2.2, p : 6.7e−5, Fisher’s exact test) were significantly enriched in the Other high impact variants category (Supplementary Figure ). As much less is known about the genetic architecture of mild ID as compared to the more severe ID diagnoses , we assessed if rare variants in the same known genes contribute equally to mild and severe forms of ID. For the analysis we combined the moderate, severe and profound ID patients in a severe category. The overall rates of Likely pathogenic (OR 5.4, p : 1.8e−9, Fisher’s exact test) and Other high impact variants (OR 2.3, p : 6.5e−7, Fisher’s exact test) were significantly higher in the mild group than in controls (Supplementary Figure ). However, severe IDs had significantly higher (OR: 2.4, p : 7.0e−4, Fisher’s exact test) proportion of Likely pathogenic variants in known ID genes as compared to mild ID (Fig. , Supplementary Figure ). For CNVs, the diagnostic rate did not follow the same pattern of increased likely pathogenic CNV in more severe cases than in mild cases (Fig. ). This is likely because a large fraction of ID patients who had a chromosomal abnormality had been identified in previous clinical cytogenetic analyses and excluded from this study. As dysmorphic features are present more often in severe ID than in mild ID, we analyzed if Likely pathogenic variants would be found more often in more severe ID due to dysmorphisms and not due to more severe ID. We repeated the enrichment analysis of our variant classification while restricting only to patients with no dysmorphisms ( n = 234) (Supplementary Figure ). We observed Likely pathogenic variants in 16/83 (19%) and 17/151(11%) among severe ID and mild ID patients respectively (OR: 1.88, p : 0.12, Fisher’s exact test). The rate of identifying Likely pathogenic variants was lower in non-dysmorphic, severe (19%) and mild (11%) ID patients than in dysmorphic severe (34%) and mild (18%) patients. There seems to be a higher rate of Likely pathogenic variants in severe ID patients than mild ID patients even among patients for which no dysmorphic features were recorded, although the difference is less pronounced. As we did not have parental exome sequencing data on all patients, we wanted to assess if the uncertainty in Likely diagnostic classification affects the result that mild ID would be less affected by de novo/ultra-rare variants in known ID genes. To this end we subset the cases to (1) full trios with confirmed de novo in dominant acting gene (2) duos where we checked that the other parent did not have the variant and (3) all patients with Likely pathogenic variants. The OR in SEVERE vs. mild ID patients having Likely pathogenic variant was OR 2.2 (0.6–9.5), 2.8 (0.9–8.8), and 2.2 (1.3–3.8) in confirmed de novos, duos and all patients respectively. This suggests that some misclassification would not change the conclusion that severe ID patients are more often affected by de novos/very rare variants in known ID genes than mild ID. Polygenic common variant load As we identified likely causative variant in only 18.5% of the cases, we wanted to study the contribution of the polygenic load of common variants associated to intelligence quotient (IQ), educational attainment (EDU) and schizophrenia (SCZ) to Northern Finnish ID. There is a partial common variant genetic overlap between cognitive function and schizophrenia – and therefore we also studied SCZ PRS. We estimated the regional prevalence of SCZ as we did for ID and observed a similar regional enrichment in Northern and Eastern Finland (Supplementary Figure ). First, to create a reference for NFID cases, we analyzed whether the geographical distribution of PRSs correspond to the population history of Finland. We genotyped and imputed 14,833 individuals from the population-based FINRISK collection and used all loci with a lead variant p -value ≤0.05 in the meta-analyses for schizophrenia, IQ and educational attainment. To visualize the geographical distribution of PRSs, we used a distance-weighted polygenic risk score in 2186 Finnish individuals who did not have any neurodevelopmental disorders and whose parents were born within 100 km of each other (see Methods). The PRSs for educational attainment and IQ were lower, and for SCZ higher in the Eastern and Northern part of Finland than in the Southern and Western Finland (Fig. ). Next we asked if the PRSs were associated with ID. All PRSs were significantly associated with the ID phenotype as compared to genetically matched Finnish controls (Fig. ). The PRS for EDU, SCZ and IQ explained 0.94%, 0.55%, and 0.48% of the heritability on the liability scale, respectively (see Supplementary Figure for heritability estimation using varying significance thresholds for locus inclusion). We next analyzed whether PRS values were different in the different ID groups: mild, moderate, and severe/profound combined. The PRS for EDU was lower and for SCZ higher in the mild ID cases compared to more severe forms, but the differences were not statistically significant (Supplementary Figure ). Unexpectedly, the IQ PRS in the mild ID group was not significantly different from matched population controls but the most severe ID was different. (Supplementary Figure ). We also hypothesized that the EDU and IQ PRSs would be lower and SCZ PRS would be higher in patients for which a likely causative mutation was not identified. Thus, we compared the PRSs between cases in different diagnostic categories but did not observe statistically significant differences between groups (Supplementary Figure ). Importantly, we also subset Likely diagnosed patients to those for which we had confirmed de novo in a known ID gene or diagnostic CNV ( n = 13). Those 13 patients were just as affected by IQ and EDU PRSs but not by SCZ PRS (Supplementary Figure ). Assuming we had sufficient power, this suggests that in addition to high penetrance variants, a more general polygenic component (ID and EDU PRS) also contributes to the genetic background of ID. Variants enriched in Finland Finally, we asked if some variants enriched in Finland might contribute to the Northern Finnish ID phenotype as variants with reduced reproductive fitness can exist in markedly higher frequency in a population with a recent bottleneck . We hypothesized that some of these variants would be associated with ID in the NFID cohort. To identify these variants, we compared the allele frequencies in Finnish samples to the allele frequency in non-Finnish Europeans in the GnomAD database. PTV and missense variants in the range of 0.1–5% (Supplementary Figure ) were proportionally more enriched compared to other variants. This is in line with our previous observation in smaller datasets . Dominant variants enriched in Finland We first analyzed low frequency and rare (MAF < 0.1% in GnomAD non-Finnish population maximum) single missense and PTV variants enriched at least two-fold in Finland or absent in GnomAD non-Finns excluding singletons (13,483 variants; 12,628 missense, 855 PTV). We identified 396 variants nominally ( p < 0.05, Fisher’s exact test) associated with ID (Supplementary Data ). We then aimed to replicate these associations in NDD cases and genetically matched controls from the Northern and Southern Finland (Table ). After meta-analyzing all three cohorts, we identified 29 variants associated with a p -value < 0.001 (Mantel–Haenzel test) (20 variants were found in cases only across the three cohorts). However, none of variants surpassed a Bonferroni multiple-testing correction for 13,483 tests. Recessive variants enriched in Finland We next asked if some of the enriched PTV or missense variants with low allele frequency in GnomAD (AF < 0.01) were recessively associated with ID. We excluded singleton homozygotes and variants observed as homozygous in GnomAD. After these filtering steps we performed a recessive analysis for 1408 variants (1379 missense variants and 29 PTVs). Eighteen variants were observed as homozygous more than once in cases across the three cohorts but not in controls (Table ). We identified a homozygous missense variant in the CRADD gene in three independent ID cases. Additionally, we identified one CRADD missense homozygote in the Northern Finland NDD case cohort (RAFT meta p : 5.75E−8). The variant is over 50 times more frequent in Finland than in non-Finnish Europeans. The variant is located in the DEATH domain through which CRADD interacts with other DEATH domain proteins . Another variant in the HGF gene achieved a p -value surviving Bonferroni correction ( p : 1.3e−5, RAFT meta), but it was observed only in two cases. Homozygote variants in HGF have been identified in consanguineous families ascertained for non-syndromic deafness . Our cases did not have hearing problems. Among the 18 genes with case-only recessive candidate variants we observed significantly more genes that are intolerant of homozygote PTV variation (pRec > 0.8 ) than expected by chance. A pREC metric was available for 17 of the 18 of the candidate genes, of which eight were intolerant of homozygote PTV variation. In ExAC 4,508 out of 18,241 genes have pRec > 0.8, and therefore we would expect 4.2 genes by chance (binomial test p -value 0.046). This suggests that some of the 18 candidate variants are true risk variants for ID (see Supplementary Data for all 57 nominally significant associations). Variance explained by different variant categories To put the relative contribution of different classes of genetic variation to a context, we estimated the variance explained by each significant category in the case–control comparisons. We added the three CRADD homozygotes to the likely pathogenic category as we clearly demonstrated the variant to be a causative recessive variant (Table ). For likely diagnostic and other high impact variants, we used genetically matched cases and controls for which both exome and CNV data were available (433 cases and 1100 controls). For the polygenic risk score, we used 439 cases and 2195 genetically matched controls. As we observed geographical differences in PRSs within Finland, we corrected the variance explained estimation using the first four PCs. The PRS’s contribution to heritability is lower (IQ 0.48%, 95% CI: 0.067–1.25%; SCZ 0.55%, 95% CI: 0.078–1.5%; EDU 0.94%, 95% CI: 0.31–1.92%) than that of pathogenic variants in known genes (4.15%, 95% CI: 2.78–5.77%) or other high impact variants (2.25%, 95% CI: 1.30–3.52%) (Fig. ). When comparing the different ID severities, the heritability explained for PRSs was the highest in mild ID for EDU (2.1%, 95% CI: 0.46–4.5%) and smaller in more severe ID (0.52%, 95% CI: 0.04–1.60%). The heritability estimation for all PRSs and ID categories is presented in Supplementary Figure . The variance explained by Likely pathogenic variants in known genes was slightly higher in more severe ID (6.2%, 95% CI: 3.8–9.1%) than in mild ID (4.0%, 95% CI: 1.8–7.1%). This is expected as we observed a significantly lower proportion of Likely pathogenic variants in mild ID (13%) vs. more severe ID (25%) (Figs. and ).
We first estimated the regional prevalence of ID in Finland using the social security disability benefits register. We observed a higher prevalence of individuals receiving disability benefits for ID in the Eastern and Northern parts of Finland as compared to Southern and Western Finland (Fig. ). The highest prevalence was observed in Kainuu and North-Ostrobothnia, two of the primary municipalities of the NFID patient collection (Fig. ).
After joint genotype calling and quality control, we analyzed the exomes of 442 independent ID patients (Tables and ) and 2206 genetically matched population controls. Out of the 442 independent patients we had exome data for 138 full trios, 133 duos and the remaining 171 patients were cases only. To identify individuals with a potential causative variant in the exome analysis, we first searched for damaging missense or protein truncating variants (PTV) in 818 known developmental delay genes (see Materials and Methods and gene list in Supplementary Data ). For genes where autosomal recessive inheritance has been reported, only homozygote variants were considered. Within these 818 genes we identified a Likely pathogenic mutation in 64 patients (Supplementary Data , see Supplementary Data for clinical details of each patient). For the subset of individuals for which we had parental exome available (138 trios and 133 duos), we further filtered the list of Likely pathogenic variants by not inherited from a parent without learning disability. This step filtered 5/24 likely pathogenic variants in trios and 0/15 in duos (Supplementary Data ). We also excluded 1 Likely diagnostic variants when the clinical phenotype was clearly different (assessed by clinical geneticist) than reported in the literature. After these filterings we identified Likely pathogenic diagnosis for 59/422 patients in exome sequencing. When comparing the rate of likely pathogenic variants to the 2206 genetically matched controls, we observed the strongest enrichment in PTV variants (OR: 10.94, 95% CI: 4.89–26.21, p : 2.7e−10, Fisher’s exact test) followed by dominant acting (OR: 5.47, 95% CI: 3.19–9.38, p : 7.5e−12, Fisher’s exact test) and recessive (OR: 1.83, 95% CI: 0.7–4.30, p : 1.4e−1, Fisher’s exact test) constrained/damaging missense variant classes (Fig. ).
Given that ~86% of our cases did not have a variant affecting a known NDD gene, we wanted to assess if there was a burden of rare variants outside of known genes. We performed an enrichment analysis of variants that were either PTV or constrained damaging missense (MPC > 2) variants and not observed in the non-Finnish GnomAD samples or in our internal Finnish controls (different controls used for filtering and enrichment, see Table ). First, we verified that there was no spurious enrichment of variants caused by stratification or batch effects by analyzing if there was an enrichment of synonymous variants (not observed in GnomAD or our Finnish controls) between cases and controls. No such enrichment was observed, suggesting that QC and case control matching were successful (Fig. ). Dominant PTVs in high pLI genes (OR: 2.65, 95% CI: 2.02–3.47, p : 2.2e−12, Fisher’s exact test) and constrained damaging missense variants not seen in GnomAD or Finnish controls within novel genes (OR: 1.64, 95% CI: 1.29–2.08, p : 5.9e−5, Fisher’s exact test) were significantly enriched in cases (Fig. ). The signal for PTV variants was almost exclusively in genes intolerant of PTV-mutations (pLI < 0.95, OR: 1.16, 95% CI: 0.94–1.44, 1.7e−1; Fig. ). Homozygous PTVs (likely complete knockout of a gene) in novel genes were over twofold enriched in cases, but were not statistically significant (OR 2.51, 95% CI: 0.40–11.78, p : 1.8e−1, Fisher’s exact test; Fig. ).
After QC (see Methods), we assessed the contribution of likely diagnostic CNVs in 433 NFID patients and 1100 genetically matched controls. Deletions of any type (>100 kb) were observed slightly more often in cases than in controls (OR: 1.3 (CI 0.94–1.7) p : 0.098, Fig. : n cases = 85 (19.6%), n controls = 177 (16.1%)). However, large deletions (>500 kb) were more frequent in cases, regardless of chromosomal location (OR 4.4 (CI 2.4–8.3) p : 4.8e−7 (Fisher’s exact test), NFID: 31 individuals (7.2%), controls: 19 individuals (1.8%); Fig. ). CNVs that have previously been associated with syndromes, or deleted a known ID gene, were strongly enriched in cases (OR: 26.5 (CI 6.4–233.9), p : 4.4e−10, Fisher’s exact test) 20 patients (4.6%) vs. two population controls (0.02%); Fig. ). Using our classification algorithm, we identified a Likely pathogenic CNV in a total of 29 cases (Supplementary Data ). Large deletions (>1 Mb) were the most commonly identified likely pathogenic CNVs (21 cases, 4.9%; 7 controls 0.6%) (Fig. ). A total of 17 cases (3.9%) and two controls (0.2%) carried a CNV overlapping a region previously linked to syndromic ID (Fig. ). A single 4.7 Mb duplication meeting pathogenicity criteria was detected, overlapping the well-established Prader-Willi/Angelman syndrome region at 15q11-q13. The syndromic CNVs identified in controls were non-ID associated (12p13.33 deletion) and a region with known variable phenotype (22q11 duplication syndrome ). Known ID-associated gene was deleted in 14 cases (3.2%) and 0 controls (Fig. ). The distribution of duplication sizes is presented in Fig. . As a pathogenic CNV was observed in only 29 cases (6.7%), we analyzed if there was an excess of smaller deletions in genes intolerant of PTV variations not previously associated with cognitive phenotype. After removing likely pathogenic CNV types, we observed such deletions in 12 cases (2.8%) and 9 controls (0.8%) (OR (CI 1.3 - 9.3), p : 5.8e-3, Fisher’s exact test) (Fig. and Supplementary Figure ).
After combining exome and CNV data, we identified a likely diagnosis for 80 (18.5%) patients (Fig. ) of the 433 patients with both exome and CNV data available). The strongest risk factor was having a PTV in a known neurodevelopmental disorder gene (OR 11.1, 95% CI: 4.1–38.1, p : 3.0e−8, Fisher’s exact test) followed by a likely pathogenic deletion (OR 8.7, 95% CI: 4.0–21.1, p : 6.5e−10, Fisher’s exact test) and a constrained missense variant in a known developmental disorder gene (OR 5.8, 95% CI: 3.0–11.6, p : 9.5e−9, Fisher’s exact test) (Fig. ). We then analyzed if there was a signal from damaging variants (PTVs, missenses MPC > 2 or CNVs) outside of known ID-associated genes (termed Other high impact variants). We observed a significant enrichment of Other high impact variants in cases vs. controls (Fig. ). PTVs (OR 3.0, 95% CI: 2.2–4.2, p : 1.7e−12, Fisher’s exact test) and deletions (OR 3.5, 95% CI: 1.3–9.4, p : 5.8e−3, Fisher’s exact test) in high pLI genes as well as constrained missense variants (OR 1.7, 95% CI: 1.3–2.2, p : 6.7e−5, Fisher’s exact test) were significantly enriched in the Other high impact variants category (Supplementary Figure ). As much less is known about the genetic architecture of mild ID as compared to the more severe ID diagnoses , we assessed if rare variants in the same known genes contribute equally to mild and severe forms of ID. For the analysis we combined the moderate, severe and profound ID patients in a severe category. The overall rates of Likely pathogenic (OR 5.4, p : 1.8e−9, Fisher’s exact test) and Other high impact variants (OR 2.3, p : 6.5e−7, Fisher’s exact test) were significantly higher in the mild group than in controls (Supplementary Figure ). However, severe IDs had significantly higher (OR: 2.4, p : 7.0e−4, Fisher’s exact test) proportion of Likely pathogenic variants in known ID genes as compared to mild ID (Fig. , Supplementary Figure ). For CNVs, the diagnostic rate did not follow the same pattern of increased likely pathogenic CNV in more severe cases than in mild cases (Fig. ). This is likely because a large fraction of ID patients who had a chromosomal abnormality had been identified in previous clinical cytogenetic analyses and excluded from this study. As dysmorphic features are present more often in severe ID than in mild ID, we analyzed if Likely pathogenic variants would be found more often in more severe ID due to dysmorphisms and not due to more severe ID. We repeated the enrichment analysis of our variant classification while restricting only to patients with no dysmorphisms ( n = 234) (Supplementary Figure ). We observed Likely pathogenic variants in 16/83 (19%) and 17/151(11%) among severe ID and mild ID patients respectively (OR: 1.88, p : 0.12, Fisher’s exact test). The rate of identifying Likely pathogenic variants was lower in non-dysmorphic, severe (19%) and mild (11%) ID patients than in dysmorphic severe (34%) and mild (18%) patients. There seems to be a higher rate of Likely pathogenic variants in severe ID patients than mild ID patients even among patients for which no dysmorphic features were recorded, although the difference is less pronounced. As we did not have parental exome sequencing data on all patients, we wanted to assess if the uncertainty in Likely diagnostic classification affects the result that mild ID would be less affected by de novo/ultra-rare variants in known ID genes. To this end we subset the cases to (1) full trios with confirmed de novo in dominant acting gene (2) duos where we checked that the other parent did not have the variant and (3) all patients with Likely pathogenic variants. The OR in SEVERE vs. mild ID patients having Likely pathogenic variant was OR 2.2 (0.6–9.5), 2.8 (0.9–8.8), and 2.2 (1.3–3.8) in confirmed de novos, duos and all patients respectively. This suggests that some misclassification would not change the conclusion that severe ID patients are more often affected by de novos/very rare variants in known ID genes than mild ID.
As we identified likely causative variant in only 18.5% of the cases, we wanted to study the contribution of the polygenic load of common variants associated to intelligence quotient (IQ), educational attainment (EDU) and schizophrenia (SCZ) to Northern Finnish ID. There is a partial common variant genetic overlap between cognitive function and schizophrenia – and therefore we also studied SCZ PRS. We estimated the regional prevalence of SCZ as we did for ID and observed a similar regional enrichment in Northern and Eastern Finland (Supplementary Figure ). First, to create a reference for NFID cases, we analyzed whether the geographical distribution of PRSs correspond to the population history of Finland. We genotyped and imputed 14,833 individuals from the population-based FINRISK collection and used all loci with a lead variant p -value ≤0.05 in the meta-analyses for schizophrenia, IQ and educational attainment. To visualize the geographical distribution of PRSs, we used a distance-weighted polygenic risk score in 2186 Finnish individuals who did not have any neurodevelopmental disorders and whose parents were born within 100 km of each other (see Methods). The PRSs for educational attainment and IQ were lower, and for SCZ higher in the Eastern and Northern part of Finland than in the Southern and Western Finland (Fig. ). Next we asked if the PRSs were associated with ID. All PRSs were significantly associated with the ID phenotype as compared to genetically matched Finnish controls (Fig. ). The PRS for EDU, SCZ and IQ explained 0.94%, 0.55%, and 0.48% of the heritability on the liability scale, respectively (see Supplementary Figure for heritability estimation using varying significance thresholds for locus inclusion). We next analyzed whether PRS values were different in the different ID groups: mild, moderate, and severe/profound combined. The PRS for EDU was lower and for SCZ higher in the mild ID cases compared to more severe forms, but the differences were not statistically significant (Supplementary Figure ). Unexpectedly, the IQ PRS in the mild ID group was not significantly different from matched population controls but the most severe ID was different. (Supplementary Figure ). We also hypothesized that the EDU and IQ PRSs would be lower and SCZ PRS would be higher in patients for which a likely causative mutation was not identified. Thus, we compared the PRSs between cases in different diagnostic categories but did not observe statistically significant differences between groups (Supplementary Figure ). Importantly, we also subset Likely diagnosed patients to those for which we had confirmed de novo in a known ID gene or diagnostic CNV ( n = 13). Those 13 patients were just as affected by IQ and EDU PRSs but not by SCZ PRS (Supplementary Figure ). Assuming we had sufficient power, this suggests that in addition to high penetrance variants, a more general polygenic component (ID and EDU PRS) also contributes to the genetic background of ID.
Finally, we asked if some variants enriched in Finland might contribute to the Northern Finnish ID phenotype as variants with reduced reproductive fitness can exist in markedly higher frequency in a population with a recent bottleneck . We hypothesized that some of these variants would be associated with ID in the NFID cohort. To identify these variants, we compared the allele frequencies in Finnish samples to the allele frequency in non-Finnish Europeans in the GnomAD database. PTV and missense variants in the range of 0.1–5% (Supplementary Figure ) were proportionally more enriched compared to other variants. This is in line with our previous observation in smaller datasets .
We first analyzed low frequency and rare (MAF < 0.1% in GnomAD non-Finnish population maximum) single missense and PTV variants enriched at least two-fold in Finland or absent in GnomAD non-Finns excluding singletons (13,483 variants; 12,628 missense, 855 PTV). We identified 396 variants nominally ( p < 0.05, Fisher’s exact test) associated with ID (Supplementary Data ). We then aimed to replicate these associations in NDD cases and genetically matched controls from the Northern and Southern Finland (Table ). After meta-analyzing all three cohorts, we identified 29 variants associated with a p -value < 0.001 (Mantel–Haenzel test) (20 variants were found in cases only across the three cohorts). However, none of variants surpassed a Bonferroni multiple-testing correction for 13,483 tests.
We next asked if some of the enriched PTV or missense variants with low allele frequency in GnomAD (AF < 0.01) were recessively associated with ID. We excluded singleton homozygotes and variants observed as homozygous in GnomAD. After these filtering steps we performed a recessive analysis for 1408 variants (1379 missense variants and 29 PTVs). Eighteen variants were observed as homozygous more than once in cases across the three cohorts but not in controls (Table ). We identified a homozygous missense variant in the CRADD gene in three independent ID cases. Additionally, we identified one CRADD missense homozygote in the Northern Finland NDD case cohort (RAFT meta p : 5.75E−8). The variant is over 50 times more frequent in Finland than in non-Finnish Europeans. The variant is located in the DEATH domain through which CRADD interacts with other DEATH domain proteins . Another variant in the HGF gene achieved a p -value surviving Bonferroni correction ( p : 1.3e−5, RAFT meta), but it was observed only in two cases. Homozygote variants in HGF have been identified in consanguineous families ascertained for non-syndromic deafness . Our cases did not have hearing problems. Among the 18 genes with case-only recessive candidate variants we observed significantly more genes that are intolerant of homozygote PTV variation (pRec > 0.8 ) than expected by chance. A pREC metric was available for 17 of the 18 of the candidate genes, of which eight were intolerant of homozygote PTV variation. In ExAC 4,508 out of 18,241 genes have pRec > 0.8, and therefore we would expect 4.2 genes by chance (binomial test p -value 0.046). This suggests that some of the 18 candidate variants are true risk variants for ID (see Supplementary Data for all 57 nominally significant associations).
To put the relative contribution of different classes of genetic variation to a context, we estimated the variance explained by each significant category in the case–control comparisons. We added the three CRADD homozygotes to the likely pathogenic category as we clearly demonstrated the variant to be a causative recessive variant (Table ). For likely diagnostic and other high impact variants, we used genetically matched cases and controls for which both exome and CNV data were available (433 cases and 1100 controls). For the polygenic risk score, we used 439 cases and 2195 genetically matched controls. As we observed geographical differences in PRSs within Finland, we corrected the variance explained estimation using the first four PCs. The PRS’s contribution to heritability is lower (IQ 0.48%, 95% CI: 0.067–1.25%; SCZ 0.55%, 95% CI: 0.078–1.5%; EDU 0.94%, 95% CI: 0.31–1.92%) than that of pathogenic variants in known genes (4.15%, 95% CI: 2.78–5.77%) or other high impact variants (2.25%, 95% CI: 1.30–3.52%) (Fig. ). When comparing the different ID severities, the heritability explained for PRSs was the highest in mild ID for EDU (2.1%, 95% CI: 0.46–4.5%) and smaller in more severe ID (0.52%, 95% CI: 0.04–1.60%). The heritability estimation for all PRSs and ID categories is presented in Supplementary Figure . The variance explained by Likely pathogenic variants in known genes was slightly higher in more severe ID (6.2%, 95% CI: 3.8–9.1%) than in mild ID (4.0%, 95% CI: 1.8–7.1%). This is expected as we observed a significantly lower proportion of Likely pathogenic variants in mild ID (13%) vs. more severe ID (25%) (Figs. and ).
Here we have described a comprehensive genetic analysis of an ID cohort from a population with a relatively high prevalence of ID. We studied the contribution of SNVs and INDELs, CNVs, and of a genome-wide common variant polygenic load. Unlike most published studies our ID cohort consists mostly of relatively mild ID cases. We identified a likely pathogenic variant in genes known to be associated with ID in 18% of the cases for which both exome and CNV data were available (Fig. ), explaining an estimated 4.2% of the heritability (Fig. ). Additionally, we observed a significant ~2-fold enrichment of damaging variants/CNVs in loss-of-function intolerant genes not yet linked to ID, which explained an additional 2.3% of the heritability (Figs. and ). We then demonstrated that a common variant polygenic load is associated with ID. We observed educational attainment, IQ and schizophrenia polygenic risk scores to be associated with ID explaining an estimated 0.94%, 0.48%, and 0.55% of the heritability, respectively. We then focused on characterizing the genetic architecture of mild vs. more severe forms of ID and observed that a likely causative variant in known ID genes was significantly more often identified in more severe ID cases than in mild ID cases (Fig. ). This suggests that either mild ID has a more complex etiology or that variants in genes predisposing to mild ID are partly different than those predisposing to more severe forms of ID. Our observation is in agreement with epidemiological studies where mild ID has been suggested to represent a highly heritable low end of a normal distribution of IQ whereas severe ID is a distinct condition with different etiology . Therefore, mild ID should have less contribution from de novo and extremely rare variants, which have been the major focus of most genetic studies of ID. To study the possibly more complex etiology of mild ID, we first showed that the polygenic risk score of low educational attainment, low IQ, and schizophrenia were all higher in the Eastern and Northern parts of Finland, coinciding with the more recent bottleneck and higher prevalence of intellectual disability and schizophrenia within those regions in Finland . We then showed that the PRS for educational attainment, intelligence and SCZ all were significantly associated with ID in our cohort when compared to the genetically matched control population, thereby demonstrating the contribution of common low-risk variants to intellectual disability. This observation could be in part because most of our ID patients had mild ID. Indeed, the highest heritability explained (2.1%) was observed with EDU PRS in mild ID. The EDU PRS has been reported to explain 2.9% of the heritability of educational attainment in a population sample independent of the original GWAS . Our results suggest that mild ID might be just a continuum of the population distribution of cognitive capacity and support the hypothesis of the polygenic background. The observation that the heritability explained by EDU PRS is clearly smaller in severe ID (0.5%) supports the earlier epidemiological findings that the genetic background of severe ID is different from mild ID , where penetrant mutations contribute more to the phenotype. The PRS for IQ was only slightly below the matched controls in mild ID. This was unexpected. The reason remains speculative, but could be contributed by the fact that the IQ PRS was generated from a smaller study samples ( n = 78,308) than the EDU score ( n = 293,723). After observing a significant association between the common variant load and ID, we hypothesized that PRSs would be different in those individuals in whom a likely pathogenic variant was identified and those where such variants were not identified. However, such a difference was not observed, not even a suggestive trend (Supplementary Figure ). This observation could be explained by assuming that rare high-risk variants and the common variant load act additively to increase the risk of ID. Another explanation could be that there still might be other unidentified strong or moderate variants explaining the phenotype in many of the cases in which we did not identify a causative variant. We explored this hypothesis by grouping patients into the Other high impact variant category if they carried a PTV, CNV or damaging missense mutation in loss of function intolerant genes not previously linked to NDDs, but did not observe a difference in PRSs in that group either (Supplementary Figure ). An additive effect of high impact rare variants and common variant polygenic load has recently been suggested in the genetic etiology of ASD , our data suggest a similar genetic architecture for ID. Finally, we studied if some variants enriched in Finland in the relatively recent bottleneck would be associated with ID in our cohort. We conclusively identified a recessive variant in the CRADD gene enriched in Finland in three NFID patients and one NDD patient from the population NDD cohorts (Table ). The allele frequency of this variant is 50× higher in the Finnish population than in non-Finnish Europeans. Recently recessive variants in CRADD have been reported in six patients from four families with megalencephaly, frontal predominant pachygyria, intellectual disability, and seizures . All three of our patients had pachygyria, consistent with previously reported cases . One of the patients identified in Di Donate et al. had Finnish origins and carries exactly the same homozygotic variant as our patients, clearly demonstrating that the variant is a causal for a specific syndrome. We also observed three cases that had the same missense variant in homozygous state in the INTS1 gene (Table ). Recently a loss-of-function variants in INTS1 have been identified in three unrelated moderate to severe ID patients . One of our patients had mild ID and the two others had moderate/severe ID. In the dominant association analysis of Finnish enriched variants, none of the variants surpassed multiple testing correction (Supplementary Data ). However, one variant among the top 10 variants, a missense variant in the DENR gene, was totally absent in non-Finnish GnomAD individuals, is very rare in the Finnish population but enriched in Northern Finland (6.3 × 10 -4 in GnomAD Finns; 9.7 × 10 -4 in our Northern Controls and 3.1 × 10 -4 in Southern controls). The variant replicated in the Northern NDD cohort and was extremely rare in Southern Finnish NDD cases and controls (1/322 in cases and 1/1594 in controls) but had a high OR estimate consistent with associations in NFID and Northern NDD samples. Two DENR de novo missense variants have previously been identified in patients ascertained for autism spectrum disorder , . The case in Neale et al. had an IQ of 67 and the case in Haas et al, had a language delay and poor comprehension. Two of the three DENR variant carriers in the NFID cohort had a suspected or confirmed ASD diagnosis. Eight individuals in the population NDD cases were schizophrenia patients. The SCZ cases had low scores on processing speed and verbal learning cognitive tests as compared to population controls (Supplementary Figure ). ID or autism were not systematically diagnosed in the collection. Further studies are needed to conclusively determine if some of the other identified candidate genes are truly ID associated. Limitations of the study includes the fact that we used exome sequencing although non-coding rare variants also contribute to the etiology of ID . Also, we did not have exome sequencing for parents for 2/3 of the patients, but we performed sensitivity analyzes on the subset of patients, where we had full trios. These supported the conclusions that common variant polygenic load and rare variants might act additively and that mild ID is less affected by de novo/extremely rare variants in known ID genes (see total genetic diagnosis rate chapter and Supplementary Figure ). In conclusion, we demonstrate that a common variant polygenic load is a contributing factor in ID and more broadly characterized the genetic architecture of mild ID, which so far has been understudied. We also show that some damaging variants enriched in frequency in Finland contribute to intellectual disability and provide, yet another example of the power of utilizing population isolates such as Finland in disease gene mapping.
Samples Since January 2013 subjects for the NFID (Northern Finland Intellectual Disability) project have been recruited from the Northern Ostrobothnia Hospital District Center for Intellectual Disability Care and from the Department of Clinical Genetics of Oulu University Hospital. In January 2016 the recruitment was expanded to include all pediatric neurology units and centers for intellectual disability care in the special responsibility area of Oulu University Hospital. Subjects of all ages with either intellectual disability or pervasive and specific developmental disorders (ICD-10 codes F70-79 and F80-89, respectively) of unknown etiology were included. Individuals with copy number variations of unknown clinical significance or highly variable phenotypes were also included in order to uncover other possible factors of genetic etiology. Subjects were identified through hospital records and invited via mail to take part in the study. In addition, they were recruited during routine visits to any of the study centers. The cases have been evaluated and examined clinically by multi-professional teams. Depending on the situation in question the team may consist of psychologist, physician, speech and occupational therapist, physiotherapist, nurse and social worker. Standardized IQ tests that were used included different versions of following tests: Wechsler Preschool And Primary Scale Of Intelligence (WPPSI), Wechsler Intelligence Scale for Children (WISC) and Wechsler Adult Intelligence Scale (WAIS) for adults. In case of autism spectrum disorder the diagnoses were also based on multiprofessional evaluation and different, clinically used methods such as ADOS (Autism Diagnostic Observation Schedule), ADI-R (Autism Diagnostic Interview), and CARS (Childhood Autism Rating Scale). All research subjects and/or their legal guardians provided a written informed consent to participate in the study. DNA samples from the participants were extracted primarily from peripheral blood. In a few cases where a blood sample could not be obtained, DNA was extracted from saliva. The ethical committees of the Northern Ostrobothnia Hospital District and the Hospital District of Helsinki and Uusimaa approved the study. Clinical diagnostic tests varied considerably depending on the subject´s age, clinical diagnosis and phenotype. During the past 20 years, blood and urine metabolic screening tests, chromosome karyotyping, FMR1 CGG repeat analysis, electroencephalography (EEG) and brain computed tomography (CT) or magnetic resonance imaging (MRI) have been routinely performed on almost all individuals with remarkable developmental delay or intellectual disability. Array CGH and whole exome sequencing have been widely used for less than ten and three years, respectively. Identification of other neurodevelopmental disorder cases We identified individuals with neurodevelopmental disorder (NDD) phenotypes (intellectual disability, schizophrenia, autism and epilepsy; N = 636, NFNDD and SFNDD cases in Table ) among 5904 individuals with exome sequence data in the FINRISK study. FINRISK is a series of population-based health examination surveys carried out every 5 years since 1972 to monitor the risk of chronic diseases . The cohorts have been followed up for disease end-points using annual record linkage with the Finnish National Hospital Discharge Register and the National Causes-of-Death Register. Additional Finnish NDD cases were included from cohorts of schizophrenia and autism patients sequenced as part of the UK10K-study (i.e. subcohorts UK10K_NK_SCZ, UK10K_KUUSAMO_SCZ and UK10K_ASDFI) and a collection of autism patients from Southern Finland (AUTISM_ASDFI) (see Supplementary Data for cohort descriptions). We genetically matched each NDD case to five exome sequenced controls using the first 2 principal components (PCs). We further divided these cases and controls approximately to Northern Finnish NDD (NFNDD, Northern Finland NeuroDevelopmental Disorder) and Southern Finnish NDD (SFNDD, Southern Finland NeuroDevelopmental Disorder) cohorts based on principal component analysis (PCA). Regional prevalence of intellectual disability in Finland To estimate regional prevalence of ID and SCZ in Finland, we used The Social Insurance Institution of Finland provides social security coverage for Finnish residents. The Social Insurance Institution of Finland centrally provides all disability pensions in Finland and maintains a database of all residents on a disability pension and the reason for the pension. We requested the number of individuals over 16 years of age receiving a disability pension for ID or schizophrenia (SCZ) at the end of year 2016 in each of the 19 high-level administrative regions in Finland. We divided the number of beneficiaries by the population aged over 16 in each region to get a crude estimate of the relative prevalence of more severe SCZ and ID cases. The prevalence of schizophrenia particularly is higher in more detailed prevalence estimaties . Schizophrenia tends to be underdiagnosed in the first years of illness , and only 50% of patients with schizophrenia receive a disability pension after 5 years of initial diagnosis . CNV analysis To analyze the copy number variations (CNVs), we performed DNA Chip Array (Illumina HumanCoreExome v 12.0, Illumina PsychArray) based copy number analysis of 497 cases and 504 unaffected family members of the NFID cohort. To assess CNV frequencies in the general population, we used as controls a population-based cohort of 13,390 participants from the FINRISK study . CNV calls in controls were generated using raw data from the Illumina HumanCoreExome v12.0 and v12.1 chips. CNVs were called using a CNV pipeline powered by PennCNV for sensitive CNV calling. Adjacent CNVs of similar copy number were called as one if the adjoining region between the two calls was ≤20% of the joined CNV. To increase the confidence in the called CNVs, we considered only CNVs supported by at least 10 consecutive probes and which covered a genomic region of at least 100 kb, omitting known CNV artifacts regions . The large regional requirement was set to support analysis across the different DNA chips. Samples were excluded if they had: (1) a high variance (SD > 0.3) in intensity (1.5% in NFID; 5.6% in FINRISK), (2) a high (>0.005) drift of B allele frequency (0 additional samples in NFID; 0.2% in FINRISK), and (3) CNVs called in excess of 10 for one individual (10 samples in NFID; 8.9% in FINRISK). All called CNVs for the NFID cohort, both for patients and for unaffected family members, were manually curated. For the FINRISK population cohort, CNVs were manually curated if large (>500 kb) or if they fit into a category of interest relevant to study (see Identifying likely pathogenic mutations chapter below). Otherwise, CNVs of controls were rejected if at least 50% of the CNV overlapped a known artifact region , or had a poor coverage (≤1.08 SNPs per 10 kb). GWAS data processing All samples were genotyped in seven batches on either the Illumina CoreExome or Illumina PsychArray, which contains 480,000 common variants. The NFID samples were genotyped in three batches, one with Illumina CoreExome and two with PsychArray. FINRISK population controls were genotyped in five batches using Illumina CoreExome. We excluded markers that exhibited high missingness rates (>5%), low minor allele frequency (<1%), or failed a test of Hardy–Weinberg equilibrium ( p < 1e−9). We also excluded individuals with high rates of heterozygosity (>3sd from the mean), or a high proportion of missing genotypes (>5%). To control for population stratification, we merged the genotypes from individuals passing QC with HapMap III data from European (CEU), Asian (CHB + JPT), and African (YRI) populations. We then performed a PCA on this combined data and excluded population outliers not clustering with the Finnish samples We then merged genotyping batches one-by-one and repeated the QC procedures described above on the merged dataset. To prevent any potential batch effects in the merged data, we also excluded any markers that failed a test of differential missingness ( p < 1e−5, Fisher’s exact test) between the merged batches. Furthermore, during each round of merging we performed a association analysis (using a logistic mixed-model for individuals) between samples from each batch to identify markers where the minor allele frequency deviated significantly between batches ( p < 1e−5, score test). Finally, we removed related individuals (identity by descent > 0.185). We used a custom Finnish imputation reference panel containing 1941 low-pass whole genomes (4.6×) and 1540 high coverage exomes. We used Shape-IT for pre-phasing and Impute-2 for imputation. Exome sequencing NFID cases were exome sequenced at the Broad Institute using Illumina Nextera Rapid Capture Exome-capture kit and sequenced with Illumina HiSeq2000 or 2500. NFID cases were jointly called with a collection of Finnish individuals collected as part of the Sequencing Initiative Suomi (SISU)-study ( www.sisuproject.fi ). The sequence data processing and variant calling has been described previously . See Supplemental Note for descriptions of cohorts used in the current study. We filtered samples with estimated contamination > 3% ( n = 590), chimeric reads > 3% ( n = 51), samples significantly deviating from other samples within each project/batch on selected metrics (transition/transversion ratio, insertion/deletion ratio, heterozygous/homozygous variant ratio, number of singletons, n = 243) and finally included only those with empirically confirmed ≥99% Finnish ancestry (described in Rivas et al. ). We first split the multiallelic variants in to bi-allelic variants. For genotype QC, we set the following genotypes to missing; genotype quality (GQ) < 20, read depth (DP) < 10, heterozygote allelic balance less than 20% or greater than 80%, homozygous reference alt reads ≥10%, alternate allele homozygous reference reads ≥10%. Variants were filtered out if Variant Quality Score Recalibration (VQSR) did not indicate PASS, the p -value from a test of Hardy–Weinberg Equilibrium (pHWE) < 1e−9 in controls (in females only in the X chromosome), SNP quality-by-depth (QD) < 2, INDEL QD < 3 or more than 20% of heterozygote calls had allelic balance out of the 20–80% range. To account for the different batches of exome sequencing we required a stringent genotype call rate ≥0.95 in cases and controls separately after genotype QC. All variant and genotype QC was performed using Hail and executed in the Google Cloud dataproc cluster. Finally, we ensured cases and controls were approximately independent by filtering such that all samples had a pairwise kinship coefficient < 0.0442 to every other sample. We estimated kinship coefficient using King and when possible we always retained cases rather than a related control ( N filtered = 1531). Variant annotation We annotated variants using VEP v.85 and the LOFTEE VEP plugin [ https://github.com/konradjk/loftee ] to filter likely false positive protein truncating variants (PTV). We considered variant annotations of the canonical (as defined by ENSEMBL) transcript only. A variant was considered to be a protein truncating variant (PTV) if LOFTEE predicted it to be a high confidence loss-of-function variant (stop-gained, splice site disrupting or frameshift) without any warning flags. Identifying likely pathogenic mutations As a basis for identifying Likely pathogenic variants, we used a gene list curated within the Deciphering Developmental Disorders study (DDD) and a gene list of 93 exome-wide significant genes from the latest DDD study meta-analysis of de novo variants . We downloaded a gene list curated within the DDD study [ https://decipher.sanger.ac.uk/ddd#ddgenes ] containing 1897 genes with varying degrees of evidence of mutations in those genes causing developmental delays. We further subset the list to only confirmed or probable developmental delay genes contributing to a brain/cognition phenotype. This gene set was further extended by a set of 93 genes with a significant excess of damaging de novo variants in the latest DDD meta-analysis . These two lists resulted in a total of 818 genes (Supplemental Table ). For each ID patient we searched for PTV or damaging missense (MPC ≥2 ) variants not observed (as homozygotes in recessive genes) in non-Finnish GnomAD individuals or in our control individuals. We used only non-Finnish GnomAD individuals, as all Finnish individuals in GnomAD are included in our control exome cohort. Variants were classified as Other high impact variants if the variant was a PTV (in PTV constrained gene, pLI > 0.95) or a damaging missense variant (MPC ≥2) in a gene that was not in the list of known genes (as above) and not observed in non-Finnish GnomAD individuals or in our control individuals. For homozygotes we used CADD score > 20 to filter to putatively damaging variants, as MPC score is a measure of heterozygous constraint. CADD was chosen as pathogenicity prediction method as CADD integrates multiple different prediction tools in to a single prediction score. CADD contains both conservation-based methods (e.g., GERP, Phastcons) as well as protein level scores (e.g., SIFT and Polyphen) . In homozygote variant filtering we required that the variant was not seen as homozygous in non-Finnish GnomAD samples or in our internal Finnish controls. In cases where we had parental exome data we further filtered the “likely pathogenic” variants if they were inherited from control parent or if clinical phenotype was clearly different than what has been reported in the literature (as assessed by clinical geneticist). The algorithm for identifying pathogenic mutations was implemented in Hail and executed in a Google Cloud dataproc cluster. All CNVs passing QC criteria were classified as either (1) likely pathogenic, (2) other high impact variant, or (3) uncertain. A “likely pathogenic” classification was assigned to deletions where the size was at least 1 Mb, and 500 kb for de novo deletions. All CNV types were additionally considered likely pathogenic (class i) when overlapping at least 75% with an established disease associated locus , or deleting an ID associated gene of interest (see above). CNVs were classified as “other high impact variant” (class 2) if both: (A) they were never seen in unaffected family members, population controls, or the high-quality variant set of the Database of Genomic Variants; and (B) they deleted a gene with a high probability of loss-of-function intolerance (pLI > 0.95). Otherwise, a CNV was classified as a variant of uncertain significance (class 3). Polygenic risk scores As SNP weights we used summary statistics from GWA studies of schizophrenia , IQ , and educational attainment . To avoid potential biases caused by non-random regional sampling of individuals in the GWA studies the summary statistics were generated after excluding all Finnish cohorts. For polygenic scoring we used only well-imputed and genotyped common SNPs (Impute 2 info ≥0.9, allele frequency > 0.05). We pruned the SNPs to a subset of uncorrelated SNPs ( r 2 < 0.1 within 500 kb) and used the remaining SNPs for calculating a polygenic risk score (PRS) for each individual by summing the product of beta from the summary statistics and the number of effect alleles (genotype dosage for imputed SNPs) over all SNPs. Our primary hypothesis testing used a PRS constructed from nominally significant variants ( p < 0.05) in the original GWAS study. The genetic scores were standardized to z -scores using Finnish population controls. For visualizing geographical differences in the PRSs within Finland, we subset the controls to those whose parents’ birthplaces were within 100 km of each other. An individual’s coordinates were set to the average of the parents’ birthplaces’ longitude and latitude. We smoothed the PRS across a map of Finland. At each map position we calculated weighted average by weighting each individual’s PRS by the inverse of the squared distance between the map point and the individual’s coordinate. Individuals within 50 km from the map point contributed equally to the map point, i.e., the full weight was given to those individuals independent of their exact distance from the map point. Association analysis To control for population stratification, we matched each case to its five genetically closest controls given by the first two PC’s using the optmatch R package. For replication and for studying the neurodevelopmental spectrum of candidate variants in the exome analysis, we identified neurodevelopmental (NDD) cases (ID, SCZ, and ASD) from the Finnish FINRISK population cohort as well as disease-specific collections sequenced in the UK10K study (SCZ and ASD) (Table ). Each NDD case was genetically mapped to its five closest controls that were not matched to NFID patients. For the dominant association analysis, we used both Fisher’s exact test and Firth bias corrected logistic regression using the four first PC’s as covariates. We meta-analyzed the results across the three cohorts (NFID, North NDD and South NDD) using Mantel–Haenzel meta-analysis (rma.mh in metaphor R package) for Fisher’s analysis and a sample size weighted meta-analysis for Firth . For the recessive analysis we used a recessive allele frequency test (RAFT) , which takes the population allele frequency of the variant tested into account to estimate the probability of observing as many cases and controls as homozygotes under the null. As we genetically matched all cases to controls we present the analysis results from Fisher’s exact test and present Mantel–Haenzel meta-analysis and Firth results in the supplement. Association analyses were performed using Hail and executed in a Google Cloud dataproc cluster. Enrichment analysis For testing if different classes of variants were enriched in cases vs. controls we used Fisher’s exact test and for significant variant classes we estimated the variance explained by Nagelkerke’s pseudo r 2 . For the CNV analysis, we used the same cases and controls as in the exome analysis where GWAS data was available (433 cases and 1100 controls passing QC for CNV analysis). Association analysis was performed testing carrier ratios using Fisher’s exact test. The relevant categories were: (1) CNVs overlapping one of DECIPHER’s syndromic regions (2) deletions overlapping a known developmental delay gene (Supplementary Data ), and (3) deletions overlapping a gene with high probability of protein truncating variant intolerance (pLI > 0.95) . Heritability estimation We estimated the variance explained by different variant categories by fitting a logistic model and computing Nagelkerke’s pseudo r 2 from the fitted full and null models. Case/control status was used as a dependent variable and as an explanatory variable we used either a binary indicator for presence of variant in a given category (likely diagnostic or other high impact) or a continuous variable for PRS variance estimation. As we observed geographical differences in all evaluated PRSs we corrected for the first four PCs even after genetic matching of cases and controls to account for any residual stratification (i.e., the null model included the first four PCs). Confidence intervals for r 2 were estimated using adjusted bootstrap percentile method by drawing 5000 bootstrap samples and computing the r 2 for each sample. We compared the variance explained for the whole ID cohort and also in mild and severe ID separately. As mild and severe ID have different population prevalence we transformed the observed scale variance explained to the liability scale . We used the population prevalence from a cumulative normal distribution function with mean 100 and standard deviation 15. Prevalence of 1.94%, 1.91% and 0.034% were used for all ID (IQ < 70), mild ID (50 ≤ IQ < 70) and other more severe ID combined (IQ < 50), respectively. Code availability All code used within the manuscript for all analyses is available from the corresponding author upon reasonable request. Reporting summary Further information on experimental design is available in the linked to this article.
Since January 2013 subjects for the NFID (Northern Finland Intellectual Disability) project have been recruited from the Northern Ostrobothnia Hospital District Center for Intellectual Disability Care and from the Department of Clinical Genetics of Oulu University Hospital. In January 2016 the recruitment was expanded to include all pediatric neurology units and centers for intellectual disability care in the special responsibility area of Oulu University Hospital. Subjects of all ages with either intellectual disability or pervasive and specific developmental disorders (ICD-10 codes F70-79 and F80-89, respectively) of unknown etiology were included. Individuals with copy number variations of unknown clinical significance or highly variable phenotypes were also included in order to uncover other possible factors of genetic etiology. Subjects were identified through hospital records and invited via mail to take part in the study. In addition, they were recruited during routine visits to any of the study centers. The cases have been evaluated and examined clinically by multi-professional teams. Depending on the situation in question the team may consist of psychologist, physician, speech and occupational therapist, physiotherapist, nurse and social worker. Standardized IQ tests that were used included different versions of following tests: Wechsler Preschool And Primary Scale Of Intelligence (WPPSI), Wechsler Intelligence Scale for Children (WISC) and Wechsler Adult Intelligence Scale (WAIS) for adults. In case of autism spectrum disorder the diagnoses were also based on multiprofessional evaluation and different, clinically used methods such as ADOS (Autism Diagnostic Observation Schedule), ADI-R (Autism Diagnostic Interview), and CARS (Childhood Autism Rating Scale). All research subjects and/or their legal guardians provided a written informed consent to participate in the study. DNA samples from the participants were extracted primarily from peripheral blood. In a few cases where a blood sample could not be obtained, DNA was extracted from saliva. The ethical committees of the Northern Ostrobothnia Hospital District and the Hospital District of Helsinki and Uusimaa approved the study. Clinical diagnostic tests varied considerably depending on the subject´s age, clinical diagnosis and phenotype. During the past 20 years, blood and urine metabolic screening tests, chromosome karyotyping, FMR1 CGG repeat analysis, electroencephalography (EEG) and brain computed tomography (CT) or magnetic resonance imaging (MRI) have been routinely performed on almost all individuals with remarkable developmental delay or intellectual disability. Array CGH and whole exome sequencing have been widely used for less than ten and three years, respectively.
We identified individuals with neurodevelopmental disorder (NDD) phenotypes (intellectual disability, schizophrenia, autism and epilepsy; N = 636, NFNDD and SFNDD cases in Table ) among 5904 individuals with exome sequence data in the FINRISK study. FINRISK is a series of population-based health examination surveys carried out every 5 years since 1972 to monitor the risk of chronic diseases . The cohorts have been followed up for disease end-points using annual record linkage with the Finnish National Hospital Discharge Register and the National Causes-of-Death Register. Additional Finnish NDD cases were included from cohorts of schizophrenia and autism patients sequenced as part of the UK10K-study (i.e. subcohorts UK10K_NK_SCZ, UK10K_KUUSAMO_SCZ and UK10K_ASDFI) and a collection of autism patients from Southern Finland (AUTISM_ASDFI) (see Supplementary Data for cohort descriptions). We genetically matched each NDD case to five exome sequenced controls using the first 2 principal components (PCs). We further divided these cases and controls approximately to Northern Finnish NDD (NFNDD, Northern Finland NeuroDevelopmental Disorder) and Southern Finnish NDD (SFNDD, Southern Finland NeuroDevelopmental Disorder) cohorts based on principal component analysis (PCA).
To estimate regional prevalence of ID and SCZ in Finland, we used The Social Insurance Institution of Finland provides social security coverage for Finnish residents. The Social Insurance Institution of Finland centrally provides all disability pensions in Finland and maintains a database of all residents on a disability pension and the reason for the pension. We requested the number of individuals over 16 years of age receiving a disability pension for ID or schizophrenia (SCZ) at the end of year 2016 in each of the 19 high-level administrative regions in Finland. We divided the number of beneficiaries by the population aged over 16 in each region to get a crude estimate of the relative prevalence of more severe SCZ and ID cases. The prevalence of schizophrenia particularly is higher in more detailed prevalence estimaties . Schizophrenia tends to be underdiagnosed in the first years of illness , and only 50% of patients with schizophrenia receive a disability pension after 5 years of initial diagnosis .
To analyze the copy number variations (CNVs), we performed DNA Chip Array (Illumina HumanCoreExome v 12.0, Illumina PsychArray) based copy number analysis of 497 cases and 504 unaffected family members of the NFID cohort. To assess CNV frequencies in the general population, we used as controls a population-based cohort of 13,390 participants from the FINRISK study . CNV calls in controls were generated using raw data from the Illumina HumanCoreExome v12.0 and v12.1 chips. CNVs were called using a CNV pipeline powered by PennCNV for sensitive CNV calling. Adjacent CNVs of similar copy number were called as one if the adjoining region between the two calls was ≤20% of the joined CNV. To increase the confidence in the called CNVs, we considered only CNVs supported by at least 10 consecutive probes and which covered a genomic region of at least 100 kb, omitting known CNV artifacts regions . The large regional requirement was set to support analysis across the different DNA chips. Samples were excluded if they had: (1) a high variance (SD > 0.3) in intensity (1.5% in NFID; 5.6% in FINRISK), (2) a high (>0.005) drift of B allele frequency (0 additional samples in NFID; 0.2% in FINRISK), and (3) CNVs called in excess of 10 for one individual (10 samples in NFID; 8.9% in FINRISK). All called CNVs for the NFID cohort, both for patients and for unaffected family members, were manually curated. For the FINRISK population cohort, CNVs were manually curated if large (>500 kb) or if they fit into a category of interest relevant to study (see Identifying likely pathogenic mutations chapter below). Otherwise, CNVs of controls were rejected if at least 50% of the CNV overlapped a known artifact region , or had a poor coverage (≤1.08 SNPs per 10 kb).
All samples were genotyped in seven batches on either the Illumina CoreExome or Illumina PsychArray, which contains 480,000 common variants. The NFID samples were genotyped in three batches, one with Illumina CoreExome and two with PsychArray. FINRISK population controls were genotyped in five batches using Illumina CoreExome. We excluded markers that exhibited high missingness rates (>5%), low minor allele frequency (<1%), or failed a test of Hardy–Weinberg equilibrium ( p < 1e−9). We also excluded individuals with high rates of heterozygosity (>3sd from the mean), or a high proportion of missing genotypes (>5%). To control for population stratification, we merged the genotypes from individuals passing QC with HapMap III data from European (CEU), Asian (CHB + JPT), and African (YRI) populations. We then performed a PCA on this combined data and excluded population outliers not clustering with the Finnish samples We then merged genotyping batches one-by-one and repeated the QC procedures described above on the merged dataset. To prevent any potential batch effects in the merged data, we also excluded any markers that failed a test of differential missingness ( p < 1e−5, Fisher’s exact test) between the merged batches. Furthermore, during each round of merging we performed a association analysis (using a logistic mixed-model for individuals) between samples from each batch to identify markers where the minor allele frequency deviated significantly between batches ( p < 1e−5, score test). Finally, we removed related individuals (identity by descent > 0.185). We used a custom Finnish imputation reference panel containing 1941 low-pass whole genomes (4.6×) and 1540 high coverage exomes. We used Shape-IT for pre-phasing and Impute-2 for imputation.
NFID cases were exome sequenced at the Broad Institute using Illumina Nextera Rapid Capture Exome-capture kit and sequenced with Illumina HiSeq2000 or 2500. NFID cases were jointly called with a collection of Finnish individuals collected as part of the Sequencing Initiative Suomi (SISU)-study ( www.sisuproject.fi ). The sequence data processing and variant calling has been described previously . See Supplemental Note for descriptions of cohorts used in the current study. We filtered samples with estimated contamination > 3% ( n = 590), chimeric reads > 3% ( n = 51), samples significantly deviating from other samples within each project/batch on selected metrics (transition/transversion ratio, insertion/deletion ratio, heterozygous/homozygous variant ratio, number of singletons, n = 243) and finally included only those with empirically confirmed ≥99% Finnish ancestry (described in Rivas et al. ). We first split the multiallelic variants in to bi-allelic variants. For genotype QC, we set the following genotypes to missing; genotype quality (GQ) < 20, read depth (DP) < 10, heterozygote allelic balance less than 20% or greater than 80%, homozygous reference alt reads ≥10%, alternate allele homozygous reference reads ≥10%. Variants were filtered out if Variant Quality Score Recalibration (VQSR) did not indicate PASS, the p -value from a test of Hardy–Weinberg Equilibrium (pHWE) < 1e−9 in controls (in females only in the X chromosome), SNP quality-by-depth (QD) < 2, INDEL QD < 3 or more than 20% of heterozygote calls had allelic balance out of the 20–80% range. To account for the different batches of exome sequencing we required a stringent genotype call rate ≥0.95 in cases and controls separately after genotype QC. All variant and genotype QC was performed using Hail and executed in the Google Cloud dataproc cluster. Finally, we ensured cases and controls were approximately independent by filtering such that all samples had a pairwise kinship coefficient < 0.0442 to every other sample. We estimated kinship coefficient using King and when possible we always retained cases rather than a related control ( N filtered = 1531).
We annotated variants using VEP v.85 and the LOFTEE VEP plugin [ https://github.com/konradjk/loftee ] to filter likely false positive protein truncating variants (PTV). We considered variant annotations of the canonical (as defined by ENSEMBL) transcript only. A variant was considered to be a protein truncating variant (PTV) if LOFTEE predicted it to be a high confidence loss-of-function variant (stop-gained, splice site disrupting or frameshift) without any warning flags.
As a basis for identifying Likely pathogenic variants, we used a gene list curated within the Deciphering Developmental Disorders study (DDD) and a gene list of 93 exome-wide significant genes from the latest DDD study meta-analysis of de novo variants . We downloaded a gene list curated within the DDD study [ https://decipher.sanger.ac.uk/ddd#ddgenes ] containing 1897 genes with varying degrees of evidence of mutations in those genes causing developmental delays. We further subset the list to only confirmed or probable developmental delay genes contributing to a brain/cognition phenotype. This gene set was further extended by a set of 93 genes with a significant excess of damaging de novo variants in the latest DDD meta-analysis . These two lists resulted in a total of 818 genes (Supplemental Table ). For each ID patient we searched for PTV or damaging missense (MPC ≥2 ) variants not observed (as homozygotes in recessive genes) in non-Finnish GnomAD individuals or in our control individuals. We used only non-Finnish GnomAD individuals, as all Finnish individuals in GnomAD are included in our control exome cohort. Variants were classified as Other high impact variants if the variant was a PTV (in PTV constrained gene, pLI > 0.95) or a damaging missense variant (MPC ≥2) in a gene that was not in the list of known genes (as above) and not observed in non-Finnish GnomAD individuals or in our control individuals. For homozygotes we used CADD score > 20 to filter to putatively damaging variants, as MPC score is a measure of heterozygous constraint. CADD was chosen as pathogenicity prediction method as CADD integrates multiple different prediction tools in to a single prediction score. CADD contains both conservation-based methods (e.g., GERP, Phastcons) as well as protein level scores (e.g., SIFT and Polyphen) . In homozygote variant filtering we required that the variant was not seen as homozygous in non-Finnish GnomAD samples or in our internal Finnish controls. In cases where we had parental exome data we further filtered the “likely pathogenic” variants if they were inherited from control parent or if clinical phenotype was clearly different than what has been reported in the literature (as assessed by clinical geneticist). The algorithm for identifying pathogenic mutations was implemented in Hail and executed in a Google Cloud dataproc cluster. All CNVs passing QC criteria were classified as either (1) likely pathogenic, (2) other high impact variant, or (3) uncertain. A “likely pathogenic” classification was assigned to deletions where the size was at least 1 Mb, and 500 kb for de novo deletions. All CNV types were additionally considered likely pathogenic (class i) when overlapping at least 75% with an established disease associated locus , or deleting an ID associated gene of interest (see above). CNVs were classified as “other high impact variant” (class 2) if both: (A) they were never seen in unaffected family members, population controls, or the high-quality variant set of the Database of Genomic Variants; and (B) they deleted a gene with a high probability of loss-of-function intolerance (pLI > 0.95). Otherwise, a CNV was classified as a variant of uncertain significance (class 3).
As SNP weights we used summary statistics from GWA studies of schizophrenia , IQ , and educational attainment . To avoid potential biases caused by non-random regional sampling of individuals in the GWA studies the summary statistics were generated after excluding all Finnish cohorts. For polygenic scoring we used only well-imputed and genotyped common SNPs (Impute 2 info ≥0.9, allele frequency > 0.05). We pruned the SNPs to a subset of uncorrelated SNPs ( r 2 < 0.1 within 500 kb) and used the remaining SNPs for calculating a polygenic risk score (PRS) for each individual by summing the product of beta from the summary statistics and the number of effect alleles (genotype dosage for imputed SNPs) over all SNPs. Our primary hypothesis testing used a PRS constructed from nominally significant variants ( p < 0.05) in the original GWAS study. The genetic scores were standardized to z -scores using Finnish population controls. For visualizing geographical differences in the PRSs within Finland, we subset the controls to those whose parents’ birthplaces were within 100 km of each other. An individual’s coordinates were set to the average of the parents’ birthplaces’ longitude and latitude. We smoothed the PRS across a map of Finland. At each map position we calculated weighted average by weighting each individual’s PRS by the inverse of the squared distance between the map point and the individual’s coordinate. Individuals within 50 km from the map point contributed equally to the map point, i.e., the full weight was given to those individuals independent of their exact distance from the map point.
To control for population stratification, we matched each case to its five genetically closest controls given by the first two PC’s using the optmatch R package. For replication and for studying the neurodevelopmental spectrum of candidate variants in the exome analysis, we identified neurodevelopmental (NDD) cases (ID, SCZ, and ASD) from the Finnish FINRISK population cohort as well as disease-specific collections sequenced in the UK10K study (SCZ and ASD) (Table ). Each NDD case was genetically mapped to its five closest controls that were not matched to NFID patients. For the dominant association analysis, we used both Fisher’s exact test and Firth bias corrected logistic regression using the four first PC’s as covariates. We meta-analyzed the results across the three cohorts (NFID, North NDD and South NDD) using Mantel–Haenzel meta-analysis (rma.mh in metaphor R package) for Fisher’s analysis and a sample size weighted meta-analysis for Firth . For the recessive analysis we used a recessive allele frequency test (RAFT) , which takes the population allele frequency of the variant tested into account to estimate the probability of observing as many cases and controls as homozygotes under the null. As we genetically matched all cases to controls we present the analysis results from Fisher’s exact test and present Mantel–Haenzel meta-analysis and Firth results in the supplement. Association analyses were performed using Hail and executed in a Google Cloud dataproc cluster.
For testing if different classes of variants were enriched in cases vs. controls we used Fisher’s exact test and for significant variant classes we estimated the variance explained by Nagelkerke’s pseudo r 2 . For the CNV analysis, we used the same cases and controls as in the exome analysis where GWAS data was available (433 cases and 1100 controls passing QC for CNV analysis). Association analysis was performed testing carrier ratios using Fisher’s exact test. The relevant categories were: (1) CNVs overlapping one of DECIPHER’s syndromic regions (2) deletions overlapping a known developmental delay gene (Supplementary Data ), and (3) deletions overlapping a gene with high probability of protein truncating variant intolerance (pLI > 0.95) .
We estimated the variance explained by different variant categories by fitting a logistic model and computing Nagelkerke’s pseudo r 2 from the fitted full and null models. Case/control status was used as a dependent variable and as an explanatory variable we used either a binary indicator for presence of variant in a given category (likely diagnostic or other high impact) or a continuous variable for PRS variance estimation. As we observed geographical differences in all evaluated PRSs we corrected for the first four PCs even after genetic matching of cases and controls to account for any residual stratification (i.e., the null model included the first four PCs). Confidence intervals for r 2 were estimated using adjusted bootstrap percentile method by drawing 5000 bootstrap samples and computing the r 2 for each sample. We compared the variance explained for the whole ID cohort and also in mild and severe ID separately. As mild and severe ID have different population prevalence we transformed the observed scale variance explained to the liability scale . We used the population prevalence from a cumulative normal distribution function with mean 100 and standard deviation 15. Prevalence of 1.94%, 1.91% and 0.034% were used for all ID (IQ < 70), mild ID (50 ≤ IQ < 70) and other more severe ID combined (IQ < 50), respectively.
All code used within the manuscript for all analyses is available from the corresponding author upon reasonable request.
Further information on experimental design is available in the linked to this article.
Supplementary Information Peer Review File Description of Additional Supplementary Files Supplementary Data 1 Supplementary Data 2 Supplementary Data 3 Supplementary Data 4 Supplementary Data 5 Supplementary Data 6 Reporting Summary Source Data
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Feline eosinophilic sclerosing fibroplasia associated with T-/natural killer-cell lymphoma | e76e1293-8d1b-45ac-92a5-46a65841d7f9 | 11874600 | Anatomy[mh] | Archived surgical biopsy and necropsy samples of 17 cats with a histologic diagnosis of FESF and intralesional lymphoproliferative disease were collected at the Veterinary University of Vienna, Austria (9 cases), the Schwarzman Animal Medical Center, New York, USA (2 cases), and the University of Tennessee College of Veterinary Medicine, Knoxville, USA (6 cases). Sections of formalin-fixed paraffin-embedded tissues were stained with hematoxylin and eosin. Immunohistochemistry was performed on formalin-fixed paraffin-embedded samples for CD3, CD20, CD56, CD57, granzyme B, and MUM1 antigen on an automated immunostainer (Lab Vision AS 360, Lab Vision, Thermo-Fisher Scientific, Fremont, California) ( Supplemental Table S1 ). Horseradish peroxidase polymer (ImmunoLogic, Duiven, The Netherlands) was applied and visualized with DAB Quanto Substrate System (Lab Vision, Thermo-Fisher Scientific). Normal tissues from feline spleen, lymph node, and small intestine were used as a positive control. Antibody specificity for CD56, CD57, and granzyme B in feline lymphoid cells has already been evaluated. , , The primary antibody was omitted from negative controls, and in addition, a feline ileocecal B-cell lymphoma served as a control. For the polymerase chain reaction (PCR)-based lymphocyte clonality assay, total genomic DNA was extracted from archived surgical biopsy and necropsy tissue samples with 200 µl elution buffer using a commercial kit following the manufacturers’ instructions (E.Z.N.A. Tissue DNA Kit, Omega Biotech, Norcross, Georgia). Genomic DNA concentration and quality were determined using the NanoDrop 2000c spectrophotometer (Thermo-Fisher Scientific, Waltham, Massachusetts) in pedestal mode. The threshold was set to 30 ng/µl with desired 260/280 ratios of 1.8 to 2.0 and 260/230 ratios above or equal 2 (2.0-2.2). The genomic DNA samples were assayed by amplifying a 189 base pair fragment of the feline androgen receptor gene; the immunoglobulin heavy chain (IGH)-VDJ gene rearrangements with the primer sets IGH-VDJ, IGH-DJ, Kde, and IGL; and the T-cell receptor gamma ( TRG ) chain VJ gene rearrangements with the primer sets TRG-J1, TRG-J2, and TRG-J3. , , , Each PCR reaction was carried out in triplicate including positive and negative PCR controls in each run. , After PCR, 10 µl of DNA Dilution Buffer (Qiagen, Hilden, Germany) was added to each PCR reaction and size separated using the QIAxcel Advanced System capillary electrophoresis analyzer with the QIAxcel DNA High Resolution Kit and the QX Alignment Marker 15 bp/1000 bp (Qiagen). The presence and size of obtained PCR products were accurately determined using QIAxcel ScreenGel Software (Qiagen). Identical PCR triplicates verified the reproducibility of the clonality patterns, which were interpreted as described previously. , ,
The study population comprised 12 of 17 domestic shorthair cats, 3 of 17 domestic longhair cats, 1 of 17 mixed breed cat, and 1 of 17 Maine coon cat; 8 of 17 male castrated and 8 of 17 spayed female animals as well as 1 of 17 intact female cat. The median age of the cats was 10.6 years, ranging from 5 to 15 years. Of 13 cases for which information was available, 9 animals were euthanized and 4 animals died naturally. Nine cats died within 3 months after clinical presentation. The survival time of 4 cats treated with chemotherapy was 4, 9, 10, and 12 months. A review of complete blood count findings revealed that 12 of 15 cats in this case series had peripheral eosinophilia. The lesions were focal or multifocally localized in mesenteric lymph nodes (13 of 17 cases), small intestine (9 of 17 cases), stomach (2 of 17 cases), and liver (1 of 17 cases). Histologically, all gastrointestinal and mass lesions contained a variable degree of fibrosis partially composed of branching collagen trabecular structures and activated fibroblasts . This finding was accompanied by eosinophilic infiltration of variable severity . The inflammation ranged from mucosal to transmural and was multifocal, coalescing, or diffuse. Enlarged mesenteric lymph nodes contained focal to multifocal eosinophilic inflammation and prominent sclerosis. In addition, lesions were accompanied by variable amounts of lymphoid cells with nuclei ranging from 1.5 to 2 times the diameter of an erythrocyte (interpreted as intermediate sized) with minimal to moderate cellular atypia. These cells contained scant cytoplasm; round to oval and occasionally indented or clefted nuclei with dispersed chromatin; and a single, commonly centrally located, sometimes prominent nucleolus . The mitotic count ranged from 1 to 19 mitotic figures per 10 high-power field (HPF) with an ocular field number of 22 (0.237 mm 2 ) each (1-19 mitotic figures/2.37 mm2). Representative cases with these histopathologic characteristics are depicted in . In addition, in some animals, lymphoma without FESF lesions was localized apart from the gastrointestinal tract, specifically in the liver, kidney, lung, and cranial mediastinal lymph node. Information about patient specifications, survival times, chemotherapy, and lesion sites are provided in . CD56 immunohistochemistry revealed variable amounts of strong membranous immunolabeling in 14 of 17 cases. Of these 14 CD56 + cases, 7 of 14 were CD3 + indicating natural killer T-cells (NKT cells) and 7 were CD3 − fitting for natural killer (NK) cells. The 3 cases that were immunohistochemically negative for CD56 antigen, demonstrated strong cytoplasmic CD3 immunolabeling. Of these 3 T-cell cases, 2 were granzyme B − and 1 case was granzyme B + . Five of the 7 NKT cases as well as 5 of the 7 NK cases were granzyme B + . Neoplastic round cell populations were consistently immunohistochemically negative for CD20, CD57, and MUM1 antigen. Characteristics of the most common immunohistochemical phenotypes are depicted in . Detailed results of immunolabeling are shown in . Clonality testing performed in all 17 patients showed clonality for TRG in 6 of 17 cases. The IGH-VDJ gene of all samples showed a polyclonal/negative/pseudoclonal result. A polyclonal/pseudoclonal TRG result was seen in the remaining 11 of 17 cases. Of the TRG clonal PCR results, 2 of 6 cases were monoclonal with a polyclonal background, and 2 cases each were biclonal (2 of 6 cases) and oligoclonal (2 of 6 cases). The 2 monoclonal cases with polyclonal background were represented by 1 CD3 + CD56 + granzyme B + case, which was interpreted as NKT origin. The other case was CD3 − CD56 + granzyme B + . The 2 biclonal cases were CD3 + CD56 − cells—one of which was granzyme B + and the other a granzyme B − T-cell lymphoma. The oligoclonal samples were represented by CD3 + CD56 + granzyme B − NKT cells and CD3 + CD56 − granzyme B − T-cells, respectively. Detailed results of lymphocyte clonality PCR testing for TRG and proposed entity are shown in .
Despite the initial suspicion that FESF is always non-neoplastic, the current case series provides evidence that lymphoma can accompany eosinophilic inflammation and sclerosing fibrosis within the feline gastrointestinal tract. To our knowledge, thus far, there is only 1 case report of FESF and concurrent lymphoma. The lymphoma in that case emerged 7 months after surgical resection of an FESF-associated jejunal mass lesion and was concurrently in the jejunum and gastric serosa with typical FESF lesions. However, the lymphoma subtype of that case was not further specified. The etiology of FESF is currently unknown, and the potential role of pathogens observed within the lesions remains unclear. A genetic predisposition for the proliferative response stimulated by unknown antigens has been suggested. The inconsistent presence of infectious agents indicates that the pathogenesis of this proliferative, inflammatory disease may be multifactorial with potential contributing factors including food allergy or intolerance, and intestinal microbiota dysbiosis. Pathogens identified in previous studies include various bacteria, , Toxoplasma gondii , phycomycetes, zygomycete fungi, and feline immunodeficiency virus. Other viral agents such as feline leukemia virus, feline coronavirus, and feline herpesvirus type 1 have not been detected thus far. Specific viruses have a carcinogenic potential in human and various animal species, and some (eg, retroviruses such as feline leukemia virus and feline immunodeficiency virus) may induce lymphoproliferative disease. An unidentified viral infection can be considered as a potential trigger of lymphoma following lymphoproliferation in this subset of FESF cases and additional investigative studies should be performed. A review of complete blood count findings revealed that 12 of 15 cats in this case series had peripheral eosinophilia, which is also frequently demonstrated in cats with FESF. , , , , Intralesional eosinophils can be found regularly but variably in FESF, suggesting that they may play a central role in pathogenesis due to proinflammatory and immunomodulatory activities. Some authors suggest that FESF could also represent an unusual manifestation of the feline eosinophilic granuloma complex. Eosinophils can promote neoplastic growth by releasing various factors that stimulate angiogenesis, inflammation, and tissue remodeling. Furthermore, eosinophils can produce interleukin-5, which stimulates proliferation of eosinophils and other inflammatory cells. The presence of intralesional eosinophils in T-cell lymphoma, at least in the canine peripheral T-cell lymphoma, is described and there are few reports of T-cell lymphoma associated with severe hypereosinophilic syndrome in cats, , demonstrating a close interaction between T-cells and eosinophils. In general, mast cell neoplasm, which is commonly associated with eosinophils, must be considered as a differential diagnosis for intestinal round cell neoplasia. A case series documented intestinal sclerosing mast cell neoplasm in cats, which were accompanied by eosinophilic infiltrates, but some authors suggest that these cases may instead represent an inflammatory process, such as FESF. , Blastic NK cell lymphoma/leukemia has been described in a cat, characterized by multisystemic infiltration of large, atypical round cells; however, eosinophil infiltration and fibrosis were not prevalent features. The neoplasm was in the subcutis, spleen, lymph nodes, bone marrow, and liver. The NK cells are characterized by the expression of CD56 antigen and lack of CD3 labeling. CD57 antigen represents another NK cell–associated surface protein in humans. Cytotoxic markers like granzyme B protein can be found in NK cells as well as T-cells. The NKT cells are defined by expression of both CD56 and CD3 antigen. Summarizing the results of immunolabeling in our cases, the neoplastic lymphoid cells were interpreted as either NK cells (7 of 17 cases), NKT cells (7 of 17 cases), or T-cells (3 of 17 cases). The NK cells play a significant role in preventing intracellular invasion of microorganisms by directly killing them without prior sensitization. The intestinal immune system comprises innate lymphoid cells including NK cells. Some authors propose that NK cell proliferation restricted to the gastrointestinal tract is most probably induced by local inflammation or an immune reaction. The NK cells are involved in promotion and inhibition of fibrogenesis. In addition, eosinophils seem to be linked to immune-mediated fibrosis. In human medicine, intestinal NK cell lymphoproliferative disorders are uncommon and designated as NK cell enteropathy or extranodal NKT cell lymphoma. The NK cell enteropathy is a benign, localized, lymphoproliferative disorder of NK cells in the gastrointestinal tract with spontaneous regression or persistence. In contrast, extranodal NKT cell lymphoma is a heterogeneous, clinically aggressive neoplasm that is almost always associated with Epstein-Barr virus. , Epstein-Barr virus has been serologically detected in cats, but the significance of infection is unclear. Of the 17 samples, 6 cases showed a clonal result for TRG . All IGH primer sets revealed no clonal result, so no cross-lineage phenomenon was present. The clonal TRG result was seen in the 3 T-cell lymphomas diagnosed (cases 12, 13, and 15), which showed a CD3 + CD56 − immunolabeling pattern. Of the 7 CD3 + CD56 + NKT cases, 2 cases (cases 3 and 6) showed a clonal result for TRG . A clonal result for all 7 NKT cases would be expected as T-cells are present, but to date, it is unclear whether feline lymphoma of NKT cells should demonstrate a clonal result for TRG . Six of 7 NK cell neoplasia cases showed no clonal result for TRG as expected. However, 1 CD3 − CD56 + granzyme B + NK case (case 17) had a monoclonal TRG result with a polyclonal background. This result should be evaluated further in an additional study. If treated appropriately with a multimodal approach, long survival times have been reported for some cats with FESF. Remission has been described following corticosteroid administration. However, definitive therapeutic guidelines have not yet been established. In our study, most cats (9 of 13 cases for which outcome information was available) were euthanized within 3 months of the initial clinical diagnosis due to gastrointestinal disease, indicating an aggressive process with a relatively poor prognosis. Four cats treated with chemotherapy showed a survival time between 4 and 12 months, which suggests that this therapeutic method may be helpful in some cases. However, its efficiency would need to be reproduced and validated in larger studies. This unique subtype of NK, NKT, or T-cell lymphoma should be considered as a differential diagnosis for gastrointestinal mass lesions and round cell tumors associated with FESF. We propose the term “eosinophilic sclerosing lymphoma” to intimate the similarities between FESF and this unique subtype of lymphoma. Further studies are required to better characterize the etiology, classification, outcome, and treatment response of this subset of FESF in order to optimize patient care.
sj-pdf-1-vet-10.1177_03009858241281911 – Supplemental material for Feline eosinophilic sclerosing fibroplasia associated with T-/natural killer-cell lymphoma Supplemental material, sj-pdf-1-vet-10.1177_03009858241281911 for Feline eosinophilic sclerosing fibroplasia associated with T-/natural killer-cell lymphoma by Andrea Klang, Christof A. Bertram, Taryn A. Donovan, Linden E. Craig, Ingrid Walter, Birgitt Wolfesberger, Brigitte Degasperi, Elisabeth Baszler, Barbara C. Rütgen, Sabine E. Hammer and Andrea Fuchs-Baumgartinger in Veterinary Pathology
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Study design considerations to assess the impact of potential | d24a2a79-2297-42bc-942d-41619304afba | 10176012 | Internal Medicine[mh] | STUDIES IN ALTERNATIVE PATIENT POPULATIONS DUE TO INTERACTING CONCOMITANT THERAPIES When a new oncologic drug is not expected to be cytotoxic, genotoxic, or target a specific genetic alteration found in only the intended study population, it may be reasonable to conduct FIH studies in healthy subjects or in patients who do not routinely require the interacting concomitant therapies. These data from the FIH study can then be leveraged to select doses to be conducted in a drug‐drug interaction (DDI) study. As such, DDI studies can be conducted in a separate study to help select the recommended dosing regimen of the new oncologic drug for intended patient population when administered with interacting concomitant therapies based on exposure matching. This approach was used for glasdegib, a Hedgehog pathway inhibitor, approved for the treatment of patients with newly diagnosed AML who are on nonintensive chemotherapy. In vitro studies indicated that glasdegib is metabolized by CYP3A4. Initially, dose escalation studies were conducted in patients with hematologic malignancies and solid tumors not requiring azole antifungals. These studies demonstrated a maximum tolerated dosage of 400 mg once daily (q.d.) in patients with hematological malignancies, dose proportional pharmacokinetics (PKs), and saturable pharmacodynamic (PD) activity at 100 mg q.d. A DDI study conducted to understand the effects of a strong CYP3A inhibitor on the PKs of glasdegib following a single dose of 200 mg showed that a strong CYP3A4 inhibitor (i.e., ketoconazole) increased glasdegib exposure by twofold. Given the saturable PDs observed at 100 mg, and a twofold increase in exposure with a strong CYP3A inhibitor, 100 mg q.d. was selected for the registration trial in patients with AML to provide an adequate safety margin for the increased glasdegib exposure with concomitant use of azole antifungals.
STUDIES IN THE INTENDED PATIENT POPULATION WHEN THE INTERACTING CONCOMITANT THERAPIES CANNOT BE AVOIDED FIH studies that need to be conducted in the intended patient population that require interacting concomitant therapies should be conducted with a large safety margin. Although most patients enrolled into these FIH studies will be administered an interacting concomitant therapy, a cohort of patients who will not receive the interacting concomitant therapy should be enrolled for comparative purposes, as they will provide critical PK, efficacy, and safety for the indicated patient population. This approach is illustrated by the FIH study in patients with relapsed or refractory acute leukemias for SNDX‐5613, a CYP3A4 substrate. The study included one arm with patients who required azole antifungals that are CYP3A4 inhibitors and another arm with patients that did not. Dosing for each arm were started at the same dose of 113 mg Q12h. Data from the first two dose levels indicated an increase in SDNX‐5613 exposure with strong CYP3A4 inhibitors of approximately twofold, and higher rates of adverse reactions, including QT prolongation. This approach poses several challenges, particularly the possibility of underestimating the risk for potential DDI when selecting a starting dose. It is important that the starting dose administered with the interacting medication have an adequate safety margin to support its use in FIH studies. In addition, different concomitant therapies within the same class (e.g., posaconazole vs. voriconazole) or the same CYP inhibitor in different dosage forms or dosing regimen may have different magnitudes of effect on the exposure of the new oncologic drug. For example, the exposure of ibrutinib varied with different formulations and dosing regimen of posaconazole, and with voriconazole and other strong CYP3A inhibitors. As such, early DDI studies or dose escalation studies with and without interfering drugs may not provide a complete assessment of the potential interactions, but can inform on the impact of concomitant medications on the recommended phase II dose during the course of development. FIH studies in patients who will be treated with a concomitant therapy should consider the following: Assess the potential for DDIs based on in vitro metabolic activity screens and/or in vivo DDI studies. These data will inform the selection of a safe starting/dose escalation plan, and/or the choice of medications to address the non‐disease morbidity. If proceeding without a separate DDI study, a cohort of patients without interacting concomitant therapy provides a comparison to assess the potential impact of the medications on the investigational drug. An appropriate dose escalation strategy to safely identify the recommended dosage(s) for further development of the new oncologic drug when co‐administered with the interacting concomitant therapy should be implemented. A staggered dose escalation approach may be incorporated into these FIH studies, wherein the safety, PD, and PK data from the initial cohorts are utilized to inform dosing in the interacting arm and subsequent dosing cohorts in both arms.
There are instances when a new oncologic drug is also a perpetrator of the DDI and potentially affect the exposure of the commonly used concomitant therapies, thus impact the safety or effectiveness of the concomitant drugs. Physiologically‐based PK (PBPK) modeling and simulations can be leveraged to understand the impact of potential DDIs and to provide dosage recommendations to be tested during clinical development. An example which highlights this approach is ivosidenib, a kinase inhibitor approved for the treatment of adult patients with AML with a susceptible IDH1 mutation. Ivosidenib exhibits nonlinear kinetics, is metabolized by CYP3A4, and induces CYP3A4. Ivosidenib is not only prone to interactions from strong CYP3A4 inhibitors and inducers, but it may in fact also decrease exposure to antifungal drugs that are CYP3A substrates and their effectiveness. The results from an in vivo DDI study showed that concurrent use of a strong CYP3A4 inhibitor (e.g., itraconazole) increased single‐dose ivosidenib exposure by 169%. This study was used as the basis for PBPK modeling and simulations to predict the effect of ivosidenib as a CYP3A inducer: multiple doses of ivosidenib could reduce the single‐dose exposure of a CYP3A4 sensitive substrate, such as midazolam by 83%, and the steady‐state exposure of itraconazole (also a CYP3A4 substrate) by 90%. The simulations also predicted an increase in the steady‐state exposure of ivosidenib by 3.8‐fold with a strong CYP3A4 inhibitor which itself is not a substrate of CYP3A4. Further, the PBPK simulations indicated a 1.9‐fold increase in ivosidenib with a moderate CYP3A4 inhibitor (e.g., fluconazole). The PBPK modeling formed the basis for the ivosidenib labeling recommendations to healthcare providers to avoid co‐administration of azole antifungals that are CYP3A4 substrates, including itraconazole and ketoconazole, as it may result in a loss of antifungal efficacy, and to reduce the dose of ivosidenib when co‐administered with a strong CYP3A inhibitor as it may increase exposure of ivosidenib and potentially increasing the severity and incidence of adverse reactions, including QT interval prolongation.
During drug development, it is critically important to identify the optimal doses of the new therapeutic for patients to assure safety and efficacy. For drugs that may be impacted by their concomitant medications, nonclinical and in vitro studies are key to understanding the potential risks for DDIs with a new oncologic drug and designing FIH studies to select doses that account for these DDI issues. Strategies, such as exploring the DDIs in healthy subjects or in patients with other cancers who do not require interacting concomitant therapies, where possible, or evaluating the drug in the intended patient population with additional strategies to safely evaluate the PKs, safety, and activity of the new oncology drug, have been successfully used to identify recommended dosage(s) for further clinical development and support labeling recommendations. These approaches help minimize exposure to toxic or ineffective dosages and help identify the recommended dosage(s) for the intended population who will be receiving interacting concomitant therapies.
No funding was received for this work.
The authors declared no competing interests for this work.
The opinions expressed in this manuscript are those of the authors and should not be interpreted as the position of the US Food and Drug Administration.
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Experience with comprehensive pharmacogenomic multi-gene panel in clinical practice: a retrospective single-center study | 200520dc-ba4e-47dc-85ad-c87323bc3d32 | 9284022 | Pharmacology[mh] | St. Catherine Specialty Hospital's electronic medical records were retrospectively reviewed to extract the data on patients who had undergone pharmacogenetic testing with the RightMed test. From September 1, 2018, to December 10, 2021, 373 tests were performed. Complete medical history was missing for 54 patients, so 319 patients were enrolled . The RightMed test was performed with buccal swabs, which were placed in a 1-mL saliva collection tube (RightMed test kit, ORACollectDx, DNA Genotek, Ottawa, ON, Canada). The DNA was analyzed by using the RightMedR panel with a TaqMan quantitative real-time PCR method and copy number variation analysis to determine the SNPs in the 27 targeted genes . Genomic DNA was analyzed with PCR using Thermo Fisher TaqMan® (Thermo Fisher, Waltham, MS, USA) and/or LGC Biosearch BHQ® (Hoddesdon, UK) probe-based methods. Haplotypes, or combinations of inherited variants on a chromosome, were annotated according to legacy nomenclature for the genes. The test does not detect all known and unknown variations in the genes tested, nor does the absence of a detectable variant (designated as *1 for genes encoding drug metabolizing enzymes) rule out the presence of other, non-detected variants. These assays cannot differentiate between the maternal and paternal chromosomes. In the cases where observed variants are associated with more than one haplotype, OneOme infers and reports the most likely diplotype based on published allele frequency and/or ethnicity data. Results of the DNA analysis were then generated in individual test reports available on OneOme’s HIPAA-secure portal. Complete medical history from the 319 enrolled patients was analyzed to find the data on the number of drugs in patients’ therapy. Patients were subcategorized into three groups: those who used up to 3 drugs (group 1), those who used between 4 and 8 drugs (group 2), and those who used 9 and more drugs (group 3). Pharmacogenomic test reports were analyzed according to the drugs the patient reported using. We assessed the number of drugs with known gene-drug interactions, the number of drugs with available genotype-based guidelines, and the number of drugs with significant gene-drug interactions according to the patients’ phenotype. The latter were then categorized with respect to major drug groups. Statistical analysis We used descriptive statistics to summarize genotype and phenotype data (drug metabolizer rates). Normality of the distribution was tested with the Kolmogorov-Smirnov test. The Kruskal-Wallis and Mann-Whitney test were used to assess the differences between the groups. Statistical analysis was performed with SPSS 23.0 (IBM, Armonk, NY, USA), with the significance level set at P < 0.05.
We used descriptive statistics to summarize genotype and phenotype data (drug metabolizer rates). Normality of the distribution was tested with the Kolmogorov-Smirnov test. The Kruskal-Wallis and Mann-Whitney test were used to assess the differences between the groups. Statistical analysis was performed with SPSS 23.0 (IBM, Armonk, NY, USA), with the significance level set at P < 0.05.
The samples were collected from 140 men and 179 women. The median age was 54 years (range 1-88 years). Women were significantly older than men (57 years vs 51 years; Mann-Whitney, P = 0.019). Out of 319 patients, 155 had up to 3 drugs in their therapy (group 1), 126 had between 4 and 8 drugs in therapy (group 2), while 38 patients had 9 or more drugs in their therapy (group 3). Group 1 patients were significantly younger than group 2 (Mann-Whitney test, P < 0.001) and group 3 patients (Mann-Whitney test, P < 0.001). Forty-six patients had no drugs in their therapy. When observing the complete data set, only 84 patients had no interactions between drugs in their therapy, while 235 (73.7%) patients had at least one gene-drug pair. Out of these 235 patients, 111 (34.8%) patients had 3 or more gene-drug pairs. For drugs in the therapy of 133 (56.7%) patients, there were available genotype-based prescribing guidelines, with 95 (40.4%) patients having at least one such drug in their therapy, 30 (12.8%) having two, 6 (2.6%) having three, and 2 (0.9%) having four. The pharmacogenetic analysis demonstrated that 139 (43.6%) patients had significant gene-drug interactions to at least one drug present in therapy, while 180 (56.4%) patients did not have significant gene-drug interactions. With respect to the therapeutic groups of drugs that were found to have significant gene-drug interactions, the highest frequency was observed for psychiatric drugs (47.6%), followed by gastroenterology drugs (25.5%), and cardiovascular drugs (18.6%) . A subgroup analysis was performed with respect to the number of drugs in patients’ therapy . In group 1 (n = 155), 77 (49.7%) patients had at least one gene-drug pair in their therapy. A genotype-based guideline was available for 34 (21.9%), and 33 (21.3%) patients had at least one actionable gene-drug interaction. In group 2 (n = 126), 120 (95.2%) patients had at least one actionable gene-drug pair. A genotype-based guideline was available for 69 (54.8%) patients, and 80 (63.5%) patients had at least one actionable gene-drug interaction. In group 3 (n = 38), all of the patients had at least one gene-drug interaction in their therapy. A genotype-based guideline was available for 30 (78.9%) patients, and 26 (68.4%) patients had at least one actionable gene-drug interaction.
The majority of our patients (73.7%) in our study had at least one gene-drug pair known to affect the pharmacologic properties of the drug, which indicates a growing need for the implementation of pharmacogenomics in patient care. The proportion of patients with gene-drug interactions increased with respect to the number of drugs in their therapy. This high percentage was reported by other groups as well. Elchynski et al reported this rate to be between 70% and 75% for patients who were genotyped for CYP2C19 and CYP2D6 . Overall, 46 (14.4%) patients in our study underwent pharmacogenomic testing preemptively, before using any drugs. Preemptive testing is already advocated as the best strategy to maximally utilize the pharmacogenomic tests . Prospective studies confirmed that this approach could be useful in the primary care setting. Van der Wouden et al reported that 24.2% of newly prescribed medications were actionable and required therapeutic adjustment in 2 years in the primary care setting . Similarly, Youssef et al reported this percentage to range between 19.1% and 21.1% . Bank et al reported it to be 23.6% . In our study, significant gene-drug pairs that can alter the pharmacologic effect of drugs were present in 139 (43.6%) patients. Due to the retrospective nature of the study and no available data on therapeutic intervention made after the test results were obtained, we cannot assess the prospective clinical utility of the performed pharmacogenomic tests and benefit to the patients. Furthermore, the presence of actionable interventions when found retrospectively should not be taken as an imperative to change a previously well-established therapy. Pharmacogenomic test results should be interpreted by professionals trained in the field who understand that the reasons for the history of adverse drug reactions or the lack of therapeutic effect do not necessarily include only the patient's genotype, but also the epigenetic changes, comorbidities, age, and other factors . As demonstrated by our results, younger patients used less drugs in their therapy compared with older patients. Older patients in general are at a greater risk for adverse drug reactions (ADRs) because of the metabolic changes associated with aging. When the number of drugs in their therapy increases, the risk of ADRs increases exponentially, which may lead to decreased compliance, poor quality of life, and unnecessary drug expenses . We observed that the percentage of significant gene drug interactions was higher with respect to the number of drugs in the patients’ therapy. Therefore, we presume that pharmacogenomic testing for this group of patients could improve their therapeutic outcome and reduce the number of experienced ADRs. However, further research assessing the therapeutic intervention based on pharmacogenomic testing, with a longer follow-up, is warranted to fortify the rationale for testing in routine clinical practice. Psychiatric drugs are the archetypal drugs heavily influenced by gene-drug interactions resulting in adverse drug reactions and the lack of therapeutic effect. This often leads to a trial-and-error approach to prescribing. In this study, we found significant gene-drug interactions for clozapine in 8 patients. Clozapine pharmacokinetics is influenced by CYP3A4 and CYP3A5 activity, as well as polymorphisms in HLA-B that can cause clozapine-induced neutropenia . Information provided by pharmacogenetic testing should be used to personalize treatment in psychiatry. This is best done by combining genotyping with therapeutic drug monitoring . A meta-analysis including 1556 patients showed that the outcomes of major depressive disorder treatment were superior in patients who received genotype-guided treatment . Our results support the potential of proactive pharmacogenomic testing for patients with psychiatric conditions, as the majority of detected actionable gene-drug interactions were detected for these drugs. Furthermore, the International Society of Psychiatric Genetics decided in favor of testing for polymorphisms in CYP2C9 , CYP2D6, HLA-A, and HLA-B at the current level of understanding, while also indicating the potential of a wider implementation of pharmacogenomic testing in psychiatry . In our study, proton pump inhibitors (PPIs) were the second most common drug group with significant gene-drug interactions. PPIs' therapeutic effect is partly determined by polymorphisms in the CYP2C19 . The favorable side-effect profile of these commonly prescribed drugs allows them to be implemented in the case of reduced metabolism. However, patients who are rapid metabolizers are at greater risk for the lack of therapeutic effect . Therefore, it would be prudent to determine these polymorphisms in cases of a lack of therapeutic effect. The third most common group of drugs with a significant gene-drug interactions in our patients was the cardiovascular drugs. Statins and beta-blockers are among the most commonly used drugs. Atorvastatin and metoprolol particularly (which were the two most common gene-drug pairs with significant interactions in the cardiovascular group in this population) are among the top 10 most prescribed drugs in the United States . In Croatia, atorvastatin was the third most consumed drug in 2020 . Statins and beta-blockers also have a well-established gene-drug interaction profile with genotype-guided therapy guidelines for statins already available to the attending clinician . A recent randomized controlled trial demonstrated that the adherence to this guideline did not reduce the effect of statin therapy . Another category of drugs closely related to cardiovascular disease are anti-platelet and anti-coagulation drugs, which were actionable in 11 patients. Clopidogrel was actionable in 7 patients. Patients who have decreased CYP2C19 activity using clopidogrel have an increased risk of ischemic events due to the lack of effectiveness of secondary prevention . Recently, it was found that a genotype-guided strategy was non-inferior to standard practice, but with a lower incidence of bleeding events . Anti-inflammatory and analgesic drug-gene pairs were found in 14 and 13 patients’ therapy regiments, respectively. The effect of genetic variance on their pharmacological effect and side-effect profile is well-established . Genotype-based guidelines are available for some of the most prescribed drugs including ibuprofen, meloxicam, celecoxib, and others, allowing for their more precise prescription to avoid the side effects of their decreased metabolism . A genotype-based guideline is available for tramadol, codeine, and hydrocodone dosing based on CYP2D6 genotype . Opioid analgesics are also known for their addictive potential, with genetic factors possibly having an important role in this mechanism. Currently, predictive models are being developed to help determine the risk of addiction . In order to reap clear benefits for the patient, pharmacogenetic test results should be integrated into the patient’s electronic health record, where they can be correlated with other important patient-related factors that could also affect the therapeutic outcome. The integration of these data should foremost be used to avoid preventable, genotype-determined, severe adverse drug reactions and to identify the patients who are at risk of a reduced therapeutic outcome (particularly important in secondary prevention) . Such integration enabled 97% of patients to reuse the pharmacogenomic test results in the future . This can be further reinforced with the development of more genotype-based prescribing guidelines, which, when integrated, can serve as an easily accessible reference. The current study showed that for 56.7% of the patients who had at least one gene-drug pair, there was an established prescribing guideline. In the future, with more research being available, this proportion is likely to increase. The limitations of this study include its retrospective design, which did not allow for an insight into the change of patients’ therapy after genotyping. Furthermore, at the time of testing the patients’ reports might not have included some more commonly prescribed over-the-counter drugs with known gene-drug interactions, ie, ibuprofen, diclofenac, etc. The results of this study demonstrate that multi-gene pharmacogenomic testing provides actionable clinical information in two out of three patients. The increasing digitalization of health care in developed countries provides the necessary infrastructure for a successful implementation of proactive pharmacogenomic testing, which could enable personalized therapy prescribing. However, further effort has to be made to educate the patients and health care providers on the benefits of personalized prescribing.
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Application of novel nanomaterials with dual functions of antimicrobial and remineralization in mouthwashes | 94b73630-aba4-4b5a-8533-196a8b0ca9d9 | 11584742 | Dentistry[mh] | According to the recently published Global Burden Disease (GBD), dental caries is the most common disease worldwide, affecting nearly 2.3 billion people , . The Fourth National Oral Health Epidemiology Survey published in August 2018 showed that the prevalence of caries among Chinese residents was on the rise, with 71.9% in the 5-year-old group, 38.5% in the 12-year-old group, 89.0% in the 35–44-year-old group, and 98.0% in the 65–74-year-old group. The caries process is dynamic, with alternating demineralization and remineralization of tooth structure, and caries can be reversed or arrested even if the loss of minerals in the lesion is sufficient to manifest clinically as a white spot on the tooth surface , . Therefore, the key to caries control lies in prevention and routine maintenance, including preventing plaque formation, reducing enamel demineralization, and promoting remineralization of lesions . Zinc oxide nanoparticles are potent antimicrobial agents because of their ability to accumulate on bacterial cell membranes by electrostatic attraction. In addition, it has osteogenic, anticancer and remineralization-promoting properties – . Mouthwashes containing zinc oxide nanoparticles have been shown to have high in vitro activity against cariogenic bacteria and positively impact dentin by impeding its demineralization . Meanwhile, silver nanoparticles have attracted broad attention owing to their low cost, nontoxicity, and high antimicrobial activity – . According to previous studies, silver nanoparticles were found to not only improve the properties of zinc oxide nanoparticles, but also reduce the amount of ingredients – . In addition, it has also been shown that the combination of antimicrobial materials with calcium compounds (e.g., calcium carbonate, etc.) with remineralization ability is expected to further promote the anti-caries properties of the materials , . Oyster shells, as a natural green material rich in calcium carbonate and similar to the formation process of natural teeth and bones, have high bioactivity and biocompatibility compared with traditional oral materials, as well as adsorption, biomineralization, and non-toxicity, which can well stabilize and disperse nanoparticles, and can be used as excellent carriers for various antimicrobial agents , , . In the previous study, our group synthesized Ag/ZnO/Oyster Shell nanocomposites with good antimicrobial properties by a green method , . Mouthwash, as a daily-use oral care product, can effectively reduce oral pathogenic microorganisms, and the addition of nano-anti-caries materials to it is a worthy research topic , . Studies have shown that mouthwashes containing alcohol may cause damage, irritation, or sensitization to oral mucosa or tooth enamel. In this study, a mouthwash with pH above the demineralization threshold of 5.5 and free of fluoride and alcohol was selected as a matrix for nanomaterials to perform the relevant test experiments. In this study, the synthesized Ag/ZnO/Oyster Shell was applied to mouthwash Ora ® to investigate the antimicrobial and remineralization-promoting properties, which would provide a basis for the subsequent development of a new type of mouthwash with both antimicrobial and remineralization capabilities.
Antibacterial potential of Ag/ZnO/Oyster Shell In this study, oyster shell-derived CaCO 3 was used as a solid support loaded with 2 nm Ag and 10 nm ZnO nanoparticles to construct an efficient Ag/ZnO/Oyster Shell, referring to the relevant literature of previous studies , , . The washed and dried oyster shells were powdered in a grinder, sieved through a 200 mesh sieve. 2 g of oyster shells were dispersed in 50 mL of 0.5 mol L −1 Zn(NO 3 ) 2 ·6H 2 O solution under magnetic stirring for 24 h. After vacuuming and drying, the ZnO/Oyster Shell nanocomposites were obtained by placing in a muffle furnace and calcined at 600℃ for 4 h with a heating rate of 5℃ min −1 . Thereafter, 1 g of the ZnO/Oyster Shell was immersed in 10 mL of 0.1 mol L 1 AgNO 3 , and 10 mL of Cacumen platycladi extract was added. The mixture was combined with magnetic stirring for 48 h without light, and then thoroughly washed with ethanol and water, and dried. For comparison, Ag/Oyster Shell nanocomposites were prepared under similar experimental conditions without the Zn(NO 3 ) 2 ·6H 2 O solution. The S. mutans standard strain (ATCC 25175) and L. acidophilus standard strain (ATCC 4356) procured from ATCC were utilized to evaluate the antibacterial potential. S. mutans was cultured in BHI broth (Brain Heart infusion broth, Oxoid Ltd, Basingstoke, Hants, UK), and L. acidophilus was cultured in MRS broth (de Man, Rogosa and Sharpe Broth, Huankai Microbial, Guangzhou, China). The bacterial suspension was uniformly spread on agar plates, and tablets made of 70 mg of Oyster Shell, Ag/Oyster Shell, ZnO/Oyster Shell or Ag/ZnO/Oyster Shell nanocomposite were each placed on the media for inhibition zone experiment. The agar plates were incubated at 5% carbon dioxide and 37℃ for 24 h and 48 h for S. mutans and L. acidophilus , respectively. Next, the S. mutans and L. acidophilus suspension and medium were mixed at a volume ratio of 1 µL:1 mL and dispensed evenly into 6 sterilised centrifuge tubes with a volume of 2 mL per tube. The Ag/ZnO/Oyster Shell suspension was added to each tube with gradient concentrations of 0, 37.5, 75, 150, 300, 600 µg/mL. The S. mutans suspension was incubated at 5% carbon dioxide and 37℃ in an orbital shaker for 12 h, while L. acidophilus was incubated for 24 h. 100 µL of the medium was transferred to a 96-well plate. The absorbance at 600 nm was measured using a microplate reader (Molecular Devices, USA) to determine the minimum inhibitory concentration (MIC). Each group had 3 auxiliary wells, and each experiment was repeated three times. To determine the production of reactive oxygen species (ROS) in cells, a 20 mM ROS assay kit containing DCFH-DA was used as a fluorescent probe. As a non-fluorescent dye, DCFH-DA is able to penetrate into the cells where it would be hydrolyzed to DCFH. In the presence of intracellular ROS, DCFH is converted into green fluorescent DCF for further analysis. In addition, S. mutans and L. acidophilus were cultivated in medium with different materials of Ag/Oyster Shell, ZnO/Oyster Shell or Ag/ZnO/Oyster Shell nanocomposite for 6 h and 8 h, respectively. Thereafter, DCFH-DA was added and incubated for 6 h at 37℃. Finally, a fluorescence spectrophotometer (200 Pro, Tecan Infinite, Austria) was used for analysis. Data were normalized by relative expression and statistical analysis by the Student’s t test. In addition, FESEM (Tecnai F30, FEI, USA) was used to characterize the microstructure of bacteria under sample treatment. 2 mg of Ag/ZnO/Oyster Shell was added to 10 mL DI water and ultrasonicated for 15 min. Afterward, 1 mL of the sample solution was added to 0.5 mL of the bacterial solution under shaking for 8 h. The bacterial suspension was rinsed three times with PBS, fixed with 35% glutaraldehyde for 30 min, and dehydrated in a graded ethanol series (30, 50, 70, 90, 100%) for 15 min. Finally, bacterial droplets were dried on silicon wafers overnight prior to FESEM observation. S. mutans was incubated on 24-well plates at 37℃ for 24 h and L. acidophilus for 48 h to form mature single-species biofilms, respectively. The original medium in the 24-well plate was replaced and different masses of Ag/ZnO/Oyster Shell composites were added to the new medium to obtain sample suspensions with concentrations of 0, 37.5, 75, 150, 300, 600 and 1200 µg/mL, and incubation was continued for 24 h. Remove the suspended bacteria and medium from the plate, and gently rinse the surface of the biofilm with PBS solution 3 times to remove the floating bacteria and impurities on the surface. Add new corresponding medium, gently blow the adherent bacteria, and elute the bacteria with a turbo-shaker, and take 200 µL into the special microtiter plate, and set up three duplicate wells for each group. Dynamic growth curves of biofilm residual bacteria after sample treatment were recorded and plotted using a Bioscreen automated growth curve analyzer (Bioscreen C Pro, Finlan Inc.), which measured optical density (OD) at a wavelength of 600 nm under constant medium-rate oscillations at 37℃ for a period of 48 h. Furthermore, the live/dead assay was performed using a 200 µL live/dead kit (Thermo Fisher, USA) to soak the treated biofilm residual bacteria in another sample plate for 30 min under a fluorescence microscope (Zeiss, Germany). The excitation and emission wavelengths of SYTO9 are 480 and 500 nm respectively, and those of PI are 490 and 635 nm respectively. Each group had 3 auxiliary wells, and each experiment was repeated three times. Biosafety Research of Ag/ZnO/Oyster Shell This study was conducted to the ethical guideline of Declaration of Helsinki and was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. After obtaining informed consent from the patients, gingival tissues were cut from the margins of the third molar extractions, and human gingival fibroblasts (HGFs) cells were separated and cultured. Cell samples were sent for Short Tandem Repeats (STR) identification. The medium was low-sugar Dulbecco’s modified eagle medium (DMEM), 10% Fetal Bovine Serum (FBS), and 1% antibiotic. 15 mg of Ag/ZnO/CaCO 3 nanocomposite was weighed and added to 45 mL of low sugar DMEM culture solution. The supernatant was collected by centrifugation at 8000 rpm for 5 min, and then 5 mL of 10% FBS and 1% antibiotic mixture was added to form a final concentration of 300 µg/mL of sample extract culture medium, and then the culture medium was diluted twice to obtain 75 and 150 µg/mL of sample extract culture medium. The blank group was cell culture medium containing different concentrations of sample extracts. The cells were then inoculated in 96-well plates for 72 h. The original medium was discarded and washed twice with PBS solution. 110 µL of culture medium containing 10 µL of Cell Counting Kit-8 (CCK-8) was added to each well and the plates were incubated at 37 °C for 1 h. The OD was measured at 450 nm. [12pt]{minimal}
$$\:RGR=$$ . Each group had 3 auxiliary wells, and each experiment was repeated three times. Three random microscopic photographs were taken in each group. Remineralization Research of Ag/ZnO/Oyster Shell This study was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. Freshly extracted orthodontic premolar teeth were collected and cut into enamel blocks using a low-speed precision cutter (IsoMet1000, Buehler Corporation, USA). The surface was polished under running water with 800, 1500, 2000 and 2400 grit sandpaper. A 3 × 3-mm window was left in the center of the surface and surrounded by acid-resistant nail polish . To establish a demineralization model, the samples were placed in the demineralization solution (2.2 mM Ca(NO 3 ) 2 , 2.2 mM KH 2 PO 4 , 50 mM CH 3 COOH, 1.0 mM NaN 3 , 0.1 mM NaF, pH adjusted to 4.5) under magnetic stirring at 50 rpm for 72 h. The demineralization solution was replaced every 24 h. The samples were randomly grouped according to the hardness value of the samples after demineralization, with 15 samples in each group. The pH cycling was carried out with experimental group of 300 µg/mL Ag/CaCO 3 , 300 µg/mL ZnO/CaCO 3 , 300 µg/mL Ag/ZnO/CaCO 3 , the negative ddH 2 O and the positive NaF control group , under magnetic stirring at 37 °C and 50 rpm, including 2 h demineralization and 22 h remineralization (20 mM HEPES, 0.9 mM KH 2 PO 4 , 1.5 mM CaCl 2 , 130 mM KCl, 1.0 mM NaN 3 , pH adjusted to 7.0.). The treatment was carried out before and after demineralization. The sample was placed into the treatment solution under magnetic stirring at 37 °C at 50 rpm for 3 min each time. The entire pH cycling lasted for 12 d – . Vickers hardness was measured by a microhardness tester (HXD-1000TM/LCD, Taiming, China) under 50-gf load for 10 s. Three points (100 μm apart) were randomly measured in the windowed area of each sample, and each point was measured three times. The average value was taken as the baseline SMH 0 , SMH 1 after demineralization, and SMH 2 after pH cycling. The surface profilometer (SEF680, Kosaka Institute, Japan) randomly selects the window area and enamel surface. The height difference between datum plane and treatment surface was regarded as the depth of the surface hard tissue loss . The sampling length was 0.8 mm, the measuring length was 2.0 mm, and the testing speed was 0.5 mm/s. The average Ra value is regarded as the surface roughness. In addition, 6 samples were randomly selected from each group and the surface and cross-sectional images after sputtering gold were observed by field emission scanning electron microscopy (FESEM) . Furthermore, after stained with 0.1 mmol/L rhodamine B for 1 h in the dark, the samples were examined by confocal laser scanning microscopy (CLSM) using a Carl Zeiss SP8 laser confocal microscope, and the scanning plane should be 50 μm below the surface to avoid the interference of the smear layer . IBM SPSS 25.0 statistical analysis software was applied, and all the data were checked for normal distribution using the Kolmogorov-Smirnov test. The data were analysed by One-way analyses of variance (ANOVA), and a P-value < 0.05 was measured as statistically significant. Preparation and Property of Mouthwash containing Ag/ZnO/Oyster Shell Among the various mouthwashes available on the market, the fluorine-free and alcohol-free Ora ® Bright White Mouthwash was chosen as an ingredient because of its pH value > 5.5. 150 mg of Ag/ZnO/Oyster Shell was weighed and added into 500 mL of mouthwash, ultrasonicated for 10 min, and then left at room temperature for 24 h. The supernatant was collected by centrifugation at 8000 rpm for 15 min, and then the mouthwash was configured into a final concentration of 300 µg/mL of Ag/ZnO/Oyster Shell Ora ® mouthwash. Moreover, relevant antimicrobial, biosafety research and remineralization properties of mouthwash was detected as described above according to the standards of ISO 16408 − 2015. Animal Research of New Mouthwash Mouthwash to mucosa irritation experiment reference standard (YY/T 0127.13, China ) were approved by the Animal Care and Use Committee of Fujian Medical University (approval number FYKQ-2018-036). And all experiments were performed in accordance with relevant guidelines (ARRIVE guidelines 2.0) and regulations methods. Twelve male specifific-pathogen-free (SPF) SD rats (7–8 weeks old) with healthy mucosa were obtained from Shanghai Jihui Experimental Animal Breeding Company, China. The SD rats were randomly and evenly divided into three groups. Random numbers were generated using the standard = RAND function in Microsoft Excel. Rats were anesthetized with isopropaner by inhalation, and the perioral area was disinfected with iodophor. Bilateral buccal and tongue mucosa of rats were coated with 5 mL of mouthwash, mouthwash containing Ag/ZnO/Oyster Shell, or ddH 2 O respectively, for 3 min each. The operation totaled 14 days, twice a day. 8 mL of blood was taken from each rat, placed in a water bath at 37 °C for 15 min and centrifuged at 3000 r/min for 5 min to obtain at least 2 mL of serum. Hepatocyte damage index in serum, such as aspartate transaminase (AST) and alanine transaminase (ALT), and renal function indexes: serum urea nitrogen (BUN) and serum creatinine (CREA) were detected using an automatic biochemical analyzer. The buccal mucosa tissue about 2 × 1 × 0.5-cm and the lingual mucosa tissue about 4 cm× 1 cm× 0.5-cm were collected respectively, fixed in 4% paraformaldehyde for 24 h. The tissues were then stained with hematoxylin-eosin (HE) and the mucosal tissues were evaluated microscopically by two histopathologists according to YY/T 0127.13. At the end of the experiment, the rats were euthanised with 2% Sodium pentobarbital (100 mg/kg).
In this study, oyster shell-derived CaCO 3 was used as a solid support loaded with 2 nm Ag and 10 nm ZnO nanoparticles to construct an efficient Ag/ZnO/Oyster Shell, referring to the relevant literature of previous studies , , . The washed and dried oyster shells were powdered in a grinder, sieved through a 200 mesh sieve. 2 g of oyster shells were dispersed in 50 mL of 0.5 mol L −1 Zn(NO 3 ) 2 ·6H 2 O solution under magnetic stirring for 24 h. After vacuuming and drying, the ZnO/Oyster Shell nanocomposites were obtained by placing in a muffle furnace and calcined at 600℃ for 4 h with a heating rate of 5℃ min −1 . Thereafter, 1 g of the ZnO/Oyster Shell was immersed in 10 mL of 0.1 mol L 1 AgNO 3 , and 10 mL of Cacumen platycladi extract was added. The mixture was combined with magnetic stirring for 48 h without light, and then thoroughly washed with ethanol and water, and dried. For comparison, Ag/Oyster Shell nanocomposites were prepared under similar experimental conditions without the Zn(NO 3 ) 2 ·6H 2 O solution. The S. mutans standard strain (ATCC 25175) and L. acidophilus standard strain (ATCC 4356) procured from ATCC were utilized to evaluate the antibacterial potential. S. mutans was cultured in BHI broth (Brain Heart infusion broth, Oxoid Ltd, Basingstoke, Hants, UK), and L. acidophilus was cultured in MRS broth (de Man, Rogosa and Sharpe Broth, Huankai Microbial, Guangzhou, China). The bacterial suspension was uniformly spread on agar plates, and tablets made of 70 mg of Oyster Shell, Ag/Oyster Shell, ZnO/Oyster Shell or Ag/ZnO/Oyster Shell nanocomposite were each placed on the media for inhibition zone experiment. The agar plates were incubated at 5% carbon dioxide and 37℃ for 24 h and 48 h for S. mutans and L. acidophilus , respectively. Next, the S. mutans and L. acidophilus suspension and medium were mixed at a volume ratio of 1 µL:1 mL and dispensed evenly into 6 sterilised centrifuge tubes with a volume of 2 mL per tube. The Ag/ZnO/Oyster Shell suspension was added to each tube with gradient concentrations of 0, 37.5, 75, 150, 300, 600 µg/mL. The S. mutans suspension was incubated at 5% carbon dioxide and 37℃ in an orbital shaker for 12 h, while L. acidophilus was incubated for 24 h. 100 µL of the medium was transferred to a 96-well plate. The absorbance at 600 nm was measured using a microplate reader (Molecular Devices, USA) to determine the minimum inhibitory concentration (MIC). Each group had 3 auxiliary wells, and each experiment was repeated three times. To determine the production of reactive oxygen species (ROS) in cells, a 20 mM ROS assay kit containing DCFH-DA was used as a fluorescent probe. As a non-fluorescent dye, DCFH-DA is able to penetrate into the cells where it would be hydrolyzed to DCFH. In the presence of intracellular ROS, DCFH is converted into green fluorescent DCF for further analysis. In addition, S. mutans and L. acidophilus were cultivated in medium with different materials of Ag/Oyster Shell, ZnO/Oyster Shell or Ag/ZnO/Oyster Shell nanocomposite for 6 h and 8 h, respectively. Thereafter, DCFH-DA was added and incubated for 6 h at 37℃. Finally, a fluorescence spectrophotometer (200 Pro, Tecan Infinite, Austria) was used for analysis. Data were normalized by relative expression and statistical analysis by the Student’s t test. In addition, FESEM (Tecnai F30, FEI, USA) was used to characterize the microstructure of bacteria under sample treatment. 2 mg of Ag/ZnO/Oyster Shell was added to 10 mL DI water and ultrasonicated for 15 min. Afterward, 1 mL of the sample solution was added to 0.5 mL of the bacterial solution under shaking for 8 h. The bacterial suspension was rinsed three times with PBS, fixed with 35% glutaraldehyde for 30 min, and dehydrated in a graded ethanol series (30, 50, 70, 90, 100%) for 15 min. Finally, bacterial droplets were dried on silicon wafers overnight prior to FESEM observation. S. mutans was incubated on 24-well plates at 37℃ for 24 h and L. acidophilus for 48 h to form mature single-species biofilms, respectively. The original medium in the 24-well plate was replaced and different masses of Ag/ZnO/Oyster Shell composites were added to the new medium to obtain sample suspensions with concentrations of 0, 37.5, 75, 150, 300, 600 and 1200 µg/mL, and incubation was continued for 24 h. Remove the suspended bacteria and medium from the plate, and gently rinse the surface of the biofilm with PBS solution 3 times to remove the floating bacteria and impurities on the surface. Add new corresponding medium, gently blow the adherent bacteria, and elute the bacteria with a turbo-shaker, and take 200 µL into the special microtiter plate, and set up three duplicate wells for each group. Dynamic growth curves of biofilm residual bacteria after sample treatment were recorded and plotted using a Bioscreen automated growth curve analyzer (Bioscreen C Pro, Finlan Inc.), which measured optical density (OD) at a wavelength of 600 nm under constant medium-rate oscillations at 37℃ for a period of 48 h. Furthermore, the live/dead assay was performed using a 200 µL live/dead kit (Thermo Fisher, USA) to soak the treated biofilm residual bacteria in another sample plate for 30 min under a fluorescence microscope (Zeiss, Germany). The excitation and emission wavelengths of SYTO9 are 480 and 500 nm respectively, and those of PI are 490 and 635 nm respectively. Each group had 3 auxiliary wells, and each experiment was repeated three times. Biosafety Research of Ag/ZnO/Oyster Shell This study was conducted to the ethical guideline of Declaration of Helsinki and was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. After obtaining informed consent from the patients, gingival tissues were cut from the margins of the third molar extractions, and human gingival fibroblasts (HGFs) cells were separated and cultured. Cell samples were sent for Short Tandem Repeats (STR) identification. The medium was low-sugar Dulbecco’s modified eagle medium (DMEM), 10% Fetal Bovine Serum (FBS), and 1% antibiotic. 15 mg of Ag/ZnO/CaCO 3 nanocomposite was weighed and added to 45 mL of low sugar DMEM culture solution. The supernatant was collected by centrifugation at 8000 rpm for 5 min, and then 5 mL of 10% FBS and 1% antibiotic mixture was added to form a final concentration of 300 µg/mL of sample extract culture medium, and then the culture medium was diluted twice to obtain 75 and 150 µg/mL of sample extract culture medium. The blank group was cell culture medium containing different concentrations of sample extracts. The cells were then inoculated in 96-well plates for 72 h. The original medium was discarded and washed twice with PBS solution. 110 µL of culture medium containing 10 µL of Cell Counting Kit-8 (CCK-8) was added to each well and the plates were incubated at 37 °C for 1 h. The OD was measured at 450 nm. [12pt]{minimal}
$$\:RGR=$$ . Each group had 3 auxiliary wells, and each experiment was repeated three times. Three random microscopic photographs were taken in each group. Remineralization Research of Ag/ZnO/Oyster Shell This study was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. Freshly extracted orthodontic premolar teeth were collected and cut into enamel blocks using a low-speed precision cutter (IsoMet1000, Buehler Corporation, USA). The surface was polished under running water with 800, 1500, 2000 and 2400 grit sandpaper. A 3 × 3-mm window was left in the center of the surface and surrounded by acid-resistant nail polish . To establish a demineralization model, the samples were placed in the demineralization solution (2.2 mM Ca(NO 3 ) 2 , 2.2 mM KH 2 PO 4 , 50 mM CH 3 COOH, 1.0 mM NaN 3 , 0.1 mM NaF, pH adjusted to 4.5) under magnetic stirring at 50 rpm for 72 h. The demineralization solution was replaced every 24 h. The samples were randomly grouped according to the hardness value of the samples after demineralization, with 15 samples in each group. The pH cycling was carried out with experimental group of 300 µg/mL Ag/CaCO 3 , 300 µg/mL ZnO/CaCO 3 , 300 µg/mL Ag/ZnO/CaCO 3 , the negative ddH 2 O and the positive NaF control group , under magnetic stirring at 37 °C and 50 rpm, including 2 h demineralization and 22 h remineralization (20 mM HEPES, 0.9 mM KH 2 PO 4 , 1.5 mM CaCl 2 , 130 mM KCl, 1.0 mM NaN 3 , pH adjusted to 7.0.). The treatment was carried out before and after demineralization. The sample was placed into the treatment solution under magnetic stirring at 37 °C at 50 rpm for 3 min each time. The entire pH cycling lasted for 12 d – . Vickers hardness was measured by a microhardness tester (HXD-1000TM/LCD, Taiming, China) under 50-gf load for 10 s. Three points (100 μm apart) were randomly measured in the windowed area of each sample, and each point was measured three times. The average value was taken as the baseline SMH 0 , SMH 1 after demineralization, and SMH 2 after pH cycling. The surface profilometer (SEF680, Kosaka Institute, Japan) randomly selects the window area and enamel surface. The height difference between datum plane and treatment surface was regarded as the depth of the surface hard tissue loss . The sampling length was 0.8 mm, the measuring length was 2.0 mm, and the testing speed was 0.5 mm/s. The average Ra value is regarded as the surface roughness. In addition, 6 samples were randomly selected from each group and the surface and cross-sectional images after sputtering gold were observed by field emission scanning electron microscopy (FESEM) . Furthermore, after stained with 0.1 mmol/L rhodamine B for 1 h in the dark, the samples were examined by confocal laser scanning microscopy (CLSM) using a Carl Zeiss SP8 laser confocal microscope, and the scanning plane should be 50 μm below the surface to avoid the interference of the smear layer . IBM SPSS 25.0 statistical analysis software was applied, and all the data were checked for normal distribution using the Kolmogorov-Smirnov test. The data were analysed by One-way analyses of variance (ANOVA), and a P-value < 0.05 was measured as statistically significant. Preparation and Property of Mouthwash containing Ag/ZnO/Oyster Shell Among the various mouthwashes available on the market, the fluorine-free and alcohol-free Ora ® Bright White Mouthwash was chosen as an ingredient because of its pH value > 5.5. 150 mg of Ag/ZnO/Oyster Shell was weighed and added into 500 mL of mouthwash, ultrasonicated for 10 min, and then left at room temperature for 24 h. The supernatant was collected by centrifugation at 8000 rpm for 15 min, and then the mouthwash was configured into a final concentration of 300 µg/mL of Ag/ZnO/Oyster Shell Ora ® mouthwash. Moreover, relevant antimicrobial, biosafety research and remineralization properties of mouthwash was detected as described above according to the standards of ISO 16408 − 2015. Animal Research of New Mouthwash Mouthwash to mucosa irritation experiment reference standard (YY/T 0127.13, China ) were approved by the Animal Care and Use Committee of Fujian Medical University (approval number FYKQ-2018-036). And all experiments were performed in accordance with relevant guidelines (ARRIVE guidelines 2.0) and regulations methods. Twelve male specifific-pathogen-free (SPF) SD rats (7–8 weeks old) with healthy mucosa were obtained from Shanghai Jihui Experimental Animal Breeding Company, China. The SD rats were randomly and evenly divided into three groups. Random numbers were generated using the standard = RAND function in Microsoft Excel. Rats were anesthetized with isopropaner by inhalation, and the perioral area was disinfected with iodophor. Bilateral buccal and tongue mucosa of rats were coated with 5 mL of mouthwash, mouthwash containing Ag/ZnO/Oyster Shell, or ddH 2 O respectively, for 3 min each. The operation totaled 14 days, twice a day. 8 mL of blood was taken from each rat, placed in a water bath at 37 °C for 15 min and centrifuged at 3000 r/min for 5 min to obtain at least 2 mL of serum. Hepatocyte damage index in serum, such as aspartate transaminase (AST) and alanine transaminase (ALT), and renal function indexes: serum urea nitrogen (BUN) and serum creatinine (CREA) were detected using an automatic biochemical analyzer. The buccal mucosa tissue about 2 × 1 × 0.5-cm and the lingual mucosa tissue about 4 cm× 1 cm× 0.5-cm were collected respectively, fixed in 4% paraformaldehyde for 24 h. The tissues were then stained with hematoxylin-eosin (HE) and the mucosal tissues were evaluated microscopically by two histopathologists according to YY/T 0127.13. At the end of the experiment, the rats were euthanised with 2% Sodium pentobarbital (100 mg/kg).
This study was conducted to the ethical guideline of Declaration of Helsinki and was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. After obtaining informed consent from the patients, gingival tissues were cut from the margins of the third molar extractions, and human gingival fibroblasts (HGFs) cells were separated and cultured. Cell samples were sent for Short Tandem Repeats (STR) identification. The medium was low-sugar Dulbecco’s modified eagle medium (DMEM), 10% Fetal Bovine Serum (FBS), and 1% antibiotic. 15 mg of Ag/ZnO/CaCO 3 nanocomposite was weighed and added to 45 mL of low sugar DMEM culture solution. The supernatant was collected by centrifugation at 8000 rpm for 5 min, and then 5 mL of 10% FBS and 1% antibiotic mixture was added to form a final concentration of 300 µg/mL of sample extract culture medium, and then the culture medium was diluted twice to obtain 75 and 150 µg/mL of sample extract culture medium. The blank group was cell culture medium containing different concentrations of sample extracts. The cells were then inoculated in 96-well plates for 72 h. The original medium was discarded and washed twice with PBS solution. 110 µL of culture medium containing 10 µL of Cell Counting Kit-8 (CCK-8) was added to each well and the plates were incubated at 37 °C for 1 h. The OD was measured at 450 nm. [12pt]{minimal}
$$\:RGR=$$ . Each group had 3 auxiliary wells, and each experiment was repeated three times. Three random microscopic photographs were taken in each group.
This study was approved by the institutional ethics committee of School and Hospital of Stomatology, Fujian Medical University. Freshly extracted orthodontic premolar teeth were collected and cut into enamel blocks using a low-speed precision cutter (IsoMet1000, Buehler Corporation, USA). The surface was polished under running water with 800, 1500, 2000 and 2400 grit sandpaper. A 3 × 3-mm window was left in the center of the surface and surrounded by acid-resistant nail polish . To establish a demineralization model, the samples were placed in the demineralization solution (2.2 mM Ca(NO 3 ) 2 , 2.2 mM KH 2 PO 4 , 50 mM CH 3 COOH, 1.0 mM NaN 3 , 0.1 mM NaF, pH adjusted to 4.5) under magnetic stirring at 50 rpm for 72 h. The demineralization solution was replaced every 24 h. The samples were randomly grouped according to the hardness value of the samples after demineralization, with 15 samples in each group. The pH cycling was carried out with experimental group of 300 µg/mL Ag/CaCO 3 , 300 µg/mL ZnO/CaCO 3 , 300 µg/mL Ag/ZnO/CaCO 3 , the negative ddH 2 O and the positive NaF control group , under magnetic stirring at 37 °C and 50 rpm, including 2 h demineralization and 22 h remineralization (20 mM HEPES, 0.9 mM KH 2 PO 4 , 1.5 mM CaCl 2 , 130 mM KCl, 1.0 mM NaN 3 , pH adjusted to 7.0.). The treatment was carried out before and after demineralization. The sample was placed into the treatment solution under magnetic stirring at 37 °C at 50 rpm for 3 min each time. The entire pH cycling lasted for 12 d – . Vickers hardness was measured by a microhardness tester (HXD-1000TM/LCD, Taiming, China) under 50-gf load for 10 s. Three points (100 μm apart) were randomly measured in the windowed area of each sample, and each point was measured three times. The average value was taken as the baseline SMH 0 , SMH 1 after demineralization, and SMH 2 after pH cycling. The surface profilometer (SEF680, Kosaka Institute, Japan) randomly selects the window area and enamel surface. The height difference between datum plane and treatment surface was regarded as the depth of the surface hard tissue loss . The sampling length was 0.8 mm, the measuring length was 2.0 mm, and the testing speed was 0.5 mm/s. The average Ra value is regarded as the surface roughness. In addition, 6 samples were randomly selected from each group and the surface and cross-sectional images after sputtering gold were observed by field emission scanning electron microscopy (FESEM) . Furthermore, after stained with 0.1 mmol/L rhodamine B for 1 h in the dark, the samples were examined by confocal laser scanning microscopy (CLSM) using a Carl Zeiss SP8 laser confocal microscope, and the scanning plane should be 50 μm below the surface to avoid the interference of the smear layer . IBM SPSS 25.0 statistical analysis software was applied, and all the data were checked for normal distribution using the Kolmogorov-Smirnov test. The data were analysed by One-way analyses of variance (ANOVA), and a P-value < 0.05 was measured as statistically significant.
Among the various mouthwashes available on the market, the fluorine-free and alcohol-free Ora ® Bright White Mouthwash was chosen as an ingredient because of its pH value > 5.5. 150 mg of Ag/ZnO/Oyster Shell was weighed and added into 500 mL of mouthwash, ultrasonicated for 10 min, and then left at room temperature for 24 h. The supernatant was collected by centrifugation at 8000 rpm for 15 min, and then the mouthwash was configured into a final concentration of 300 µg/mL of Ag/ZnO/Oyster Shell Ora ® mouthwash. Moreover, relevant antimicrobial, biosafety research and remineralization properties of mouthwash was detected as described above according to the standards of ISO 16408 − 2015.
Mouthwash to mucosa irritation experiment reference standard (YY/T 0127.13, China ) were approved by the Animal Care and Use Committee of Fujian Medical University (approval number FYKQ-2018-036). And all experiments were performed in accordance with relevant guidelines (ARRIVE guidelines 2.0) and regulations methods. Twelve male specifific-pathogen-free (SPF) SD rats (7–8 weeks old) with healthy mucosa were obtained from Shanghai Jihui Experimental Animal Breeding Company, China. The SD rats were randomly and evenly divided into three groups. Random numbers were generated using the standard = RAND function in Microsoft Excel. Rats were anesthetized with isopropaner by inhalation, and the perioral area was disinfected with iodophor. Bilateral buccal and tongue mucosa of rats were coated with 5 mL of mouthwash, mouthwash containing Ag/ZnO/Oyster Shell, or ddH 2 O respectively, for 3 min each. The operation totaled 14 days, twice a day. 8 mL of blood was taken from each rat, placed in a water bath at 37 °C for 15 min and centrifuged at 3000 r/min for 5 min to obtain at least 2 mL of serum. Hepatocyte damage index in serum, such as aspartate transaminase (AST) and alanine transaminase (ALT), and renal function indexes: serum urea nitrogen (BUN) and serum creatinine (CREA) were detected using an automatic biochemical analyzer. The buccal mucosa tissue about 2 × 1 × 0.5-cm and the lingual mucosa tissue about 4 cm× 1 cm× 0.5-cm were collected respectively, fixed in 4% paraformaldehyde for 24 h. The tissues were then stained with hematoxylin-eosin (HE) and the mucosal tissues were evaluated microscopically by two histopathologists according to YY/T 0127.13. At the end of the experiment, the rats were euthanised with 2% Sodium pentobarbital (100 mg/kg).
Ag/ZnO/Oyster Shell nanomaterials have the ability to inhibit the plaque of cariogenic bacteria Compared with Oyster Shell (0.50 cm), ZnO/Oyster Shell (0.50 cm) and Ag/Oyster Shell (0.72 cm), Ag/ZnO/Oyster Shell (0.80 cm) showed a larger zone of inhibition against S. mutans (Fig. A). Similarly, Ag/ZnO/Oyster Shell (0.78 cm) compared to Oyster Shell (0.50 cm), ZnO/Oyster Shell (0.55 cm) and Ag/Oyster Shell (0.72 cm) showed a larger zone of inhibition against L. acidophilus (Fig. B), suggesting stronger antibacterial activity. As shown in Fig. C and E, the Ag/ZnO/Oyster Shell at concentrations of 75 µg/mL and 150 µg/mL can completely inhibit the growth of S. mutans and L. acidophilus , while the colony-forming units of bacteria were reduced to zero at a concentration of 300 µg/mL and 600 µg/mL, respectively. As compared to the binary Ag/Oyster Shell and ZnO/Oyster Shell, Ag/ZnO/Oyster Shell produced an approximate 2-fold increase of ROS. All of these studies revealed that the Ag/ZnO/Oyster Shell were capable of producing ROS, and resulted in irreversible DNA damage and bacteria death (Fig. D). Additionally, SEM observations (Fig. F and G) showed that untreated S. mutans were smooth spherical or ovoid in shape. When co-cultured with the samples, the cell membrane was damaged and distortion, resulting in the leakage of intracellular components and finally cell lysis. Similarly, L. acidophilus was initially elongated with rounded ends, whereas after Ag/ZnO/Oyster Shell treatment, the surface became rough, the organism to shrank into short rods, with cell contents leaking and blurring the surface morphology of the nanomaterials (Fig. H and I). These results suggest that Ag/ZnO/Oyster Shell disrupted the structure of the bacteria, causing it to deform or disintegrate, which in turn led to the death of the bacterial cell. The common cariogenic bacterium S. mutans or L. acidophilus usually exists in the form of plaque biofilm. The inhibitory effect of Ag/ZnO/Oyster Shell on the formed biofilms of S. mutans or L. acidophilus was further investigated through a series of experiments. As shown in Fig. A and B, the residual bacteria in S. mutans and L. acidophilus biofilm began to be inhibited when the material concentrations reached 150 µg/mL and 300 µg/mL, respectively. Moreover, under the microscope, S. mutans and L. acidophilus biofilm in the control groups displayed a large amount of green fluorescence and a small amount of red fluorescence, while the Ag/ZnO/Oyster Shell groups exhibited the opposite (Fig. C and D). Ag/ZnO/Oyster Shell Nanomaterials have good biosafety Ag/ZnO/Oyster Shell nanomaterials were added to HGF cells and the viability of the cells was assayed for cytotoxicity using the cck-8 assay. The results in Fig. A showed that the material at a concentration of 75 µg/mL did not have a significant effect on cell proliferation compared to the negative control. Figure B showed the relative proliferation rates of HGFs, which were (97.55 ± 1.36)%, (80.92 ± 1.62)% and (62.27 ± 1.52)%, respectively, where the cytotoxicity of the 75 and 150 µg/mL groups was non-cytotoxic, and the cytotoxicity of the 300 µg/mL group was slightly cytotoxic, and none of them were recognized as having cytotoxicity. The microscopic structural morphology of HGFs was shown in Fig. C, and the growth was consistent with CCK-8 and RGR results. Ag/ZnO/Oyster Shell promotes remineralization The pH cycle model (Fig. A) can mimic the caries process well and is therefore widely used to estimate the anti-caries potential and to promote remineralization properties . The results in Fig. B and C showed an increase in hardness recovery and a decrease in surface hard tissue loss after treatment with Ag/ZnO/Oyster Shell and positive control NaF as compared to the negative control ddH 2 O. In contrast, no significant difference was observed in hardness recovery and the depth of surface hard tissue loss in the binary composite Ag/Oyster Shell and ZnO/Oyster Shell compared to the negative control. The results of the CLSM research (Fig. D and E) were consistent with the abovementioned results.The results showed significantly lower fluorescence area and average fluorescence for both Ag/ZnO/Oyster shells and the positive control compared to the negative control, suggesting a smaller amount of mineral loss. Whereas no significant differences were seen in all three aspects between the negative control, the binary material Ag/Oyster Shell and ZnO/Oyster Shell. Mouthwash containing Ag/ZnO/Oyster Shell possessed strong properties The mouthwash containing Ag/ZnO/Oyster shells was a pale yellow, clarified and unadulterated solution with a pH of 6.6. As shown in Fig. A, the novel mouthwash is capable of achieving a good bacteriostatic effect as the existing mouthwash due to the surfactant and foaming agent components. Compared with the negative control ddH 2 O, the hardness recovery and the hard tissue loss (Fig. B and C) treated by new mouthwash and the mouthwash containing NaF changed significantly ( P < 0.05). SEM observation of enamel cross-sectional morphology, as seen in Fig. D-G, the control-treated enamel column was rough, and the center was dissolved and destroyed, while the morphology of the enamel columns treated with mouthwash, new mouthwash, and NaF containing mouthwash did not show any obvious damage. Besides scattered mineral deposition particles were seen on the surface of the enamel columns treated with new mouthwash. As shown in Fig. H, the fluorescence excited in the lesion areas of the control-treated and mouthwash-treated groups was higher than that of the other two groups in terms of area and intensity, indicating a greater loss of minerals. Whereas no significant differences were seen between the new mouthwash group and the NaF-containing group. After 14 days of the mucosal experiment (Fig. A), comparing the control, new mouthwash and mouthwash groups, there was no significant difference in the liver function indexes ALT and AST and kidney function indexes BUN and CREA in each group of rats, as shown in Fig. B. Figure C showed the pathomorphology of the buccal and lingual mucosa of the rats after the experiment, none of which were significantly different. After the pathologist’s reading and scoring, the score of buccal mucosa was 0.07 and the lingual mucosa score was 0 in all three groups, suggesting that there was no mucosal irritation in all three groups.
Compared with Oyster Shell (0.50 cm), ZnO/Oyster Shell (0.50 cm) and Ag/Oyster Shell (0.72 cm), Ag/ZnO/Oyster Shell (0.80 cm) showed a larger zone of inhibition against S. mutans (Fig. A). Similarly, Ag/ZnO/Oyster Shell (0.78 cm) compared to Oyster Shell (0.50 cm), ZnO/Oyster Shell (0.55 cm) and Ag/Oyster Shell (0.72 cm) showed a larger zone of inhibition against L. acidophilus (Fig. B), suggesting stronger antibacterial activity. As shown in Fig. C and E, the Ag/ZnO/Oyster Shell at concentrations of 75 µg/mL and 150 µg/mL can completely inhibit the growth of S. mutans and L. acidophilus , while the colony-forming units of bacteria were reduced to zero at a concentration of 300 µg/mL and 600 µg/mL, respectively. As compared to the binary Ag/Oyster Shell and ZnO/Oyster Shell, Ag/ZnO/Oyster Shell produced an approximate 2-fold increase of ROS. All of these studies revealed that the Ag/ZnO/Oyster Shell were capable of producing ROS, and resulted in irreversible DNA damage and bacteria death (Fig. D). Additionally, SEM observations (Fig. F and G) showed that untreated S. mutans were smooth spherical or ovoid in shape. When co-cultured with the samples, the cell membrane was damaged and distortion, resulting in the leakage of intracellular components and finally cell lysis. Similarly, L. acidophilus was initially elongated with rounded ends, whereas after Ag/ZnO/Oyster Shell treatment, the surface became rough, the organism to shrank into short rods, with cell contents leaking and blurring the surface morphology of the nanomaterials (Fig. H and I). These results suggest that Ag/ZnO/Oyster Shell disrupted the structure of the bacteria, causing it to deform or disintegrate, which in turn led to the death of the bacterial cell. The common cariogenic bacterium S. mutans or L. acidophilus usually exists in the form of plaque biofilm. The inhibitory effect of Ag/ZnO/Oyster Shell on the formed biofilms of S. mutans or L. acidophilus was further investigated through a series of experiments. As shown in Fig. A and B, the residual bacteria in S. mutans and L. acidophilus biofilm began to be inhibited when the material concentrations reached 150 µg/mL and 300 µg/mL, respectively. Moreover, under the microscope, S. mutans and L. acidophilus biofilm in the control groups displayed a large amount of green fluorescence and a small amount of red fluorescence, while the Ag/ZnO/Oyster Shell groups exhibited the opposite (Fig. C and D). Ag/ZnO/Oyster Shell Nanomaterials have good biosafety Ag/ZnO/Oyster Shell nanomaterials were added to HGF cells and the viability of the cells was assayed for cytotoxicity using the cck-8 assay. The results in Fig. A showed that the material at a concentration of 75 µg/mL did not have a significant effect on cell proliferation compared to the negative control. Figure B showed the relative proliferation rates of HGFs, which were (97.55 ± 1.36)%, (80.92 ± 1.62)% and (62.27 ± 1.52)%, respectively, where the cytotoxicity of the 75 and 150 µg/mL groups was non-cytotoxic, and the cytotoxicity of the 300 µg/mL group was slightly cytotoxic, and none of them were recognized as having cytotoxicity. The microscopic structural morphology of HGFs was shown in Fig. C, and the growth was consistent with CCK-8 and RGR results. Ag/ZnO/Oyster Shell promotes remineralization The pH cycle model (Fig. A) can mimic the caries process well and is therefore widely used to estimate the anti-caries potential and to promote remineralization properties . The results in Fig. B and C showed an increase in hardness recovery and a decrease in surface hard tissue loss after treatment with Ag/ZnO/Oyster Shell and positive control NaF as compared to the negative control ddH 2 O. In contrast, no significant difference was observed in hardness recovery and the depth of surface hard tissue loss in the binary composite Ag/Oyster Shell and ZnO/Oyster Shell compared to the negative control. The results of the CLSM research (Fig. D and E) were consistent with the abovementioned results.The results showed significantly lower fluorescence area and average fluorescence for both Ag/ZnO/Oyster shells and the positive control compared to the negative control, suggesting a smaller amount of mineral loss. Whereas no significant differences were seen in all three aspects between the negative control, the binary material Ag/Oyster Shell and ZnO/Oyster Shell. Mouthwash containing Ag/ZnO/Oyster Shell possessed strong properties The mouthwash containing Ag/ZnO/Oyster shells was a pale yellow, clarified and unadulterated solution with a pH of 6.6. As shown in Fig. A, the novel mouthwash is capable of achieving a good bacteriostatic effect as the existing mouthwash due to the surfactant and foaming agent components. Compared with the negative control ddH 2 O, the hardness recovery and the hard tissue loss (Fig. B and C) treated by new mouthwash and the mouthwash containing NaF changed significantly ( P < 0.05). SEM observation of enamel cross-sectional morphology, as seen in Fig. D-G, the control-treated enamel column was rough, and the center was dissolved and destroyed, while the morphology of the enamel columns treated with mouthwash, new mouthwash, and NaF containing mouthwash did not show any obvious damage. Besides scattered mineral deposition particles were seen on the surface of the enamel columns treated with new mouthwash. As shown in Fig. H, the fluorescence excited in the lesion areas of the control-treated and mouthwash-treated groups was higher than that of the other two groups in terms of area and intensity, indicating a greater loss of minerals. Whereas no significant differences were seen between the new mouthwash group and the NaF-containing group. After 14 days of the mucosal experiment (Fig. A), comparing the control, new mouthwash and mouthwash groups, there was no significant difference in the liver function indexes ALT and AST and kidney function indexes BUN and CREA in each group of rats, as shown in Fig. B. Figure C showed the pathomorphology of the buccal and lingual mucosa of the rats after the experiment, none of which were significantly different. After the pathologist’s reading and scoring, the score of buccal mucosa was 0.07 and the lingual mucosa score was 0 in all three groups, suggesting that there was no mucosal irritation in all three groups.
Ag/ZnO/Oyster Shell nanomaterials were added to HGF cells and the viability of the cells was assayed for cytotoxicity using the cck-8 assay. The results in Fig. A showed that the material at a concentration of 75 µg/mL did not have a significant effect on cell proliferation compared to the negative control. Figure B showed the relative proliferation rates of HGFs, which were (97.55 ± 1.36)%, (80.92 ± 1.62)% and (62.27 ± 1.52)%, respectively, where the cytotoxicity of the 75 and 150 µg/mL groups was non-cytotoxic, and the cytotoxicity of the 300 µg/mL group was slightly cytotoxic, and none of them were recognized as having cytotoxicity. The microscopic structural morphology of HGFs was shown in Fig. C, and the growth was consistent with CCK-8 and RGR results.
The pH cycle model (Fig. A) can mimic the caries process well and is therefore widely used to estimate the anti-caries potential and to promote remineralization properties . The results in Fig. B and C showed an increase in hardness recovery and a decrease in surface hard tissue loss after treatment with Ag/ZnO/Oyster Shell and positive control NaF as compared to the negative control ddH 2 O. In contrast, no significant difference was observed in hardness recovery and the depth of surface hard tissue loss in the binary composite Ag/Oyster Shell and ZnO/Oyster Shell compared to the negative control. The results of the CLSM research (Fig. D and E) were consistent with the abovementioned results.The results showed significantly lower fluorescence area and average fluorescence for both Ag/ZnO/Oyster shells and the positive control compared to the negative control, suggesting a smaller amount of mineral loss. Whereas no significant differences were seen in all three aspects between the negative control, the binary material Ag/Oyster Shell and ZnO/Oyster Shell.
The mouthwash containing Ag/ZnO/Oyster shells was a pale yellow, clarified and unadulterated solution with a pH of 6.6. As shown in Fig. A, the novel mouthwash is capable of achieving a good bacteriostatic effect as the existing mouthwash due to the surfactant and foaming agent components. Compared with the negative control ddH 2 O, the hardness recovery and the hard tissue loss (Fig. B and C) treated by new mouthwash and the mouthwash containing NaF changed significantly ( P < 0.05). SEM observation of enamel cross-sectional morphology, as seen in Fig. D-G, the control-treated enamel column was rough, and the center was dissolved and destroyed, while the morphology of the enamel columns treated with mouthwash, new mouthwash, and NaF containing mouthwash did not show any obvious damage. Besides scattered mineral deposition particles were seen on the surface of the enamel columns treated with new mouthwash. As shown in Fig. H, the fluorescence excited in the lesion areas of the control-treated and mouthwash-treated groups was higher than that of the other two groups in terms of area and intensity, indicating a greater loss of minerals. Whereas no significant differences were seen between the new mouthwash group and the NaF-containing group. After 14 days of the mucosal experiment (Fig. A), comparing the control, new mouthwash and mouthwash groups, there was no significant difference in the liver function indexes ALT and AST and kidney function indexes BUN and CREA in each group of rats, as shown in Fig. B. Figure C showed the pathomorphology of the buccal and lingual mucosa of the rats after the experiment, none of which were significantly different. After the pathologist’s reading and scoring, the score of buccal mucosa was 0.07 and the lingual mucosa score was 0 in all three groups, suggesting that there was no mucosal irritation in all three groups.
The inhibitory effect of Ag/ZnO/Oyster Shell nanocomposites on bacteria may be related to the synergistic antimicrobial properties of silver nanoparticles and zinc oxide nanoparticles. Studies on the antibacterial mechanism have shown that silver nanoparticles and zinc oxide nanoparticles can establish contact with bacteria. Contacts can be made through van der Waals forces , electrostatic interactions , hydrophobic interactions , and receptor ligands . Subsequently, nanoparticles act on the cell membranes by releasing metal ions or enter the bacteria to cause oxidative stress , which alters cell membrane permeability, disrupting the electrolyte balance, inhibiting and inactivating certain enzymes, generating oxygen-active free radicals, disrupting cellular metabolic processes, and ultimately leading to microbial death. It may also inhibit bacterial DNA replication, affect ATP production and alter gene expression , . The antimicrobial activity of silver nanoparticles is influenced by the concentration of silver ions they release. It is also affected by its particle size, and its biological activity and stability increase with decreasing particle size , . Smaller silver nanoparticles have a higher surface area-to-volume ratio, which allows them to penetrate biological surfaces more readily, disrupting the lipid bilayer by interacting with cell membranes, leading to an increase in membrane permeability and thus bacterial lysis , . It has been shown that silver nanoparticles with particle size between 5 and 20 nm have stronger antibacterial activity against Staphylococcus aureus compared to those with particle size of 30 nm . In the Ag/ZnO/Oyster Shell synthesized in this study, the silver nanoparticles have a particle size size of about 2–10 nm, which is structurally superior. On the other hand, studies on the antimicrobial mechanism of ZnO nanoparticles have shown that ZnO nanoparticles can generate a large amount of ROS, such as OH − , H 2 O 2 , and O 2− , which cause oxidative stress in bacteria and lead to cell death . The incorporation of silver nanoparticles better serves as an electron reservoir, which enhances the production of ROS . Furthermore, it has been shown that more than 60% of microbial infections are associated with biofilm formation . Since biofilms are stable colonies that protect bacteria from environmental challenges, inhibiting biofilms is inherently more challenging than killing planktonic bacteria . In this study, we explored the inhibitory effect of single bacterial biofilms of Streptococcus mutans and Lactobacillus acidophilus, which often exist in the form of biofilm, by using Ag/ZnO/Oyster Shell treatments containing different concentrations of Ag/ZnO/ Oyster Shell after culturing Streptococcus mutans and Lactobacillus acidophilus to form a biofilm, and carried out residual bacterial kinetic tests and SYTO9/PI staining experiments in a targeted manner. The results showed that when the concentration of Ag/ZnO/Oyster Shell was greater than 300 µg/mL, it could almost completely inhibit the growth of the residual bacteria in the biofilm of Streptococcus mutans and lead to the death of more than half of Lactobacillus acidophilus biofilm bacteria, and the bactericidal effect was more obvious with the increase of the concentration. Regarding the study on the remineralization capacity of enamel, Ag/ZnO/Oyster Shell showed a clear pro-remineralization effect. During enamel demineralization, hydroxyapatite crystals dissociate and diffuse by acid, resulting in the loss of calcium and inorganic salts such as Ca 2+ , CO 3 2− and OH − . Oyster shells are primarily composed of calcium carbonate (CaCO 3 , 80–85%) and also contain calcium phosphate (Ca 3 (PO 4 ) 2 ), and calcium sulfate(CaSO 4 ) . In the oral salivary environment, Ca 2+ , HCO 3 − , CO 3 2− , OH − , and PO 4 3− increase the local ion concentrations, thereby reversing enamel demineralization. At the same time, Ca 2+ , CO 3 2− , OH − also neutralize external acids and reduce enamel demineralization damage. In addition, some studies in vitro have shown that zinc is not only an important component of enamel, and its distribution and amount in enamel may affect caries progression, but zinc ions are also known to reduce the rate of enamel demineralization , . It has been reported that hydroxyapatite pretreated with zinc ions has the ability to resist acid dissolution at a level similar in magnitude to that of fluorine at equivalent molar concentrations . In this study, the results of ZnO/CaCO 3 -treated group did not show any significant difference compared to the negative control, whereas the Ag/ZnO/Oyster Shell group showed a significant pro-remineralization effect, which may be attributed to the increase in the efficacy of ZnO nanoparticles caused by the addition of silver nanoparticles. Compared to raw material mouthwash, the results of the study suggest that Ag/ZnO/Oyster Shell-containing mouthwash has a certain effect of promoting enamel remineralization. In this study, the biosafety of this material was further explored by in vivo animal experiments with reference to the YY/T 0127.13–2018 standard. By simulating the use of mouthwash, which was applied to the oral mucosa of rats twice a day, the pathological morphology of the buccal and lingual mucosal tissues of rats was compared among the use of the negative control ddH 2 O, the Ag/ZnO/Oyster Shell-containing mouthwash, and the mouthwash, and was scored by a pathologist who examined the slides under a microscope, and the results showed that there was no mucosal irritation in any of the three groups. In addition, in this study, the serum liver function indexes ALT and AST and kidney function indexes BUN and CREA of rats treated with different treatments were checked, and the results did not show any remarkable abnormality. This indicates that the new mouthwash has no significant effect on the liver and kidney functions of rats and has good biological safety.
Mouthwash containing Ag/ZnO/Oyster Shell exhibited a strong inhibitory effect on common carious bacterial biofilms and has a high potential in enamel remineralization. Additionally, its lack of irritation to mucosal tissues and its favorable safety profile in vivo experiments suggest a wide range of clinical applications.
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Advances in Nutrition in Pediatric Gastroenterology | 7c8f8f86-d296-43e8-a7ae-543f564f9b6b | 10181381 | Internal Medicine[mh] | |
Pediatric Departmental Advocacy: Our Experience Addressing the Social Challenges of Coronavirus Disease 2019 and Racism | 5aa695d7-9b00-4caa-8ade-796f41f1941c | 9750186 | Pediatrics[mh] | There has been momentum to advance community pediatrics over the last 2 decades. The Accreditation Council for Graduate Medical Education continues to incorporate community engagement and advocacy for child health within its program requirements. In accordance with these requirements, the American Academy of Pediatrics (AAP) has provided Community Access to Child Health grants to over 1700 programs to support academic and community partnerships advancing child health since 1993. The AAP also established the Community Pediatrics Training Institute (CPTI) in 2005, providing guidance to residency programs, including their six drivers of success ( ; available at www.jpeds.com ). Community pediatric training results in increased community-engaged physicians and CPTI framework incorporates residency curricula, faculty development, and community interventions. To address the intersectionality between racism, poverty, and child health disparities, the AAP and the Journal of Adolescent Health have released policy statements with recommendations to train health professionals to address social determinants of health of youth by working effectively with disadvantaged communities, collaborating with community organizations to support families, and advocating for essential benefits programs. , The Stanford School of Medicine and the Lucile Packard Children's Hospital established the Pediatric Advocacy Program in 2002 that has directed a community pediatrics and child advocacy rotation and a track in community-engagement and advocacy. Over time, the Advocacy Program expanded its reach, incorporating all 6 CPTI components to provide comprehensive structures for community-engagement and advocacy . The Advocacy Program maintains decade's long partnerships with community organizations and outpatient providers to address child health needs at a population level. In 2016, Advocacy Program directors formed a pediatric advocacy coalition across 5 community healthcare centers and 4 healthcare systems to address child health disparities. The Pediatric Residency Advocacy Council was formed in 2018 to coordinate resident-led, grassroot advocacy efforts, education, and skills-building open to all pediatric residents and fellows. In parallel, a new leadership position, Associate Chair of Policy and Community Engagement, was established to coordinate department-wide, community-engaged activities, support faculty developing careers in advocacy, and provide opportunities for participation in policy initiatives to advance child health equity. These structures, teams, and partnerships allowed the Department of Pediatrics to respond to the challenges of 2020.
Principle 1: Community Engagement Requires Sustained Commitment When the economic devastation of COVID-19 posed a threat to children, the Advocacy Program immediately mobilized long-term partnerships , to address urgent pandemic-related child health needs. The week after shelter in place was enacted, the Advocacy Program convened 15 community organizations and 5 clinical partners ( ; available at www.jpeds.com ). Together they prioritized challenges and defined avenues for collective action. Pre-existing coalitions, prior work with community organizations, and the longstanding nature of these partnerships allowed immediate mobilization of trusted entities to address COVID-driven challenges, linking families to key resources (principle 2) and organizing physician advocacy to support community-identified policy solutions (principle 3). Principle 2: Departments of Pediatrics Must Listen First Community organizations expressed being overwhelmed by the influx of new resources to support an increasing number of struggling families. In response, the Advocacy Program catalogued COVID-19 resources, which were then vetted by community partners. The result was a series of multilingual, COVID-19 resource guides highlighting relevant family resources. The guide was made available in both hard-copy and digital formats (using scannable QR codes linking to websites), to ensure families have access to the most updated, evolving information, in either mode. Moving from community to clinical dissemination, the Advocacy Program worked with the children's hospital social work team and information technology department to make these resource guides available for inpatients via smart phrases in the electronic health record. Meanwhile, the resident Advocacy Council disseminated guides in outpatient clinics and the school of medicine's emergency department. These resources have been disseminated in over 13 000 flyers via school meal distributions and patient mail and accessed 2300 times via QR scan. In addition, the Advocacy Council built a Nursery Navigation Program in the Well-Baby Nursery where residents on the Community Pediatrics Rotation are “on call” to meet with parents, review the resource guide, and conduct warm handoffs to community organizations. The resource guide was sought after because we started by listening, developing a relevant resource guide requires community input and understanding evolving community dynamics. Principle 3: Policy Engagement Requires Coordination Community organizations voiced COVID-19–driven challenges that required policy solutions, including eviction moratoriums. The Advocacy Program's collaboration with the children's hospital Government Relations Office has persisted for 20 years and works closely with our AAP chapter and district leadership. Prior to COVID-19, the Advocacy Program built an email distribution list of over 250 faculty, trainees, and staff who receive monthly child policy updates. When community partners shared that an eviction moratorium was on the agenda in local jurisdictions and asked for physicians to weigh in, we reached out to AAP district leadership who provided a letter of support as housing security is critical for child well-being. With coordination from the hospital's Government Relations Office, the AAP letter was shared in an Action Alert. Similar requests from local organizations included initiatives to protect child welfare, distribute personal protective equipment to essential food workers, and expand public food benefits. The Department of Pediatrics' powerful collective voice was quickly leveraged to support child-friendly policy needs, but this work would be reckless in isolation: it must be done in coordination with community partners, advocacy groups, the AAP and in trusting relationship with the institution's Government Relations Office . Principle 4: Departments of Pediatrics’ Longstanding Commitment Generates Resources The local philanthropic community was moved by the news of economic stress and increasing food insecurity. Early in the pandemic, like many institutions, the Associate Chair of Policy and Community Engagement presented a grand rounds talk on the economic impacts of COVID-19, which was viewed by over 600 providers and community members. The visibility of the Advocacy Program's mobilization of our pediatric community in partnership with local organizations inspired donors to financially support the work. The Advocacy Program utilized funding to provide over 17 000 pounds of food, 45 000 diapers, and 200 thermometers to a wide range of community organizations and clinics. An academically based, community-engaged program can serve as a trusted link between community donors and the local organizations surrounding the children's hospital, which is an important emerging role for development offices to consider. Principle 5: Resident Advocacy Requires Faculty Engagement Infrastructure The resident Advocacy Council provided a critical capacity to address COVID-19 and spearhead activities addressing racism. The Advocacy Council, led by peer-elected residents and open to all, is mentored by community and policy-engaged faculty and the children's hospital Director of Government Relations. They organized resident conferences on the indirect impacts of COVID-19, disseminated pandemic resources, and provided education on legislative issues. The Council's weekly advocacy updates, read widely by the residency program, encouraged all residents to participate in advocacy projects and opportunities. Resident involvement expanded use of the resource guides (principle 2) to represent 6 counties, include 3 languages, and expand within 2 hospital systems, increasing the guide's utility and reach. On the national stage, residents wrote op-eds and sent letters of gratitude to support colleagues in areas hard-hit by the pandemic. After responding to COVID-19 demands, the Advocacy Council pivoted to respond to George Floyd's murder. Residents had worked with faculty to organize demonstrations to protect Medicaid and protest separation of immigrant families, among other issues. Expanding this activism in solidarity with the Black Lives Matter movement, the Council, with faculty support from the Leadership Education for Advancing Diversity (LEAD) program, organized over 800 members of the Stanford Medicine community for a Rally for Racial Justice. Two local news outlets covered the event where the Council called for broad individual, structural, and community level antiracism efforts. They subsequently released a letter of antiracism proposals for the Pediatric Residency program, which resulted in an academic half-day dedicated for antiracism education. Such successful resident advocacy is not accidental: it must emerge from existing infrastructure, long-term faculty support, trusting relationships with departmental and hospital leadership, and a culture of taking a stand on pressing issues. Principle 6: Departmental Commitment to Equity Requires Ongoing Self-Scrutiny and Action After the national outrage against racism and the Advocacy Council's Rally for Racial Justice, the department's need to mobilize a response was clear. The Associate Chair of Policy and Community Engagement, joined by leadership from Stanford's LEAD program, developed an initiative to involve all members (faculty, staff, learners) and across all arms (clinical care, education, research, etc). Consistent with principle 1, the initial step was a “listening campaign” to understand issues of racism and gauge solutions to move the Department of Pediatrics toward being an antiracist community. Hour-long confidential, small group conversations were held and qualitatively analyzed to extrapolate key themes. Subsequently, a modified Delphi process identified solutions for an antiracism action plan. Actions centered around 7 domains: diverse faculty and staff recruitment and promotion, human resources and measuring, training, communication, leadership representation, community engagement and research, and staff engagement ( ; available at www.jpeds.com ). Teams of faculty, staff, and trainees have been assembled to lead each domain, focused on increasing the diversity of faculty, number of underrepresented minorities in leadership, and instilling mandatory antiracism and allyship trainings. The department leadership's quick response to investigate departmental racism and engage the entire department for opportunities for change was critical in starting to build an antiracist community. Principle 7: Structural Changes Need to Support Emerging ScholarshipAround Advocacy A new leadership role, the Associate Chair of Policy and Community-engagement elevates a focus on advocacy and community-engagement, working with the School of Medicine's Appointment and Promotion Committee to articulate a career path for junior faculty. The Associate Chair meets with various divisions to identify faculty champions and scholarly avenues for advocacy specific to each subspecialty. In response to the COVID-19 pandemic, the Associate Chair raised department awareness of the COVID-19–driven challenges of local communities and played the crucial role of generating resources to support the community (principle 4). In the department efforts to address racism (principle 6), the Associate Chair helps coordinate 7 antiracism teams led by faculty and staff dyads, enabling department members at every level to lead the charge to devise antiracist solutions. While creating pathways for members of the department to lead these efforts, the Associate Chair functions to ensure faculty and staff are supported by navigating key contacts, providing guidance for systems change, and working with senior leadership to move solutions from ideation to action. Departments of Pediatrics benefit from structural leadership—including a chair position—to ensure that advocacy and associated scholarship is supported.
When the economic devastation of COVID-19 posed a threat to children, the Advocacy Program immediately mobilized long-term partnerships , to address urgent pandemic-related child health needs. The week after shelter in place was enacted, the Advocacy Program convened 15 community organizations and 5 clinical partners ( ; available at www.jpeds.com ). Together they prioritized challenges and defined avenues for collective action. Pre-existing coalitions, prior work with community organizations, and the longstanding nature of these partnerships allowed immediate mobilization of trusted entities to address COVID-driven challenges, linking families to key resources (principle 2) and organizing physician advocacy to support community-identified policy solutions (principle 3).
Community organizations expressed being overwhelmed by the influx of new resources to support an increasing number of struggling families. In response, the Advocacy Program catalogued COVID-19 resources, which were then vetted by community partners. The result was a series of multilingual, COVID-19 resource guides highlighting relevant family resources. The guide was made available in both hard-copy and digital formats (using scannable QR codes linking to websites), to ensure families have access to the most updated, evolving information, in either mode. Moving from community to clinical dissemination, the Advocacy Program worked with the children's hospital social work team and information technology department to make these resource guides available for inpatients via smart phrases in the electronic health record. Meanwhile, the resident Advocacy Council disseminated guides in outpatient clinics and the school of medicine's emergency department. These resources have been disseminated in over 13 000 flyers via school meal distributions and patient mail and accessed 2300 times via QR scan. In addition, the Advocacy Council built a Nursery Navigation Program in the Well-Baby Nursery where residents on the Community Pediatrics Rotation are “on call” to meet with parents, review the resource guide, and conduct warm handoffs to community organizations. The resource guide was sought after because we started by listening, developing a relevant resource guide requires community input and understanding evolving community dynamics.
Community organizations voiced COVID-19–driven challenges that required policy solutions, including eviction moratoriums. The Advocacy Program's collaboration with the children's hospital Government Relations Office has persisted for 20 years and works closely with our AAP chapter and district leadership. Prior to COVID-19, the Advocacy Program built an email distribution list of over 250 faculty, trainees, and staff who receive monthly child policy updates. When community partners shared that an eviction moratorium was on the agenda in local jurisdictions and asked for physicians to weigh in, we reached out to AAP district leadership who provided a letter of support as housing security is critical for child well-being. With coordination from the hospital's Government Relations Office, the AAP letter was shared in an Action Alert. Similar requests from local organizations included initiatives to protect child welfare, distribute personal protective equipment to essential food workers, and expand public food benefits. The Department of Pediatrics' powerful collective voice was quickly leveraged to support child-friendly policy needs, but this work would be reckless in isolation: it must be done in coordination with community partners, advocacy groups, the AAP and in trusting relationship with the institution's Government Relations Office .
The local philanthropic community was moved by the news of economic stress and increasing food insecurity. Early in the pandemic, like many institutions, the Associate Chair of Policy and Community Engagement presented a grand rounds talk on the economic impacts of COVID-19, which was viewed by over 600 providers and community members. The visibility of the Advocacy Program's mobilization of our pediatric community in partnership with local organizations inspired donors to financially support the work. The Advocacy Program utilized funding to provide over 17 000 pounds of food, 45 000 diapers, and 200 thermometers to a wide range of community organizations and clinics. An academically based, community-engaged program can serve as a trusted link between community donors and the local organizations surrounding the children's hospital, which is an important emerging role for development offices to consider.
The resident Advocacy Council provided a critical capacity to address COVID-19 and spearhead activities addressing racism. The Advocacy Council, led by peer-elected residents and open to all, is mentored by community and policy-engaged faculty and the children's hospital Director of Government Relations. They organized resident conferences on the indirect impacts of COVID-19, disseminated pandemic resources, and provided education on legislative issues. The Council's weekly advocacy updates, read widely by the residency program, encouraged all residents to participate in advocacy projects and opportunities. Resident involvement expanded use of the resource guides (principle 2) to represent 6 counties, include 3 languages, and expand within 2 hospital systems, increasing the guide's utility and reach. On the national stage, residents wrote op-eds and sent letters of gratitude to support colleagues in areas hard-hit by the pandemic. After responding to COVID-19 demands, the Advocacy Council pivoted to respond to George Floyd's murder. Residents had worked with faculty to organize demonstrations to protect Medicaid and protest separation of immigrant families, among other issues. Expanding this activism in solidarity with the Black Lives Matter movement, the Council, with faculty support from the Leadership Education for Advancing Diversity (LEAD) program, organized over 800 members of the Stanford Medicine community for a Rally for Racial Justice. Two local news outlets covered the event where the Council called for broad individual, structural, and community level antiracism efforts. They subsequently released a letter of antiracism proposals for the Pediatric Residency program, which resulted in an academic half-day dedicated for antiracism education. Such successful resident advocacy is not accidental: it must emerge from existing infrastructure, long-term faculty support, trusting relationships with departmental and hospital leadership, and a culture of taking a stand on pressing issues.
After the national outrage against racism and the Advocacy Council's Rally for Racial Justice, the department's need to mobilize a response was clear. The Associate Chair of Policy and Community Engagement, joined by leadership from Stanford's LEAD program, developed an initiative to involve all members (faculty, staff, learners) and across all arms (clinical care, education, research, etc). Consistent with principle 1, the initial step was a “listening campaign” to understand issues of racism and gauge solutions to move the Department of Pediatrics toward being an antiracist community. Hour-long confidential, small group conversations were held and qualitatively analyzed to extrapolate key themes. Subsequently, a modified Delphi process identified solutions for an antiracism action plan. Actions centered around 7 domains: diverse faculty and staff recruitment and promotion, human resources and measuring, training, communication, leadership representation, community engagement and research, and staff engagement ( ; available at www.jpeds.com ). Teams of faculty, staff, and trainees have been assembled to lead each domain, focused on increasing the diversity of faculty, number of underrepresented minorities in leadership, and instilling mandatory antiracism and allyship trainings. The department leadership's quick response to investigate departmental racism and engage the entire department for opportunities for change was critical in starting to build an antiracist community.
A new leadership role, the Associate Chair of Policy and Community-engagement elevates a focus on advocacy and community-engagement, working with the School of Medicine's Appointment and Promotion Committee to articulate a career path for junior faculty. The Associate Chair meets with various divisions to identify faculty champions and scholarly avenues for advocacy specific to each subspecialty. In response to the COVID-19 pandemic, the Associate Chair raised department awareness of the COVID-19–driven challenges of local communities and played the crucial role of generating resources to support the community (principle 4). In the department efforts to address racism (principle 6), the Associate Chair helps coordinate 7 antiracism teams led by faculty and staff dyads, enabling department members at every level to lead the charge to devise antiracist solutions. While creating pathways for members of the department to lead these efforts, the Associate Chair functions to ensure faculty and staff are supported by navigating key contacts, providing guidance for systems change, and working with senior leadership to move solutions from ideation to action. Departments of Pediatrics benefit from structural leadership—including a chair position—to ensure that advocacy and associated scholarship is supported.
The events of 2020 have challenged Departments of Pediatrics to self-scrutinize current practices to promote health equity for all children. The shift by many pediatric academic centers to incorporate community-engaged, advocacy infrastructure has prepared the field of pediatrics to respond. As next steps, we recommend an assessment of the percentage of pediatric programs that provide structure for advocacy and community engagement and a priori-driven research to discern best practice for community-engaged advocacy. With the lessons from the COVID-19 pandemic and unveiling of racism fresh in our minds, now is the time to advance Departments of Pediatrics to incorporate community engagement, advocacy, and antiracism as a central fabric of our work.
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What are the experiences of teleophthalmology in optometric referral pathways? A qualitative interview study with patients and clinicians | 8e4f7ba1-8189-4221-b7ba-5850f66a0f3e | 11129051 | Ophthalmology[mh] | Primary eyecare in the UK is mainly delivered by community optometry practices. If patients are suspected of having a retinal condition, referrals to hospital eye services (HES) are typically processed by their general practitioner (GP) based on recommendations from the community-based optometrist. Thus, optometrists are often not involved in making direct referrals using electronic referral platforms or informed of outcomes. The additional step can reduce the specificity of clinical details included in the referral, as GPs are not specialists in eye care and rarely have the time or expertise to undertake eye examinations. For several reasons, including concerns over capacity, changes in practice due to the COVID-19 pandemic, and the high number of referrals to HES, there is a need for disruptive changes in the optometric referral pathways for suspected retinal conditions (SRC). We explore the experiences of patients, optometrists, and ophthalmologists of teleophthalmology for SRC. Teleophthalmology describes the process of providing health information with medical technology at a distance, geographical, temporal or both, to facilitate decision-making. In our study, we focused on an asynchronous platform; this allowed later review, through the uploading of clinical information and multimodal retinal imaging, that is, fundus photography and macular optical coherence tomography (OCT) scans directly from the optometry practice, by the receiving HES-based ophthalmologists. A benefit of the custom-built study platform, when compared with recent attempts for the commissioning of teleophthalmology-like store-and-forward referral pathways, is that it enables optometrists to upload full-volume OCT scans from multiple device manufacturers, in both their proprietary and open-source file format, which can then be parsed and reconstructed into a high-quality full volume scan, directly viewable on the platform’s embedded viewer. Given the critical role of OCT imaging for diagnosing and managing medical retina conditions, a minimum clinical data set including full-volume OCT is a prerequisite for the safe and efficient delivery of teleophthalmology referral triaging, providing ophthalmologists with essential information to confidently make referral triaging decisions. In the absence of teleophthalmology, or when attempts to implement teleophthalmology-like pathways are made with minimal input from clinical informatics and HES-based clinician and imaging experts, triaging ophthalmologists receive referrals, either without any accompanying imaging or frequently with one or a few selected cross-sectional images, not the entire volume, then referred patients are seen face to face to assess whether further investigation or treatment is needed. The non-urgent referral pathway with and without teleophthalmology is presented in . A recent systematic review reported that teleophthalmology and digital referrals could reduce waiting time, costs, and unnecessary referrals. It also noted that teleophthalmology could lead to earlier detection and diagnosis and as such is an underutilised resource for HES. This review was based on reviewing referrals, not people’s first-hand experiences. Therefore, there is a need to understand how implementation would affect users in practice. Reports have shown that the growing use of OCT scanning has increased the number of referrals to HES; therefore, teleophthalmology has been suggested to reduce unnecessary referrals, manage growing capacity concerns, and potentially manage increasing workloads by reviewing referrals before patients are seen in clinics. We present findings from a study linked with a cluster randomised clinical trial (HERMES) evaluating the effectiveness of a teleophthalmology platform. Those in the intervention arm of the trial were using teleophthalmology to refer patients to HES, while those in the control arm were using their regular referral pathways. We report the novel qualitative findings of patients’ and healthcare professionals’ experiences to understand the practical implications of implementing teleophthalmology. This study’s overall aims, objectives, and recruitment strategy are detailed elsewhere; we summarise key points here. We undertook semistructured interviews with 41 participants from across the UK, between December 2021 and May 2022. All participants were recruited from sites participating in the wider HERMES trial. These comprised six ophthalmologists who were all making remote referral decisions; 18 community optometrists, of whom 12 were from the intervention arm and six from the control arm of the HERMES study; and 17 patients recruited from community practices, of which 14 were from clinics in the intervention arm and three from clinics in the control arm. These sites were affiliated with four NHS Trusts; Moorfields Eye Hospital NHS Foundation Trust, Central Middlesex Hospital at London North West University Healthcare NHS Trust, Birmingham University Hospital NHS Foundation Trust and North West Anglia NHS Foundation Trust. A semistructured topic guide (attached in ) was used for all interviews and was tailored to each participant group. All interviews were audiorecorded with consent. Five interviews were manually transcribed verbatim to aid familiarisation; the remaining interviews were transcribed using Scrintal Software. All transcripts were anonymised and checked for accuracy. The transcripts were coded using NVivo by an independent researcher who did not conduct the interviews, using inductive thematic analysis methods. Of note, 35 codes were initially defined and discussed with the research team. These were then refined and categorised into overarching themes. We present the three main themes which explore experiences of teleophthalmology for referrals for SRC. 10.1136/bmjopen-2023-078161.supp1 Supplementary data Patients and public involvement Eighteen patients were consulted in the planning and development of the wider HERMES study, which has been detailed in the protocol paper. The insights raised about understanding the benefits of teleophthalmology contributed to the design of this qualitative study. As noted above, 17 patients participated in interviews. Eighteen patients were consulted in the planning and development of the wider HERMES study, which has been detailed in the protocol paper. The insights raised about understanding the benefits of teleophthalmology contributed to the design of this qualitative study. As noted above, 17 patients participated in interviews. We present our findings under three themes, Efficiencies of Teleophthalmology; Teleophthalmology enables Feedback; and Concerns about Teleophthalmology . We found most participants were optimistic about the implementation of teleophthalmology in the optometric referral pathway due to the efficiencies the platform would enable. All participants expressed needing feedback during the referral process to improve care and highlighted some concerns. Efficiencies of teleophthalmology All welcomed teleophthalmology due to its ability to improve patient and clinician experiences. There is regional variation in referral pathways depending on the specific condition; GPs typically process routine referrals for SRC. However, it was reported that GPs were not always suited to create referrals due to their limited skillset in specialist eyecare. Patients often described GPs as the unnecessary ‘middleman’. Patients reported being keen to be referred directly by their optometrist and felt this would reduce their waiting time to hear back from HES if referrals were processed directly. If the optician can do the referral directly rather than you know, the optician telling me you’ll need to go and see your GP who will refer you (…) I would be more comfortable because they (optometrist) know what they’re doing whereas the GP is just saying you are alright then, if your optician told you that, then I’ll send you. (Patient 11) In the HERMES study, optometrists used teleophthalmology to refer patients to HES, enabling a quicker referral process direct to triaging ophthalmologists. They shared that teleophthalmology could improve patient satisfaction and help relieve hospital capacity pressures by reducing unnecessary hospital visits. I think the whole teleophthalmology thing will improve patient satisfaction and it makes life a lot easier, less patients, elderly patients having to find transport to the hospital, and being dilated once in the optometry practice and then being dilated again, back at the hospital and patient transport having to be arranged, so overall good, big saving of cost and finance and less crowded waiting rooms at the hospital. (Optometrist 18) Ophthalmologists shared that the teleophthalmology platform introduced uniformity to the referral process by requiring the same data fields to be completed for each patient, which was easy for the referring optometrist. This enabled referrals to be triaged and reviewed more quickly: referral decisions could be made promptly, and the appropriate triaging decision could be made regarding the indication and the urgency for a hospital visit. It’s more informative because, as you know, the platform has the questions with the tick box, um, on the optician findings which (is) not always involved in a classic referral proforma. And obviously, it has the imaging as well, which helps us to make a decision very quickly. (Ophthalmologist 1) As mentioned, the key benefit of the teleophthalmology platform is the ability to review and triage patient referrals without them having to attend a face-to-face appointment. All participants recognised and shared the advantage of saving time and resources by using teleophthalmology. Teleophthalmology enables feedback Some patients reported that they were happy for teleophthalmology to be used to assess their referrals as they would not want to attend HES if not required. Still, they expected feedback to explain the reason for not being seen for a face-to-face appointment. This was not always provided. Some patients reported dissatisfaction with their referral experience due to the lack of communication. This was also shared in the context of not receiving feedback promptly. Patients expected to hear about their referral decision more promptly through the teleophthalmology process, which increased concerns over their eye health when this expectation was not satisfied. In these cases, patients wanted to be seen or told directly and promptly why an appointment was not required and not to be kept waiting in uncertainty. Teleophthalmology can overcome this expectation discrepancy through accurate information presentation and timely and clear feedback. If the patients were to get a letter or some form of communication from the hospital or the specialist to reassure them that your case has been looked at and this is what has been concluded, I think that would be enough to put somebody’s mind at ease. (Patient 10) Optometrists stated that one of the significant benefits of teleophthalmology was the ability to receive feedback from ophthalmologists. Optometrists reported that when patients were referred to HES in the absence of teleophthalmology, patients would often return to them seeking more information and advice about their care; therefore, it was important for optometrists to be involved in the referral pathway and remain informed of their patients’ management plans. Optometrists shared that many patients were not a reliable source of information about their eye health/treatment, which could affect future care or monitoring they provided. Once we refer the patient, we don't actually know then what is happening thereafter, unless we chase the patient or, our patients are quite loyal, so they would, we would see them a year later, we will say or remember, we referred you last time, what happened? (…) So, it’s actually we're basing it off what the patient is then telling us, so we are actually getting like the second story through the patient rather than the actual clinical information. (Optometrist 12) By receiving feedback, optometrists can also verify whether their referrals were appropriate and audit themselves to improve the quality of their referrals. Because if we keep referring something that we think is urgent, but (the) ophthalmologist tells us this is not urgent, and if you learn by that, that’s going to help you, you see. Right now, there’s no feedback (…). But if I got feedback from the ophthalmologist that saw the patient and I will know for next time when I see that similar sort of situation that well, actually this isn't urgent. (Optometrist 10) Having a system where the community-based clinic is connected to the HES was also seen as a great benefit for ophthalmologists. They welcomed being able to provide feedback to the referring optometrists, especially to enable the sharing of referral decisions directly and concurred with the need to provide feedback on the referral quality to improve future referrals. It was suggested that the teleophthalmology system should send referral replies to the referring optometrist, patient, and GP so all are informed of the outcome. Concerns about teleophthalmology There were some concerns about using technology to manage patient referrals. Some patients still wanted the reassurance of seeing a clinician rather than having their referral decision and notification completed remotely. Seeing someone face to face provided the holistic care some patients reported wanting and addressed their worries and anxieties. I think (if) you don't get a chance to see the patient yourself, there is something about looking at data visually transactionally, that is fine, but there is also something about talking to the patients about how they're feeling and how they're coping with things. (Patient 10) Optometrists were mainly concerned with the practicalities of implementing a new system into their workflow. This included concerns over training to use the equipment, the reliability of network connectivity, and equipment costs that some smaller practices may not be able to bear, as well as remuneration for their time for taking on additional roles. Some also reported that completing a referral on the teleophthalmology platform took time. The barriers would be cost, because this is all based on the information that is being sent from an OCT device, yeah, as part of the process of referral, it’s not just from a letter, so when it comes to having the equipment, that’s an immediate barrier. And having the right remuneration for the equipment. (Optometrist 2) Ophthalmologists also shared these concerns; however, they were positive towards the ability of teleophthalmology, enabling them to use their time more efficiently. All welcomed teleophthalmology due to its ability to improve patient and clinician experiences. There is regional variation in referral pathways depending on the specific condition; GPs typically process routine referrals for SRC. However, it was reported that GPs were not always suited to create referrals due to their limited skillset in specialist eyecare. Patients often described GPs as the unnecessary ‘middleman’. Patients reported being keen to be referred directly by their optometrist and felt this would reduce their waiting time to hear back from HES if referrals were processed directly. If the optician can do the referral directly rather than you know, the optician telling me you’ll need to go and see your GP who will refer you (…) I would be more comfortable because they (optometrist) know what they’re doing whereas the GP is just saying you are alright then, if your optician told you that, then I’ll send you. (Patient 11) In the HERMES study, optometrists used teleophthalmology to refer patients to HES, enabling a quicker referral process direct to triaging ophthalmologists. They shared that teleophthalmology could improve patient satisfaction and help relieve hospital capacity pressures by reducing unnecessary hospital visits. I think the whole teleophthalmology thing will improve patient satisfaction and it makes life a lot easier, less patients, elderly patients having to find transport to the hospital, and being dilated once in the optometry practice and then being dilated again, back at the hospital and patient transport having to be arranged, so overall good, big saving of cost and finance and less crowded waiting rooms at the hospital. (Optometrist 18) Ophthalmologists shared that the teleophthalmology platform introduced uniformity to the referral process by requiring the same data fields to be completed for each patient, which was easy for the referring optometrist. This enabled referrals to be triaged and reviewed more quickly: referral decisions could be made promptly, and the appropriate triaging decision could be made regarding the indication and the urgency for a hospital visit. It’s more informative because, as you know, the platform has the questions with the tick box, um, on the optician findings which (is) not always involved in a classic referral proforma. And obviously, it has the imaging as well, which helps us to make a decision very quickly. (Ophthalmologist 1) As mentioned, the key benefit of the teleophthalmology platform is the ability to review and triage patient referrals without them having to attend a face-to-face appointment. All participants recognised and shared the advantage of saving time and resources by using teleophthalmology. Some patients reported that they were happy for teleophthalmology to be used to assess their referrals as they would not want to attend HES if not required. Still, they expected feedback to explain the reason for not being seen for a face-to-face appointment. This was not always provided. Some patients reported dissatisfaction with their referral experience due to the lack of communication. This was also shared in the context of not receiving feedback promptly. Patients expected to hear about their referral decision more promptly through the teleophthalmology process, which increased concerns over their eye health when this expectation was not satisfied. In these cases, patients wanted to be seen or told directly and promptly why an appointment was not required and not to be kept waiting in uncertainty. Teleophthalmology can overcome this expectation discrepancy through accurate information presentation and timely and clear feedback. If the patients were to get a letter or some form of communication from the hospital or the specialist to reassure them that your case has been looked at and this is what has been concluded, I think that would be enough to put somebody’s mind at ease. (Patient 10) Optometrists stated that one of the significant benefits of teleophthalmology was the ability to receive feedback from ophthalmologists. Optometrists reported that when patients were referred to HES in the absence of teleophthalmology, patients would often return to them seeking more information and advice about their care; therefore, it was important for optometrists to be involved in the referral pathway and remain informed of their patients’ management plans. Optometrists shared that many patients were not a reliable source of information about their eye health/treatment, which could affect future care or monitoring they provided. Once we refer the patient, we don't actually know then what is happening thereafter, unless we chase the patient or, our patients are quite loyal, so they would, we would see them a year later, we will say or remember, we referred you last time, what happened? (…) So, it’s actually we're basing it off what the patient is then telling us, so we are actually getting like the second story through the patient rather than the actual clinical information. (Optometrist 12) By receiving feedback, optometrists can also verify whether their referrals were appropriate and audit themselves to improve the quality of their referrals. Because if we keep referring something that we think is urgent, but (the) ophthalmologist tells us this is not urgent, and if you learn by that, that’s going to help you, you see. Right now, there’s no feedback (…). But if I got feedback from the ophthalmologist that saw the patient and I will know for next time when I see that similar sort of situation that well, actually this isn't urgent. (Optometrist 10) Having a system where the community-based clinic is connected to the HES was also seen as a great benefit for ophthalmologists. They welcomed being able to provide feedback to the referring optometrists, especially to enable the sharing of referral decisions directly and concurred with the need to provide feedback on the referral quality to improve future referrals. It was suggested that the teleophthalmology system should send referral replies to the referring optometrist, patient, and GP so all are informed of the outcome. There were some concerns about using technology to manage patient referrals. Some patients still wanted the reassurance of seeing a clinician rather than having their referral decision and notification completed remotely. Seeing someone face to face provided the holistic care some patients reported wanting and addressed their worries and anxieties. I think (if) you don't get a chance to see the patient yourself, there is something about looking at data visually transactionally, that is fine, but there is also something about talking to the patients about how they're feeling and how they're coping with things. (Patient 10) Optometrists were mainly concerned with the practicalities of implementing a new system into their workflow. This included concerns over training to use the equipment, the reliability of network connectivity, and equipment costs that some smaller practices may not be able to bear, as well as remuneration for their time for taking on additional roles. Some also reported that completing a referral on the teleophthalmology platform took time. The barriers would be cost, because this is all based on the information that is being sent from an OCT device, yeah, as part of the process of referral, it’s not just from a letter, so when it comes to having the equipment, that’s an immediate barrier. And having the right remuneration for the equipment. (Optometrist 2) Ophthalmologists also shared these concerns; however, they were positive towards the ability of teleophthalmology, enabling them to use their time more efficiently. While previous work has focused on the efficacy and efficiency of teleophthalmology platforms through reviewing referrals, we report insights based on experiences from patients, optometrists, and ophthalmologists to validate previous findings on perceptions of using teleophthalmology for SRC. All participants recognised the value of implementing a teleophthalmology system into their ophthalmic care pathway due to its potential to improve patient care and health services efficiencies. This is supported by others, who found through a review of referrals that teleophthalmology can reduce unnecessary HES visits and significantly impact patient anxieties. Our study has shown this in practice, with many patients sharing that they would not want to attend HES if not required. Both optometrists and ophthalmologists reported that teleophthalmology’s significant advantage is the ability to electronically refer patients directly from optometrist practices to HES, which can significantly reduce the waiting time for patients. The ability to triage referrals electronically also enabled ophthalmologists to provide replies and feedback to the referring optometrist via the teleophthalmology platform, which they greatly valued. Implementing teleophthalmology into the eye care pathway would remove the burden on GPs of having to process patient referrals, but they must be informed of such referrals. GPs have, in principle, supported the suggestion of optometrists referring patients directly, and we found that patients and optometrists would support this change in practice. There is great value in involving optometrists in the referral process, as it has been reported that this could reduce unnecessary referrals by approximately half The overarching theme shared by all participants which substantiates many of the benefits of the teleophthalmology platform, is the potential of the platform to facilitate the provision of feedback. The importance of receiving timely feedback in eye care, in general, has been reported by others and was essential for patients to alleviate their concerns over their eye health. Harvey et al specifically outline the factors that could affect the provision of feedback, and a key implication of their work is the call for technology to support this provision. Thus, we found that teleophthalmology could overcome concerns in the optometric referral pathway. While feedback can keep both patients and optometrists informed, it can also improve future referral quality through open conversations between referring clinicians. Our results concur as we report optometrists greatly value receiving referral replies directly from ophthalmologists to remain informed of their patients’ care and audit their referrals. Additionally, previous research has highlighted that the lack of communication between optometrists and ophthalmologists can be problematic; therefore, implementing a teleophthalmology platform could help to overcome this. Potential barriers raised by some optometrists were the initial setup costs, which include time, training, and financial costs. While others have reported this should be considered, we found this to be a key concern in practice. According to the current General Ophthalmic Services contract (2023), OCT scans are not a contracted service in optometric care. Therefore, there is a need to ensure that optometrists are appropriately remunerated for providing this service. Optometrists would also need to have appropriate access to NHS e-referral systems to expediently refer patients to the HES system. Others have begun to explore the cost-effectiveness of implementing teleophthalmology systems; further work is needed to establish health-economic benefits concerning SRC that were raised in our study. To successfully implement teleophthalmology into the optometric referral pathway, there needs to be an investment to enable parity among optometry practices to support new technology setup. While the implementation of teleophthalmology was perceived to initially increase the workload of optometrists to process referrals and ophthalmologists to triage referrals, with the correct remuneration, there is significant potential to relieve pressures on stretched eye care services. We acknowledge study limitations including the influence of participation bias. The participants who chose to participate in our research may have different views from those who did not participate, which have not been captured in our study. We also recognise that the ophthalmologists who chose to participate were involved in the HERMES study itself, which led to increased knowledge of teleophthalmology. Future work should endeavour to recruit a more diverse sample of participants to capture broader views on the experiences of teleophthalmology. However, the strengths of our study include the use of in-depth interviews, through which we were able to elicit the lived experiences of those involved in the study, many of whom had direct experience with the teleophthalmology platform. We were also able to recruit participants across the stakeholder group, thus providing multiple perspectives on the teleophthalmology pathway. Optometrists and ophthalmologists provided their perspectives on using the platform and the practicalities involved in use, while patients reported on the personal impacts of navigating their eye-health journey through teleophthalmology. These diverse perspectives have enabled us to corroborate and extend existing understanding of the practical implications of implementing teleophthalmology. Implementing teleophthalmology into the optometric referral pathway has numerous benefits, as outlined by all participants. Through our in-depth interview study with patients, optometrists, and ophthalmologists, we found that they generally report great value in implementing teleophthalmology through improving efficiency and the ability to provide and receive feedback. Patients were satisfied if their referrals were reviewed with teleophthalmology to reduce the possibility of unnecessary HES visits if this was clearly and efficiently communicated back to them. Optometrists felt they were better suited than GPs to write and process patient referrals and would feel more valued if they were more directly involved in the pathway. Finally, ophthalmologists were pleased with a system enabling them to manage their caseloads more efficiently. Further efficiencies teleophthalmology can promote include removing the burden on GPs, the time patients wait to be seen by HES, the time it takes for ophthalmologists to review and provide referral replies and finally, the overarching benefit to all participants of being involved and receiving feedback. Future work could explore how to overcome barriers such as connectivity and the specific health economics of implementing teleophthalmology to validate our findings. Reviewer comments Author's manuscript |
Implementing a safer and more reliable system to monitor test results at a teaching university-affiliated facility in a family medicine group: a quality improvement process report | 32fa0684-5817-4166-8a7e-c331a44b8650 | 10582889 | Family Medicine[mh] | Approximately 40% of patients who consult in a primary care facility receive a prescription for a medical laboratory test or medical imaging. Despite the prescribers’ medicolegal responsibility to ensure a sufficiently reliable system is in place to securely monitor the process and efficiently communicating results, most clinical settings prioritise ‘no news is good news’. The lack of test results follow-up ends in an unfavourable outcome for the prescribing physician in more than 90% of complaints to the College of Family Physicians.
This project shows that with quality improvement methods, it is possible to implement an improved, more reliable and efficient system for tracking test results, thus reducing risks to patient safety. It also shows that residents who experienced this improved system during their residency want to implement it in their medical practice. Also, calls for normal results are not as time consuming as expected and the time spent making the calls is more than compensated for by increased patient satisfaction. Patients appreciated receiving normal results as it brought them peace of mind.
Hopefully, this project will inspire other clinical settings to implement an improved, more reliable and efficient system for tracking test results in the setting and move away from the ‘no news is good news’ concept.
Approximately 40% of patients who consult in a primary care facility receive a prescription for a medical laboratory test or medical imaging. Following the Act amending the Professional Code and other legislative provisions in the field of health , there are now a larger number of prescribers in Quebec, including medical doctors, residents, nurses and pharmacists. In 2010–2011, approximately 171 million procedures in medical biology laboratories and 7.5 million medical imaging procedures were carried out in the province. Although these numbers continue to increase, mechanisms to transmit test results to prescribers have not evolved, highlighting the potentially harmful consequences of weaknesses in the process. Several steps are required between prescription (referring to medical laboratory test or medical imaging or medication) and follow-up with the patient: ordering, performing, result tracking, results returning to the office and prescribers, results being reviewed, results being documented and filed, patient being notified of test results and patient follow-up. Potential errors at various stages of the process can be detrimental to patients. Critical analyses are often misplaced or ignored due to inconsistent follow-up procedures. Moreover, an additional level of complexity is added by technologies such as electronic medical record (EMR) systems. Despite the prescribers’ medicolegal responsibility to ensure a sufficiently reliable system is in place to securely monitor the process and efficiently communicating results, most clinical settings operate according to ‘no news is good news’. The lack of test results follow-up ends in an unfavourable outcome for the prescribing physician in more than 90% of complaints to the College of Family Physicians. Problem description In this clinical setting, a major contextual change in regional administrative affiliation brought additional challenges to ensure the safe follow-up of test results, which were aggravated by confusion with technology. On several occasions, results were recorded in patients’ files, but prescribers were not informed of the outcomes. This problem had an impact on patient safety and continuity of care (ie, positive results for stool tests for blood, abnormal mammograms, elevated prostate antigen test). To address the situation, two clinicians working in the setting completed training from the Canadian Medical Protective Association (CMPA) on the safe follow-up of test results. The training increased awareness of medicolegal responsibilities and the possible ramifications of an ineffective results monitoring system for prescribers. The team wanted to confirm their impressions, based on several risk-related mishaps in our facility, by measuring the number of incidents reported. As a teaching facility, it was important to develop a more reliable and secure system for test results follow-up through a quality improvement (QI) implementation process. Available knowledge All prescribers of investigations or screenings have the ethical obligation to follow-up on the patient’s condition, to transfer this follow-up to a colleague if they cannot provide it themselves and to respond to results in an appropriate and timely manner. According to Article 100 of the Act respecting health services and social services , providers in clinical settings have a strict obligation to ensure the provision of quality health and social services that are continuous, accessible, safe and respectful of people’s rights and needs to reduce or resolve the health and welfare problems of various population groups. These should also be integrated and operationalised within diagnostic services. It is the responsibility of providers in the setting to demonstrate reasonable efforts to ensure that a reliable system to manage the testing process is in place and is equal or superior to those in place in other settings. In Canada, a committee for the safe monitoring of investigation or screening results (CMPA), with the assistance of clinicians and managers from the health and social services network, identified the most important areas of weakness in the process of transmitting test results to prescribers. The committee also suggested a series of actions to reinforce this process by establishing better habits and stronger safety nets. Committee members also agreed on the need for organisations to carry out periodic audits of key steps in the process of monitoring test results. Rationale of intervention In 2017, the Agency for Health Research and Quality (AHRQ) prepared a revised and improved version of a toolkit to increase the security and reliability of the process of monitoring test results. This new version was intended to support those in clinical settings to increase the reliability of testing process management from prescription to patient follow-up. The improved model was modified to fit the realities of a teaching facility by including residents during implementation. This project was inspired by the Plan-Do-Study-Act (PDSA) QI model described in the AHRQ’s improved toolkit and the Framework for Safe Management Follow-Up of Investigation or Screening Results. Specific aims The main goal of this project was to ensure safety of care through reliable test results follow-up and adapting processes to available technology. The following subgoals were determined: Implement an improved, more reliable and efficient system for tracking test results in the setting (after an internal audit). Increase prescribers in the clinical setting’s perceived reliability and safety of the test results monitoring system.
In this clinical setting, a major contextual change in regional administrative affiliation brought additional challenges to ensure the safe follow-up of test results, which were aggravated by confusion with technology. On several occasions, results were recorded in patients’ files, but prescribers were not informed of the outcomes. This problem had an impact on patient safety and continuity of care (ie, positive results for stool tests for blood, abnormal mammograms, elevated prostate antigen test). To address the situation, two clinicians working in the setting completed training from the Canadian Medical Protective Association (CMPA) on the safe follow-up of test results. The training increased awareness of medicolegal responsibilities and the possible ramifications of an ineffective results monitoring system for prescribers. The team wanted to confirm their impressions, based on several risk-related mishaps in our facility, by measuring the number of incidents reported. As a teaching facility, it was important to develop a more reliable and secure system for test results follow-up through a quality improvement (QI) implementation process.
All prescribers of investigations or screenings have the ethical obligation to follow-up on the patient’s condition, to transfer this follow-up to a colleague if they cannot provide it themselves and to respond to results in an appropriate and timely manner. According to Article 100 of the Act respecting health services and social services , providers in clinical settings have a strict obligation to ensure the provision of quality health and social services that are continuous, accessible, safe and respectful of people’s rights and needs to reduce or resolve the health and welfare problems of various population groups. These should also be integrated and operationalised within diagnostic services. It is the responsibility of providers in the setting to demonstrate reasonable efforts to ensure that a reliable system to manage the testing process is in place and is equal or superior to those in place in other settings. In Canada, a committee for the safe monitoring of investigation or screening results (CMPA), with the assistance of clinicians and managers from the health and social services network, identified the most important areas of weakness in the process of transmitting test results to prescribers. The committee also suggested a series of actions to reinforce this process by establishing better habits and stronger safety nets. Committee members also agreed on the need for organisations to carry out periodic audits of key steps in the process of monitoring test results.
In 2017, the Agency for Health Research and Quality (AHRQ) prepared a revised and improved version of a toolkit to increase the security and reliability of the process of monitoring test results. This new version was intended to support those in clinical settings to increase the reliability of testing process management from prescription to patient follow-up. The improved model was modified to fit the realities of a teaching facility by including residents during implementation. This project was inspired by the Plan-Do-Study-Act (PDSA) QI model described in the AHRQ’s improved toolkit and the Framework for Safe Management Follow-Up of Investigation or Screening Results.
The main goal of this project was to ensure safety of care through reliable test results follow-up and adapting processes to available technology. The following subgoals were determined: Implement an improved, more reliable and efficient system for tracking test results in the setting (after an internal audit). Increase prescribers in the clinical setting’s perceived reliability and safety of the test results monitoring system.
Context This project was conducted as a QI process. In order to ensure team adherence to the process, many contextual factors were considered, including the fact that the setting is a teaching facility of 6000 patients with multiple prescribers: 14 supervising physicians, 1 specialised nurse practitioner, 38 resident physicians, 25 other learners (externs, primary care specialised nurses and third year specialty residents), 2 clinical nurses, 1 pharmacist and 15 administrative staff were involved. In the setting, about 33% of consultations resulted in a laboratory or imaging test. During the project, repartition of prescriptions was: supervising physicians (10291), learners (5419), nurse practitioners (688) and clinical nurses (397). The human factor and potential resistance to change were prioritised when proposed actions affected staff and patients. During the period, the facility also underwent a transition in the EMR system, which led to a need for adaptation and improvement. Adjustments related to the pandemic also became a major part of the process due to its multiple consequences, such as staff shortages. Description of the intervention To launch the implementation, an internal audit was conducted measuring the number of incidents reported and compiled from 1 November 2018 to 23 January 2019. To facilitate incident reporting, the QI agent created a mailbox in the EMR dedicated to reporting incidents. Following audit results, a multidisciplinary team was assembled and steps for test results monitoring were mapped in a flow chart. This flow chart allowed the team to target specific change opportunities to test. The Pareto chart in highlights the three main categories of incidents: (1) issuance to residents, when the resident’s name does not appear on the result or does not appear in the correct place, (2) scanning and indexing, which groups the results digitised with erroneous information or in the wrong file and, finally, (3) transmission to the residents when the results are sent to the supervisor only. The other errors were of a varied nature, for example: a priority result was transmitted in the non-priority way and a patient misplaced his prescription and thus omitted to go for the examination. The Pareto chart was used to prioritise actions towards the three main causes (categories of incidents). Based on the initial results, the team members chose and designed several mechanisms to measure, mitigate and reduce the number of incidents. To validate the impact of the changes implemented, the team also conducted surveys to validate patients, residents and staff members’ perception. The QI agent investigated reported incidents, identified the root causes, suggested solutions, implemented corrective measures into the process and ensured follow-up so that corrections could be made if necessary (ie, retransmitting test results to the right person, deleting duplicates). The management and QI committee of the clinical setting took the opportunity to dedicate their annual retreat to launch the project, thereby demonstrating their commitment to the process, and encouraging the adherence of staff members. The multidisciplinary team developed an accredited training programme for the safer and more reliable system to monitor test result. The first part of the activity focused on the medicolegal and ethical obligations of prescribers, and the second part was dedicated to a workshop inspired by the CMPA model that considered the contextual particularities of teaching facility environments. During the retreat, the QI agent facilitated a half-day workshop: mapping the actual process and the problems experienced, developing change ideas, prioritising and operationalising the change ideas. The result of the workshop is summarised in the driver diagram shown in . Team members developed change ideas that were tested and implemented in the setting through PDSA cycles over the following months: First cycle: recognising family medicine residents as prescribers The management team ensured that laboratory and imaging departments were informed the teaching facility’s mission and medical residents’ role, thus legitimising the role of residents as prescribers. Residents were permitted to request tests in their name instead of that of their supervisor to facilitate learning of the process, accountability and continuity of care for their patients. The working group designed a tool that was displayed in every consultation room. This visually accessible checklist aimed to remind prescribers of their responsibility to signal non-reception of test results and to suggest best practices. This tool should be displayed as an ongoing reminder in the setting. All staff members were trained on processes and methods of mitigation: how to use the right request, how to route it correctly and how to implement them alongside the tracking method. The academic team added training on result tracking processes during residents’ first week at the facility, thus ensuring sustainability. The training also applies to all new staff members. Second cycle: announcing normal results The team opted to systematically inform patients of normal results, moving away from the ‘no news is good news’ concept. To operationalise this innovation, a dedicated mailbox was created in the EMR. When signing a normal result, prescribers create a task in this mailbox for nursing assistants to call patients over the next three working days to communicate the result. Third cycle: connecting prescribers to regional techno-centre Adequate and efficient connection of prescribers to the regional techno-centre was ensured allowing electronic transmission. The contact information of prescribers who practise in several different facilities was adjusted and monitored. Fourth cycle: eliminating duplicates through a computer protocol A computer protocol was negotiated and secured with the anatomy-pathology department to eliminate automatic duplicates. The other services approached refused to test the protocol. Study of the intervention Shewhart control chart with its specific rules for determining special cause was used to show improvement and measure the impact of the intervention. Measures The main variables were chosen to confirm that the system properly identified incidents, was not time consuming for staff members and considered patient, prescriber and staff member satisfaction while being efficient and safe in terms of continuity of patient care. There were no additional costs associated with the implemented system. One main concern during the process was to be mindful of staff members by avoiding overloading human resources at the facility and optimising the use of staff members’ time. Number of errors (outcome measure): was collected via systematic reporting of incidents monthly, and error rate calculated according to number of prescriptions issued for the same period. Patient satisfaction (balance measure): when patients were called with normal results, they were asked for consent to answer two questions related to their satisfaction. Prescribers’ satisfaction (balance measure) and compliance with incident reporting (process measure): a general survey including 24 questions was sent by email to eight prescribers at the facility. Three questions were related to their appreciation of the change process, four questions assessed tools implemented throughout the process, three questions were self-assessments of their confidence level with results tracking methods and two questions asked about normal results (scale of 1–5). The survey also included self-assessment questions about tracking test results and identification methods for residents. Residents’ satisfaction (balance measure): a survey was sent via email to 38 residents (22 of which are now practising physicians) to evaluate the impacts of the implemented system. In addition to descriptive data, residents were asked to select which aspect of the improved system they most appreciated, if they felt the system was secure and reliable enough, which aspect of the system they found most difficult, what the system brought to their learning of the profession, what they remembered most about the process, what they plan to continue to implement in their practice facility, perceived obstacles to implementing a similar system in their practice facility and comments or recommendations for a results follow-up system in their practice and in general. Time spent communicating normal results (balance measures): staff members recorded the amount of time spent communicating normal results or leaving message when patients were clearly identified in the voicemail greeting. Analyses Microsoft Excel software was used for the data analysis. Data were displayed on an XmR Shewhart chart, and mean error rate and SD of the error rate were calculated. To determine statistical change, established rules for differentiating special versus common cause variation were used for this chart.
This project was conducted as a QI process. In order to ensure team adherence to the process, many contextual factors were considered, including the fact that the setting is a teaching facility of 6000 patients with multiple prescribers: 14 supervising physicians, 1 specialised nurse practitioner, 38 resident physicians, 25 other learners (externs, primary care specialised nurses and third year specialty residents), 2 clinical nurses, 1 pharmacist and 15 administrative staff were involved. In the setting, about 33% of consultations resulted in a laboratory or imaging test. During the project, repartition of prescriptions was: supervising physicians (10291), learners (5419), nurse practitioners (688) and clinical nurses (397). The human factor and potential resistance to change were prioritised when proposed actions affected staff and patients. During the period, the facility also underwent a transition in the EMR system, which led to a need for adaptation and improvement. Adjustments related to the pandemic also became a major part of the process due to its multiple consequences, such as staff shortages.
To launch the implementation, an internal audit was conducted measuring the number of incidents reported and compiled from 1 November 2018 to 23 January 2019. To facilitate incident reporting, the QI agent created a mailbox in the EMR dedicated to reporting incidents. Following audit results, a multidisciplinary team was assembled and steps for test results monitoring were mapped in a flow chart. This flow chart allowed the team to target specific change opportunities to test. The Pareto chart in highlights the three main categories of incidents: (1) issuance to residents, when the resident’s name does not appear on the result or does not appear in the correct place, (2) scanning and indexing, which groups the results digitised with erroneous information or in the wrong file and, finally, (3) transmission to the residents when the results are sent to the supervisor only. The other errors were of a varied nature, for example: a priority result was transmitted in the non-priority way and a patient misplaced his prescription and thus omitted to go for the examination. The Pareto chart was used to prioritise actions towards the three main causes (categories of incidents). Based on the initial results, the team members chose and designed several mechanisms to measure, mitigate and reduce the number of incidents. To validate the impact of the changes implemented, the team also conducted surveys to validate patients, residents and staff members’ perception. The QI agent investigated reported incidents, identified the root causes, suggested solutions, implemented corrective measures into the process and ensured follow-up so that corrections could be made if necessary (ie, retransmitting test results to the right person, deleting duplicates). The management and QI committee of the clinical setting took the opportunity to dedicate their annual retreat to launch the project, thereby demonstrating their commitment to the process, and encouraging the adherence of staff members. The multidisciplinary team developed an accredited training programme for the safer and more reliable system to monitor test result. The first part of the activity focused on the medicolegal and ethical obligations of prescribers, and the second part was dedicated to a workshop inspired by the CMPA model that considered the contextual particularities of teaching facility environments. During the retreat, the QI agent facilitated a half-day workshop: mapping the actual process and the problems experienced, developing change ideas, prioritising and operationalising the change ideas. The result of the workshop is summarised in the driver diagram shown in . Team members developed change ideas that were tested and implemented in the setting through PDSA cycles over the following months: First cycle: recognising family medicine residents as prescribers The management team ensured that laboratory and imaging departments were informed the teaching facility’s mission and medical residents’ role, thus legitimising the role of residents as prescribers. Residents were permitted to request tests in their name instead of that of their supervisor to facilitate learning of the process, accountability and continuity of care for their patients. The working group designed a tool that was displayed in every consultation room. This visually accessible checklist aimed to remind prescribers of their responsibility to signal non-reception of test results and to suggest best practices. This tool should be displayed as an ongoing reminder in the setting. All staff members were trained on processes and methods of mitigation: how to use the right request, how to route it correctly and how to implement them alongside the tracking method. The academic team added training on result tracking processes during residents’ first week at the facility, thus ensuring sustainability. The training also applies to all new staff members. Second cycle: announcing normal results The team opted to systematically inform patients of normal results, moving away from the ‘no news is good news’ concept. To operationalise this innovation, a dedicated mailbox was created in the EMR. When signing a normal result, prescribers create a task in this mailbox for nursing assistants to call patients over the next three working days to communicate the result. Third cycle: connecting prescribers to regional techno-centre Adequate and efficient connection of prescribers to the regional techno-centre was ensured allowing electronic transmission. The contact information of prescribers who practise in several different facilities was adjusted and monitored. Fourth cycle: eliminating duplicates through a computer protocol A computer protocol was negotiated and secured with the anatomy-pathology department to eliminate automatic duplicates. The other services approached refused to test the protocol.
Shewhart control chart with its specific rules for determining special cause was used to show improvement and measure the impact of the intervention.
The main variables were chosen to confirm that the system properly identified incidents, was not time consuming for staff members and considered patient, prescriber and staff member satisfaction while being efficient and safe in terms of continuity of patient care. There were no additional costs associated with the implemented system. One main concern during the process was to be mindful of staff members by avoiding overloading human resources at the facility and optimising the use of staff members’ time. Number of errors (outcome measure): was collected via systematic reporting of incidents monthly, and error rate calculated according to number of prescriptions issued for the same period. Patient satisfaction (balance measure): when patients were called with normal results, they were asked for consent to answer two questions related to their satisfaction. Prescribers’ satisfaction (balance measure) and compliance with incident reporting (process measure): a general survey including 24 questions was sent by email to eight prescribers at the facility. Three questions were related to their appreciation of the change process, four questions assessed tools implemented throughout the process, three questions were self-assessments of their confidence level with results tracking methods and two questions asked about normal results (scale of 1–5). The survey also included self-assessment questions about tracking test results and identification methods for residents. Residents’ satisfaction (balance measure): a survey was sent via email to 38 residents (22 of which are now practising physicians) to evaluate the impacts of the implemented system. In addition to descriptive data, residents were asked to select which aspect of the improved system they most appreciated, if they felt the system was secure and reliable enough, which aspect of the system they found most difficult, what the system brought to their learning of the profession, what they remembered most about the process, what they plan to continue to implement in their practice facility, perceived obstacles to implementing a similar system in their practice facility and comments or recommendations for a results follow-up system in their practice and in general. Time spent communicating normal results (balance measures): staff members recorded the amount of time spent communicating normal results or leaving message when patients were clearly identified in the voicemail greeting.
Microsoft Excel software was used for the data analysis. Data were displayed on an XmR Shewhart chart, and mean error rate and SD of the error rate were calculated. To determine statistical change, established rules for differentiating special versus common cause variation were used for this chart.
The interventions led to a decrease in the error rate from a mean of 6.1% to 1.9%. Prior to the process initiative there was a large variation in the error rate, with a range of 2.7–12.1%. The variation decreased from 0% to 4.8%. After the initiative was implemented, the fourth rule for special cause applied. This rule states that there is a special cause when 2 out of 3 consecutive points are near (outer one-third) the control limit. Our data showed 4 consecutive points in the critical area of the lower control limit. The intervention led to a decrease in the variation error rate, with the SD decreasing from 2.1% to 1.2%. The reduction in the variation of error rate is illustrated in the control chart which shows less variation after intervention. Though the error rate increased again due to difficulty with connection of new residents to the regional techno-centre, the improvement is sustained in time, data never crossing the control lines . For time spent communicating normal results, administrative staff members made a maximum of 15 calls per day averaging a total duration of 3–5 min per call. The 30 patients surveyed gave a score of 10 out of 10 for their satisfaction with receiving a call communicating normal results. Twenty-three patients justified their satisfaction with a feeling of reassurance and seven with a feeling of joy. A total of six of eight surveyed prescribers responded. The respondents reported being satisfied with the training on safe follow-up of test results. When it came to residents, six of the 38 residents surveyed responded (one from 2020, one from 2021 and four from 2022). Of these, four were second year residents. Regarding their practice facilities, two were in family medicine groups, one was at a teaching facility and two were in hospital facilities. Residents most appreciated that normal results started to be announced to patients (5), that they could receive their test results themselves directly in their EMR (5) and that they could request test prescriptions themselves (4). They perceived that the system was reliable because of duplicate results communications (residents and supervisors). They indicated that it was difficult to choose the appropriate method to identify results not received (5), to manage reminders for tracking non-received results (3), to manage the flow of incoming results from the EMR (2), to add their supervisor to the test order (1) and to transfer normal results to administrative agents (1). In terms of professional learning, they appreciated that the new system facilitated patients’ accountability for their results (reception of normal and abnormal results) and reminders on the importance of following up on ordered tests and not ordering tests for no specific reason.
In this study, we found that with QI methods, we were able to implement an improved, more reliable and efficient system for tracking test results. We were also able to reduce the error rate and its variation by adapting processes to available technology. Prescribers felt that the system was more reliable and secure. Based on their experience with the process, residents reported that it is important to find alternative methods to ensure safe monitoring of results. In their eventual practice facilities, graduated residents continue to use reminders to follow-up on results and communicate normal results to patients. When asked about possible obstacles in the implementation of such a system in non-teaching family medicine groups, residents mentioned possible difficulties in standardising practices and consent, which must be obtained before sending emails. Residents also suggested that this follow-up system may be difficult to maintain with an increased case load of patients. Using the resources available through the EMR, residents agreed that they would advocate for their present practice facilities to implement a similar follow-up system. In terms of improvements to the follow-up system that they experienced, residents suggested adding automated reminders in the EMR when a request for testing is made and for acceptable lengths of time to be defined. Initial staff reluctance regarding an aversion to time-consuming calls proved to be unfounded and was more than compensated for by increased patient satisfaction. Patients appreciated receiving normal results as it brought them peace of mind. Whereas patients previously called the facility often about test results, this no longer happened following implementation of the system. This outcome alone has saved a significant amount of time because administrative staff are less often required to communicate to physicians the need to contact patients for follow-up as it is now all integrated in one system. To empower patients under the new system, it is important for prescribers to inform patients of the point in time at which they should contact the facility if they have not received test results. The administrative agents and auxiliary nurses making these calls quickly realised that many patients were not answering calls made from hidden numbers. This doubled or tripled the number of calls made to these patients. Therefore, patients were asked for their consent to leave voice messages communicating normal test results. Messages were left only if patients properly identified themselves with their name in their voicemail greeting. Otherwise, staff did not leave a message to avoid sensitive information being disclosed in cases of dialling error, for example. Most patients gave their consent, which made the process faster and easier. Strengths of the project This project had many strengths, as it was based on documented approaches and gathered the input of patients, staff and prescribers to ensure the implementation of a reliable, safe and secure system. It proposes contextual aspects to facilitate adaptation in other facility settings and suggests approaches to avoid staff overload and facilitate residents’ autonomy. The results showed a significant decrease in error rates. The system proved to be time efficient as well. Management considered the human resistance factor when it came to change and made sure to put mobilising actions in place to facilitate adherence to the process. The system is set up to be highly sustainable, as it is directly implemented in the EMR, thereby making use of technology while remaining secure. Training provided during the first week of new residents, physicians, other health professionals and administrative agents ensures continuity of the system. In terms of reporting mechanisms, a facilitated process is in place to report risks to be investigated and resolved as well as to meet the obligation to have a reliable system in place. Finally, including residents as autonomous prescribers exposes them to the realities of the practice and increases their awareness of accountability in terms of results follow-up. The implemented follow-up system meets CanMEDS Framework guidelines regarding the topics that must be taught to residents and the skills they need to develop, including the following: medical, actively promoting the promotion of QI and increased patient safety, individually and within their team, by implementing mechanisms to optimise patient care in their practice; leadership, contributing to the improvement of comprehensive, holistic and continuous patient-centred care provided within teams, organisations and systems; and scholarly, teaching students, residents, other healthcare professionals and the public, and ensuring that patient safety is maintained when learners are involved in care. Limitations Caution is advised in terms of generalising the results of this study because it was conducted in one facility that is a teaching setting. It is important to consider specific contextual particularities when implementing a similar system. Iterative QI process and contextual aspects must be taken into consideration when replicating this approach. It was paramount that the management team reinforced the importance of the project with staff members by prioritising it and ensuring mobilisation around its achievement. Another limitation is the low response rate to the post implementation survey for residents. Most of the solicited residents were practising graduates who lack time and may no longer use the available email addresses used to contact them. However, those who did respond gave detailed answers and provided generous insights. Additionally, satisfaction was only assessed for patients who were successfully reached by phone for the purpose of transmitting normal test results. Patients for whom voicemails were left or who had abnormal test results and were contacted by their treating prescriber were not part of the sample. Furthermore, as the system was implemented using an iterative process, it is important to be aware of the need for continuous adaption to new technologies and to plan staff training accordingly to ensure the system’s sustainability. It is not enough to ensure that results are indexed, and patients notified; it is also necessary to ensure that any test requested by a prescriber is followed up on to prevent results from not being transmitted and to minimise the occurrence of missing results.
This project had many strengths, as it was based on documented approaches and gathered the input of patients, staff and prescribers to ensure the implementation of a reliable, safe and secure system. It proposes contextual aspects to facilitate adaptation in other facility settings and suggests approaches to avoid staff overload and facilitate residents’ autonomy. The results showed a significant decrease in error rates. The system proved to be time efficient as well. Management considered the human resistance factor when it came to change and made sure to put mobilising actions in place to facilitate adherence to the process. The system is set up to be highly sustainable, as it is directly implemented in the EMR, thereby making use of technology while remaining secure. Training provided during the first week of new residents, physicians, other health professionals and administrative agents ensures continuity of the system. In terms of reporting mechanisms, a facilitated process is in place to report risks to be investigated and resolved as well as to meet the obligation to have a reliable system in place. Finally, including residents as autonomous prescribers exposes them to the realities of the practice and increases their awareness of accountability in terms of results follow-up. The implemented follow-up system meets CanMEDS Framework guidelines regarding the topics that must be taught to residents and the skills they need to develop, including the following: medical, actively promoting the promotion of QI and increased patient safety, individually and within their team, by implementing mechanisms to optimise patient care in their practice; leadership, contributing to the improvement of comprehensive, holistic and continuous patient-centred care provided within teams, organisations and systems; and scholarly, teaching students, residents, other healthcare professionals and the public, and ensuring that patient safety is maintained when learners are involved in care.
Caution is advised in terms of generalising the results of this study because it was conducted in one facility that is a teaching setting. It is important to consider specific contextual particularities when implementing a similar system. Iterative QI process and contextual aspects must be taken into consideration when replicating this approach. It was paramount that the management team reinforced the importance of the project with staff members by prioritising it and ensuring mobilisation around its achievement. Another limitation is the low response rate to the post implementation survey for residents. Most of the solicited residents were practising graduates who lack time and may no longer use the available email addresses used to contact them. However, those who did respond gave detailed answers and provided generous insights. Additionally, satisfaction was only assessed for patients who were successfully reached by phone for the purpose of transmitting normal test results. Patients for whom voicemails were left or who had abnormal test results and were contacted by their treating prescriber were not part of the sample. Furthermore, as the system was implemented using an iterative process, it is important to be aware of the need for continuous adaption to new technologies and to plan staff training accordingly to ensure the system’s sustainability. It is not enough to ensure that results are indexed, and patients notified; it is also necessary to ensure that any test requested by a prescriber is followed up on to prevent results from not being transmitted and to minimise the occurrence of missing results.
This project’s main goal of ensuring safety and continuity of care through reliable test results follow-up and by adapting processes to available technology was achieved by implementing an improved, more reliable and efficient system for tracking test results (after an internal audit) that was perceived by prescribers as reliable and safe.
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Machine learning and multi-omics in precision medicine for ME/CFS | bf696984-14e6-4a6b-a882-d3232e9a5f1b | 11731168 | Biochemistry[mh] | The chronic illness Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) evolves and perpetuates from a combination of biological and environmental determinants. Onset often occurs after a trigger event , such as viral infection, trauma, or toxin exposure, which induces a physiological response. Such responses are typically transient, however are thought to become persistent or dysfunctional in ME/CFS, manifesting as idiopathic fatigue lasting for 3-months or longer, post-exertional malaise (PEM), brain fog, tender lymph nodes, dizziness, muscle or joint pain, digestive problems, or unrefreshing sleep . The exact biological mechanism that results in a chronic ME/CFS state remains unidentified. However, accumulating evidence indicates anomalies in various biological systems including energy metabolism , neuroendocrine function , immunology , and autonomic regulation . ME/CFS may be considered as a cluster of related, but distinct pathophysiological constructs , contrasting the reductionist view of it as a singular entity with stages of disease progression. Additionally, the similarities between long COVID and ME/CFS pathophysiologies —despite long COVID developing from a known viral origin (SARS-CoV-2 infection)—suggest that diverse symptom manifestations may be driven more by individual physiological response, rather than specific underlying causes. There are currently no definitive laboratory tests, and diagnosis is made based on exclusion. One of the significant challenges in diagnosing ME/CFS is that the symptoms are inherent to a wide range of medical conditions. While comorbid conditions like long COVID, fibromyalgia (FM), and postural orthostatic tachycardia syndrome (POTS) are common in ME/CFS, the more critical diagnostic complication arises from symptom presentations that resemble pre-malignant states, and undiagnosed rheumatic diseases, neurological diseases and endocrinopathies, increasing the risk of misdiagnosis. This not only delays proper treatment but also makes downstream data analysis more difficult by introducing unknown sources of heterogeneity into the patient population. Consequently, the prolonged and unstructured diagnosis and treatment of ME/CFS results in a substantial economic loss, estimated at $14.5 billion in Australia and a minimum of $149 billion in the USA , encompassing medical expenses, lost income, disability benefits, and increased use of social services. The heterogeneous nature and healthcare burden of ME/CFS present a timely opportunity for precision medicine, which aims to understand the molecular and biological factors that initiate and progress human diseases at the individual level . This approach integrates biological data including genetic profiles, medical history, social, and behavioural information, to enable tailored decision-making for disease prevention, prediction, and treatment . For example, in oncology, precision medicine has transformed care through targeted therapies for patients with specific molecular markers, such as HER2 protein in breast cancer and EGFR gene mutations in non-small cell lung cancer . However, applying precision medicine to ME/CFS is more challenging due to the lack of well-defined pathology, reproducible biomarkers , and identifiable treatment targets. The goal in ME/CFS is to move beyond symptom-based classifications and focus on the biological mechanisms driving the disease . This shift requires advanced computational tools such as machine learning and bioinformatic approaches to model the complex, multi-dimensional data and uncover the key pathways involved in the diverse ME/CFS presentations. Although omics studies have yet to identify definitive pathways in ME/CFS, recent advancements in computational power, growing datasets (data type, volume and sample size), and more efficient machine learning algorithms can reveal previously missed or hidden underlying mechanisms. Once these pathways are identified, the application of precision medicine can be fully realised through endpoints like (differential) biomarker-based diagnostics, patient subgrouping, and personalised treatments targeting specific pathways. This review outlines the essential machine learning steps, key multi-omics findings, and necessary data requirements for future ME/CFS studies implementing these computational frameworks. ME/CFS presents new challenges to traditional healthcare The traditional procedure for classification of a disease proceeds by identifying the primary dysfunctional organ in which the cardinal symptoms manifest . ME/CFS does not fit neatly into this approach as symptoms can arise from the musculoskeletal, immunological, cardiovascular, gastrointestinal, and neuroendocrine systems (Fig. ). It challenges the current diagnosis procedure which are based on observable characteristics (generic symptoms and subjective questionnaires) and rely on continuously evolving case definitions (Fukuda 1994 , Canadian Consensus Criteria 2003 , International Consensus Criteria 2011 , National Academy of Medicine 2015 , UK National Institute for Health and Care Excellence 2021 ). ME/CFS patients undergo extensive family and medical history assessments, series of tests, and may see numerous general practitioners and specialists to receive a clinical diagnosis . Physical examination, clinical measurements and pathology tests often return results within the expected reference range, which does not eliminate ME/CFS diagnosis but can be used to exclude other conditions or to guide further testing. The definition of a “reference range” includes lower and upper bounds determined by a population average, with conventional medical practises suggesting only an outlier can indicate an afflicted state. However, this paradigm does not account for the possibility that a shift from an individual’s healthy baseline can occur and still lie within this predefined range (Fig. ). Patients often have high baseline variation, so what is “normal” for one individual might not be for another. This is relevant for ME/CFS, where symptoms and severity fluctuate, and patients experience periods of relative wellness and exacerbation. Thus, there are limitations to relying on single measurements taken at an isolated timepoint, emphasising the importance of capturing dynamic changes over time in the individual, for both research and clinical settings. Once continuous data is collected, machine learning algorithms such as time series forecasting and anomaly detection, can be employed to model an individual’s baseline, identify deviations from this baseline, and predict adverse events, such as PEM accordingly . Previous small-scale study in intensive care units demonstrated that customised reference ranges significantly reduced false positive alerts . In addition, individualised baselines have been developed to detect COVID-19 pre-symptomatically using wearable data including heart rate and step count . The integration of advanced technologies such as wearable devices (for continuous passive data collection), at-home testing kits (for convenience), and high-throughput profiling now enables repeated, real-time measurements and standardised dynamic data collection, which were not previously accessible or widely utilised. Treatment strategies for ME/CFS prioritise managing symptoms through social, physical, and occupational support, and energy conservation via pacing . However, similar symptoms can arise from different aetiological events and pathophysiological mechanisms, causing varied responses to the same therapies. Although both pharmacologic and nonpharmacologic interventions are available to alleviate symptoms , they are often prescribed on a trial-and-error basis. This uncertainty has led to a growing online community of ME/CFS patients sharing their self-medication experiences, highlighting the urgent need for personalised treatment approaches that target the underlying biology of the individual. The promise of “big” biological data Advances in analytical instrumentation including higher throughput and lower running costs have made deep phenotyping increasingly popular. Such developments have led to comprehensive multi-omics measurements, the collection of imaging data, and detailed physical and pathology results. Here, the term “big data” extends beyond the sheer volume of data to include the hypothesis-generating nature of system biology experiments, where the exploration and analysis of large datasets leads to the formation of a testable hypothesis to initiate a subsequent hypothesis-driven approach . The four main pillars of the omics cascade, genomics, transcriptomics, proteomics, and metabolomics, offer insights into the intricate networks and pathways that drive cellular functions, disease mechanism, and organismal behaviours . Genomics has had the most success in precision medicine, especially in monogenic diseases (due to direct link to a single gene mutation) and cancer applications. The inherent stability of DNA against changes in the environment (cellular or external) facilitates the standardisation of genetic testing in different settings. This contrasts with more sensitive biomolecules like RNA, proteins, and metabolites which require specific analytical instruments or the development of validated assays to be translated into clinical practise. While genomic analyses require advanced bioinformatic methods, once candidate variants are identified, the results can be biologically interpreted in a relatively simple, i.e., binary manner (e.g., presence or absence of a mutation) compared to the continuous and context-dependent variations seen in the downstream omics. Nevertheless, transcriptomics can identify dysregulated gene pathways through gene expression data, while proteomics can validate, or independently identify and quantify proteins and enzymes involved in (mostly downstream) disease processes. Metabolomics offers a dynamic snapshot of the biological state, influenced by genetics, pathogens, diet, lifestyle, and environmental factors, and is valuable for biomarker discovery and real-time tracking of disease progression and treatment response. The various roles of metabolites in multiple pathways (e.g., substrate, intermediate, end-product etc.) can also complicate the linkage of small molecule biomarkers to specific disease mechanisms. Omics data can be enriched by analysing different biofluids and cell types as they provide complementary insights into the mechanistic roles of potential biomarkers, especially in metabolomics . Each type of biofluid provides either systemic or localised biomarker information. For example, blood serves as a key transporter of circulating nutrients, hormones, and metabolites, reflecting systemic metabolic processes that help maintain homeostasis. Different fractions of blood, such as plasma and peripheral blood mononuclear cells (PBMCs), serve distinct roles—plasma in transport and PBMCs in immune function. Urine captures metabolic by-products and toxins highlighting detoxification pathways and the body’s clearance efficiency. Cerebrospinal fluid (CSF), separated from blood by the blood-brain barrier, mirrors the central nervous system’s biochemical environment, aiding in diagnosing neurological conditions. Saliva contains hormones, antibodies, and proteins useful for non-invasive monitoring of stress, infection, and endocrine function. While single-biofluid biomarkers may be sufficient as diagnostic biomarkers, the complexity of ME/CFS suggests that correlating biomarker levels in blood with those in other biofluids may offer a more comprehensive understanding of their mechanistic roles. This cross-compartmental correlation is particularly important in ME/CFS, where the interplay between multiple biological systems (e.g., immune, metabolic, and neurological) is likely driving disease pathology. Several biofluids—including interstitial fluid, urine, and sweat—are either directly influenced by blood or result from its filtration and exchange processes. Furthermore, metabolites related to energy metabolism are transported via the bloodstream and consumed at the tissue level. Correlating biomarker levels between these biofluids can validate biological processes by confirming consistent patterns and changes across the different compartments . However, it is important to note that collecting some of these biofluids may require invasive procedures. Omics technologies are now routinely employed in ME/CFS studies, offering numerous opportunities to explore potential biomarkers. Due to the hypothesis-generating nature of these omics datasets, study outcomes can vary based on several factors including the chosen omics platform, batch effects, sample collection methods, analytical instrument , storage and handling. Increasing the sample size is often considered one of the most effective strategies for minimising the influence of technical outliers and strengthening statistical power without indirectly introducing bias. However, this approach can be limited by practical constraints such as cost and data availability. In such cases, normalisation and batch effect correction techniques can be applied post-data acquisition to reduce variability , however, different techniques may change study outcomes. When sufficient quality control data or internal standards are available, technical variation can be measured and subsequently removed . Once the data is appropriately pre-processed, advanced bioinformatics tools and machine learning algorithms can be implemented to make sense of multi-modal data and to analyse inter-individual variation. Machine learning concepts State-of-the-art machine learning techniques are increasingly becoming reliable tools for addressing complex biological problems. Machine learning is a branch of artificial intelligence (AI) that aims to emulate human decision making by learning patterns from previous examples drawing on statistics, probability, and optimisation. These patterns are represented as “features” including quantitative, categorical, and unstructured variables such as text or images. There are three types of machine learning: supervised, unsupervised and reinforcement. Supervised algorithms learn patterns from labelled training data to predict responses, which can be either binary/multi-class (classification) or continuous (regression). Different algorithms can be employed to find patterns without initial data assumptions , utilising Boolean logic (AND, OR, NOT), absolute conditionality (IF, THEN, ELSE), conditional probabilities (the probability of X given Y) or optimisation , which enable predictions for new input with unknown labels. This method provides more flexibility for data that are non-linear or are interdependent, especially suitable for biological data. Unsupervised learning is employed to identify dissimilarities in unlabelled data for clustering purposes. Reinforcement learning is a dynamic process in which the model trains by reward and punishment mechanisms. Machine learning capabilities that can be applied in ME/CFS, and diseases in general, using classification algorithms involve diagnosis, predicting treatment efficacy and risk susceptibility, and unsupervised algorithms can be employed for disease subtyping via clustering and dimensionality reduction. When a model is trained on more features than samples (a phenomenon known as the curse of dimensionality), it may become overfitted, meaning that the patterns learnt are too specific to the dataset. Consequently, the model may not make reliable predictions on new input, especially from different data sources. There are various methods to prevent overfitting including feature selection which removes redundant information (see next section), dimensionality reduction and cross-validation. Dimensionality reduction condenses a large number of features into a smaller set that retains the explained variance in the original data. Techniques include principal components analysis (PCA), linear discriminant analysis (LDA) and t-SNE. Cross-validation involves training the model on different subsets of the training data which introduces controlled variability and validates the model on the remaining data subset. Additionally, for a machine learning model to serve as a clinical support tool, it must be interpretable (explainable AI) so clinicians and researchers can understand and trust its predictions. For example, decision trees, regression models, and SHAP (SHapley Additive exPlanations) values provide intellectual oversight by explaining the contribution of individual features to the model’s predictions. Classification tasks in ME/CFS The classification pipeline includes data partitioning, data preparation, feature selection, model selection, training, and evaluation with a blind test set (Fig. ). In ME/CFS, classification applications have focused on biomarker discovery and diagnosis. The main difference between these endpoints is that the biomarker discovery studies typically do not choose a single optimal model; instead, important features from all candidate models are considered as potential biomarkers. Both types of studies are summarised in Table , and this section explores the detailed steps involved in these classification applications. Feature selection simplifies the machine learning model and prevents overfitting caused by high dimensional data (e.g., > 500 features for sample sizes < 100) . There are three main feature selection methods. The first method is a filter approach, which selects features based on statistical tests, independent of the machine learning algorithm. For example, Yagin et al. selected features based on F-value by performing Analysis of Variance (ANOVA) on 892 different plasma metabolomic features. They trained six algorithms on varying decremental feature groups and found that the top 50 features trained on an Extreme Gradient Boosting (XGBoost) classifier was the most optimal model. In another study, Xu et al. performed supervised LDA to extract 76 important features from 1019 Raman spectroscopic peaks based on contribution scores. The advantage of the filter method is the reduced computation burden during model training, though it may not consider the direct contribution of important features to the model’s predictions. The second method is the wrapper method which searches for the best combination of features in the dataset by iteratively adding (forward feature selection) or removing (backward feature selection) features until the best model performance is achieved. This method is algorithm-specific, so different algorithms may choose different feature sets from the same initial features. The third method has feature selection embedded into the algorithm such as LASSO (least absolute shrinkage selector operator) regression. It can involve using algorithm-specific metrics to extract feature importance as demonstrated by Yagin et al. . They trained an initial model on the entire feature set, computed the feature importance using Gini’s impurity score which measures the contribution of each feature to the likelihood of a misclassification, and then retrained the model with the top 20 ranked features. A blind test set is crucial for evaluating any model or diagnostic tool to ensure unbiased, accurate, and generalisable performance. Best practices involve holding out the blind test set at the start of the machine learning pipeline and not exposing it during training. This step is often overlooked especially if exploratory data analysis and machine learning steps overlap at column-wise data standardisation and filter feature selection. Only a few studies had performed model evaluation using a blind test set, likely due to the limited sample sizes (Table ). Xiong et al. did not use a blind test set. Instead, they validated their model with data from a second time point (on the same individuals) and an additional external cohort . Their metabolomics-only classifier achieved an area under the receiver operating characteristic curve (AUC) of 0.82 from a 10-fold cross validation, 0.90 for the temporal validation and 0.72 for the external validation. Through temporal validation, they showed that their classifier had stable performance over time, and external validation was possible as raw metabolomics data was shared publicly and acquired using the same analytical platform (Metabolon). In the future, assessing the model with a blind test set should be prioritised to demonstrate a rigorous and unbiased evaluation process. Model performance can be improved by combining a set of learners into an ensemble model, where the final prediction is derived from aggregating the outputs of several individual models. Ensemble methods such as random forest and XGBoost use decision trees as their base learner but differ in how they aggregate predictions. Random forest employs a technique known as bagging, where multiple decision trees are built on random subsets of the data, and their predictions are averaged, thereby reducing variance and mitigating overfitting. In contrast, XGBoost uses boosting, a sequential method where each new model corrects the errors of the previous one, gradually improving accuracy. Additionally, ensemble models can be constructed through stacking, a method in which different algorithms are combined, with a meta-model learning to optimise the final prediction. For example, Xu et al. used eight different and uncorrelated classification models, each achieving individual accuracies between 47.1 and 61.2%. By stacking these models using a gradient boosted machine model (the meta model) increased the test accuracy to 83.3%. Snapshot of ME/CFS omics biomarkers This section offers an overview of the current state of ME/CFS research into biomarkers (for the main omics levels), highlighting what is known, unknown, needed, and should be prioritised. We do not discuss in detail specific biomarkers as many published reviews have collated findings from genomics , immunology , and metabolomics studies, and biomarkers in general . The search for genetic markers has focused on identifying single nucleotide polymorphisms (SNPs) through genome wide association studies (GWAS) and candidate gene studies . Traditional GWAS in ME/CFS have lacked statistical power, revealing only a few significant SNPs, which have not been replicated across studies, even within the same UK Biobank cohort. This suggests variation in variant quality control, sample quality control (e.g., ethnicity, gender, relatedness) and analytical methods can lead to discrepancies in the results and require standardised parameters and larger, and more diverse populations. Recently, a combinatorial analysis identified 199 significant SNPs in five biological domains related to viral/bacterial susceptibility, metabolism, autoimmune and sleep. The analysis iteratively tested combinations of 3–5 SNPs in 1000 bootstrapped samples of case and control groups . The sensitive nature of this approach suggested that the identified SNPs were relevant to potential subgroups within ME/CFS, rather than the entire disease. However, the computational burden of fully sampling the entire cohort space and SNP combinations remains a limitation. Nonetheless, this approach targets the polygenicity and heterogeneity of ME/CFS cohorts and represents a shift from seeking a single genetic aetiological variant to recognising multiple common variants , each with small effects that can cumulatively contribute to ME/CFS presentations. For future directions these broader searches may be preferable, for example exploring options for generating polygenic risk scores that enhance GWAS association signals and performing a PheWAS on putative ME/CFS SNPs to elucidate genetic signals shared between other diseases or traits. Transcriptomic studies have examined differentially expressed genes at both the single cell level and the population level in PBMCs before and after an exercise challenge. At the single cell level, ME/CFS patients exhibited increased monocyte dysregulation and was unable to respond to tissue damage caused by high energy demands due to improper platelet activation . At the population level, no significant differences in gene expression of immune cells were found between the two timepoints in ME/CFS, while the healthy control group showed overexpression of genes in multiple pathways . Proteomic, immunologic, and metabolomic studies have demonstrated significant variability, especially when identifying biomarkers in non-invasive and minimally processed biofluids such as serum, plasma, and urine. Not only has a diverse array of biomarkers been identified, but their concentration levels in ME/CFS have also been contradictory. For example, sphingomyelins, a class of lipids involved in cell membrane structure and signalling, were found to be both increased , and decreased in ME/CFS patients, suggesting potential disruptions in membrane fluidity or lipid metabolism. Other lipids, such as phosphatidylcholines, ceramides, cholesterol, cholesterol esters, and triglycerides have also generated inconsistent results . This variability highlights the importance of focusing on divergent biochemical pathways rather than individual biomarkers, where both increased and decreased biomarker levels present viable perturbed pathways for different subgroups in ME/CFS. Many studies have identified pathways through pathway enrichment analysis or manual inference from surveying literature. However, a more robust approach would involve validating the findings through integrating multi-omics data, which holistically reflects the state of disrupted pathways in ME/CFS and incorporating longitudinal monitoring. Understanding whether a biomarker (or a pathway) is merely correlated with ME/CFS or plays a causative role is essential for developing effective treatments . While correlational biomarkers can aid in early detection and monitoring, causal biomarkers can lead to interventions that modify the disease course. Determining causality requires prospective studies, where biomarkers are measured before disease onset and tracked over time. One prospective study identified various dysregulated pathways including glutathione metabolism, nucleotide metabolism, the TCA cycle, glycolysis and urea cycle between individuals that recovered from infectious mononucleosis and those that went on to develop severe ME/CFS . In addition to prospective designs, Mendelian randomisation and randomised controlled trials can further support causal inferences by demonstrating that targeting a biomarker affects disease outcomes . However, in the absence of long-term large scale prospective data for ME/CFS, meta-analysis of case-control studies still offer valuable insights . Meta-analyses can help assess whether reported biomarkers consistently correlate with demographics, symptoms, or external influences, helping to refine biomarker for future causal investigations . While not sufficient for proving causality, this approach is critical for identifying patterns in existing data and guiding the design of future prospective studies. Integrating multi-omics and multi-modal data Multi-omics describes two or more omics, which can be integrated simultaneously or in parallel . The parallel method involves analysing each omics dataset individually and benefits from efficient workflows. Simultaneous analysis considers multiple omics datasets together, offering the advantage of identifying shared sources of variation across different data modalities . This integrated approach contrasts with parallel analysis which does not explicitly link the biological relevance of each individual dataset. Simultaneous integration methods draw on statistical concepts and can be broadly implemented using multivariate analyses, graph-based methods, marginal associations, and unsupervised methods. The parallel method is analysis-agnostic and offers a simple and flexible solution to multi-omics integration. For example, Xiong et al. integrated three data sets: species abundance (obtained from shotgun metagenomics on gut microbiota), normalised KEGG gene abundance and normalised metabolite profile (plasma metabolomics), into a multi-omics classifier. They first built three individual gradient boosted models for each dataset, ranked features based on their importance and extracted the top 10 features for each model which were then used to train the multi-omics classifier. This approach enabled the identification of potential biomarkers within each omics layer, including low abundance of butyrate-producing microbes and decreased plasma isobutyrate from a correlation analysis post-classification. Kitami et al. performed deep molecular phenotyping on 48 ME/CFS and 52 health controls and collected clinical lab tests, metabolome, immunophenotype, transcriptome and microbiome. They identified 26 significant molecular markers across the five data modalities using two-tailed Mann-Whitney U-test with Benjamini-Hochberg correction and integrated the features using partial least square discriminant analysis. Multivariate integration methods, applied in simultaneous analysis, are highly effective for disease classification and biomarker elucidation. Giloteaux et al. integrated 353 features including extracellular vesicle (EV) cytokines, plasma cytokines and plasma proteomics with a multi-omics classifier. Feature importance scores were assigned to all the molecular entities based on their direct contribution to the model performance. The top 20 performing features comprised of 15 plasma proteins and 5 EV proteins. This approach contrasts Xiong et al. who had arbitrarily included features into the multi-omics classifier based on prior individual models. Multivariate integrations can also be performed with mixOmics and MetaboAnalyst . Biological networks are complex systems of interconnected components, making graph-based methods ideal for mapping multi-omics interactions . Nagy-Szakal et al. performed a topological data analysis on the AYASDI platform (Ayasdi, Menlo Park, California) integrating 562 plasma metabolites, 574 faecal bacterial relative abundances, 587 metabolic bacterial variables, 61 immune molecules, and 81 questionnaire items for 50 ME/CFS and 50 health controls. To compare how both continuous and categorical variables were related, they used a measure called Jaccard distance, which looks at how dissimilar the variables are between two groups. They also used dimensionality reduction methods to simplify the data for easier visualisation. Their visualisations showed clear class distinctions in the network graphs and showed that bacterial relative abundance features were stronger drivers for class separation than plasma metabolomic features. However, the study lacked biological interpretation from the network analysis, relying instead on univariate logistic regression and independent correlation analysis between bacteria, metabolites, and questionnaire scores (parallel method). Other network analysis approaches include similarity network fusion , which is also an unsupervised method that could be used to cluster ME/CFS into subgroups with both discrete and continuous data types. Marginal association and unsupervised multi-omics integration methods are yet to be rigorously applied in ME/CFS studies but hold significant potential for future applications. Generalised linear models are often employed for case-control studies to identify biomarker associations. Alternatively, marginal association tests can be performed between two different omics, similar to expression quantitative trait loci (eQTLs) analysis, which tests for association of genetic variants and gene expression levels , or metabolite GWAS which combines functional genomics and metabolomics . Unsupervised techniques worth exploring include Multi-Omics Factor Analysis (MOFA) , and PathME , which both have open-source code available for implementation. The primary use case for MOFA is to identify unbroken axes of variation across different data modalities targeted towards heterogenous diseases. Multiple different omics datasets are decomposed into a single matrix comprising of factors [12pt]{minimal} $$\:\:$$ samples. These factors can be queried to identify the variance explained by each data modality and the individual contributions of the features using loadings scores. PathME provides direct pathway interpretations and clustering capabilities. Different omics features are first mapped to specific pathways, a score is then assigned to each sample for the different pathways using a sparse denoising autoencoder. Bi-clustering is performed on samples and pathways to generate subgroups. Here, we have only briefly discussed a few integration methods that could be applied in ME/CFS. As ME/CFS studies are now generating higher volumes of data with greater variety, the application of advanced data integration tools should be prioritised. These tools are more effective and reliable than having researchers manually link significant findings from different datasets, as there is a possibility to miss connections or introduce errors. Future endeavours Biobanks Efforts to build ME/CFS-specific biobanks have gained momentum, with initiatives like the UK ME/CFS Biobank , AusME Biobank, and DecodeME project leading the way. The UK ME/CFS Biobank has been instrumental in collecting and providing biological samples and datasets to researchers worldwide. Similarly, the DecodeME project aims to conduct a large-scale genetic study by recruiting 25,000 individuals with ME/CFS, dramatically boosting the statistical power compared to previous studies. In addition, non-disease specific biobanks such as the UK Biobank, Biobank Japan, Estonian Biobank, China Kadoorie Biobank, and the All of Us Research Program in the United States contain vast amounts of genetic, phenotypic, and health data from diverse populations. These resources are invaluable for creating control groups with different ethnicities and for comparing comorbid conditions. Analysing biobanks with linked electronic health records could also help elucidate whether individuals diagnosed with ME/CFS have specific health trajectories that differ from other disease groups . In particular, the ability to cross-reference comorbid diagnoses and sequential disease development provides an opportunity to address the diagnostic ambiguity and develop more precise clinical profiles for ME/CFS. The volume of biobank data also requires standardised collection and processing procedures, ensuring consistency and reliability across timepoints. Consequently, validating multiple small-scale studies with biobank data enhances the accuracy and robustness of their research findings. Data harmonisation and data sharing There is also the challenge of managing the vast amounts of data collected from small- and medium-scale studies. Studies often employ different questionnaires such as Bell CFIDS disability scale, Chalder fatigue scale, DePaul Symptom Questionnaire, Short Form 36-Item Health Survey, Fatigue Severity Scale, and others, to assess symptoms, severity, and functionality; with each questionnaire having their own focus and format. Developing an intermediary data format that can summarise, or map questionnaire responses to standardised values using schema matching and machine learning would be a more productive solution than continuously creating or updating questionnaires. This approach will facilitate data integration and meta-analysis, allowing researchers to combine and compare results across older and newer studies more effectively. Additionally, the National Institutes of Health (NIH) has also released a data sharing portal, mapMECFS , for registered researchers to upload their data, including metadata and biological data, to be compiled into summary statistics. Depositing raw biological data in repositories is also strongly encouraged so different data harmonisation and normalisation strategies can be trialled. Increasing reproducibility The varying results across ME/CFS omics studies can also be attributed to the different statistical and machine learning methods employed. The exploratory nature of omics studies means researchers often apply various analytical techniques until a novel pattern is detected, which may lead to inconsistent findings. To improve the reproducibility and transparency of these studies, adopting open science practices, such as study pre-registration (e.g., COS Preregistration ) and the use of AI/Machine Learning checklists (e.g., AIMe Registry ), can be invaluable. Pre-registration ensures that study objectives, hypotheses, and analysis plans are clearly defined in advance, reducing biases and selective reporting. Meanwhile, checklists for AI and machine learning algorithms promote the use of standardised, transparent practises, helping to mitigate the impact of varying analytical approaches. These measures are not meant to restrict research, but to provide a clear distinction between exploratory and confirmatory studies and guide robust hypothesis testing designs in future research. Longitudinal studies Longitudinal studies provide insights into the progression and fluctuations of ME/CFS. A recent case study ( n = 1) combined various types of data, such as cytokine profiles and clinical information, with AI techniques like natural language processing and sentiment analysis . This approach extracted functional capacity information from blog posts written during periods of exacerbation, effectively mapping out the patient’s journey through ME/CFS onset, progression, and their responses to different treatments over the span of twenty years. Additionally, the study showcased the untapped potential of integrating electronic health records and personal writings in a retrospective study to identify patterns or signs that could predict disease onset or relapses before physical symptoms appear. Additional tools such as integrative personal omics profile (iPOP) and multiscale, multifactorial response network (MMRN) can provide objective interpretations as sample sizes for longitudinal studies increase. Wearables and digital biomarkers Integrating digital biomarkers collected through wearable devices offers a transformative approach to monitoring ME/CFS in both longitudinal studies and general settings . Wearables can continuously track various physiological parameters that are highly relevant to ME/CFS. For example, reduced physical activity, temperature, and disrupted sleep patterns can serve as objective indicators of disease severity, while heart rate variability reflects autonomic dysfunction, indicating the body’s stress response and overall cardiovascular health . These insights are unattainable through periodic clinical visits, provide an alternative to patient symptom descriptions, can help establish individualised patient reference ranges and be used to identify early signs of flare-ups. Additionally, because wearable data is passively collected, it mitigates potential sampling bias and captures comprehensive data on both good and bad days. ME/CFS researchers can incorporate continuous digital monitoring into their study designs by utilising platforms like the Digital Medicine Society’s playbook for standard protocols. Embracing AI While this review primarily focused on machine learning applications, there is also a growing body of research highlighting how deep learning (another branch of AI) can address the heterogeneity of ME/CFS. Deep learning uses neural networks comprising of layers of connected nodes that pass information from one layer to another depending on model parameters such as weights, and biases, and activation functions . The learning process is dynamic and iterative, involving forward propagation to predict output labels and backward propagation (a feedback loop) which adjust the model parameters according to the prediction error, thereby refining the learning process. Deep learning offers several advantages over machine learning for ME/CFS, including the ability to predict multiple outcomes (e.g., phenotypes, clinical scores) for an individual, rather than assigning a single outcome (e.g., ME/CFS or non-ME/CFS label). Hence, this capability is crucial for identifying distinct clinical or biological features of ME/CFS, where heterogeneous individuals can be classified based on their unique combinations of features influenced by symptoms, genetic markers, immune responses, and other biomarkers. Recently, a deep learning framework called BioMapAI was developed to simultaneously integrate microbiome, immune and metabolomic profiles, which were mapped onto 12 clinical symptoms . The model reconstructed clinical symptoms from biological data and elucidated non-linear and biphasic relationships between the two data types through explainable AI . This framework can also be extrapolated to predict other multi-label endpoints, and to include genomic data, demonstrating the effectiveness of deep learning in handling raw, high-dimensional, and multi-modal data necessary to holistically capture the diverse ME/CFS symptomatology. The traditional procedure for classification of a disease proceeds by identifying the primary dysfunctional organ in which the cardinal symptoms manifest . ME/CFS does not fit neatly into this approach as symptoms can arise from the musculoskeletal, immunological, cardiovascular, gastrointestinal, and neuroendocrine systems (Fig. ). It challenges the current diagnosis procedure which are based on observable characteristics (generic symptoms and subjective questionnaires) and rely on continuously evolving case definitions (Fukuda 1994 , Canadian Consensus Criteria 2003 , International Consensus Criteria 2011 , National Academy of Medicine 2015 , UK National Institute for Health and Care Excellence 2021 ). ME/CFS patients undergo extensive family and medical history assessments, series of tests, and may see numerous general practitioners and specialists to receive a clinical diagnosis . Physical examination, clinical measurements and pathology tests often return results within the expected reference range, which does not eliminate ME/CFS diagnosis but can be used to exclude other conditions or to guide further testing. The definition of a “reference range” includes lower and upper bounds determined by a population average, with conventional medical practises suggesting only an outlier can indicate an afflicted state. However, this paradigm does not account for the possibility that a shift from an individual’s healthy baseline can occur and still lie within this predefined range (Fig. ). Patients often have high baseline variation, so what is “normal” for one individual might not be for another. This is relevant for ME/CFS, where symptoms and severity fluctuate, and patients experience periods of relative wellness and exacerbation. Thus, there are limitations to relying on single measurements taken at an isolated timepoint, emphasising the importance of capturing dynamic changes over time in the individual, for both research and clinical settings. Once continuous data is collected, machine learning algorithms such as time series forecasting and anomaly detection, can be employed to model an individual’s baseline, identify deviations from this baseline, and predict adverse events, such as PEM accordingly . Previous small-scale study in intensive care units demonstrated that customised reference ranges significantly reduced false positive alerts . In addition, individualised baselines have been developed to detect COVID-19 pre-symptomatically using wearable data including heart rate and step count . The integration of advanced technologies such as wearable devices (for continuous passive data collection), at-home testing kits (for convenience), and high-throughput profiling now enables repeated, real-time measurements and standardised dynamic data collection, which were not previously accessible or widely utilised. Treatment strategies for ME/CFS prioritise managing symptoms through social, physical, and occupational support, and energy conservation via pacing . However, similar symptoms can arise from different aetiological events and pathophysiological mechanisms, causing varied responses to the same therapies. Although both pharmacologic and nonpharmacologic interventions are available to alleviate symptoms , they are often prescribed on a trial-and-error basis. This uncertainty has led to a growing online community of ME/CFS patients sharing their self-medication experiences, highlighting the urgent need for personalised treatment approaches that target the underlying biology of the individual. Advances in analytical instrumentation including higher throughput and lower running costs have made deep phenotyping increasingly popular. Such developments have led to comprehensive multi-omics measurements, the collection of imaging data, and detailed physical and pathology results. Here, the term “big data” extends beyond the sheer volume of data to include the hypothesis-generating nature of system biology experiments, where the exploration and analysis of large datasets leads to the formation of a testable hypothesis to initiate a subsequent hypothesis-driven approach . The four main pillars of the omics cascade, genomics, transcriptomics, proteomics, and metabolomics, offer insights into the intricate networks and pathways that drive cellular functions, disease mechanism, and organismal behaviours . Genomics has had the most success in precision medicine, especially in monogenic diseases (due to direct link to a single gene mutation) and cancer applications. The inherent stability of DNA against changes in the environment (cellular or external) facilitates the standardisation of genetic testing in different settings. This contrasts with more sensitive biomolecules like RNA, proteins, and metabolites which require specific analytical instruments or the development of validated assays to be translated into clinical practise. While genomic analyses require advanced bioinformatic methods, once candidate variants are identified, the results can be biologically interpreted in a relatively simple, i.e., binary manner (e.g., presence or absence of a mutation) compared to the continuous and context-dependent variations seen in the downstream omics. Nevertheless, transcriptomics can identify dysregulated gene pathways through gene expression data, while proteomics can validate, or independently identify and quantify proteins and enzymes involved in (mostly downstream) disease processes. Metabolomics offers a dynamic snapshot of the biological state, influenced by genetics, pathogens, diet, lifestyle, and environmental factors, and is valuable for biomarker discovery and real-time tracking of disease progression and treatment response. The various roles of metabolites in multiple pathways (e.g., substrate, intermediate, end-product etc.) can also complicate the linkage of small molecule biomarkers to specific disease mechanisms. Omics data can be enriched by analysing different biofluids and cell types as they provide complementary insights into the mechanistic roles of potential biomarkers, especially in metabolomics . Each type of biofluid provides either systemic or localised biomarker information. For example, blood serves as a key transporter of circulating nutrients, hormones, and metabolites, reflecting systemic metabolic processes that help maintain homeostasis. Different fractions of blood, such as plasma and peripheral blood mononuclear cells (PBMCs), serve distinct roles—plasma in transport and PBMCs in immune function. Urine captures metabolic by-products and toxins highlighting detoxification pathways and the body’s clearance efficiency. Cerebrospinal fluid (CSF), separated from blood by the blood-brain barrier, mirrors the central nervous system’s biochemical environment, aiding in diagnosing neurological conditions. Saliva contains hormones, antibodies, and proteins useful for non-invasive monitoring of stress, infection, and endocrine function. While single-biofluid biomarkers may be sufficient as diagnostic biomarkers, the complexity of ME/CFS suggests that correlating biomarker levels in blood with those in other biofluids may offer a more comprehensive understanding of their mechanistic roles. This cross-compartmental correlation is particularly important in ME/CFS, where the interplay between multiple biological systems (e.g., immune, metabolic, and neurological) is likely driving disease pathology. Several biofluids—including interstitial fluid, urine, and sweat—are either directly influenced by blood or result from its filtration and exchange processes. Furthermore, metabolites related to energy metabolism are transported via the bloodstream and consumed at the tissue level. Correlating biomarker levels between these biofluids can validate biological processes by confirming consistent patterns and changes across the different compartments . However, it is important to note that collecting some of these biofluids may require invasive procedures. Omics technologies are now routinely employed in ME/CFS studies, offering numerous opportunities to explore potential biomarkers. Due to the hypothesis-generating nature of these omics datasets, study outcomes can vary based on several factors including the chosen omics platform, batch effects, sample collection methods, analytical instrument , storage and handling. Increasing the sample size is often considered one of the most effective strategies for minimising the influence of technical outliers and strengthening statistical power without indirectly introducing bias. However, this approach can be limited by practical constraints such as cost and data availability. In such cases, normalisation and batch effect correction techniques can be applied post-data acquisition to reduce variability , however, different techniques may change study outcomes. When sufficient quality control data or internal standards are available, technical variation can be measured and subsequently removed . Once the data is appropriately pre-processed, advanced bioinformatics tools and machine learning algorithms can be implemented to make sense of multi-modal data and to analyse inter-individual variation. State-of-the-art machine learning techniques are increasingly becoming reliable tools for addressing complex biological problems. Machine learning is a branch of artificial intelligence (AI) that aims to emulate human decision making by learning patterns from previous examples drawing on statistics, probability, and optimisation. These patterns are represented as “features” including quantitative, categorical, and unstructured variables such as text or images. There are three types of machine learning: supervised, unsupervised and reinforcement. Supervised algorithms learn patterns from labelled training data to predict responses, which can be either binary/multi-class (classification) or continuous (regression). Different algorithms can be employed to find patterns without initial data assumptions , utilising Boolean logic (AND, OR, NOT), absolute conditionality (IF, THEN, ELSE), conditional probabilities (the probability of X given Y) or optimisation , which enable predictions for new input with unknown labels. This method provides more flexibility for data that are non-linear or are interdependent, especially suitable for biological data. Unsupervised learning is employed to identify dissimilarities in unlabelled data for clustering purposes. Reinforcement learning is a dynamic process in which the model trains by reward and punishment mechanisms. Machine learning capabilities that can be applied in ME/CFS, and diseases in general, using classification algorithms involve diagnosis, predicting treatment efficacy and risk susceptibility, and unsupervised algorithms can be employed for disease subtyping via clustering and dimensionality reduction. When a model is trained on more features than samples (a phenomenon known as the curse of dimensionality), it may become overfitted, meaning that the patterns learnt are too specific to the dataset. Consequently, the model may not make reliable predictions on new input, especially from different data sources. There are various methods to prevent overfitting including feature selection which removes redundant information (see next section), dimensionality reduction and cross-validation. Dimensionality reduction condenses a large number of features into a smaller set that retains the explained variance in the original data. Techniques include principal components analysis (PCA), linear discriminant analysis (LDA) and t-SNE. Cross-validation involves training the model on different subsets of the training data which introduces controlled variability and validates the model on the remaining data subset. Additionally, for a machine learning model to serve as a clinical support tool, it must be interpretable (explainable AI) so clinicians and researchers can understand and trust its predictions. For example, decision trees, regression models, and SHAP (SHapley Additive exPlanations) values provide intellectual oversight by explaining the contribution of individual features to the model’s predictions. The classification pipeline includes data partitioning, data preparation, feature selection, model selection, training, and evaluation with a blind test set (Fig. ). In ME/CFS, classification applications have focused on biomarker discovery and diagnosis. The main difference between these endpoints is that the biomarker discovery studies typically do not choose a single optimal model; instead, important features from all candidate models are considered as potential biomarkers. Both types of studies are summarised in Table , and this section explores the detailed steps involved in these classification applications. Feature selection simplifies the machine learning model and prevents overfitting caused by high dimensional data (e.g., > 500 features for sample sizes < 100) . There are three main feature selection methods. The first method is a filter approach, which selects features based on statistical tests, independent of the machine learning algorithm. For example, Yagin et al. selected features based on F-value by performing Analysis of Variance (ANOVA) on 892 different plasma metabolomic features. They trained six algorithms on varying decremental feature groups and found that the top 50 features trained on an Extreme Gradient Boosting (XGBoost) classifier was the most optimal model. In another study, Xu et al. performed supervised LDA to extract 76 important features from 1019 Raman spectroscopic peaks based on contribution scores. The advantage of the filter method is the reduced computation burden during model training, though it may not consider the direct contribution of important features to the model’s predictions. The second method is the wrapper method which searches for the best combination of features in the dataset by iteratively adding (forward feature selection) or removing (backward feature selection) features until the best model performance is achieved. This method is algorithm-specific, so different algorithms may choose different feature sets from the same initial features. The third method has feature selection embedded into the algorithm such as LASSO (least absolute shrinkage selector operator) regression. It can involve using algorithm-specific metrics to extract feature importance as demonstrated by Yagin et al. . They trained an initial model on the entire feature set, computed the feature importance using Gini’s impurity score which measures the contribution of each feature to the likelihood of a misclassification, and then retrained the model with the top 20 ranked features. A blind test set is crucial for evaluating any model or diagnostic tool to ensure unbiased, accurate, and generalisable performance. Best practices involve holding out the blind test set at the start of the machine learning pipeline and not exposing it during training. This step is often overlooked especially if exploratory data analysis and machine learning steps overlap at column-wise data standardisation and filter feature selection. Only a few studies had performed model evaluation using a blind test set, likely due to the limited sample sizes (Table ). Xiong et al. did not use a blind test set. Instead, they validated their model with data from a second time point (on the same individuals) and an additional external cohort . Their metabolomics-only classifier achieved an area under the receiver operating characteristic curve (AUC) of 0.82 from a 10-fold cross validation, 0.90 for the temporal validation and 0.72 for the external validation. Through temporal validation, they showed that their classifier had stable performance over time, and external validation was possible as raw metabolomics data was shared publicly and acquired using the same analytical platform (Metabolon). In the future, assessing the model with a blind test set should be prioritised to demonstrate a rigorous and unbiased evaluation process. Model performance can be improved by combining a set of learners into an ensemble model, where the final prediction is derived from aggregating the outputs of several individual models. Ensemble methods such as random forest and XGBoost use decision trees as their base learner but differ in how they aggregate predictions. Random forest employs a technique known as bagging, where multiple decision trees are built on random subsets of the data, and their predictions are averaged, thereby reducing variance and mitigating overfitting. In contrast, XGBoost uses boosting, a sequential method where each new model corrects the errors of the previous one, gradually improving accuracy. Additionally, ensemble models can be constructed through stacking, a method in which different algorithms are combined, with a meta-model learning to optimise the final prediction. For example, Xu et al. used eight different and uncorrelated classification models, each achieving individual accuracies between 47.1 and 61.2%. By stacking these models using a gradient boosted machine model (the meta model) increased the test accuracy to 83.3%. This section offers an overview of the current state of ME/CFS research into biomarkers (for the main omics levels), highlighting what is known, unknown, needed, and should be prioritised. We do not discuss in detail specific biomarkers as many published reviews have collated findings from genomics , immunology , and metabolomics studies, and biomarkers in general . The search for genetic markers has focused on identifying single nucleotide polymorphisms (SNPs) through genome wide association studies (GWAS) and candidate gene studies . Traditional GWAS in ME/CFS have lacked statistical power, revealing only a few significant SNPs, which have not been replicated across studies, even within the same UK Biobank cohort. This suggests variation in variant quality control, sample quality control (e.g., ethnicity, gender, relatedness) and analytical methods can lead to discrepancies in the results and require standardised parameters and larger, and more diverse populations. Recently, a combinatorial analysis identified 199 significant SNPs in five biological domains related to viral/bacterial susceptibility, metabolism, autoimmune and sleep. The analysis iteratively tested combinations of 3–5 SNPs in 1000 bootstrapped samples of case and control groups . The sensitive nature of this approach suggested that the identified SNPs were relevant to potential subgroups within ME/CFS, rather than the entire disease. However, the computational burden of fully sampling the entire cohort space and SNP combinations remains a limitation. Nonetheless, this approach targets the polygenicity and heterogeneity of ME/CFS cohorts and represents a shift from seeking a single genetic aetiological variant to recognising multiple common variants , each with small effects that can cumulatively contribute to ME/CFS presentations. For future directions these broader searches may be preferable, for example exploring options for generating polygenic risk scores that enhance GWAS association signals and performing a PheWAS on putative ME/CFS SNPs to elucidate genetic signals shared between other diseases or traits. Transcriptomic studies have examined differentially expressed genes at both the single cell level and the population level in PBMCs before and after an exercise challenge. At the single cell level, ME/CFS patients exhibited increased monocyte dysregulation and was unable to respond to tissue damage caused by high energy demands due to improper platelet activation . At the population level, no significant differences in gene expression of immune cells were found between the two timepoints in ME/CFS, while the healthy control group showed overexpression of genes in multiple pathways . Proteomic, immunologic, and metabolomic studies have demonstrated significant variability, especially when identifying biomarkers in non-invasive and minimally processed biofluids such as serum, plasma, and urine. Not only has a diverse array of biomarkers been identified, but their concentration levels in ME/CFS have also been contradictory. For example, sphingomyelins, a class of lipids involved in cell membrane structure and signalling, were found to be both increased , and decreased in ME/CFS patients, suggesting potential disruptions in membrane fluidity or lipid metabolism. Other lipids, such as phosphatidylcholines, ceramides, cholesterol, cholesterol esters, and triglycerides have also generated inconsistent results . This variability highlights the importance of focusing on divergent biochemical pathways rather than individual biomarkers, where both increased and decreased biomarker levels present viable perturbed pathways for different subgroups in ME/CFS. Many studies have identified pathways through pathway enrichment analysis or manual inference from surveying literature. However, a more robust approach would involve validating the findings through integrating multi-omics data, which holistically reflects the state of disrupted pathways in ME/CFS and incorporating longitudinal monitoring. Understanding whether a biomarker (or a pathway) is merely correlated with ME/CFS or plays a causative role is essential for developing effective treatments . While correlational biomarkers can aid in early detection and monitoring, causal biomarkers can lead to interventions that modify the disease course. Determining causality requires prospective studies, where biomarkers are measured before disease onset and tracked over time. One prospective study identified various dysregulated pathways including glutathione metabolism, nucleotide metabolism, the TCA cycle, glycolysis and urea cycle between individuals that recovered from infectious mononucleosis and those that went on to develop severe ME/CFS . In addition to prospective designs, Mendelian randomisation and randomised controlled trials can further support causal inferences by demonstrating that targeting a biomarker affects disease outcomes . However, in the absence of long-term large scale prospective data for ME/CFS, meta-analysis of case-control studies still offer valuable insights . Meta-analyses can help assess whether reported biomarkers consistently correlate with demographics, symptoms, or external influences, helping to refine biomarker for future causal investigations . While not sufficient for proving causality, this approach is critical for identifying patterns in existing data and guiding the design of future prospective studies. Multi-omics describes two or more omics, which can be integrated simultaneously or in parallel . The parallel method involves analysing each omics dataset individually and benefits from efficient workflows. Simultaneous analysis considers multiple omics datasets together, offering the advantage of identifying shared sources of variation across different data modalities . This integrated approach contrasts with parallel analysis which does not explicitly link the biological relevance of each individual dataset. Simultaneous integration methods draw on statistical concepts and can be broadly implemented using multivariate analyses, graph-based methods, marginal associations, and unsupervised methods. The parallel method is analysis-agnostic and offers a simple and flexible solution to multi-omics integration. For example, Xiong et al. integrated three data sets: species abundance (obtained from shotgun metagenomics on gut microbiota), normalised KEGG gene abundance and normalised metabolite profile (plasma metabolomics), into a multi-omics classifier. They first built three individual gradient boosted models for each dataset, ranked features based on their importance and extracted the top 10 features for each model which were then used to train the multi-omics classifier. This approach enabled the identification of potential biomarkers within each omics layer, including low abundance of butyrate-producing microbes and decreased plasma isobutyrate from a correlation analysis post-classification. Kitami et al. performed deep molecular phenotyping on 48 ME/CFS and 52 health controls and collected clinical lab tests, metabolome, immunophenotype, transcriptome and microbiome. They identified 26 significant molecular markers across the five data modalities using two-tailed Mann-Whitney U-test with Benjamini-Hochberg correction and integrated the features using partial least square discriminant analysis. Multivariate integration methods, applied in simultaneous analysis, are highly effective for disease classification and biomarker elucidation. Giloteaux et al. integrated 353 features including extracellular vesicle (EV) cytokines, plasma cytokines and plasma proteomics with a multi-omics classifier. Feature importance scores were assigned to all the molecular entities based on their direct contribution to the model performance. The top 20 performing features comprised of 15 plasma proteins and 5 EV proteins. This approach contrasts Xiong et al. who had arbitrarily included features into the multi-omics classifier based on prior individual models. Multivariate integrations can also be performed with mixOmics and MetaboAnalyst . Biological networks are complex systems of interconnected components, making graph-based methods ideal for mapping multi-omics interactions . Nagy-Szakal et al. performed a topological data analysis on the AYASDI platform (Ayasdi, Menlo Park, California) integrating 562 plasma metabolites, 574 faecal bacterial relative abundances, 587 metabolic bacterial variables, 61 immune molecules, and 81 questionnaire items for 50 ME/CFS and 50 health controls. To compare how both continuous and categorical variables were related, they used a measure called Jaccard distance, which looks at how dissimilar the variables are between two groups. They also used dimensionality reduction methods to simplify the data for easier visualisation. Their visualisations showed clear class distinctions in the network graphs and showed that bacterial relative abundance features were stronger drivers for class separation than plasma metabolomic features. However, the study lacked biological interpretation from the network analysis, relying instead on univariate logistic regression and independent correlation analysis between bacteria, metabolites, and questionnaire scores (parallel method). Other network analysis approaches include similarity network fusion , which is also an unsupervised method that could be used to cluster ME/CFS into subgroups with both discrete and continuous data types. Marginal association and unsupervised multi-omics integration methods are yet to be rigorously applied in ME/CFS studies but hold significant potential for future applications. Generalised linear models are often employed for case-control studies to identify biomarker associations. Alternatively, marginal association tests can be performed between two different omics, similar to expression quantitative trait loci (eQTLs) analysis, which tests for association of genetic variants and gene expression levels , or metabolite GWAS which combines functional genomics and metabolomics . Unsupervised techniques worth exploring include Multi-Omics Factor Analysis (MOFA) , and PathME , which both have open-source code available for implementation. The primary use case for MOFA is to identify unbroken axes of variation across different data modalities targeted towards heterogenous diseases. Multiple different omics datasets are decomposed into a single matrix comprising of factors [12pt]{minimal} $$\:\:$$ samples. These factors can be queried to identify the variance explained by each data modality and the individual contributions of the features using loadings scores. PathME provides direct pathway interpretations and clustering capabilities. Different omics features are first mapped to specific pathways, a score is then assigned to each sample for the different pathways using a sparse denoising autoencoder. Bi-clustering is performed on samples and pathways to generate subgroups. Here, we have only briefly discussed a few integration methods that could be applied in ME/CFS. As ME/CFS studies are now generating higher volumes of data with greater variety, the application of advanced data integration tools should be prioritised. These tools are more effective and reliable than having researchers manually link significant findings from different datasets, as there is a possibility to miss connections or introduce errors. Biobanks Efforts to build ME/CFS-specific biobanks have gained momentum, with initiatives like the UK ME/CFS Biobank , AusME Biobank, and DecodeME project leading the way. The UK ME/CFS Biobank has been instrumental in collecting and providing biological samples and datasets to researchers worldwide. Similarly, the DecodeME project aims to conduct a large-scale genetic study by recruiting 25,000 individuals with ME/CFS, dramatically boosting the statistical power compared to previous studies. In addition, non-disease specific biobanks such as the UK Biobank, Biobank Japan, Estonian Biobank, China Kadoorie Biobank, and the All of Us Research Program in the United States contain vast amounts of genetic, phenotypic, and health data from diverse populations. These resources are invaluable for creating control groups with different ethnicities and for comparing comorbid conditions. Analysing biobanks with linked electronic health records could also help elucidate whether individuals diagnosed with ME/CFS have specific health trajectories that differ from other disease groups . In particular, the ability to cross-reference comorbid diagnoses and sequential disease development provides an opportunity to address the diagnostic ambiguity and develop more precise clinical profiles for ME/CFS. The volume of biobank data also requires standardised collection and processing procedures, ensuring consistency and reliability across timepoints. Consequently, validating multiple small-scale studies with biobank data enhances the accuracy and robustness of their research findings. Data harmonisation and data sharing There is also the challenge of managing the vast amounts of data collected from small- and medium-scale studies. Studies often employ different questionnaires such as Bell CFIDS disability scale, Chalder fatigue scale, DePaul Symptom Questionnaire, Short Form 36-Item Health Survey, Fatigue Severity Scale, and others, to assess symptoms, severity, and functionality; with each questionnaire having their own focus and format. Developing an intermediary data format that can summarise, or map questionnaire responses to standardised values using schema matching and machine learning would be a more productive solution than continuously creating or updating questionnaires. This approach will facilitate data integration and meta-analysis, allowing researchers to combine and compare results across older and newer studies more effectively. Additionally, the National Institutes of Health (NIH) has also released a data sharing portal, mapMECFS , for registered researchers to upload their data, including metadata and biological data, to be compiled into summary statistics. Depositing raw biological data in repositories is also strongly encouraged so different data harmonisation and normalisation strategies can be trialled. Increasing reproducibility The varying results across ME/CFS omics studies can also be attributed to the different statistical and machine learning methods employed. The exploratory nature of omics studies means researchers often apply various analytical techniques until a novel pattern is detected, which may lead to inconsistent findings. To improve the reproducibility and transparency of these studies, adopting open science practices, such as study pre-registration (e.g., COS Preregistration ) and the use of AI/Machine Learning checklists (e.g., AIMe Registry ), can be invaluable. Pre-registration ensures that study objectives, hypotheses, and analysis plans are clearly defined in advance, reducing biases and selective reporting. Meanwhile, checklists for AI and machine learning algorithms promote the use of standardised, transparent practises, helping to mitigate the impact of varying analytical approaches. These measures are not meant to restrict research, but to provide a clear distinction between exploratory and confirmatory studies and guide robust hypothesis testing designs in future research. Longitudinal studies Longitudinal studies provide insights into the progression and fluctuations of ME/CFS. A recent case study ( n = 1) combined various types of data, such as cytokine profiles and clinical information, with AI techniques like natural language processing and sentiment analysis . This approach extracted functional capacity information from blog posts written during periods of exacerbation, effectively mapping out the patient’s journey through ME/CFS onset, progression, and their responses to different treatments over the span of twenty years. Additionally, the study showcased the untapped potential of integrating electronic health records and personal writings in a retrospective study to identify patterns or signs that could predict disease onset or relapses before physical symptoms appear. Additional tools such as integrative personal omics profile (iPOP) and multiscale, multifactorial response network (MMRN) can provide objective interpretations as sample sizes for longitudinal studies increase. Wearables and digital biomarkers Integrating digital biomarkers collected through wearable devices offers a transformative approach to monitoring ME/CFS in both longitudinal studies and general settings . Wearables can continuously track various physiological parameters that are highly relevant to ME/CFS. For example, reduced physical activity, temperature, and disrupted sleep patterns can serve as objective indicators of disease severity, while heart rate variability reflects autonomic dysfunction, indicating the body’s stress response and overall cardiovascular health . These insights are unattainable through periodic clinical visits, provide an alternative to patient symptom descriptions, can help establish individualised patient reference ranges and be used to identify early signs of flare-ups. Additionally, because wearable data is passively collected, it mitigates potential sampling bias and captures comprehensive data on both good and bad days. ME/CFS researchers can incorporate continuous digital monitoring into their study designs by utilising platforms like the Digital Medicine Society’s playbook for standard protocols. Embracing AI While this review primarily focused on machine learning applications, there is also a growing body of research highlighting how deep learning (another branch of AI) can address the heterogeneity of ME/CFS. Deep learning uses neural networks comprising of layers of connected nodes that pass information from one layer to another depending on model parameters such as weights, and biases, and activation functions . The learning process is dynamic and iterative, involving forward propagation to predict output labels and backward propagation (a feedback loop) which adjust the model parameters according to the prediction error, thereby refining the learning process. Deep learning offers several advantages over machine learning for ME/CFS, including the ability to predict multiple outcomes (e.g., phenotypes, clinical scores) for an individual, rather than assigning a single outcome (e.g., ME/CFS or non-ME/CFS label). Hence, this capability is crucial for identifying distinct clinical or biological features of ME/CFS, where heterogeneous individuals can be classified based on their unique combinations of features influenced by symptoms, genetic markers, immune responses, and other biomarkers. Recently, a deep learning framework called BioMapAI was developed to simultaneously integrate microbiome, immune and metabolomic profiles, which were mapped onto 12 clinical symptoms . The model reconstructed clinical symptoms from biological data and elucidated non-linear and biphasic relationships between the two data types through explainable AI . This framework can also be extrapolated to predict other multi-label endpoints, and to include genomic data, demonstrating the effectiveness of deep learning in handling raw, high-dimensional, and multi-modal data necessary to holistically capture the diverse ME/CFS symptomatology. Efforts to build ME/CFS-specific biobanks have gained momentum, with initiatives like the UK ME/CFS Biobank , AusME Biobank, and DecodeME project leading the way. The UK ME/CFS Biobank has been instrumental in collecting and providing biological samples and datasets to researchers worldwide. Similarly, the DecodeME project aims to conduct a large-scale genetic study by recruiting 25,000 individuals with ME/CFS, dramatically boosting the statistical power compared to previous studies. In addition, non-disease specific biobanks such as the UK Biobank, Biobank Japan, Estonian Biobank, China Kadoorie Biobank, and the All of Us Research Program in the United States contain vast amounts of genetic, phenotypic, and health data from diverse populations. These resources are invaluable for creating control groups with different ethnicities and for comparing comorbid conditions. Analysing biobanks with linked electronic health records could also help elucidate whether individuals diagnosed with ME/CFS have specific health trajectories that differ from other disease groups . In particular, the ability to cross-reference comorbid diagnoses and sequential disease development provides an opportunity to address the diagnostic ambiguity and develop more precise clinical profiles for ME/CFS. The volume of biobank data also requires standardised collection and processing procedures, ensuring consistency and reliability across timepoints. Consequently, validating multiple small-scale studies with biobank data enhances the accuracy and robustness of their research findings. There is also the challenge of managing the vast amounts of data collected from small- and medium-scale studies. Studies often employ different questionnaires such as Bell CFIDS disability scale, Chalder fatigue scale, DePaul Symptom Questionnaire, Short Form 36-Item Health Survey, Fatigue Severity Scale, and others, to assess symptoms, severity, and functionality; with each questionnaire having their own focus and format. Developing an intermediary data format that can summarise, or map questionnaire responses to standardised values using schema matching and machine learning would be a more productive solution than continuously creating or updating questionnaires. This approach will facilitate data integration and meta-analysis, allowing researchers to combine and compare results across older and newer studies more effectively. Additionally, the National Institutes of Health (NIH) has also released a data sharing portal, mapMECFS , for registered researchers to upload their data, including metadata and biological data, to be compiled into summary statistics. Depositing raw biological data in repositories is also strongly encouraged so different data harmonisation and normalisation strategies can be trialled. The varying results across ME/CFS omics studies can also be attributed to the different statistical and machine learning methods employed. The exploratory nature of omics studies means researchers often apply various analytical techniques until a novel pattern is detected, which may lead to inconsistent findings. To improve the reproducibility and transparency of these studies, adopting open science practices, such as study pre-registration (e.g., COS Preregistration ) and the use of AI/Machine Learning checklists (e.g., AIMe Registry ), can be invaluable. Pre-registration ensures that study objectives, hypotheses, and analysis plans are clearly defined in advance, reducing biases and selective reporting. Meanwhile, checklists for AI and machine learning algorithms promote the use of standardised, transparent practises, helping to mitigate the impact of varying analytical approaches. These measures are not meant to restrict research, but to provide a clear distinction between exploratory and confirmatory studies and guide robust hypothesis testing designs in future research. Longitudinal studies provide insights into the progression and fluctuations of ME/CFS. A recent case study ( n = 1) combined various types of data, such as cytokine profiles and clinical information, with AI techniques like natural language processing and sentiment analysis . This approach extracted functional capacity information from blog posts written during periods of exacerbation, effectively mapping out the patient’s journey through ME/CFS onset, progression, and their responses to different treatments over the span of twenty years. Additionally, the study showcased the untapped potential of integrating electronic health records and personal writings in a retrospective study to identify patterns or signs that could predict disease onset or relapses before physical symptoms appear. Additional tools such as integrative personal omics profile (iPOP) and multiscale, multifactorial response network (MMRN) can provide objective interpretations as sample sizes for longitudinal studies increase. Integrating digital biomarkers collected through wearable devices offers a transformative approach to monitoring ME/CFS in both longitudinal studies and general settings . Wearables can continuously track various physiological parameters that are highly relevant to ME/CFS. For example, reduced physical activity, temperature, and disrupted sleep patterns can serve as objective indicators of disease severity, while heart rate variability reflects autonomic dysfunction, indicating the body’s stress response and overall cardiovascular health . These insights are unattainable through periodic clinical visits, provide an alternative to patient symptom descriptions, can help establish individualised patient reference ranges and be used to identify early signs of flare-ups. Additionally, because wearable data is passively collected, it mitigates potential sampling bias and captures comprehensive data on both good and bad days. ME/CFS researchers can incorporate continuous digital monitoring into their study designs by utilising platforms like the Digital Medicine Society’s playbook for standard protocols. While this review primarily focused on machine learning applications, there is also a growing body of research highlighting how deep learning (another branch of AI) can address the heterogeneity of ME/CFS. Deep learning uses neural networks comprising of layers of connected nodes that pass information from one layer to another depending on model parameters such as weights, and biases, and activation functions . The learning process is dynamic and iterative, involving forward propagation to predict output labels and backward propagation (a feedback loop) which adjust the model parameters according to the prediction error, thereby refining the learning process. Deep learning offers several advantages over machine learning for ME/CFS, including the ability to predict multiple outcomes (e.g., phenotypes, clinical scores) for an individual, rather than assigning a single outcome (e.g., ME/CFS or non-ME/CFS label). Hence, this capability is crucial for identifying distinct clinical or biological features of ME/CFS, where heterogeneous individuals can be classified based on their unique combinations of features influenced by symptoms, genetic markers, immune responses, and other biomarkers. Recently, a deep learning framework called BioMapAI was developed to simultaneously integrate microbiome, immune and metabolomic profiles, which were mapped onto 12 clinical symptoms . The model reconstructed clinical symptoms from biological data and elucidated non-linear and biphasic relationships between the two data types through explainable AI . This framework can also be extrapolated to predict other multi-label endpoints, and to include genomic data, demonstrating the effectiveness of deep learning in handling raw, high-dimensional, and multi-modal data necessary to holistically capture the diverse ME/CFS symptomatology. There is immense potential for harnessing big data and AI for precision medicine in ME/CFS. The heterogeneity, unestablished aetiology, and suspected multifactorial disease mechanisms in ME/CFS pose significant challenges to biomarker discovery and treatment development, where progress is limited through conventional workflows. Many current studies lack sufficient statistical power, employ diverse study designs, and often rely on manual interpretations of multi-omics data, leading to inconsistent findings. While machine learning and other computational approaches are gaining traction, the limitations of recruitment, small sample sizes, and a lack of standardisation hinder their full potential. However, it is important to acknowledge that AI and machine learning are not magic bullets capable of solving all the complexities of ME/CFS. Their success depends heavily on high-quality, relevant input data and defining specific training endpoints to be modelled. Without these, even the most advanced algorithms may struggle to produce actionable insights. Looking ahead, the future of ME/CFS research looks promising. Continued efforts to expand data integration, biobank resources, transparent reporting, and collaborative research efforts will improve statistical power and reproducibility. With these advancements, we can move from exploratory studies to confirmatory ones, enabling the identification of complex biological patterns at the individual level. Ultimately, these predictive models may positively influence clinical decision making and lead to more effective and personalised treatments for ME/CFS. |
Cost–utility analysis of MR imaging-guided transurethral ultrasound ablation for the treatment of low- to intermediate-risk localised prostate cancer | 51b8e2ca-2740-42c5-8f33-9589be7ae833 | 11752021 | Surgical Procedures, Operative[mh] | According to the Federal Statistical Office in Germany, prostate cancer was responsible for 15.4% of all deaths in men in 2020. In addition, the economic burden of prostate cancer is significant due to direct medical costs, which were estimated to be (inflation-adjusted) €326 million in Germany in 2023. Among all prostate cancer patients, those with low- and favourable intermediate-risk (of) prostate cancerlow or favourable intermediate risk of prostate cancer who have a low risk of tumour spreading are the largest group. For these patients, there are three main treatment strategies: active surveillance (AS), radical prostatectomy (RARP) or external beam radiation therapy (EBRT). Both definitive treatment options (RARP and EBRT) are associated with a significant risk of long-term adverse effects (AEs), mainly erectile dysfunction (ED), urinary incontinence (UI) and bowel problems (BP). However, compared with AS, both RARP and EBRT result in more favourable oncologic outcomes (ie, overall survival, disease progression and metastases). In recent years, focal approaches (eg, high-intensity focused ultrasound (HIFU), cryotherapy, vascular-targeted photodynamic therapy and magnetic resonance imaging-guided transurethral ultrasound ablation (MR-TULSA)) have been developed to achieve oncologic outcomes similar to those of the definitive treatments and, simultaneously, to reduce the risk of AEs. MR-HIFU is still the most performed among the focal approaches, but the share of German patients treated with MR-HIFU decreased from 90% in 2017 to 75% in 2019. In contrast, since 2018, there has been a steep increase in the application of MR-TULSA procedures in Germany. MR-TULSA is a minimally invasive technique, performed with a transurethral robot-guided ultrasound device that thermally ablates the prostate cancer tissue, under real-time MR-imaging monitoring. According to recent clinical studies, MR-TULSA leads to fewer AEs than RARP and EBRT but has similar oncologic outcomes. In a recently published cost-effectiveness modelling study with a 10 year time horizon from the perspective of the British National Health Service, focal therapy (based on cryosurgery and HIFU) dominated EBRT and RARP for patients with non-metastatic prostate cancer. To evaluate the clinical and economic long-term consequences of applying MR-TULSA in low- and favourable intermediate-risk (of) prostate cancer in Germany, we compared MR-TULSA with three conventional treatment strategies (ie, AS, EBRT and RARP) from the perspective of the German Statutory Health Insurance (SHI).
To reflect the lifetime effects and costs of the treatment strategies, we developed a Markov model using TreeAge Pro Healthcare 2024 . Markov models are a frequently employed methodology for the assessment of interventions with long-term costs and effects, which are challenging to ascertain through the analysis of follow-up data derived from clinical trials. Men with (i) newly diagnosed low- to favourable intermediate-risk prostate cancer according to the D’Amico risk classification and (ii) life expectancy of more than 10 years entered the model at the age of 60. Low risk was defined as cT1–cT2a, Grade Group 1, prostate-specific antigen (PSA) <10 ng/mL and favourable-intermediate risk as one intermediate risk factor (cT2b-c or PSA 10–20 ng/mL) assigned to Grade Group 1 or 2 (<50% biopsy cores positive). When entering the model, patients were assumed to have no functional limitations in terms of ED, UI or BP. The model had a time horizon of 40 years, and 3 month cycles were used to reflect the schedule of follow-up visits in Germany . The analysis was conducted from the perspective of the German SHI and is reported according to the CHEERS checklist. Strategies for the comparison In line with international recommendations, in Germany the costs of screening have to be borne by the patient. To draw a realistic depiction of clinical practice in Germany, for patients with clinically detected prostate cancer, we chose four different treatment strategies as comparators for the model: (i) MR-TULSA, (ii) RARP, (iii) EBRT and (iv) AS. According to the 2024 German guideline on prostate cancer, patients newly diagnosed with favourable localised prostate cancer should be offered clear information on the benign course of the disease, with AS as the recommended strategy. However, patients can still opt against AS and decide on an interventional curative treatment option. In this model, we included RARP and EBRT as comparators because they represent more than 90% of procedures performed in Germany. In contrast to options (ii)–(iv), MR-TULSA was included to meet the latest technical developments and to add an innovative focal approach with increasing therapy applications to our model. MR-TULSA, including follow-up with magnetic resonance (MR)-fusion biopsies. In case of clinical progression, patients could either be treated with a second MR-TULSA or with a salvage RARP. RARP was assumed to be performed with the robot-assisted approach because the use of the conventional open technique is declining. For salvage treatment after RARP, patients were assumed to receive EBRT and 6 months of androgen deprivation therapy (ADT) with the gonadotropin-releasing hormone analogue leuprorelin. EBRT was assumed to be performed with intensity-modulated and image-guided techniques with 74–80 Gy. Salvage treatment options are a salvage RARP or ADT with leuprorelin for 2 years. AS, defined as monitoring the PSA value and performing digital rectal examinations (DRE), multi-parametric MRIs (mpMRIs) and biopsies following a pre-set protocol. In case the cancer progresses, or the patient opts out of the AS strategy, he received RARP or EBRT following the same treatment protocols described in (ii) and (iii). If a patient develops a second, non-metastatic elevation of the PSA-value during any of the salvage treatment options described above, he receives a permanent ADT with leuprorelin. Model overview In accordance with previously published cost-effectiveness analyses, our Markov model comprises five health states . All patients started in the state of ‘stable disease’. Patients who received a definitive treatment moved to the state ‘remission’. If a disease progression was biochemically identified, patients could move from ‘remission’ to ‘clinical progression’. ‘Clinical progression’ after RARP was defined as two consecutive PSA-value measurements exceeding 0.2 ng/mL. ‘Clinical progression’ after EBRT or MR-TULSA was defined as exceeding 2 ng/mL following the Phoenix definition or any other progression of the diseases (eg, local recurrence) not categorised as a metastasis. In the case of ‘clinical progression’, patients received the salvage therapy depending on their first treatment (without the option of returning to the ‘stable disease’ state). From each of the described health states, patients could move to the states ‘metastasis’ or ‘death’. The health state ‘metastasis’ was defined as metastatic hormone-sensitive prostate cancer (mHSPC). In the case of metastasis, patients were considered to be hormone sensitive because the treatment strategies (i–iv) do not comprise definitive hormonal treatment, and thus, patients cannot achieve hormone resistance. AEs of the different treatments were depicted within the inherent health state. Model input parameters Sources of data Data used for the calculation of transition probabilities and utility values were obtained from literature reviews. To identify appropriate input parameters, systematic literature searches in MEDLINE were conducted. Studies were selected based on methodological quality and applicability to the study context. All relevant literature was either obtained through open-access publications or institutional access. The search strategies are given in . Probabilities Probabilities of AEs after MR-TULSA were obtained from a single-arm, prospective cohort ( n =115 patients) with 1 year follow-up . Because in that study there were no incident AEs between 1 and 3 years, in our model AEs were assumed to be stable in the long term. Because follow-up in most studies on MR-TULSA was up to 1 year and/or was based on small sample sizes ( n <30), we assumed that the probability of clinical progression or metastasis after MR-TULSA would be similar to that evaluated in a prospective cohort of intermediate-risk prostate cancer patients for MR-HIFU. Transition probabilities and probabilities of AEs for the three comparators RARP, EBRT and AS were obtained from the ProtecT trial, a prospective multi-centre randomised controlled trial with 1643 participants over 15 years. Data from the ProtecT trial were preferred because data on the PREFERE trial were limited due to poor participation of patients. All-cause mortality was age-adjusted, taken from the German federal statistical office. Patients with metastases were assigned to have higher cancer-specific mortality. Utility values Utilities were taken from a standard gamble study with 1884 prostate cancer survivors from the USA, the CaPSURE study, which addressed various disease states of prostate cancer . A temporary decrease in utilities was assigned due to definitive treatments, while a permanent reduction was assumed due to the occurrence of AEs (ie, UI, ED and BP), according to the proportion of specific AEs per treatment strategy . To combine utility values, the multiplicative method was used. Input parameters are shown in . Costs Cost data applied in the model were calculated based on clinical guidelines and consultation with experts to reflect the resource consumption in Germany. The direct medical costs included the costs of performing different treatment strategies including specific follow-up protocols. A detailed cost breakdown included in the analysis is provided in . Costs related to the treatment of AEs were included depending on their coverage by the SHI (eg, the costs of treatment for UI are covered, while those for ED are not) . Costs for treatment, surveillance and follow-up were valued according to publicly available sources for the reimbursement of patients insured in the German SHI (eg, the German diagnosis-related groups (DRG)-catalogue). For the calculations, all costs were adjusted to €2024. The generalisability of our results for the German context was assured by averting regional differences in prizing (eg, the lump sums for reimbursements of inpatient treatment were calculated with the base case value proposed by the DRG research group). Base case analysis To capture the differences between strategies, the incremental cost-effectiveness ratio (ICER) between the four examined treatment strategies was calculated as costs per quality-adjusted life year (QALYs). Because low- to favourable intermediate-risk prostate cancer usually has a benign course, with a 15 year cancer-specific survival rate, the main differences between the different strategies derive from adverse events affecting the quality of life of patients. Therefore, calculating the ICER as cost per QALY was deemed more meaningful than cost per life year gained. An annual discount rate of 3% for costs and utility values was applied in line with German methodological guidelines. Sensitivity analyses and model validation To assess parameter uncertainty, we carried out deterministic sensitivity analyses (DSAs) of all variables (ie, varying input parameters within the 95% CI and assessing the impact on the ICER). For inpatient costs, German-DRG lump sums were varied according to the minimum and maximum length of stay. The costs of MR-TULSA and RARP varied within the same adapted range. In probabilistic sensitivity analysis, all input parameters were varied simultaneously according to predefined distributions: utility values and transition probabilities were assumed to be beta-distributed and costs to be gamma-distributed. Results from the probabilistic sensitivity analysis were plotted in a cost-effectiveness acceptability curve, showing the probability of each strategy being cost-effective at different thresholds of willingness-to-pay(WTP). In a structural sensitivity analysis, we assessed the impact of applying shorter time horizons for the model (ie, 5, 10 and 20 years). Validation efforts are reported according to the AdViSHE tool and reported in . Patient and public involvement Patients or the public were not involved in the design, conduct or reporting of our research.
In line with international recommendations, in Germany the costs of screening have to be borne by the patient. To draw a realistic depiction of clinical practice in Germany, for patients with clinically detected prostate cancer, we chose four different treatment strategies as comparators for the model: (i) MR-TULSA, (ii) RARP, (iii) EBRT and (iv) AS. According to the 2024 German guideline on prostate cancer, patients newly diagnosed with favourable localised prostate cancer should be offered clear information on the benign course of the disease, with AS as the recommended strategy. However, patients can still opt against AS and decide on an interventional curative treatment option. In this model, we included RARP and EBRT as comparators because they represent more than 90% of procedures performed in Germany. In contrast to options (ii)–(iv), MR-TULSA was included to meet the latest technical developments and to add an innovative focal approach with increasing therapy applications to our model. MR-TULSA, including follow-up with magnetic resonance (MR)-fusion biopsies. In case of clinical progression, patients could either be treated with a second MR-TULSA or with a salvage RARP. RARP was assumed to be performed with the robot-assisted approach because the use of the conventional open technique is declining. For salvage treatment after RARP, patients were assumed to receive EBRT and 6 months of androgen deprivation therapy (ADT) with the gonadotropin-releasing hormone analogue leuprorelin. EBRT was assumed to be performed with intensity-modulated and image-guided techniques with 74–80 Gy. Salvage treatment options are a salvage RARP or ADT with leuprorelin for 2 years. AS, defined as monitoring the PSA value and performing digital rectal examinations (DRE), multi-parametric MRIs (mpMRIs) and biopsies following a pre-set protocol. In case the cancer progresses, or the patient opts out of the AS strategy, he received RARP or EBRT following the same treatment protocols described in (ii) and (iii). If a patient develops a second, non-metastatic elevation of the PSA-value during any of the salvage treatment options described above, he receives a permanent ADT with leuprorelin.
In accordance with previously published cost-effectiveness analyses, our Markov model comprises five health states . All patients started in the state of ‘stable disease’. Patients who received a definitive treatment moved to the state ‘remission’. If a disease progression was biochemically identified, patients could move from ‘remission’ to ‘clinical progression’. ‘Clinical progression’ after RARP was defined as two consecutive PSA-value measurements exceeding 0.2 ng/mL. ‘Clinical progression’ after EBRT or MR-TULSA was defined as exceeding 2 ng/mL following the Phoenix definition or any other progression of the diseases (eg, local recurrence) not categorised as a metastasis. In the case of ‘clinical progression’, patients received the salvage therapy depending on their first treatment (without the option of returning to the ‘stable disease’ state). From each of the described health states, patients could move to the states ‘metastasis’ or ‘death’. The health state ‘metastasis’ was defined as metastatic hormone-sensitive prostate cancer (mHSPC). In the case of metastasis, patients were considered to be hormone sensitive because the treatment strategies (i–iv) do not comprise definitive hormonal treatment, and thus, patients cannot achieve hormone resistance. AEs of the different treatments were depicted within the inherent health state.
Sources of data Data used for the calculation of transition probabilities and utility values were obtained from literature reviews. To identify appropriate input parameters, systematic literature searches in MEDLINE were conducted. Studies were selected based on methodological quality and applicability to the study context. All relevant literature was either obtained through open-access publications or institutional access. The search strategies are given in . Probabilities Probabilities of AEs after MR-TULSA were obtained from a single-arm, prospective cohort ( n =115 patients) with 1 year follow-up . Because in that study there were no incident AEs between 1 and 3 years, in our model AEs were assumed to be stable in the long term. Because follow-up in most studies on MR-TULSA was up to 1 year and/or was based on small sample sizes ( n <30), we assumed that the probability of clinical progression or metastasis after MR-TULSA would be similar to that evaluated in a prospective cohort of intermediate-risk prostate cancer patients for MR-HIFU. Transition probabilities and probabilities of AEs for the three comparators RARP, EBRT and AS were obtained from the ProtecT trial, a prospective multi-centre randomised controlled trial with 1643 participants over 15 years. Data from the ProtecT trial were preferred because data on the PREFERE trial were limited due to poor participation of patients. All-cause mortality was age-adjusted, taken from the German federal statistical office. Patients with metastases were assigned to have higher cancer-specific mortality. Utility values Utilities were taken from a standard gamble study with 1884 prostate cancer survivors from the USA, the CaPSURE study, which addressed various disease states of prostate cancer . A temporary decrease in utilities was assigned due to definitive treatments, while a permanent reduction was assumed due to the occurrence of AEs (ie, UI, ED and BP), according to the proportion of specific AEs per treatment strategy . To combine utility values, the multiplicative method was used. Input parameters are shown in . Costs Cost data applied in the model were calculated based on clinical guidelines and consultation with experts to reflect the resource consumption in Germany. The direct medical costs included the costs of performing different treatment strategies including specific follow-up protocols. A detailed cost breakdown included in the analysis is provided in . Costs related to the treatment of AEs were included depending on their coverage by the SHI (eg, the costs of treatment for UI are covered, while those for ED are not) . Costs for treatment, surveillance and follow-up were valued according to publicly available sources for the reimbursement of patients insured in the German SHI (eg, the German diagnosis-related groups (DRG)-catalogue). For the calculations, all costs were adjusted to €2024. The generalisability of our results for the German context was assured by averting regional differences in prizing (eg, the lump sums for reimbursements of inpatient treatment were calculated with the base case value proposed by the DRG research group). Base case analysis To capture the differences between strategies, the incremental cost-effectiveness ratio (ICER) between the four examined treatment strategies was calculated as costs per quality-adjusted life year (QALYs). Because low- to favourable intermediate-risk prostate cancer usually has a benign course, with a 15 year cancer-specific survival rate, the main differences between the different strategies derive from adverse events affecting the quality of life of patients. Therefore, calculating the ICER as cost per QALY was deemed more meaningful than cost per life year gained. An annual discount rate of 3% for costs and utility values was applied in line with German methodological guidelines. Sensitivity analyses and model validation To assess parameter uncertainty, we carried out deterministic sensitivity analyses (DSAs) of all variables (ie, varying input parameters within the 95% CI and assessing the impact on the ICER). For inpatient costs, German-DRG lump sums were varied according to the minimum and maximum length of stay. The costs of MR-TULSA and RARP varied within the same adapted range. In probabilistic sensitivity analysis, all input parameters were varied simultaneously according to predefined distributions: utility values and transition probabilities were assumed to be beta-distributed and costs to be gamma-distributed. Results from the probabilistic sensitivity analysis were plotted in a cost-effectiveness acceptability curve, showing the probability of each strategy being cost-effective at different thresholds of willingness-to-pay(WTP). In a structural sensitivity analysis, we assessed the impact of applying shorter time horizons for the model (ie, 5, 10 and 20 years). Validation efforts are reported according to the AdViSHE tool and reported in .
Data used for the calculation of transition probabilities and utility values were obtained from literature reviews. To identify appropriate input parameters, systematic literature searches in MEDLINE were conducted. Studies were selected based on methodological quality and applicability to the study context. All relevant literature was either obtained through open-access publications or institutional access. The search strategies are given in .
Probabilities of AEs after MR-TULSA were obtained from a single-arm, prospective cohort ( n =115 patients) with 1 year follow-up . Because in that study there were no incident AEs between 1 and 3 years, in our model AEs were assumed to be stable in the long term. Because follow-up in most studies on MR-TULSA was up to 1 year and/or was based on small sample sizes ( n <30), we assumed that the probability of clinical progression or metastasis after MR-TULSA would be similar to that evaluated in a prospective cohort of intermediate-risk prostate cancer patients for MR-HIFU. Transition probabilities and probabilities of AEs for the three comparators RARP, EBRT and AS were obtained from the ProtecT trial, a prospective multi-centre randomised controlled trial with 1643 participants over 15 years. Data from the ProtecT trial were preferred because data on the PREFERE trial were limited due to poor participation of patients. All-cause mortality was age-adjusted, taken from the German federal statistical office. Patients with metastases were assigned to have higher cancer-specific mortality.
Utilities were taken from a standard gamble study with 1884 prostate cancer survivors from the USA, the CaPSURE study, which addressed various disease states of prostate cancer . A temporary decrease in utilities was assigned due to definitive treatments, while a permanent reduction was assumed due to the occurrence of AEs (ie, UI, ED and BP), according to the proportion of specific AEs per treatment strategy . To combine utility values, the multiplicative method was used. Input parameters are shown in .
Cost data applied in the model were calculated based on clinical guidelines and consultation with experts to reflect the resource consumption in Germany. The direct medical costs included the costs of performing different treatment strategies including specific follow-up protocols. A detailed cost breakdown included in the analysis is provided in . Costs related to the treatment of AEs were included depending on their coverage by the SHI (eg, the costs of treatment for UI are covered, while those for ED are not) . Costs for treatment, surveillance and follow-up were valued according to publicly available sources for the reimbursement of patients insured in the German SHI (eg, the German diagnosis-related groups (DRG)-catalogue). For the calculations, all costs were adjusted to €2024. The generalisability of our results for the German context was assured by averting regional differences in prizing (eg, the lump sums for reimbursements of inpatient treatment were calculated with the base case value proposed by the DRG research group).
To capture the differences between strategies, the incremental cost-effectiveness ratio (ICER) between the four examined treatment strategies was calculated as costs per quality-adjusted life year (QALYs). Because low- to favourable intermediate-risk prostate cancer usually has a benign course, with a 15 year cancer-specific survival rate, the main differences between the different strategies derive from adverse events affecting the quality of life of patients. Therefore, calculating the ICER as cost per QALY was deemed more meaningful than cost per life year gained. An annual discount rate of 3% for costs and utility values was applied in line with German methodological guidelines.
To assess parameter uncertainty, we carried out deterministic sensitivity analyses (DSAs) of all variables (ie, varying input parameters within the 95% CI and assessing the impact on the ICER). For inpatient costs, German-DRG lump sums were varied according to the minimum and maximum length of stay. The costs of MR-TULSA and RARP varied within the same adapted range. In probabilistic sensitivity analysis, all input parameters were varied simultaneously according to predefined distributions: utility values and transition probabilities were assumed to be beta-distributed and costs to be gamma-distributed. Results from the probabilistic sensitivity analysis were plotted in a cost-effectiveness acceptability curve, showing the probability of each strategy being cost-effective at different thresholds of willingness-to-pay(WTP). In a structural sensitivity analysis, we assessed the impact of applying shorter time horizons for the model (ie, 5, 10 and 20 years). Validation efforts are reported according to the AdViSHE tool and reported in .
Patients or the public were not involved in the design, conduct or reporting of our research.
Base case AS generated the highest number of QALYs (12.67), followed by EBRT (12.35), MR-TULSA (12.35) and RARP (12.20). In contrast, RARP was the strategy with the lowest lifetime costs (€46 997). MR-TULSA (€48 826), AS (€52 449) and EBRT (€54 263) were more expensive strategies. EBRT was an absolutely dominant treatment option (more expensive and less QALYs than AS). Compared with RARP, the additional costs of AS were €5452, resulting in an ICER of €11 600 per QALY (MR-TULSA vs RARP: €12 193 per QALY). Results from the base case are shown in and . Sensitivity analyses Results from DSA are shown in . The parameters most affecting the model were the probability of metastasis after any treatment alternative and the direct costs of RARP, EBRT and MR-TULSA. For all comparisons, a lower/higher probability of metastasis after stable disease/remission resulted in the largest range of the cost-effectiveness ratio to (MR-TULSA vs RARP: cost-saving to €280 000; RARP vs AS: cost saving to €24 000 and EBRT vs RARP: €9000 to €53 000). The probabilistic sensitivity analysis showed that at a WTP of zero RARP would be the preferred option (because of the lowest costs). Assuming a WTP of €10 000 or more a decision maker would favour AS ( and ). Assumed WTPs above 80 000 €/QALY, for MR-TULSA the probability of cost-effectiveness was between 20% and 30%. Structural sensitivity analyses showed that for a time horizon of 5 or 10 years, AS dominates all other strategies (ie, less costly and more QALYs). For a time horizon of 20 years, RARP becomes the cheapest strategy, followed by MR-TULSA and AS. Thus, for a time horizon of 20 years, the ICER for AS is € 3131 per QALY and the ICER for MR-TULSA is € 1733 per QALY . Validation Cross validity was assessed by comparing two models from the perspectives of the French National Health Insurance and the British National Health Service (NHS). The comparison revealed that these differed with regard to the chosen time horizons, the model structure, input data used for the model (eg, utilities and transition probabilities) and the strategies compared (focal therapy vs AS, focal therapy vs RARP or EBRT). Detailed results of the validation can be found in . All assumptions made in the model are detailed in .
AS generated the highest number of QALYs (12.67), followed by EBRT (12.35), MR-TULSA (12.35) and RARP (12.20). In contrast, RARP was the strategy with the lowest lifetime costs (€46 997). MR-TULSA (€48 826), AS (€52 449) and EBRT (€54 263) were more expensive strategies. EBRT was an absolutely dominant treatment option (more expensive and less QALYs than AS). Compared with RARP, the additional costs of AS were €5452, resulting in an ICER of €11 600 per QALY (MR-TULSA vs RARP: €12 193 per QALY). Results from the base case are shown in and .
Results from DSA are shown in . The parameters most affecting the model were the probability of metastasis after any treatment alternative and the direct costs of RARP, EBRT and MR-TULSA. For all comparisons, a lower/higher probability of metastasis after stable disease/remission resulted in the largest range of the cost-effectiveness ratio to (MR-TULSA vs RARP: cost-saving to €280 000; RARP vs AS: cost saving to €24 000 and EBRT vs RARP: €9000 to €53 000). The probabilistic sensitivity analysis showed that at a WTP of zero RARP would be the preferred option (because of the lowest costs). Assuming a WTP of €10 000 or more a decision maker would favour AS ( and ). Assumed WTPs above 80 000 €/QALY, for MR-TULSA the probability of cost-effectiveness was between 20% and 30%. Structural sensitivity analyses showed that for a time horizon of 5 or 10 years, AS dominates all other strategies (ie, less costly and more QALYs). For a time horizon of 20 years, RARP becomes the cheapest strategy, followed by MR-TULSA and AS. Thus, for a time horizon of 20 years, the ICER for AS is € 3131 per QALY and the ICER for MR-TULSA is € 1733 per QALY .
Cross validity was assessed by comparing two models from the perspectives of the French National Health Insurance and the British National Health Service (NHS). The comparison revealed that these differed with regard to the chosen time horizons, the model structure, input data used for the model (eg, utilities and transition probabilities) and the strategies compared (focal therapy vs AS, focal therapy vs RARP or EBRT). Detailed results of the validation can be found in . All assumptions made in the model are detailed in .
This is the first cost–utility analysis of MR-TULSA for the treatment of low- and favourable intermediate-risk localised prostate cancer. Our results show that over a lifetime horizon, RARP is the cheapest treatment alternative, whereas AS and MR-TULSA are cost-effective alternatives with an ICER of €116,600 per QALY and €12 193 per QALY, respectively. Compared with the definitive treatment options RARP and EBRT, MR-TULSA would meet the economic criteria for positive reimbursement decisions in German hospitals. However, for patients accepting or even preferring a non-definitive treatment option, AS would yield the highest benefit at acceptable costs. The most influential parameters for the cost-effectiveness of the MR-TULSA strategy were the costs of the procedure and the post-treatment probability of metastasis or clinical progression. In the probabilistic sensitivity analysis, the probability of MR-TULSA being cost-effective only ranges between 16% and 37% depending on the willingness-to-pay threshold. Moreover, the structural analysis showed that MR-TULSA is not cost-effective for shorter time horizons (5–10 years) due to high initial treatment costs. In the model, the costs of MR-TULSA are offset by the long-term benefits at longer time horizons. However, these benefits are yet to be demonstrated with prospective long-term follow-up. If future studies can confirm the short-term benefits for long-term oncologic outcomes, MR-TULSA is likely to be a cost-effective focal treatment option for low- to intermediate-risk localised prostate cancer. To date, evidence on MR-TULSA is promising for functional outcomes but still immature for long-term safety and efficacy. A multicentre, prospective two-arm RCT, the ‘CAPTAIN’ trial (Clinical Trials registration number: NCT05027477), is ongoing to assess the effectiveness of MR-TULSA (including the proportion of patients free from treatment failure and overall survival) compared with RARP over a period of 10 years. Once this trial is finished by 2031, an update of our model will be opportune. Additionally, improved clinical outcomes from MR-TULSA are expected to result from learning curve effects and a more targeted patient selection (eg, prostate calcifications, elderly persons and anticoagulation). Our results are opposite to those of a cost-effectiveness modelling published in 2023. According to Reddy et al , focal therapy dominated EBRT and RARP for patients with non-metastatic prostate cancer, while AS was not considered as a treatment option. The study differed from ours in the chosen time horizon (10 years vs lifelong in our analysis) and the focal treatment modalities (cryotherapy and HIFU vs MR-TULSA). In addition, in contrast to our study, transition probabilities were derived from a series of prostate cancer registries that reported clinical outcomes for patients undergoing RARP, EBRT and focal therapy, whereas adverse events were not considered. The superiority of focal therapy was mainly driven by the low costs of cryotherapy and HIFU in the UK, which were among the most influential parameters on the cost-effectiveness ratio. In addition, while Reddy et al estimated the primary cost for focal therapy to be half of that of RARP, the current reimbursement for MR-TULSA (including follow-up costs) by the German SHI is significantly higher. To date, the lump sum reimbursed for MR-TULSA is based on local arrangements between healthcare providers and the SHI; that is, once MR-TULSA is included in the general German-DRG catalogue, the lump sum will be renegotiated. Furthermore, follow-up plans for MR-TULSA include cost-intensive mpMRIs and MR-fusion biopsies and, from year 2 onwards, patients require more frequent follow-up visits to urologists than what is required for RARP and EBRT . If the long-term oncologic safety of MR-TULSA is confirmed, the follow-up scheme for patients treated with MR-TULSA could become less resource-demanding, similar to the follow-up schemes after EBRT and RARP. This is the first cost-effectiveness analysis for MR-TULSA for low- to intermediate-risk prostate cancer patients. Reddy et al compared focal therapy (including cryotherapy and HIFU) to intermediate- and high-risk prostate cancer patients, for whom active surveillance is an unsuitable option. In a literature-based modelling study from the French National Health Insurance perspective, AS dominated focal therapy for a 30 year time horizon. Indeed, the probability that focal therapy is cost-effective was 45.5% at a WTP of €30 000/QALY, indicating a high level of uncertainty (as in our study). Similarly to our study, the vast majority of the uncertainty resulted from—among others—transition probabilities related to focal therapy cancer. However, for the comparison between a definitive treatment option and AS, the patient’s preference may be more directive for the treatment decision than cost-effectiveness. The patients’ choice between a definitive treatment and AS depends on the individual risk preference between maintaining the short-term quality of life (ie, due to avoidance of treatment-related AEs) and improving long-term quality of life (ie, due to decreased risk of cancer progression). MR-TULSA could fill the gap, compromising good cancer control and high quality of life and therefore should be offered as a third treatment alternative to patients besides invasive and observational approaches. Strengths and limitations The main strength of our model is that—in contrast to previous analyses—we could rely on 15 year follow-up data on oncologic outcomes from the ProtecT trial. To respond to the degree of uncertainty of long-term outcomes (eg, mortality) from different treatment strategies for low-risk prostate cancer, a series of structural sensitivity analyses were conducted, exploring shorter time horizons for the model (10, 15 and 20 years). These analyses were informed directly by the data from the ProtecT trial. In addition, we could apply utility data from the CaPSURE study, a large cohort of long-term survivors from 2019. Because cancer therapies have developed over the last two decades, the availability of these updated clinical evidence and utility values reflects the clinical course of prostate cancer patients appropriately. Some limitations have to be acknowledged. First, due to a lack of long-term data on MR-TULSA, the long-term data of a 5 year follow-up of patients treated with MR-HIFU were used as a proxy. This choice was justified by the similarity in mechanisms of action between these methods, which are expected to lead to similar oncological outcomes. In addition, this assumption was validated by clinical experts (ie, face validity) and cross-validation (ie, comparison to previous models). Previous models have already assumed the interchangeability of different focal therapies (cryotherapy and MR-HIFU) with regard to the expected related oncologic outcomes. Therefore, we consider our model a proper and sufficient analysis that can serve as a solid basis for deciding to adopt the MR-TULSA in the German SHI system or postponing its adoption until long-term evidence is available. Second, the high overall costs of the EBRT strategy were mainly driven by the costs of ADT, while re-irritation (ie, brachytherapy, stereotaxic radiotherapy or EBRT) was not considered an alternative salvage treatment option for patients with loco-regional failure. In addition, innovative technical features in EBRT such as intensity-modulated radiotherapy were not considered in the ProtecT trial (and thus also excluded from the model). A further concern could be that our model included only 60-year-old men based on PSA testing, which makes the eligibility of these findings for Germany questionable. According to the German guideline on prostate cancer, PSA testing should only be performed (i) after clarification that the risk of overdiagnosis is not offset by the oncologic outcomes and (ii) if the patient strongly desires to undergo screening (in that case the cost of the test should be borne by the patient). However, PSA screening is still often performed in Germany, and the present cost–utility analysis did not address a PSA-based screen-and-treat strategy for prostate cancer; rather it compares treatment strategies for patients who were already diagnosed as low- and favourable intermediate-risk prostate cancer. In addition, in contrast to the German guideline, the European Association of Urology recommends PSA as the primary screening test. This recommendation is followed in several European countries with public health insurance (eg, Sweden). Until this divergence in clinical guidance can be solved, it remains relevant to provide preliminary evidence of the cost-effectiveness of different treatment options for patients with low-risk prostate cancer.
The main strength of our model is that—in contrast to previous analyses—we could rely on 15 year follow-up data on oncologic outcomes from the ProtecT trial. To respond to the degree of uncertainty of long-term outcomes (eg, mortality) from different treatment strategies for low-risk prostate cancer, a series of structural sensitivity analyses were conducted, exploring shorter time horizons for the model (10, 15 and 20 years). These analyses were informed directly by the data from the ProtecT trial. In addition, we could apply utility data from the CaPSURE study, a large cohort of long-term survivors from 2019. Because cancer therapies have developed over the last two decades, the availability of these updated clinical evidence and utility values reflects the clinical course of prostate cancer patients appropriately. Some limitations have to be acknowledged. First, due to a lack of long-term data on MR-TULSA, the long-term data of a 5 year follow-up of patients treated with MR-HIFU were used as a proxy. This choice was justified by the similarity in mechanisms of action between these methods, which are expected to lead to similar oncological outcomes. In addition, this assumption was validated by clinical experts (ie, face validity) and cross-validation (ie, comparison to previous models). Previous models have already assumed the interchangeability of different focal therapies (cryotherapy and MR-HIFU) with regard to the expected related oncologic outcomes. Therefore, we consider our model a proper and sufficient analysis that can serve as a solid basis for deciding to adopt the MR-TULSA in the German SHI system or postponing its adoption until long-term evidence is available. Second, the high overall costs of the EBRT strategy were mainly driven by the costs of ADT, while re-irritation (ie, brachytherapy, stereotaxic radiotherapy or EBRT) was not considered an alternative salvage treatment option for patients with loco-regional failure. In addition, innovative technical features in EBRT such as intensity-modulated radiotherapy were not considered in the ProtecT trial (and thus also excluded from the model). A further concern could be that our model included only 60-year-old men based on PSA testing, which makes the eligibility of these findings for Germany questionable. According to the German guideline on prostate cancer, PSA testing should only be performed (i) after clarification that the risk of overdiagnosis is not offset by the oncologic outcomes and (ii) if the patient strongly desires to undergo screening (in that case the cost of the test should be borne by the patient). However, PSA screening is still often performed in Germany, and the present cost–utility analysis did not address a PSA-based screen-and-treat strategy for prostate cancer; rather it compares treatment strategies for patients who were already diagnosed as low- and favourable intermediate-risk prostate cancer. In addition, in contrast to the German guideline, the European Association of Urology recommends PSA as the primary screening test. This recommendation is followed in several European countries with public health insurance (eg, Sweden). Until this divergence in clinical guidance can be solved, it remains relevant to provide preliminary evidence of the cost-effectiveness of different treatment options for patients with low-risk prostate cancer.
AS is the most cost-effective treatment modality for patients with low- to favourable intermediate-risk prostate cancer. Considering the current evidence base, MR-TULSA can be cost-effective from the perspective of the German SHI.
10.1136/bmjopen-2024-088495 online supplemental file 1
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Effect of saliva on accuracy of digital dental implant transfer using two different materials of intraoral scan bodies with different exposed lengths | b8e0e89d-0570-472c-ad00-69449f81447f | 11585203 | Dentistry[mh] | The passive fit of an implant-supported framework is a critical factor in achieving successful treatment outcomes over the long term . Superstructure mismatches may result in biomechanics issues . Precision and trueness are two components of accuracy, as defined by the International Organization for Standardization (ISO) 5725-1. Precision refers to the degree of conformity between a measurement and an approved or true reference, whereas trueness defines the degree of agreement between successive measurements and the same value . The lack of standardization in clinical and laboratory methods may have an adverse effect on the accuracy of the prosthesis . The misalignment of the implant superstructure is due to the cumulative effect of the varying degrees of inaccuracy in these steps . The accuracy of the impression is a crucial factor that significantly affects outcomes since it is the initial stage in the fabrication of restorations . A digital model is generated by utilizing the data collected from the scan body and its surrounding tissues. Scanning technology enables the precise digital determination of the optimal placement of implant superstructures . Direct digital implant impressions offer several advantages over traditional impression processes, including the reduction of chairside time and an increase in patient acceptance . There is a scarcity of research regarding the impact of various liquids on the precision of intraoral scanner outcomes when used in dry conditions and on the tooth surface. Furthermore, it is important to consider the elevated levels of humidity in the oral environment. Consequently, despite the constant presence of liquids in the mouth, the means to reduce their influence on the accuracy of intraoral scanners remains unknown. There is a lack of evidence regarding the use of compressed air from a three-way syringe to remove saliva from tooth surfaces before intraoral scanning, despite manufacturers’ recommendations. Previous studies have considered or proposed that factors such as saliva, blood, gingival crevicular fluid, and the moist environment in the mouth may affect the accuracy of intraoral scanners . In order to decrease scanning errors, some manufacturers of intraoral scanners suggest drying the area using compressed air before scanning it. Nevertheless, there is presently a lack of empirical evidence to support these hypotheses. For instance, there is no substantiation that a three-way syringe adequately dehydrates samples or that liquid adversely affects scanning outcomes. To the best of our knowledge, this study represents the first investigation into the impact of an adhesive substance on the accuracy of an intraoral scanner when applied to a tooth surface. The dentistry literature lacks sufficient research on the impact of surface humidity on intraoral scanning accuracy . However, the findings of those studies have been inconsistent. In a laboratory experiment, Chen et al. utilized fully dentate and scanned utilizing two IOSs in either dry, moist, or air-blown circumstances (submerging and then draining). The dry condition exhibited the highest level of accuracy compared to the other groups. After choosing a partly dentate cast with three implant analogs inserted, Park et al. used an intraoral simulator to mimic two scenarios with varied temperatures and humidity levels. To find out any discrepancies in the digital images, we measured the lengths between the arches. According to the authors, ambient factors did not have any impact on scan accuracy . The implant depth is crucial as it directly impacts the visibility of the body during the scan, consequently influencing its accuracy. Typically, the duration of the implant’s presence directly correlates with the required length of the scan body for optimal visibility. Arcuri et al. used digital impressions to investigate the depth impact of implants placed 3 and 6 mm subgingivally. The results indicated that the accuracy of digital impressions remained unaffected by the depth of the implant . According to another study conducted by Gimenez-Gonzalez et al., the accuracy of digital impressions was enhanced by subgingivally spaced implants (2 and 4 mm subgingivally). Therefore, implant depth should be taken into account when selecting an ISB design . The material of the scan bodies could also play a role. However, the only evidence available to date suggests that the data acquired by an IOS is more precise as the scanned material becomes more opaque . Therefore, it appears that scanning metallic surfaces provides inaccurate findings . When examining an SB, it is crucial to take into account its design, structure (whether it is composed of one or two pieces), and material (such as titanium and/or polyether-ether-ketone, with a preference for PEEK due to its optimal optical properties) , along with the manufacturing tolerances for the components. In a study comparing the trueness value of scan body materials, the titanium scan body demonstrated superior performance compared to the PEEK scan body. In order to prevent any potential interference, this study used PEEK and titanium scan bodies, both manufactured by the same company, to maintain the shape of the scanned body . We aimed to independently assess the impact of scan body materials on the reliability of scan data. The titanium and PEEK scan bodies utilized in this investigation were comparable. However, the titanium scan bodies had two flat faces. This difference may have resulted in the titanium scan bodies being more accurate in terms of RMS compared to the PEEK ones. Titanium scan bodies also demonstrated broader interquartile ranges for RMS values and a lower within-tolerance value compared to PEEK scan bodies. According to the manufacturer’s recommendations, scanning powder should not be used when scanning titanium scan bodies. Nevertheless, it was found that shiny metal objects exhibited lower scanning precision . Due to the matted surface of TITANIUM scan bodies, the scan results of titanium scan bodies in the present study may be jagged. This lack of precision could potentially restrict the use of titanium scan bodies in clinical practice. Aim of the study : The aim of this in vitro study is to evaluate the effect of saliva on the accuracy of digital dental Implant transfer according to the exposed length of two different materials of Intraoral scan bodies. First null hypothesis is that Saliva has no effect on the accuracy of digital scans obtained using (PEEK) and (TITANIUM) scan bodies. Second null hypothesis is that The exposed length of scan bodies has no effect on the accuracy of digital scans.
Saliva has no effect on the accuracy of digital scans obtained using (PEEK) and (TITANIUM) scan bodies.
The exposed length of scan bodies has no effect on the accuracy of digital scans.
Study setting This experimental study was conducted in the Prosthodontic Department and the CAD/CAM laboratory of the Faculty of Dentistry at Tanta University. Study’s sample size The sample size for this investigation was 48 scans. In this investigation, the power sample size was greater than 80%, and the significance threshold was set at 0.5. The statistical power was 80%, and the confidence interval was 95%. The statistical software SPSS 25 (IBM, Inc., Armonk, NY) was used for all analyses, and a significance level of α = 0.05 was set. The Kolmogorov-Smirnov test was used to determine homoscedasticity, and the Shapiro-Wilk test was used to determine the normality of deviations. The level of statistical significance was set at 0.5. Cast preparation An epoxy resin dental prosthetic cast, designed for a toothless mandibular area, was scanned using an industrial computed tomography device called a bench scanner. This scanning process was done at Ramses Medical Products Factory in Egypt to create a master cast. This is from SEOUL, Korea (DOF freedom HD): 0479. In order to import the STL file into the dental CAD software (Exocad Dental CAD, Exocad, Darmstadt, Germany), the model was exported in Standard Tessellation Language (STL). Printing and cast design Dental prosthetics were digitally fitted to the master cast from first lower molar to the other first molar on the other sideas shown in Fig. a. Subsequently, all of the virtual teeth were extracted, excluding the canines and first molars on both sides. This enabled to accurately allocate the four implant fixture positions at the canines and molars. Exocad design software was utilized at these specific locations to obtain cutbacks for implant fixtures measuring 4.3 mm in diameter and 10.5 mm long, as depicted in graphics b, c. Using a 3D printer (CREALITY 3D printer, HALOT, UK), six resin casts were created, each with the preset placements of four implant fittings. The resin was obtained from China (PROSHAPE MODEL 3D PRINTING405 NM UV RESIN), as depicted in graphics d, a. The 3D-printed casts were washed and cured using a washing and curing machine (ANYCUBIC, China). Four implant fixtures measuring 4.3 mm in diameter and 9 mm in length (C-TECH Implants n.240123, Bologna, Italy) were placed in the right canine, right first molar, left canine, and left first molar areas. Four implant fixtures 1.5 mm had been inserted below the level of the alveolar bone for each mold, as demonstrated in Fig. (b and c). Cast verification and checking The accuracy of the four implant fittings was examined twice using a graded periodontal probe. Four sets of implants were designated on each cast: (A) for the right first molar, (B) for the right canine, (D) for the left first molar, and (C) for the left canine. In order to prevent any rotational or vertical movements, the four healing abutments were carefully placed over the four implant fixtures in each cast using the same screwdriver provided by the implant company. In order to ensure proper placement of the implant fixings and healing abutments, periapical X-rays were obtained for each cast. The CMM (coordinate measuring machine, S/N GS0c/9131, UK) was used to measure six interimplant distances in micrometers at the center of the healing abutment as a reference value. The implant fixtures were positioned precisely at the center of the healing abutment. A coordinate measuring machine (CMM) was used to measure the distances for each of the six casts. The three-dimensional coordinates (x, y, and z) at the centers of the implant platforms were recorded. According to the manufacturer, the CMM had an accuracy of 0.0001 mm, and all measurements were taken using a single operator. In this context, “center of implant position” refers to the spot where the healing abutments, which were secured to the implant fixtures, were located. To determine the exact center of each healing abutment, a CMM probe was used to touch eight different spots around the outer diameter of the abutment. At this point, the flat surface was considered XY. The vertical distances between four healing abutments in the Z-axis were calculated by measuring four locations on the upper surface of each abutment to construct a plane. The PEEK and TITANIUM scan bodies underwent periapical X-rays to verify the precise positioning of the intraoral scan bodies, as shown in Fig. a–d. Placement of intraoral scan bodies over the implant fixtures At the beginning. four PEEK intraoral scan bodies were screwed on the 4 implant fixtures in each cast, The exposed length of the scan bodies was regulated by covering the cast with 2 mm of flexible polyurethane layer which and did a dry scan and wet scan for the cast, then the 2 mm polyurethane layer was replaced with another layer of polyurethane with 4 mm thickness and did another dry and wet scan. These flexible polyurethane layers were fabricated, shaped and molded on each cast of the 3D printed casts after the casts were fabricated and printed with the predetermined implant positions in each cast. The previous protocol was applied on each cast of the six casts (so a total of four digital scans on the each cast using PEEK intraoral scan bodies).Then four TITANIUM intraoral scan bodies were screwed on the 4 implant fixtures in each cast, The exposed length of the scan bodies was regulated by covering the cast with 2 mm of flexible polyurethane layer and did a dry scan and wet scan for the cast, then the 2 mm polyurethane layer was replaced with another layer of polyurethane with 4 mm thickness and did another dry and wet scan. The previous protocol was applied on each cast of the six casts (so a total of four digital scans on the each cast using TITANIUM intraoral scan bodies).So the total number of scans done was 48 scans, as shown in Fig. a, b. A digital luxmeter and a scanning platform consisting of two transparent acrylic boxes of different sizes (10 × 13 × 3 cm and 18 × 18 × 7 cm). The small rectangular box, having a 4 mm diameter hole on its bottom, was affixed to one of the upper corners of the larger box. Each tested cast was attached at the center of the bottom of the small box using utility wax were utilized to conduct 48 scans. The hole of the small box was blocked with wax and artificial saliva was slowly poured from the corner of the small box until the model was completely immersed, and the liquid reached a predetermined height (3 cm from the bottom of the smaller box to make sure complete coverage of the scan bodies), as shown in Fig. a, b,d. The wax which was applied to seal the hole of the smaller box was then removed to allow the artificial saliva to drain slowly into the larger box, leaving the tested cast surface with the attached scan bodies wet with the artificial saliva . Each cast was then scanned again using the same intraoral scanner. scans using an intraoral scanner (MEDIT i700, SEOUL, South Korea), as shown in Fig. c, in both dry and wet circumstances with artificial saliva, on each PEEK intraoral scan body there were a marked reference point fabricated on the top edge of the scan region of the scan body for the standardization of the scans done with the PEEK intraoral scan body, and for the TITANIUM intraoral scan body the center of the screw at the top of the TITANIUM intraoral scan body were taken as a marked reference point. To determine the interimplant distances between the four fixtures, the prior scans were imported into our specialized measuring program (MEDIT DESIGN, version 3.1.0). Then, these measurements were compared with the ones obtained using CMM as a reference, as demonstrated in Images c, d. Data analysis Data from the specified measures were collected, tabulated, and analyzed using IBM SPSS software package version 20.0 (New York: IBM Corp., Armonk, 1980). The Shapiro-Wilk and Kolmogorov-Smirnov tests were used to verify the normality of data. To represent quantitative data, we utilized standard deviation and mean difference. The Student’s t-test was utilized to compare the means between all groups.
This experimental study was conducted in the Prosthodontic Department and the CAD/CAM laboratory of the Faculty of Dentistry at Tanta University.
The sample size for this investigation was 48 scans. In this investigation, the power sample size was greater than 80%, and the significance threshold was set at 0.5. The statistical power was 80%, and the confidence interval was 95%. The statistical software SPSS 25 (IBM, Inc., Armonk, NY) was used for all analyses, and a significance level of α = 0.05 was set. The Kolmogorov-Smirnov test was used to determine homoscedasticity, and the Shapiro-Wilk test was used to determine the normality of deviations. The level of statistical significance was set at 0.5.
An epoxy resin dental prosthetic cast, designed for a toothless mandibular area, was scanned using an industrial computed tomography device called a bench scanner. This scanning process was done at Ramses Medical Products Factory in Egypt to create a master cast. This is from SEOUL, Korea (DOF freedom HD): 0479. In order to import the STL file into the dental CAD software (Exocad Dental CAD, Exocad, Darmstadt, Germany), the model was exported in Standard Tessellation Language (STL).
Dental prosthetics were digitally fitted to the master cast from first lower molar to the other first molar on the other sideas shown in Fig. a. Subsequently, all of the virtual teeth were extracted, excluding the canines and first molars on both sides. This enabled to accurately allocate the four implant fixture positions at the canines and molars. Exocad design software was utilized at these specific locations to obtain cutbacks for implant fixtures measuring 4.3 mm in diameter and 10.5 mm long, as depicted in graphics b, c. Using a 3D printer (CREALITY 3D printer, HALOT, UK), six resin casts were created, each with the preset placements of four implant fittings. The resin was obtained from China (PROSHAPE MODEL 3D PRINTING405 NM UV RESIN), as depicted in graphics d, a. The 3D-printed casts were washed and cured using a washing and curing machine (ANYCUBIC, China). Four implant fixtures measuring 4.3 mm in diameter and 9 mm in length (C-TECH Implants n.240123, Bologna, Italy) were placed in the right canine, right first molar, left canine, and left first molar areas. Four implant fixtures 1.5 mm had been inserted below the level of the alveolar bone for each mold, as demonstrated in Fig. (b and c).
The accuracy of the four implant fittings was examined twice using a graded periodontal probe. Four sets of implants were designated on each cast: (A) for the right first molar, (B) for the right canine, (D) for the left first molar, and (C) for the left canine. In order to prevent any rotational or vertical movements, the four healing abutments were carefully placed over the four implant fixtures in each cast using the same screwdriver provided by the implant company. In order to ensure proper placement of the implant fixings and healing abutments, periapical X-rays were obtained for each cast. The CMM (coordinate measuring machine, S/N GS0c/9131, UK) was used to measure six interimplant distances in micrometers at the center of the healing abutment as a reference value. The implant fixtures were positioned precisely at the center of the healing abutment. A coordinate measuring machine (CMM) was used to measure the distances for each of the six casts. The three-dimensional coordinates (x, y, and z) at the centers of the implant platforms were recorded. According to the manufacturer, the CMM had an accuracy of 0.0001 mm, and all measurements were taken using a single operator. In this context, “center of implant position” refers to the spot where the healing abutments, which were secured to the implant fixtures, were located. To determine the exact center of each healing abutment, a CMM probe was used to touch eight different spots around the outer diameter of the abutment. At this point, the flat surface was considered XY. The vertical distances between four healing abutments in the Z-axis were calculated by measuring four locations on the upper surface of each abutment to construct a plane. The PEEK and TITANIUM scan bodies underwent periapical X-rays to verify the precise positioning of the intraoral scan bodies, as shown in Fig. a–d.
At the beginning. four PEEK intraoral scan bodies were screwed on the 4 implant fixtures in each cast, The exposed length of the scan bodies was regulated by covering the cast with 2 mm of flexible polyurethane layer which and did a dry scan and wet scan for the cast, then the 2 mm polyurethane layer was replaced with another layer of polyurethane with 4 mm thickness and did another dry and wet scan. These flexible polyurethane layers were fabricated, shaped and molded on each cast of the 3D printed casts after the casts were fabricated and printed with the predetermined implant positions in each cast. The previous protocol was applied on each cast of the six casts (so a total of four digital scans on the each cast using PEEK intraoral scan bodies).Then four TITANIUM intraoral scan bodies were screwed on the 4 implant fixtures in each cast, The exposed length of the scan bodies was regulated by covering the cast with 2 mm of flexible polyurethane layer and did a dry scan and wet scan for the cast, then the 2 mm polyurethane layer was replaced with another layer of polyurethane with 4 mm thickness and did another dry and wet scan. The previous protocol was applied on each cast of the six casts (so a total of four digital scans on the each cast using TITANIUM intraoral scan bodies).So the total number of scans done was 48 scans, as shown in Fig. a, b. A digital luxmeter and a scanning platform consisting of two transparent acrylic boxes of different sizes (10 × 13 × 3 cm and 18 × 18 × 7 cm). The small rectangular box, having a 4 mm diameter hole on its bottom, was affixed to one of the upper corners of the larger box. Each tested cast was attached at the center of the bottom of the small box using utility wax were utilized to conduct 48 scans. The hole of the small box was blocked with wax and artificial saliva was slowly poured from the corner of the small box until the model was completely immersed, and the liquid reached a predetermined height (3 cm from the bottom of the smaller box to make sure complete coverage of the scan bodies), as shown in Fig. a, b,d. The wax which was applied to seal the hole of the smaller box was then removed to allow the artificial saliva to drain slowly into the larger box, leaving the tested cast surface with the attached scan bodies wet with the artificial saliva . Each cast was then scanned again using the same intraoral scanner. scans using an intraoral scanner (MEDIT i700, SEOUL, South Korea), as shown in Fig. c, in both dry and wet circumstances with artificial saliva, on each PEEK intraoral scan body there were a marked reference point fabricated on the top edge of the scan region of the scan body for the standardization of the scans done with the PEEK intraoral scan body, and for the TITANIUM intraoral scan body the center of the screw at the top of the TITANIUM intraoral scan body were taken as a marked reference point. To determine the interimplant distances between the four fixtures, the prior scans were imported into our specialized measuring program (MEDIT DESIGN, version 3.1.0). Then, these measurements were compared with the ones obtained using CMM as a reference, as demonstrated in Images c, d.
Data from the specified measures were collected, tabulated, and analyzed using IBM SPSS software package version 20.0 (New York: IBM Corp., Armonk, 1980). The Shapiro-Wilk and Kolmogorov-Smirnov tests were used to verify the normality of data. To represent quantitative data, we utilized standard deviation and mean difference. The Student’s t-test was utilized to compare the means between all groups.
Table ; Fig. a show the effect of the length of the intraoral scan body. There were significant differences in mean values and standard deviation between the distances (measured in micrometers) of the PEEK intraoral scan body with different exposed lengths (long and short) in six interim plant distances. ( p -value < 0.05). Table ; Fig. b show the effect of the material on the intraoral scan body. There were significant differences in the mean values and standard deviation in the distance between the materials of the intraoral scan body, PEEK, and TITANIUM in six interim plant distances ( p -value < 0.05). Table ; Fig. c display the results of an intraoral scan on the body’s wettability. When comparing the wettability of two situations, dry and wet, at six different distances within a plant, there was a statistically significant difference ( p < 0.05) in mean difference and standard deviation in micrometers (see Fig. ).
This in-vitro study measured variables along the x, y, and z-axes to determine the impact of saliva, various intraoral scan body exposed lengths, and material on the accuracy of the digital implant transfer by measuring six interimplant distances in mm from fixed points without superimmpostion. The study found that utilizing a long intraoral scan body resulted in improved accuracy in digital implant transfer compared to using a short one. In addition, this difference was statistically significant ( p < 0.05). These findings are consistent with those of other studies that found a higher trueness value for the longer intraoral scan body compared to the shorter one. Among these studies, Petchmedyai et al., examined the impact of height of the scan body and the methods of alignment in CAD software on the accuracy of digital implant transfer, particularly for varying implant depths. Furthermore, stereolithography was utilized to generate three half-arch implant models, each with a different implant depth. These models were used to simulate three different scan body exposure scenarios: fully exposed, 2/3 exposed, and 1/3 exposed. It was able to replicate the scanned body image using CAD software in order to capture deficiencies and alignment approaches. The use of 3D analysis software allowed for the evaluation of the deviation of simulated implant placements acquired from various scenarios. The 1/4 upper- and lower-part scan body insufficiency utilizing the 1-point alignment method in the 1/3 exposed scan body measured the largest angular and linear deviation (0.237 ± 0.059 degrees, 0.084 ± 0.068 mm) . According to a study by Gómez-Polo et al., digital implant transfer performed better when the scannable portion of the intraoral scan body was raised . In contrast to the results of this study, Sicilia et al. found that the supramucosal height of the scan body did not have an impact on the accuracy of intraoral scans in 17 out of 18 planned comparisons . However, the findings can vary depending on the specifics of the implant scan. The findings of this in-vitro study corroborated those of a study conducted by Gomez-Polo et al., which demonstrated that the accuracy and precision of intraoral scans were impacted by the surface humidity. Specifically, when the surfaces of the two different materials were moistened with artificial saliva, there was a significant difference ( p < 0.05) between them. The in-vitro study found that titanium intraoral scan bodies exhibited significantly higher accuracy ( p < 0.05) compared to PEEK intraoral scan bodies for both types of intraoral scan body materials . This study findings align with a study conducted by Lee et al., they analyzed the differences in terms of the materials used for the scan bodies and found that titanium had a higher trueness value than PEEK. Additionally, there were significant differences between the two intraoral scan bodies in terms of the materials utilized. Titanium scan bodies exhibited a higher trueness value compared to PEEK scan bodies. This finding can be attributed to the dissimilarity in size and shape between the titanium and PEEK scan bodies. Moreover, the titanium scan bodies have two surfaces, whereas the PEEK bodies only have one flat surface . Therefore, the null hypothesis was rejected. Nevertheless, the significant differences may indicate a decrease in scanning precision caused by variations in the surface’s humidity. The distances for all the six casts were measured using a coordinate measuring machine (CMM). It was used to record three dimensional coordinates (x, y and z) at the centers of implant platforms. The accuracy of the CMM was 0.0001 mm (according to manufacturer) and one operator made all measurements. The center of healing abutments which were tightened to the implant fixtures were considered the center of implant position. The center of each healing abutment was located using CMM probe by touching eight points on the circumference of the outer diameter of the healing abutment and then the center was determined. From this point, planar surface was regarded XY. Four points on the upper surface of each healing abutment were measured to form a plane used to calculate the vertical distances between four healing abutments in the Z-axis. The distances (in micrometers) between the implant centers with the reference point were calculated according to the following formula: The distance from the reference point (r) = [12pt]{minimal}
$$\:\:{}^{2}+{y}^{2}+{z}^{2}$$ To obtain this gold standard value with high accuracy, coordinate measuring machines (CMMs) have been introduced in dentistry . CMMs are widely used in industrial applications and are known to be precise and able to be used in the dental field, which requires micro-unit accuracy. This machine contacts the desired point with a probe and records its coordinates. They recognize the shape of the object and measure dimensional length with high accuracy . When a CMM is used with a reliable reference point, the gold standard value can be obtained for accuracy assessment of a digitized model with various scanning modalities.There are other alternatives for coordinate measuring machine(CMM) such as: photogrammetry and sterophotogrammetry. Limitations The process of aligning teeth was carried out digitally using the EXOCAD design software without the use of a maxillary cast as a reference model, as the presence of the antagonist maxillary teeth makes the setting, alignment of the opposing lower teeth more accurate. Limitation of digital scanning due to the absence of teeth. Using of one type of intraoral scanner. The difference in shape and geometery between the two different intraoral scan bodies of the same company.
The process of aligning teeth was carried out digitally using the EXOCAD design software without the use of a maxillary cast as a reference model, as the presence of the antagonist maxillary teeth makes the setting, alignment of the opposing lower teeth more accurate. Limitation of digital scanning due to the absence of teeth. Using of one type of intraoral scanner. The difference in shape and geometery between the two different intraoral scan bodies of the same company.
The use of a longer PEEK or TITANIUM intraoral scan body improved the accuracy of the digital implant transfer results. The accuracy of digital implant transfer using an intraoral scan body improved when performed in a dry setting compared to a moist one. Results of TITANIUM intraoral scan bodies were more reliable and precise compared to the those obtained from the coordinate measuring machine(CMM) than PEEK intraoral scan bodies.
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Effect of Post-transplant Dietary Restriction on Hematopoietic Reconstitution and Maintenance of Reconstitution Capacity of Hematopoietic Stem Cells | 945d9b17-2a3d-4df6-8b3d-f821005f08da | 11762425 | Surgical Procedures, Operative[mh] | Hematopoietic cell transplantation (HCT) offers curative potential for patients with hematological malignancies, red blood cell disorders, bone marrow failure, severe immune deficiency, and certain metabolic disorders . Early completion of post-transplant hematopoiesis can help reduce hospitalization costs and life-threatening complications such as infection and bleeding, thereby improving overall survival rates. Multiple factors, such as hematopoietic stem cell (HSC) functioning and the recipient’s environment, affect post-transplant hematopoiesis . Previous studies have shown that aging of hematopoietic stem cells (HSCs) negatively regulates their homing efficiency and long-term reconstitution capacity . Furthermore, transplanted HSCs require support from the bone marrow microenvironment, known as the niche, and the systemic environment of the recipients . Mouse models have shown that gut microbiota depletion can decrease energy harvesting and impair hematopoiesis after bone marrow transplantation . However, the mechanisms of delayed post-transplant hematopoiesis remain poorly understood. We previously reported that in mouse models of homeostasis, a dietary restriction (DR) of a 30% reduction in daily food intake can reverse the differentiation tendency of HSCs, causing them to increase myeloid differentiation while inhibiting lymphoid differentiation, thereby inhibiting lymphoid hematopoiesis . Long-term DR (6–9 months) can enhance the hematopoietic reconstitution function of aged HSCs . However, in transplantation models, HSCs are pressured to rebuild the entire hematopoietic system. This pressure forces the HSCs that are in a deep quiescent state under steady-state conditions to activate and rapidly proliferate. Myeloablative preconditioning can cause changes, such as intestinal epithelial damage and inflammation in recipients, significantly altering the hematopoietic environment compared with that during homeostasis. Therefore, post-transplant hematopoiesis differs from hematopoiesis under homeostasis . Studying post-transplant hematopoiesis in conjunction with reduced dietary intake will enable better understanding the biological features of HSCs under proliferation pressure and their responses to a metabolically regulated environment. In clinical practice, myeloablative preconditioning often causes nausea, vomiting, appetite loss, severe oral ulcers, gastrointestinal damage and gastroenteritis in patients, often leading to greatly reduced caloric uptake in these patients . However, the impact of these common complications on HSCs and post-transplant hematopoiesis and their potential clinical significance remain unclear. In this study, C57BL/6J mice were irradiated with a lethal X-ray dose followed by bone marrow transplantation. After transplantation, we exposed the recipient mice to either a 30% DR or an ad libitum (AL) diet to study the role of reduced dietary intake on post-transplant hematopoiesis. Post-transplant DR markedly inhibited hematopoietic reconstitution, with both lymphoid and myeloid hematopoiesis significantly delayed in the recipients. However, when the reconstituted bone marrow cells (BMCs) were serially transplanted to secondary or tertiary recipient mice fed the AL diet, the BMCs derived from the mice primarily subjected to post-transplant DR showed a significantly enhanced hematopoietic reconstitution capacity. Furthermore, we transplanted purified HSCs and found that post-transplant DR clearly inhibited HSC expansion, which may explain why hematopoietic reconstitution was delayed in the recipients while post-transplant DR enhanced the hematopoietic reconstitution capacity of the HSCs.
Mice and Diets Three-month-old C57BL/6J mice were obtained from Hunan SJA Laboratory Animal Co., Ltd. and maintained in the animal facilities of Nanchang Royo Biotech under pathogen-free conditions on a 12-h light/12-h dark cycle at 23–25 °C. The mice were housed individually and received a regimen of either an AL diet (fed an unlimited amount of food) or a DR diet (fed daily with an amount of food corresponding to 70% of the amount of food consumed by body weight- and gender-matched mice in the AL group) after bone marrow transplantation. The food amount provided remained constant over the entire DR period. The Animal Experimental Ethical Inspection of Nanchang Royo Biotech Co., Ltd. (RYEI20170513-1) approved all mouse experiments. Transplantation For the primary bone marrow transplantation, 1 million BMCs from Ly5.1 donor mice were injected via tail vein into lethally irradiated (X-ray, 9 Gy) Ly5.2 recipient mice. Bone marrow and peripheral blood analyses were performed at 1 and 4 months post-transplantation. For the secondary transplantation, 8 million BMCs from the post-transplant DR or AL mice along with 2 million BMCs from Ly5.2 mice (competition cells) were injected via tail vein into lethally irradiated Ly5.2 recipient mice. For the tertiary transplantation, 10 million BMCs from the secondary recipients were injected via tail vein into lethally irradiated Ly5.2 recipient mice. Bone marrow and peripheral blood analyses of the secondary and tertiary transplantation were performed 4 months after transplantation. For HSC transplantation, 2000 FACS-purified HSCs from Ly5.1 donor mice were injected via tail vein into lethally irradiated Ly5.2 recipient mice. Bone marrow and peripheral blood analyses were performed 3 weeks after transplantation. Flow Cytometry BMCs were obtained by crushing the hind limbs and pelvises of the donor mice in sterile phosphate-buffered saline and filtered with a 40-μm cell strainer. BMCs were resuspended in red cell lysis buffer and incubated at room temperature for 5 min to lyse the red blood cells. Afterward, the cells were washed, counted, and incubated with flow cytometric antibodies. HSCs were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD150-PerCP-Cy5.5, and CD34-FITC (BD). Common myeloid progenitors (CMPs), megakaryocyte/erythrocyte progenitors (MEPs) and granulocyte/macrophage (GMPs) were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD34-FITC (BD), and CD16/32-BV421. Common lymphoid progenitor cells (CLPs) were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-FITC, c-Kit-APC, Sca-1-PE-Cy7, CD127-PerCP-Cy5.5, and CD135-PE. Pro-B cells were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -CD11b, and -CD3), streptavidin-APC-Cy7, CD45.1-PE, CD19-PerCP-Cy5.5, B200-PE-Cy7, AA4.1-APC, and CD24-FITC. Differentiated BMCs were detected using CD45.1-FITC, B200-PE-Cy7 and CD11b-APC-Cy7. Thymocytes were detected using CD45.1-FITC, CD4-APC and CD8a-PerCP-Cy5.5. Thymocytes and peripheral blood cells were detected using CD45.1-FITC, B200-PE-Cy7, CD11b-APC-Cy7, CD4-APC, and CD8a-PerCP-Cy5.5. For chimerism analyses, HSCs were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD150-PerCP-Cy5.5, and CD34-FITC (BD). Differentiated BMCs were detected using CD45.1-PE, CD45.2-FITC, B200-PE-Cy7, and CD11b-APC-Cy7. Peripheral blood cells were detected using CD45.1-PE, CD45.2-FITC, B200-PE-Cy7, CD11b-APC-Cy7, CD4-APC, and CD8a-PerCP-Cy5.5. After staining, cells were analyzed on a flow cytometer (FACS Canto II; BD). All antibodies were obtained from BioLegend unless otherwise noted. HSC Sorting BMCs were incubated with c-Kit-APC, and c-Kit + cells were enriched using anti-APC magnetic beads and LS columns (Miltenyi Biotec). The positively selected cells were then stained for HSC markers using a lineage cocktail as described in the previous section and CD34-FITC (BD), CD150-PerCP-Cy5.5, Kit-APC, and Sca-1-PE and streptavidin-APC-Cy7. After staining, cells were sorted on a cell sorter (FACS Aria III; BD). All antibodies were obtained from BioLegend unless otherwise noted. Histology Femurs from the post-transplant DR and AL mice were collected and fixed in 4% paraformaldehyde for 24 h. Fixed samples were processed and embedded in paraffin using standard protocols, and 5-μm paraffin sections were prepared. Bone section was assessed by hematoxylin and eosin (H&E) staining. Representative areas were photographed using an OLYMPUSIX73 microscope (Japan). Peripheral Blood Cell Counting Peripheral blood cells were collected from the orbital venous plexus, placed in 5 μL 0.5 M EDTA, and counted on an automated hematology analyzer (Sysmex, XS-500i) according to the manufacturer’s instructions. Fecal Sample Collection Fresh fecal samples were directly collected from each mouse by positioning the microtube in the proximity of the anus of the mouse. Excreted fecal pellets were collected in microtubes on ice and stored at -80 °C within 1 h until DNA isolation for 16 S rRNA gene sequencing. Fecal DNA Isolation Fecal samples were weighed and total DNA was extracted with the DP328 Fecal Genome Extraction Kit (Tiangen Biotech) according to the manufacturer’s instructions. DNA concentration and purity were measured with Nanodrop 2000. 16 S rRNA Gene Sequencing Fecal-sample DNA was extracted using DNA extraction kit. The concentration and purity were measured using the NanoDrop One (Thermo Fisher Scientific, MA, USA). 16 S rRNA gene regions V3-V4 were amplified using universal primers (mice: 338 F 5ʹ-ACTCCTACGGGAGGCAGCA-3ʹ and 806R 5ʹ-GGACTACHVGGGTWTCTAAT-3ʹ) with 12 bp barcode, Primers were synthesized by Invitrogen (Invitrogen, Carlsbad, CA, USA). PCR reactions, containing 25 μl 2x Premix Taq (Takara Biotechnology, Dalian Co. Ltd., China), 1 μl each primer(10 μM) and 3 μl DNA (20 ng/μl) template in a volume of 50 μl, were amplified by thermocycling: 5 min at 94 °C for initialization; 30 cycles of 30 s denaturation at 94 °C, 30 s annealing at 52 °C, and 30 s extension at 72 °C; followed by 10 min final elongation at 72 °C. The PCR instrument was BioRad S1000 (Bio-Rad Laboratory, CA, USA). The length and concentration of the PCR products were detected by 1% agarose gel electrophoresis. PCR products were mixed in equimolar ratios according to the GeneTools Analysis Software (Version4.03.05.0, SynGene). Then, the PCR mixture was purified with EZNA Gel Extraction Kit (Omega, USA). Sequencing libraries were generated using NEBNext ® Ultra™ DNA Library Prep Kit for Illumina ® (New England Biolabs, USA) following the manufacturer’s recommendations and index codes were added. The library quality was assessed on the Qubit 2.0 Fluorometer (Thermo Scientific). Finally, the library was sequenced on an Illumina Nova6000 platform and 250 bp paired-end reads were generated. Sequencing Data Processing Paired-end Raw Reads Quality Control Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the Raw Data by sliding window(-W 4 -M 20). The primers were removed by using cutadapt software ( https://github.com/marcelm/cutadapt/ ) according to the primer information at the beginning and end of the sequence to obtain the paired-end clean reads. Paired-end Clean Reads Assembly Paired-end clean reads were merged using usearch -fastq_mergepairs (V10, http://www.drive5.com/usearch/)accordin g to the relationship of the overlap between the paired-end reads, when at least 16 bp overlap the read generated from the opposite end of the same DNA fragment, the maximum mismatch allowed in overlap region was 5 bp, and the spliced sequences were called Raw Tags. Raw Tags Quality Control Use fastp to remove low-quality sequences, calculate the average quality values for the bases in the sliding window, and then remove the non-conforming sliding windows. The -W parameter specifies the size of the sliding window, which is 4 by default, and the -M parameter is used to specify the required average quality value, which is 20 by default, which is Q20. Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the raw Data by sliding window(-W 4 -M 20) to obtain the paired-end clean tags. OTU Cluster and Species Annotation OTU (operational taxonomic units) is one of the most common terms in microbiology. Sequences analysis was performed by usearch software (V10, http://www.drive5.com/usearch/ ). Sequences with ≥ 97% similarity were assigned to the same OTU. An OTU is thought to possibly represent a species. The most frequently occurring sequence was extracted as a representative sequence for each OTU and was screened for further annotation. Statistical Analysis GraphPad Prism 9.0 software was used for statistical analysis. Unpaired two-tailed Student’s t-tests were used for two-group datasets to calculate p -values. All results are displayed as means ± standard deviation (SD). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001; ns, not significant.
Three-month-old C57BL/6J mice were obtained from Hunan SJA Laboratory Animal Co., Ltd. and maintained in the animal facilities of Nanchang Royo Biotech under pathogen-free conditions on a 12-h light/12-h dark cycle at 23–25 °C. The mice were housed individually and received a regimen of either an AL diet (fed an unlimited amount of food) or a DR diet (fed daily with an amount of food corresponding to 70% of the amount of food consumed by body weight- and gender-matched mice in the AL group) after bone marrow transplantation. The food amount provided remained constant over the entire DR period. The Animal Experimental Ethical Inspection of Nanchang Royo Biotech Co., Ltd. (RYEI20170513-1) approved all mouse experiments.
For the primary bone marrow transplantation, 1 million BMCs from Ly5.1 donor mice were injected via tail vein into lethally irradiated (X-ray, 9 Gy) Ly5.2 recipient mice. Bone marrow and peripheral blood analyses were performed at 1 and 4 months post-transplantation. For the secondary transplantation, 8 million BMCs from the post-transplant DR or AL mice along with 2 million BMCs from Ly5.2 mice (competition cells) were injected via tail vein into lethally irradiated Ly5.2 recipient mice. For the tertiary transplantation, 10 million BMCs from the secondary recipients were injected via tail vein into lethally irradiated Ly5.2 recipient mice. Bone marrow and peripheral blood analyses of the secondary and tertiary transplantation were performed 4 months after transplantation. For HSC transplantation, 2000 FACS-purified HSCs from Ly5.1 donor mice were injected via tail vein into lethally irradiated Ly5.2 recipient mice. Bone marrow and peripheral blood analyses were performed 3 weeks after transplantation.
BMCs were obtained by crushing the hind limbs and pelvises of the donor mice in sterile phosphate-buffered saline and filtered with a 40-μm cell strainer. BMCs were resuspended in red cell lysis buffer and incubated at room temperature for 5 min to lyse the red blood cells. Afterward, the cells were washed, counted, and incubated with flow cytometric antibodies. HSCs were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD150-PerCP-Cy5.5, and CD34-FITC (BD). Common myeloid progenitors (CMPs), megakaryocyte/erythrocyte progenitors (MEPs) and granulocyte/macrophage (GMPs) were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD34-FITC (BD), and CD16/32-BV421. Common lymphoid progenitor cells (CLPs) were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-FITC, c-Kit-APC, Sca-1-PE-Cy7, CD127-PerCP-Cy5.5, and CD135-PE. Pro-B cells were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -CD11b, and -CD3), streptavidin-APC-Cy7, CD45.1-PE, CD19-PerCP-Cy5.5, B200-PE-Cy7, AA4.1-APC, and CD24-FITC. Differentiated BMCs were detected using CD45.1-FITC, B200-PE-Cy7 and CD11b-APC-Cy7. Thymocytes were detected using CD45.1-FITC, CD4-APC and CD8a-PerCP-Cy5.5. Thymocytes and peripheral blood cells were detected using CD45.1-FITC, B200-PE-Cy7, CD11b-APC-Cy7, CD4-APC, and CD8a-PerCP-Cy5.5. For chimerism analyses, HSCs were detected using a lineage cocktail (biotinylated anti-TER-119, -Gr-1, -B220, -CD11b, -CD3, -CD4 and -CD8), streptavidin-APC-Cy7, CD45.1-PE, c-Kit-APC, Sca-1-PE-Cy7, CD150-PerCP-Cy5.5, and CD34-FITC (BD). Differentiated BMCs were detected using CD45.1-PE, CD45.2-FITC, B200-PE-Cy7, and CD11b-APC-Cy7. Peripheral blood cells were detected using CD45.1-PE, CD45.2-FITC, B200-PE-Cy7, CD11b-APC-Cy7, CD4-APC, and CD8a-PerCP-Cy5.5. After staining, cells were analyzed on a flow cytometer (FACS Canto II; BD). All antibodies were obtained from BioLegend unless otherwise noted.
BMCs were incubated with c-Kit-APC, and c-Kit + cells were enriched using anti-APC magnetic beads and LS columns (Miltenyi Biotec). The positively selected cells were then stained for HSC markers using a lineage cocktail as described in the previous section and CD34-FITC (BD), CD150-PerCP-Cy5.5, Kit-APC, and Sca-1-PE and streptavidin-APC-Cy7. After staining, cells were sorted on a cell sorter (FACS Aria III; BD). All antibodies were obtained from BioLegend unless otherwise noted.
Femurs from the post-transplant DR and AL mice were collected and fixed in 4% paraformaldehyde for 24 h. Fixed samples were processed and embedded in paraffin using standard protocols, and 5-μm paraffin sections were prepared. Bone section was assessed by hematoxylin and eosin (H&E) staining. Representative areas were photographed using an OLYMPUSIX73 microscope (Japan).
Peripheral blood cells were collected from the orbital venous plexus, placed in 5 μL 0.5 M EDTA, and counted on an automated hematology analyzer (Sysmex, XS-500i) according to the manufacturer’s instructions.
Fresh fecal samples were directly collected from each mouse by positioning the microtube in the proximity of the anus of the mouse. Excreted fecal pellets were collected in microtubes on ice and stored at -80 °C within 1 h until DNA isolation for 16 S rRNA gene sequencing.
Fecal samples were weighed and total DNA was extracted with the DP328 Fecal Genome Extraction Kit (Tiangen Biotech) according to the manufacturer’s instructions. DNA concentration and purity were measured with Nanodrop 2000.
Fecal-sample DNA was extracted using DNA extraction kit. The concentration and purity were measured using the NanoDrop One (Thermo Fisher Scientific, MA, USA). 16 S rRNA gene regions V3-V4 were amplified using universal primers (mice: 338 F 5ʹ-ACTCCTACGGGAGGCAGCA-3ʹ and 806R 5ʹ-GGACTACHVGGGTWTCTAAT-3ʹ) with 12 bp barcode, Primers were synthesized by Invitrogen (Invitrogen, Carlsbad, CA, USA). PCR reactions, containing 25 μl 2x Premix Taq (Takara Biotechnology, Dalian Co. Ltd., China), 1 μl each primer(10 μM) and 3 μl DNA (20 ng/μl) template in a volume of 50 μl, were amplified by thermocycling: 5 min at 94 °C for initialization; 30 cycles of 30 s denaturation at 94 °C, 30 s annealing at 52 °C, and 30 s extension at 72 °C; followed by 10 min final elongation at 72 °C. The PCR instrument was BioRad S1000 (Bio-Rad Laboratory, CA, USA). The length and concentration of the PCR products were detected by 1% agarose gel electrophoresis. PCR products were mixed in equimolar ratios according to the GeneTools Analysis Software (Version4.03.05.0, SynGene). Then, the PCR mixture was purified with EZNA Gel Extraction Kit (Omega, USA). Sequencing libraries were generated using NEBNext ® Ultra™ DNA Library Prep Kit for Illumina ® (New England Biolabs, USA) following the manufacturer’s recommendations and index codes were added. The library quality was assessed on the Qubit 2.0 Fluorometer (Thermo Scientific). Finally, the library was sequenced on an Illumina Nova6000 platform and 250 bp paired-end reads were generated.
Paired-end Raw Reads Quality Control Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the Raw Data by sliding window(-W 4 -M 20). The primers were removed by using cutadapt software ( https://github.com/marcelm/cutadapt/ ) according to the primer information at the beginning and end of the sequence to obtain the paired-end clean reads. Paired-end Clean Reads Assembly Paired-end clean reads were merged using usearch -fastq_mergepairs (V10, http://www.drive5.com/usearch/)accordin g to the relationship of the overlap between the paired-end reads, when at least 16 bp overlap the read generated from the opposite end of the same DNA fragment, the maximum mismatch allowed in overlap region was 5 bp, and the spliced sequences were called Raw Tags. Raw Tags Quality Control Use fastp to remove low-quality sequences, calculate the average quality values for the bases in the sliding window, and then remove the non-conforming sliding windows. The -W parameter specifies the size of the sliding window, which is 4 by default, and the -M parameter is used to specify the required average quality value, which is 20 by default, which is Q20. Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the raw Data by sliding window(-W 4 -M 20) to obtain the paired-end clean tags.
Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the Raw Data by sliding window(-W 4 -M 20). The primers were removed by using cutadapt software ( https://github.com/marcelm/cutadapt/ ) according to the primer information at the beginning and end of the sequence to obtain the paired-end clean reads.
Paired-end clean reads were merged using usearch -fastq_mergepairs (V10, http://www.drive5.com/usearch/)accordin g to the relationship of the overlap between the paired-end reads, when at least 16 bp overlap the read generated from the opposite end of the same DNA fragment, the maximum mismatch allowed in overlap region was 5 bp, and the spliced sequences were called Raw Tags.
Use fastp to remove low-quality sequences, calculate the average quality values for the bases in the sliding window, and then remove the non-conforming sliding windows. The -W parameter specifies the size of the sliding window, which is 4 by default, and the -M parameter is used to specify the required average quality value, which is 20 by default, which is Q20. Fastp (version 0.14.1, https://github.com/OpenGene/fastp ) was used to control the quality of the raw Data by sliding window(-W 4 -M 20) to obtain the paired-end clean tags.
OTU (operational taxonomic units) is one of the most common terms in microbiology. Sequences analysis was performed by usearch software (V10, http://www.drive5.com/usearch/ ). Sequences with ≥ 97% similarity were assigned to the same OTU. An OTU is thought to possibly represent a species. The most frequently occurring sequence was extracted as a representative sequence for each OTU and was screened for further annotation.
GraphPad Prism 9.0 software was used for statistical analysis. Unpaired two-tailed Student’s t-tests were used for two-group datasets to calculate p -values. All results are displayed as means ± standard deviation (SD). * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001; ns, not significant.
Post-transplant DR Significantly Delayed Hematopoietic Reconstitution To investigate the effect of reduced food intake on post-transplant hematopoiesis, we treated recipient mice with 30% DR directly after bone marrow transplantation (Fig. a). Peripheral blood cell counting at 1 and 4 months after transplantation showed that the numbers of white blood cells (WBCs) and lymphocytes remained markedly low in the DR-recipient mice compared with those of recipient mice fed the AL diet, although the red blood cells and platelets were unaltered (Fig. b–g). Flow cytometry analysis further showed that reconstitution of donor-derived peripheral B and T cells was severely inhibited in DR recipients both at 1 and 4 months post-transplantation, and the regeneration of donor-derived myeloid cells was also significantly delayed in DR recipients 4 months after transplantation (Fig. h–j, Fig. a-d for representative gating strategy). Recipient mice were euthanized for further analysis at 1 and 4 months after transplantation. Bone marrow cellularity was reduced in DR recipients 1 month after transplantation (54.72 ± 4.88 million cells per mouse in DR recipients versus 77.00 ± 12.57 million cells per mouse in AL recipients); however, they became similar in AL- and DR-recipient mice 4 months post-transplantation (Fig. a). H&E staining of femur sections also showed reduced cellularity and increased number of lipids in the bone marrow of DR mice 1 month after transplantation, while the cellularity become similar between both groups with lipids remaining increased in DR recipients 4 months after transplantation (Fig. b). Interestingly, the frequencies of total HSCs (CD150 + CD34 − c-Kit + Sca-1 + lineage − cells), myeloid-biased HSCs (CD150 high HSCs) and lymphoid-biased HSCs (CD150 low HSCs) were significantly lower in DR mice at both 1 and 4 months post-transplantation (Fig. c, d, Fig. a-d). Flow cytometry analysis of BMCs showed that frequencies of CMPs (CD16/32 − CD34 + c-Kit + Sca-1 − lineage − cells), MEPs (CD16/32 − CD34 − c-Kit + Sca-1 − lineage − cells) and GMPs (CD16/32 + CD34 + c-Kit + Sca-1 − lineage − cells) were significantly lower in DR recipients at 1 month after transplantation, and the frequency of CMPs remained significantly lower at 4 months after transplantation (Fig. e–g, Fig. e-h). Consistently, the frequencies of downstream myeloid cells (CD11b + BMCs) were also reduced in DR recipients 1 month after transplantation, but became similar in the AL- and DR-fed mice at 4 months after transplantation, indicating significantly delayed myeloid lineage reconstitution (Fig. h). The lymphoid lineages, including CLPs (IL-7Rα + Flt3 + c-Kit mid/low Sca-1 mid/low lineage − cells), pro-B cells (B220 + CD24 + AA4.1 + TER-119 − Gr-1 − CD11b − CD3 − cells), and B cells in bone marrow (B220 low immature B cells) also showed greatly reduced frequencies in DR recipients at 1 and 4 months after transplantation (Fig. i–n, Fig. i-t). Consistent with the significant inhibition of lymphoid cells in the peripheral blood and bone marrow, cellularity of lymphoid organs, including the thymus and spleen, remained significantly lower in DR recipients at 1 and 4 months after transplantation (Fig. o, p). Flow cytometry analysis further showed that frequencies of donor-derived cells were significantly lower in these organs in DR recipients (Fig. q–t). These results indicated that post-transplant DR significantly inhibited both myeloid and lymphoid hematopoietic reconstitution. Post-transplant DR Improved the Reconstitution Potential of BMCs in Serial Transplantations Post-transplant energy restriction by DR severely impaired hematopoietic regeneration in the recipient mice. To investigate the effect of post-transplant DR on the reconstitution potential of regenerated BMCs in recipient mice, mice were fed an AL or DR diet after transplantation, and the regenerated BMCs were harvested 1 month after transplantation and serially transplanted along with competitor cells into secondary and tertiary recipient mice fed AL after transplantation (Fig. a). In the secondary transplantation, DR-recipient donor-derived bone marrow showed significantly higher outputs of peripheral WBCs, B cells , and myeloid cells at 4 months after the secondary transplantation in both the peripheral blood and bone marrow (Fig. b, c). Interestingly, DR-derived HSCs also showed significantly higher chimerism (Fig. d). In the tertiary transplantation, DR-recipient donor-derived bone marrow was superior in the post-transplant hematopoietic reconstitution with greatly enhanced outputs of peripheral WBCs, lymphocytes, and myeloid cells in the peripheral blood and bone marrow (Fig. e, f, h, i, Fig. a-d). DR-derived HSCs also exhibited significantly higher chimerism than that of AL-derived HSCs, which was nearly undetectable after tertiary transplantation (Fig. g, j, Fig. e-f). Because the HSC frequency in the reconstituted bone marrow after primary transplantation was significantly lower in DR recipients than in AL recipients (Fig. c), the results indicate that compared with AL feeding, post-transplant DR for 1 month enhanced the regeneration potential of the reconstituted bone marrow. Thus, we inferred that short-term post-transplant DR (for 1 month) strengthened the regeneration potential of the reconstituted HSCs. We previously showed that longer term DR had a stronger effect on improving the reconstitution potential of HSCs in aging mice under homeostasis conditions . To investigate the effect of a longer post-transplant DR on the reconstitution potential of regenerated BMCs in recipient mice, mice were fed either an AL or DR diet after transplantation. The regenerated BMCs were then harvested 4 months after transplantation and serially transplanted along with competitor cells into secondary and tertiary recipient mice, which were fed AL after transplantation (Fig. a). Surprisingly, the longer post-transplantation DR (4 months) did not improve the reconstitution of WBCs, lymphocytes or myeloid cells in the peripheral blood or bone marrow in the secondary transplantation (Fig. b, c). DR-recipient donor-derived BMCs even showed significantly reduced chimerism in HSCs compared with that of the AL-recipient donor-derived BMCs (Fig. d). In the tertiary transplantation, DR-recipient donor-derived bone marrow showed higher outputs of WBCs, lymphocytes, and myeloid cells in the peripheral blood and bone marrow (Fig. e, f, h, i, Fig. a-d). The HSC chimerism from the DR-derived donors was also significantly increased compared with that from AL-derived donors (Fig. g, j, Fig. e-f). These results indicated that short-term DR (1 month) after transplantation significantly improved the reconstitution of WBCs, lymphocytes, and myeloid cells in the peripheral blood or bone marrow, as well as HSCs, in the secondary and tertiary transplantations. However, long-term DR (4 months) after transplantation differed from long-term DR under steady-state conditions, showing no significant improvement in the secondary transplantation but significantly improving reconstitution in the tertiary transplantation. Post-transplant DR Significantly Inhibited HSC Expansion and Delayed Hematopoietic Reconstitution To further investigate the underlying mechanism by which post-transplant DR protects the regeneration activities of HSCs while delaying post-transplant hematopoietic reconstitution, pure HSCs were sorted by FACS and transplanted at 2000 cells/mouse into recipient mice fed AL or DR after transplantation. Hematopoietic reconstitution was analyzed 3 weeks after transplantation (Fig. a). Bone marrow cellularity was mildly but significantly reduced in the DR-recipient mice (Fig. b). The number of donor-derived HSCs was 608,300 per mouse, representing a 304-fold expansion compared with that of the 2000 HSCs initially transplanted in the AL recipients. Conversely, the DR recipients’ HSC count was only 33,900 per mouse, indicating a 17-fold expansion in these mice at this time point, suggesting that post-transplant DR strongly inhibited HSC expansion (Fig. c, d, Fig. a-b). Consistently, the numbers of B cells and myeloid cells in the bone marrow were significantly lower in DR recipients (Fig. e–g, Fig. c-d). The peripheral blood of DR recipients contained markedly fewer WBCs, donor-derived B cells, myeloid cells, CD4 + T cells, and CD8 + T cells (Fig. h–k, Fig. e-f). These results indicated that post-transplant DR significantly inhibited HSC expansion and delayed hematopoietic reconstitution. Post-transplant DR Significantly Altered the Gut Microbiotas of the Recipient Mice We previously reported that increased Bacteroidaceae mediated lymphopoiesis inhibition in DR mice under homeostasis conditions . We also found that Lactobacillales conferred a protective effect on chemotherapy-induced intestinal toxicity by downregulating inflammatory responses . Furthermore, studies have shown that the gut microbiota plays important roles in hematopoiesis after bone marrow transplantation . To investigate the effect of post-transplantation DR on the gut microbiota, the recipient mice were fed AL or a DR diet for 4 months after bone marrow transplantation, and their feces were collected for 16 S rRNA gene deep-sequencing (Illumina; 250-bp paired-end). Principal coordinate analysis based on Bray-Curtis distance showed that DR significantly changed the overall structure of the gut microbiota (Fig. a). However, Chao1 and Shannon indices were not significantly different between DR and AL mice, indicating that microbial diversity (alpha diversity) was not altered by post-transplant DR (Fig. b). These results indicated that DR significantly altered the structure of the gut microbiota without affecting its diversity, including species richness and evenness. Furthermore, analysis of the gut microbiota composition at the family level showed higher percentages of pathogenic bacteria (e.g., Betaproteobacterales and Enterobacteriales) in DR-recipient mice (Fig. c). We then used linear discriminant analysis (LDA) scores > 3.5 and looked at the top 18 bacteria in each direction. Bacteroidaceae, Bacteroides, Lactobacillus , Lactobacillaceae, and Lactobacillales were among the top 5 enriched taxa in DR mice compared with the AL mice (Fig. d). Statistical analysis further indicated significantly increased relative abundances of Bacteroidaceae and Lactobacillales in the gut microbiotas of the DR-recipient mice (Fig. e, f). Conversely, DR decreased the relative abundances of Erysipelotrichaceae, Prevotellaceae and Rikenellaceae in the gut microbiotas of the DR-recipient mice (Fig. g–i). The results indicate that post-transplant DR increased the relative abundance of anti-inflammatory bacteria in the gut of mice, including Bacteroidaceae and Lactobacillaceae, and decreased the relative abundance of pro-inflammatory bacteria, including Erysipelotrichaceae, Prevotellaceae, and Rikenellaceae.
To investigate the effect of reduced food intake on post-transplant hematopoiesis, we treated recipient mice with 30% DR directly after bone marrow transplantation (Fig. a). Peripheral blood cell counting at 1 and 4 months after transplantation showed that the numbers of white blood cells (WBCs) and lymphocytes remained markedly low in the DR-recipient mice compared with those of recipient mice fed the AL diet, although the red blood cells and platelets were unaltered (Fig. b–g). Flow cytometry analysis further showed that reconstitution of donor-derived peripheral B and T cells was severely inhibited in DR recipients both at 1 and 4 months post-transplantation, and the regeneration of donor-derived myeloid cells was also significantly delayed in DR recipients 4 months after transplantation (Fig. h–j, Fig. a-d for representative gating strategy). Recipient mice were euthanized for further analysis at 1 and 4 months after transplantation. Bone marrow cellularity was reduced in DR recipients 1 month after transplantation (54.72 ± 4.88 million cells per mouse in DR recipients versus 77.00 ± 12.57 million cells per mouse in AL recipients); however, they became similar in AL- and DR-recipient mice 4 months post-transplantation (Fig. a). H&E staining of femur sections also showed reduced cellularity and increased number of lipids in the bone marrow of DR mice 1 month after transplantation, while the cellularity become similar between both groups with lipids remaining increased in DR recipients 4 months after transplantation (Fig. b). Interestingly, the frequencies of total HSCs (CD150 + CD34 − c-Kit + Sca-1 + lineage − cells), myeloid-biased HSCs (CD150 high HSCs) and lymphoid-biased HSCs (CD150 low HSCs) were significantly lower in DR mice at both 1 and 4 months post-transplantation (Fig. c, d, Fig. a-d). Flow cytometry analysis of BMCs showed that frequencies of CMPs (CD16/32 − CD34 + c-Kit + Sca-1 − lineage − cells), MEPs (CD16/32 − CD34 − c-Kit + Sca-1 − lineage − cells) and GMPs (CD16/32 + CD34 + c-Kit + Sca-1 − lineage − cells) were significantly lower in DR recipients at 1 month after transplantation, and the frequency of CMPs remained significantly lower at 4 months after transplantation (Fig. e–g, Fig. e-h). Consistently, the frequencies of downstream myeloid cells (CD11b + BMCs) were also reduced in DR recipients 1 month after transplantation, but became similar in the AL- and DR-fed mice at 4 months after transplantation, indicating significantly delayed myeloid lineage reconstitution (Fig. h). The lymphoid lineages, including CLPs (IL-7Rα + Flt3 + c-Kit mid/low Sca-1 mid/low lineage − cells), pro-B cells (B220 + CD24 + AA4.1 + TER-119 − Gr-1 − CD11b − CD3 − cells), and B cells in bone marrow (B220 low immature B cells) also showed greatly reduced frequencies in DR recipients at 1 and 4 months after transplantation (Fig. i–n, Fig. i-t). Consistent with the significant inhibition of lymphoid cells in the peripheral blood and bone marrow, cellularity of lymphoid organs, including the thymus and spleen, remained significantly lower in DR recipients at 1 and 4 months after transplantation (Fig. o, p). Flow cytometry analysis further showed that frequencies of donor-derived cells were significantly lower in these organs in DR recipients (Fig. q–t). These results indicated that post-transplant DR significantly inhibited both myeloid and lymphoid hematopoietic reconstitution.
Post-transplant energy restriction by DR severely impaired hematopoietic regeneration in the recipient mice. To investigate the effect of post-transplant DR on the reconstitution potential of regenerated BMCs in recipient mice, mice were fed an AL or DR diet after transplantation, and the regenerated BMCs were harvested 1 month after transplantation and serially transplanted along with competitor cells into secondary and tertiary recipient mice fed AL after transplantation (Fig. a). In the secondary transplantation, DR-recipient donor-derived bone marrow showed significantly higher outputs of peripheral WBCs, B cells , and myeloid cells at 4 months after the secondary transplantation in both the peripheral blood and bone marrow (Fig. b, c). Interestingly, DR-derived HSCs also showed significantly higher chimerism (Fig. d). In the tertiary transplantation, DR-recipient donor-derived bone marrow was superior in the post-transplant hematopoietic reconstitution with greatly enhanced outputs of peripheral WBCs, lymphocytes, and myeloid cells in the peripheral blood and bone marrow (Fig. e, f, h, i, Fig. a-d). DR-derived HSCs also exhibited significantly higher chimerism than that of AL-derived HSCs, which was nearly undetectable after tertiary transplantation (Fig. g, j, Fig. e-f). Because the HSC frequency in the reconstituted bone marrow after primary transplantation was significantly lower in DR recipients than in AL recipients (Fig. c), the results indicate that compared with AL feeding, post-transplant DR for 1 month enhanced the regeneration potential of the reconstituted bone marrow. Thus, we inferred that short-term post-transplant DR (for 1 month) strengthened the regeneration potential of the reconstituted HSCs. We previously showed that longer term DR had a stronger effect on improving the reconstitution potential of HSCs in aging mice under homeostasis conditions . To investigate the effect of a longer post-transplant DR on the reconstitution potential of regenerated BMCs in recipient mice, mice were fed either an AL or DR diet after transplantation. The regenerated BMCs were then harvested 4 months after transplantation and serially transplanted along with competitor cells into secondary and tertiary recipient mice, which were fed AL after transplantation (Fig. a). Surprisingly, the longer post-transplantation DR (4 months) did not improve the reconstitution of WBCs, lymphocytes or myeloid cells in the peripheral blood or bone marrow in the secondary transplantation (Fig. b, c). DR-recipient donor-derived BMCs even showed significantly reduced chimerism in HSCs compared with that of the AL-recipient donor-derived BMCs (Fig. d). In the tertiary transplantation, DR-recipient donor-derived bone marrow showed higher outputs of WBCs, lymphocytes, and myeloid cells in the peripheral blood and bone marrow (Fig. e, f, h, i, Fig. a-d). The HSC chimerism from the DR-derived donors was also significantly increased compared with that from AL-derived donors (Fig. g, j, Fig. e-f). These results indicated that short-term DR (1 month) after transplantation significantly improved the reconstitution of WBCs, lymphocytes, and myeloid cells in the peripheral blood or bone marrow, as well as HSCs, in the secondary and tertiary transplantations. However, long-term DR (4 months) after transplantation differed from long-term DR under steady-state conditions, showing no significant improvement in the secondary transplantation but significantly improving reconstitution in the tertiary transplantation.
To further investigate the underlying mechanism by which post-transplant DR protects the regeneration activities of HSCs while delaying post-transplant hematopoietic reconstitution, pure HSCs were sorted by FACS and transplanted at 2000 cells/mouse into recipient mice fed AL or DR after transplantation. Hematopoietic reconstitution was analyzed 3 weeks after transplantation (Fig. a). Bone marrow cellularity was mildly but significantly reduced in the DR-recipient mice (Fig. b). The number of donor-derived HSCs was 608,300 per mouse, representing a 304-fold expansion compared with that of the 2000 HSCs initially transplanted in the AL recipients. Conversely, the DR recipients’ HSC count was only 33,900 per mouse, indicating a 17-fold expansion in these mice at this time point, suggesting that post-transplant DR strongly inhibited HSC expansion (Fig. c, d, Fig. a-b). Consistently, the numbers of B cells and myeloid cells in the bone marrow were significantly lower in DR recipients (Fig. e–g, Fig. c-d). The peripheral blood of DR recipients contained markedly fewer WBCs, donor-derived B cells, myeloid cells, CD4 + T cells, and CD8 + T cells (Fig. h–k, Fig. e-f). These results indicated that post-transplant DR significantly inhibited HSC expansion and delayed hematopoietic reconstitution.
We previously reported that increased Bacteroidaceae mediated lymphopoiesis inhibition in DR mice under homeostasis conditions . We also found that Lactobacillales conferred a protective effect on chemotherapy-induced intestinal toxicity by downregulating inflammatory responses . Furthermore, studies have shown that the gut microbiota plays important roles in hematopoiesis after bone marrow transplantation . To investigate the effect of post-transplantation DR on the gut microbiota, the recipient mice were fed AL or a DR diet for 4 months after bone marrow transplantation, and their feces were collected for 16 S rRNA gene deep-sequencing (Illumina; 250-bp paired-end). Principal coordinate analysis based on Bray-Curtis distance showed that DR significantly changed the overall structure of the gut microbiota (Fig. a). However, Chao1 and Shannon indices were not significantly different between DR and AL mice, indicating that microbial diversity (alpha diversity) was not altered by post-transplant DR (Fig. b). These results indicated that DR significantly altered the structure of the gut microbiota without affecting its diversity, including species richness and evenness. Furthermore, analysis of the gut microbiota composition at the family level showed higher percentages of pathogenic bacteria (e.g., Betaproteobacterales and Enterobacteriales) in DR-recipient mice (Fig. c). We then used linear discriminant analysis (LDA) scores > 3.5 and looked at the top 18 bacteria in each direction. Bacteroidaceae, Bacteroides, Lactobacillus , Lactobacillaceae, and Lactobacillales were among the top 5 enriched taxa in DR mice compared with the AL mice (Fig. d). Statistical analysis further indicated significantly increased relative abundances of Bacteroidaceae and Lactobacillales in the gut microbiotas of the DR-recipient mice (Fig. e, f). Conversely, DR decreased the relative abundances of Erysipelotrichaceae, Prevotellaceae and Rikenellaceae in the gut microbiotas of the DR-recipient mice (Fig. g–i). The results indicate that post-transplant DR increased the relative abundance of anti-inflammatory bacteria in the gut of mice, including Bacteroidaceae and Lactobacillaceae, and decreased the relative abundance of pro-inflammatory bacteria, including Erysipelotrichaceae, Prevotellaceae, and Rikenellaceae.
In this study, we, for the first time, systematically investigated the role of post-transplant DR on hematopoietic reconstitution and HSC function after HCT. Post-transplant DR significantly inhibited hematopoietic reconstitution, including lymphopoiesis and myelopoiesis. However, post-transplant DR significantly protected the regeneration capacity of HSCs. Furthermore, the transplantation assay with pure HSCs showed that the HSC pool greatly expanded after transplantation under AL conditions, reflecting the physiological behavior of HSCs after transplantation. This may explain the decreased HSC regeneration capacity in serial transplantations. However, DR significantly inhibited HSC expansion after transplantation, which partially explained its protective effect on HSC function. Previous studies have reported that the gut microbiota plays an important role in post-transplant hematopoiesis . We and other researchers have conducted extensive studies on gut microbiota, DR, and HSCs. Our early studies reported that DR under steady-state conditions can delay and rejuvenate HSC aging and improve regenerative functions of HSCs. Subsequently, we found that short-term DR before MTX or 5-FU chemotherapy can significantly alter the composition of the gut microbiota, such as promoting the upregulation of beneficial bacteria like Lactobacillus and inhibiting opportunistic pathogens like Proteus mirabilis and Enterococcus, thereby protecting intestinal epithelial cells and blocking bacterial translocation and corresponding lethal infections . We also reported that DR under steady-state conditions can increase intestinal Bacteroides and inhibiting lymphoid hematopoiesis by promoting butyrate utilization . DR in aging mice can significantly alter their gut microbiota composition, making it more similar to that of young mice. Numerous previous studies have also revealed the important role of gut microbiota in hematopoiesis. Zhang et al. reported that gut microbiota is crucial for hematopoietic recovery after 5-FU chemotherapy or radiotherapy, as depletion of the gut microbiota can significantly delay hematopoietic recovery . Huang et al. found that gut microbiota is crucial for HSC aging, with the gut microbiota of aging mice promoting HSC aging, while the gut microbiota of young mice can reverse HSC aging in elderly mice . In allogeneic hematopoietic stem cell transplantation (allo-HSCT), gut microbiota also plays a key role in the development of graft-versus-host disease . Furthermore, gut microbiota plays a critical role in food breakdown and energy absorption, which are vital for hematopoietic recovery after transplantation. However, these studies have not explored the effects of DR on gut microbiota, HSCs, and hematopoietic recovery after HSCT. The current study provides preliminary and worthy exploration in this area, suggesting that DR after HSCT can alter the gut microbiota composition and reduce pro-inflammatory bacteria. Although we have not yet conducted in-depth studies on the causal relationship between these changes in gut microbiota and HSC function and hematopoietic recovery after transplantation, we provide interesting preliminary findings that can be further explored in future research. We found that post-transplant DR significantly changed the gut microbiota composition. We previously reported that increased intestinal Bacteroides is a major factor mediating lymphopoiesis inhibition by DR. Our results showed that post-transplant DR significantly increased intestinal Bacteroides , which may help suppress hematopoietic reconstitution via DR after transplantation. Erysipelotrichaceae, Prevotellaceae and Rikenellaceae are reported to help promote inflammation. We and others have reported that DR can significantly suppress inflammatory responses . Specifically, short-term DR before methotrexate treatment increased Lactobacillales in the gut, which ameliorated intestinal inflammation and improved survival . In the current study, we showed that post-transplant DR significantly regulated inflammatory-related bacterial taxa, including increased Lactobacillales and decreased Erysipelotrichaceae, Prevotellaceae and Rikenellaceae, which may inhibit inflammatory responses after transplantation, thus protecting HSCs. However, patients undergoing HCT are exposed to various factors that can disrupt the gut microbiota before transplantation, during the peri-transplant period, and after transplantation, including chemotherapy, antibiotics, and dietary changes. These disruptions result in changes in gut microbiota profile characterized by a loss of microbial diversity, dysbiosis, and the expansion of opportunistic pathogens such as Enterococcus, Streptococcus, or Proteus compared to healthy individuals . In contrast, in the bone marrow transplantation mouse model, changes in the gut microbiota are only slight. A major reason of the difference is considered to be patients frequently use antibiotics, whereas antibiotics are not commonly used in mice . More clinical studies are needed to systematically analyze HSCs and their downstream cells in patients undergoing DR and to explore the underlying mechanisms. However, there are practical difficulties in administering DR in patients and collecting samples, making comprehensive analysis unlikely to be achievable in the short term. The significance of this study lies in its systematic investigation of the effects of post-transplant DR on the hematopoietic system, particularly on HSCs, from short-term to long-term perspectives at both phenotypic and cellular levels. Moreover, due to differences between humans and mice in metabolism, immune response, and gut microbiota, it is currently challenging to directly apply these findings to clinical practice, necessitating more in-depth translational research. We previously reported that long-term DR (6–9 months) under homeostasis conditions significantly inhibited lymphoid hematopoiesis and promoted myeloid hematopoiesis. However, when transplanted into AL-recipient mice, DR-donor-derived HSCs showed a significantly enhanced reconstitution capacity, especially in the lymphoid lineage, indicating rescue of the HSC aging phenotype, including myeloid skewing and functional decline. In the current study, we investigated the role of DR in post-transplant hematopoiesis. Unlike hematopoiesis under homeostasis conditions, in HCT, the original hematopoietic system in recipients must be cleared by myeloablation treatments. Therefore, the donor-derived hematopoietic cells are challenged with rebuilding the hematopoietic system when transplanted into recipients. We found that post-transplant DR significantly inhibited lymphoid hematopoiesis and inhibited myeloid hematopoiesis in recipients. Moreover, the frequencies of both myeloid-biased (CD150 hi ) and lymphoid-biased (CD150 lo ) HSCs were significantly reduced, as were the frequencies of myeloid progenitor cells (CMPs, GMPs, and MEPs) and lymphoid progenitor cells (CLPs and pro-Bs). The delayed reconstitution of the entire hematopoietic system by DR under post-transplant conditions differed from that of enhanced myeloid hematopoiesis by DR under homeostasis conditions. That DR significantly and comprehensively delays hematopoietic reconstruction has important significance for clinical practice. Patients who receive HCT often suffer from anorexia, aphthous ulcers and gastrointestinal damage due to the toxicity induced by the conditioning regimen, which reduces their appetite and weakens their absorption and digestive functions. Our results indicate that post-transplant diet and calorie management greatly affect hematopoietic reconstruction, which may play crucial roles in transplantation-related complications, such as infections. Therefore, our findings may have important implications for clinical work and should draw attention to post-transplant calorie management. Post-transplant DR significantly protected and improved HSC functions, although it significantly delayed hematopoietic reconstruction. Sequentially transplanting BMCs from recipients after AL or DR for 1 month, along with competitive BMCs from mice without transplantation at a 4:1 ratio, into AL-recipient mice greatly reduced the serially transplanted HSCs’ ability to compete for hematopoietic reconstruction compared with that of competing cells (the chimerism of donor-derived cells in peripheral blood was only 3.26% in the 2nd treatment and 0.92% in the 3rd treatment). This indicated that the HSCs’ potential for hematopoietic reconstruction was significantly reduced after transplantation. Interestingly, the chimerism was significantly higher in DR-donor-derived cells than in AL-donor-derived cells. These results indicate that short-term DR after transplantation significantly preserved and improved the regeneration capacity of transplanted HSCs. Mechanistically, the transplantation experiment with pure HSCs showed that the transplanted HSCs in the AL-recipient mice expanded by 304-fold at 3 weeks of transplantation, whereas they expanded only 17-fold in the DR recipients. These results further show that DR significantly inhibited HSC proliferation, even under the great pressure of hematopoietic reconstruction, which we speculate may be an important mechanism by which DR preserves HSC function. The results of long-term (4 months) and short-term (1 month) DR in the secondary transplantation group differed. After transplanting BMCs from recipients 4 months after AL or DR at a 4:1 ratio with competitive BMCs from untransplanted mice into AL-recipient mice, the number of chimeric cells derived from AL mice was higher than that from mice that underwent serial transplantation 1 month after primary transplantation. At this timepoint, DR for 4 months after transplantation did not improve the chimerism compared with that of the AL mice. However, in the tertiary transplantation, DR-donor-derived chimerism was higher than was AL-donor-derived chimerism. Analysis of the BMCs harvested at 1 and 4 months post-transplantation suggested that serially transplanting the HSCs within 1 month impaired the reconstitution potential of the HSCs more strongly than did transplantation within 4 months, whereas DR did not appear to affect this. This may be because in addition to hematopoietic reconstruction pressure, HSCs are also affected by a strong inflammatory response in the recipient’s body early after transplantation, which may also harm the HSCs’ survival and functioning. We and others have reported that DR can reduce inflammation; therefore, it may protect HSCs by inhibiting proliferation and inflammation at earlier times after transplantation, which requires further study. Previous studies have shown that in the early stages post-HSCT, patients release large amounts of inflammatory cytokines , and HSCs can sense inflammatory stimuli, proliferating to produce more defense cells . Interestingly, we and others have reported that DR can reduce inflammation . Therefore, we speculate that post-transplant DR in the early stages reduces inflammation, thus reducing HSC proliferation and maintaining HSC function. This hypothesis requires further research. At present, in situ bone tissue engineering is garnering significant interest. For example, Krasilnikova et al. have reported for repairing bone tissue defects by isolating autologous osteoblasts, bone marrow stromal cells, or chondrocytes, culturing and expanding them in vitro, then seeding them onto synthetic scaffolds, and implanting them into bone defect sites . Our research suggests that DR during hematopoietic system regeneration can inhibit the repair of the bone marrow microenvironment and impair HSC reconstruction, thereby significantly delaying hematopoietic recovery. Whether similar phenotypes can be replicated in other regenerative medicine models is a very interesting question that could have important implications for improving the regeneration of corresponding tissues. This will require further research to confirm. In summary, our results suggest that even under the great pressure of hematopoietic reconstruction, DR significantly inhibited HSC expansion, which protected the reconstitution capacity of HSCs. However, DR also suppressed and delayed post-transplant hematopoiesis. Because reduced food intake and problems with digestion and absorption are common in patients undergoing HCT, our findings show that caloric management after transplantation deserves attention.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Kollaborationen bei kinderanästhesiologischen Publikationen im D-A-CH-Raum | 002fc429-ae36-472f-ba4c-d91c9cad4ce0 | 11446977 | Pediatrics[mh] | Wissenschaftliche Arbeit ist essenziell zur Evidenzgenerierung, für die Entwicklung von Leitlinien sowie für die kontinuierliche Aus- und Weiterbildung und trägt damit entscheidend zur Weiterentwicklung eines Fachgebietes bei . Durch die Veröffentlichung wissenschaftlicher Arbeiten in Fachzeitschriften werden Forschungsergebnisse und andere für das Fachgebiet relevante Inhalte wie aktuelle Therapieempfehlungen kommuniziert und verbreitet. Kollaborationen zwischen Institutionen sind hierfür ein wichtiger Impulsgeber . Dies trifft auch auf die Kinderanästhesiologie zu, wo in vielen Bereichen ein geringes Evidenzlevel besteht. Diese Evidenzlücken zu schließen, gelingt zunehmend durch internationale Kollaborationen, wie beispielsweise bei den rezent publizierten, großen multizentrischen Studien APRICOT oder NECTARINE . Die durch die Fachgesellschaften wie den Wissenschaftlichen Arbeitskreis Kinderanästhesie der Deutschen Gesellschaft für Anästhesiologie und Intensivmedizin (DGAI), die European Society of Paediatric Anaesthesiology oder die World Federation of Societies of Anesthesiologists etablierten Vernetzungen spielen dabei heute eine wesentliche Rolle . Dies wird auch durch eine kürzlich veröffentlichte szientometrische Analyse von weltweiten Publikationen in der Kinderanästhesiologie der letzten zwei Dekaden unterstützt: Bei einem generellen Anstieg der Publikationsaktivität – analog zu einem Anstieg der Anzahl der Publikationen im gesamten Fachgebiet der Anästhesiologie – war v. a. das überproportionale Wachstum an internationalen Kollaborationen in der Kinderanästhesiologie auffällig . Wie sich die Publikationsaktivität und der Vernetzungsgrad in der Kinderanästhesiologie innerhalb von Deutschland, Österreich und der Schweiz (D-A-CH) entwickelt haben, wo zuletzt von einem Rückgang der Originalarbeiten in der Anästhesiologie berichtet wurde , ist bislang unbekannt. Mit der Hypothese, dass die Zahl der kinderanästhesiologischen Publikationen im D‑A-CH-Raum zugenommen und sich v. a. das Kollaborationsverhalten über die letzten beiden Jahrzehnte deutlich ausgeweitet hat, war es das Ziel dieser szientometrischen Arbeit, die Publikationsaktivität und -dynamik sowie den nationalen und internationalen Vernetzungsgrad zu analysieren. Wir führten eine szientometrische Analyse durch, welche kinderbezogene Publikationen mit anästhesiologischer Autorenschaft aus den D‑A-CH-Staaten der Jahre 2001 bis 2020 untersuchte. Erfasst wurden alle Artikeltypen von Publikationen in gelisteten Fachzeitschriften. Das angewandte Abfrageschema bedingt die Inklusion aller 5 Säulen der Anästhesiologie, wobei sämtliche inkludierten Publikationen unter dem Oberbegriff „Publikationen in der Kinderanästhesiologie“ subsumiert wurden. Da keine persönlichen oder sensiblen Daten verarbeitet wurden, war weder ein Ethikvotum noch eine Studienregistrierung erforderlich. Datengrundlage Als Grundlage diente die Datenbank und anschließende Datenverarbeitung aus der globalen Publikationsanalyse der Kinderanästhesiologie von Miller et al. , welche Abfragen von Web of Science und PubMed mit Stichtag 04.10.2021 kombinierte. Diese Quellen gelten als die beiden bedeutendsten Publikationsdatenbanken im medizinischen Bereich , wobei Web of Science aufgrund vollständigerer Datensätze als primäre Datenquelle genutzt und fehlende Daten mittels PubMed ergänzt wurden . Um kinderanästhesiologische Publikationen bestmöglich zu identifizieren, kombinierte die Suchabfrage 2 Parameter: Einerseits wurde die Zugehörigkeit mindestens einer Autorenschaft zu einer anästhesiologischen Institution erfasst, indem der Stamm des Wortes Anästhesiologie im Zugehörigkeitsfeld („affiliation field“) abgefragt wurde (beispielsweise durch „anaest*“, „anest*“ plus sprachbedingt mögliche Präfixe wie „Kinder-*“) . Andererseits wurden kinderbezogene Publikationen durch Stichworte wie „Kind*“, „infant*“, „pediat*“ oder „child*“ im Titel oder im Abstract abgefragt. Verschiedenste sprachliche Variationen wurden berücksichtigt. Zur Beschränkung auf die letzten zwei Dekaden wurden die Publikationen nach ihrem Erscheinungsjahr zwischen 2001 und 2020 gefiltert. Die genaue Abfragesystematik ist bei Miller et al. einzusehen . Datenverarbeitung Anhand der Korrespondenzadresse im Zugehörigkeitsfeld wurde jeder Publikation eine Institution, eine Stadt (eine Stadt kann mehrere publizierende Institutionen beinhalten) und ein Staat (D, A, oder CH) zugewiesen. War keine primäre Korrespondenz unter den Autorenschaften genannt (was insbesondere bei Daten von PubMed vor 2014 vorkommt ), wurde die Anschrift der Erstautorenschaft als Korrespondenzadresse verwendet. Sprachliche Varianten von Institutionsnamen (z. B. Hannover Medical School und Medizinische Hochschule Hannover) oder Städtenamen (z. B. Cologne und Köln) wurden entsprechend homogenisiert. War bei einer Publikation mehr als eine Institution genannt, wurde die Publikation bei jeder nicht als Korrespondenz genannten Institution als Co-Autorenschaft gezählt. Dadurch ergab sich im Fall von Mehrfachnennungen zu jeder Korrespondenzadresse eine Liste an Kollaborationspartnerschaften. Hierfür wurde eine vollständige Zählweise verwendet. Zudem wurden die Publikationen dem jeweiligen Erscheinungsjahr sowie der Fachzeitschrift zugeordnet. Auch bei den Fachzeitschriften erfolgte eine Homogenisierung bei Namensänderungen im Untersuchungszeitraum (z. B. wurde Der Anaesthesist zu Die Anaesthesiologie ). Studienendpunkte Primärer Endpunkt war die Erhebung der Publikationsaktivität und -dynamik in der Kinderanästhesiologie im D‑A-CH-Raum zwischen 2001 und 2020, dargestellt anhand der Anzahl der Veröffentlichungen mit Korrespondenzautorenschaft und den jeweiligen Wachstumsraten der drei Staaten. Sekundäre Endpunkte waren (i) der Anteil an Kollaborationen inner- und außerhalb des D‑A-CH-Raums, (ii) die Verteilung der Publikationsaktivität und der Anteil an Kollaborationen auf institutioneller Ebene innerhalb des D‑A-CH-Raums und (iii) die bedeutendsten Fachzeitschriften für Publikationen aus dem D‑A-CH-Raum. Statistik Numerische Daten wurden als absolute Zahlen oder Prozentsätze angegeben und auf eine Kommastelle gerundet. Die Wachstumsrate über einen Zeitraum t wurde berechnet als [12pt]{minimal} $$(}{})^{}-1$$ Anzahl Erstjahr Anzahl Letztjahr 1 t - 1 , wobei für den Gesamtzeitraum von 2001 bis 2020 t = 20 Jahre galt. Um die individuelle durchschnittliche Wachstumsrate einzelner Institutionen oder Staaten zu bestimmen, wurde eine lineare Regression der jeweiligen jährlichen Publikationszahlen durchgeführt und die Steigung der Regressionsgeraden als durchschnittliche Wachstumsrate für den Gesamtzeitraum verwendet. Zu Datenverarbeitung und -auswertung setzten wir LibreOffice Calc 7.6.4 sowie JupyterLab 4.0.11 mit Python 3.11 ein. Für Illustrationen und Statistikauswertungen wurden zudem die Python-Bibliotheken matplotlib 3.8.1, GeoPandas 0.14.2 und scikit-learn 1.3 verwendet sowie folium 0.16 zur Erstellung der interaktiven webbasierten Landkarte. Als Grundlage diente die Datenbank und anschließende Datenverarbeitung aus der globalen Publikationsanalyse der Kinderanästhesiologie von Miller et al. , welche Abfragen von Web of Science und PubMed mit Stichtag 04.10.2021 kombinierte. Diese Quellen gelten als die beiden bedeutendsten Publikationsdatenbanken im medizinischen Bereich , wobei Web of Science aufgrund vollständigerer Datensätze als primäre Datenquelle genutzt und fehlende Daten mittels PubMed ergänzt wurden . Um kinderanästhesiologische Publikationen bestmöglich zu identifizieren, kombinierte die Suchabfrage 2 Parameter: Einerseits wurde die Zugehörigkeit mindestens einer Autorenschaft zu einer anästhesiologischen Institution erfasst, indem der Stamm des Wortes Anästhesiologie im Zugehörigkeitsfeld („affiliation field“) abgefragt wurde (beispielsweise durch „anaest*“, „anest*“ plus sprachbedingt mögliche Präfixe wie „Kinder-*“) . Andererseits wurden kinderbezogene Publikationen durch Stichworte wie „Kind*“, „infant*“, „pediat*“ oder „child*“ im Titel oder im Abstract abgefragt. Verschiedenste sprachliche Variationen wurden berücksichtigt. Zur Beschränkung auf die letzten zwei Dekaden wurden die Publikationen nach ihrem Erscheinungsjahr zwischen 2001 und 2020 gefiltert. Die genaue Abfragesystematik ist bei Miller et al. einzusehen . Anhand der Korrespondenzadresse im Zugehörigkeitsfeld wurde jeder Publikation eine Institution, eine Stadt (eine Stadt kann mehrere publizierende Institutionen beinhalten) und ein Staat (D, A, oder CH) zugewiesen. War keine primäre Korrespondenz unter den Autorenschaften genannt (was insbesondere bei Daten von PubMed vor 2014 vorkommt ), wurde die Anschrift der Erstautorenschaft als Korrespondenzadresse verwendet. Sprachliche Varianten von Institutionsnamen (z. B. Hannover Medical School und Medizinische Hochschule Hannover) oder Städtenamen (z. B. Cologne und Köln) wurden entsprechend homogenisiert. War bei einer Publikation mehr als eine Institution genannt, wurde die Publikation bei jeder nicht als Korrespondenz genannten Institution als Co-Autorenschaft gezählt. Dadurch ergab sich im Fall von Mehrfachnennungen zu jeder Korrespondenzadresse eine Liste an Kollaborationspartnerschaften. Hierfür wurde eine vollständige Zählweise verwendet. Zudem wurden die Publikationen dem jeweiligen Erscheinungsjahr sowie der Fachzeitschrift zugeordnet. Auch bei den Fachzeitschriften erfolgte eine Homogenisierung bei Namensänderungen im Untersuchungszeitraum (z. B. wurde Der Anaesthesist zu Die Anaesthesiologie ). Primärer Endpunkt war die Erhebung der Publikationsaktivität und -dynamik in der Kinderanästhesiologie im D‑A-CH-Raum zwischen 2001 und 2020, dargestellt anhand der Anzahl der Veröffentlichungen mit Korrespondenzautorenschaft und den jeweiligen Wachstumsraten der drei Staaten. Sekundäre Endpunkte waren (i) der Anteil an Kollaborationen inner- und außerhalb des D‑A-CH-Raums, (ii) die Verteilung der Publikationsaktivität und der Anteil an Kollaborationen auf institutioneller Ebene innerhalb des D‑A-CH-Raums und (iii) die bedeutendsten Fachzeitschriften für Publikationen aus dem D‑A-CH-Raum. Numerische Daten wurden als absolute Zahlen oder Prozentsätze angegeben und auf eine Kommastelle gerundet. Die Wachstumsrate über einen Zeitraum t wurde berechnet als [12pt]{minimal} $$(}{})^{}-1$$ Anzahl Erstjahr Anzahl Letztjahr 1 t - 1 , wobei für den Gesamtzeitraum von 2001 bis 2020 t = 20 Jahre galt. Um die individuelle durchschnittliche Wachstumsrate einzelner Institutionen oder Staaten zu bestimmen, wurde eine lineare Regression der jeweiligen jährlichen Publikationszahlen durchgeführt und die Steigung der Regressionsgeraden als durchschnittliche Wachstumsrate für den Gesamtzeitraum verwendet. Zu Datenverarbeitung und -auswertung setzten wir LibreOffice Calc 7.6.4 sowie JupyterLab 4.0.11 mit Python 3.11 ein. Für Illustrationen und Statistikauswertungen wurden zudem die Python-Bibliotheken matplotlib 3.8.1, GeoPandas 0.14.2 und scikit-learn 1.3 verwendet sowie folium 0.16 zur Erstellung der interaktiven webbasierten Landkarte. Zwischen 2001 und 2020 wurden insgesamt 3406 kinderanästhesiologische Publikationen mit Beteiligung aus dem D‑A-CH-Raum identifiziert (Abb. ). Davon wiesen 2807 (82,4 %) Publikationen eine Korrespondenzadresse im D‑A-CH-Raum auf. Bei 1894 lag diese in Deutschland, bei 295 in Österreich und bei 618 in der Schweiz (Abb. ). Die durchschnittliche jährliche Wachstumsrate der Publikationen mit Korrespondenzadresse lag für den D‑A-CH-Raum bei + 2,9 %. Für Deutschland lag sie bei + 2,9 %, für Österreich bei + 5,3 %, und für die Schweiz bei + 1,7 %. Der Anteil jener Publikationen, bei denen eine Institution aus dem D‑A-CH-Raum eine Co-Autorenschaft zu einer Institution mit Korrespondenzadresse außerhalb des D‑A-CH-Raums hatte, nahm im Untersuchungszeitraum um durchschnittlich 7,4 % pro Jahr zu (von 5,8 % 2001 auf 24,3 % 2020). Kollaborationen auf staatlicher Ebene Von den 2807 Publikationen mit Korrespondenzadresse im D‑A-CH-Raum hatten 1296 (46,2 %) mindestens eine weitere Kollaborationspartnerschaft. Die jeweilige Anzahl an Publikationen mit zwei, drei, vier, fünf und mehr als fünf Kollaborationspartnerschaften nahm zwischen 2001 und 2020 zu (Abb. ). Die durchschnittliche jährliche Wachstumsrate der Publikationen mit mindestens einer weiteren Kollaborationspartnerschaft betrug + 7,7 %. Mit Korrespondenzadresse aus Deutschland waren 908 (47,9 % von 1894) der Publikationen Kollaborationen. Davon waren 627 (69,0 %) ausschließlich innerhalb des D‑A-CH-Raums, 173 (19,1 %) gemischt mit Kollaborationspartnerschaften inner- und außerhalb und 108 (11,9 %) ausschließlich außerhalb des D‑A-CH-Raums. Mit Korrespondenzadresse aus Österreich waren 133 (45,1 % von 295) der Publikationen Kollaborationen. Davon waren 80 (60,1 %) ausschließlich innerhalb des D‑A-CH-Raums, 16 (12,0 %) gemischt inner- und außerhalb und 37 (27,8 %) ausschließlich außerhalb. Mit Korrespondenzadresse aus der Schweiz waren 255 (41,3 % von 618) der Publikationen Kollaborationen. Davon waren 101 (39,6 %) ausschließlich innerhalb des D‑A-CH-Raums, 38 (14,9 %) gemischt inner- und außerhalb und 116 (45,5 %) ausschließlich außerhalb. Institutionelle Ebene Die 2807 Publikationen mit Korrespondenzadresse im D‑A-CH-Raum wurden von 251 Institutionen aus 163 Städten veröffentlicht. Davon stammen 197 Institutionen aus Deutschland, 22 aus Österreich und 32 aus der Schweiz. Bezüglich der Verteilung stammen über 90 % aller Publikationen mit Korrespondenzadresse von 68 Institutionen aus 46 Städten (Abb. ). Diese 46 haben jeweils mindestens 10 Publikationen zwischen 2001 und 2020 veröffentlicht. Co-Autorenschaften inklusive waren 370 verschiedene Institutionen aus dem D‑A-CH-Raum an kinderanästhesiologischen Publikationen beteiligt; 295 aus Deutschland, 31 aus Österreich und 44 aus der Schweiz. Kollaborationen auf institutioneller Ebene Publikationen aus der Stadt Genf hatten mit 179 die meisten Kollaborationspartnerschaften, während Publikationen aus der Stadt Essen mit 78,3 % den höchsten Anteil an Publikationen mit mindestens einer Kollaborationspartnerschaft hatten (Tab. ). Den höchsten Anteil der Publikationen mit ausschließlich Kollaborationspartnerschaften innerhalb des D‑A-CH-Raums hatten Publikationen aus Homburg, Klagenfurt (je 100 %) und Regensburg (93,3 %). Den höchsten Anteil der Publikationen mit ausschließlich Kollaborationspartnerschaften außerhalb des D‑A-CH-Raums hatten Publikationen aus Basel (64,1 %), Genf (60,0 %) und Luzern (57,1 %, Tab. ). Die drei häufigsten Kollaborationen waren zwischen den Städten Köln und Witten (21), Berlin und Hannover (18) sowie Berlin und Köln (17) (Abb. ). Eine interaktive Kartenversion ist online unter https://www.kinderanaesthesie-talk.de/szientometrie verfügbar. Publikationsorgane Während Publikationen aus Deutschland am häufigsten in der Fachzeitschrift Die Anaesthesiologie erschienen ( n = 154), wurden Publikationen aus Österreich und der Schweiz am häufigsten in Pediatric Anesthesia veröffentlicht ( n = 39 bzw. n = 99, Tab. ). Von den 2807 Publikationen mit Korrespondenzadresse im D‑A-CH-Raum hatten 1296 (46,2 %) mindestens eine weitere Kollaborationspartnerschaft. Die jeweilige Anzahl an Publikationen mit zwei, drei, vier, fünf und mehr als fünf Kollaborationspartnerschaften nahm zwischen 2001 und 2020 zu (Abb. ). Die durchschnittliche jährliche Wachstumsrate der Publikationen mit mindestens einer weiteren Kollaborationspartnerschaft betrug + 7,7 %. Mit Korrespondenzadresse aus Deutschland waren 908 (47,9 % von 1894) der Publikationen Kollaborationen. Davon waren 627 (69,0 %) ausschließlich innerhalb des D‑A-CH-Raums, 173 (19,1 %) gemischt mit Kollaborationspartnerschaften inner- und außerhalb und 108 (11,9 %) ausschließlich außerhalb des D‑A-CH-Raums. Mit Korrespondenzadresse aus Österreich waren 133 (45,1 % von 295) der Publikationen Kollaborationen. Davon waren 80 (60,1 %) ausschließlich innerhalb des D‑A-CH-Raums, 16 (12,0 %) gemischt inner- und außerhalb und 37 (27,8 %) ausschließlich außerhalb. Mit Korrespondenzadresse aus der Schweiz waren 255 (41,3 % von 618) der Publikationen Kollaborationen. Davon waren 101 (39,6 %) ausschließlich innerhalb des D‑A-CH-Raums, 38 (14,9 %) gemischt inner- und außerhalb und 116 (45,5 %) ausschließlich außerhalb. Die 2807 Publikationen mit Korrespondenzadresse im D‑A-CH-Raum wurden von 251 Institutionen aus 163 Städten veröffentlicht. Davon stammen 197 Institutionen aus Deutschland, 22 aus Österreich und 32 aus der Schweiz. Bezüglich der Verteilung stammen über 90 % aller Publikationen mit Korrespondenzadresse von 68 Institutionen aus 46 Städten (Abb. ). Diese 46 haben jeweils mindestens 10 Publikationen zwischen 2001 und 2020 veröffentlicht. Co-Autorenschaften inklusive waren 370 verschiedene Institutionen aus dem D‑A-CH-Raum an kinderanästhesiologischen Publikationen beteiligt; 295 aus Deutschland, 31 aus Österreich und 44 aus der Schweiz. Publikationen aus der Stadt Genf hatten mit 179 die meisten Kollaborationspartnerschaften, während Publikationen aus der Stadt Essen mit 78,3 % den höchsten Anteil an Publikationen mit mindestens einer Kollaborationspartnerschaft hatten (Tab. ). Den höchsten Anteil der Publikationen mit ausschließlich Kollaborationspartnerschaften innerhalb des D‑A-CH-Raums hatten Publikationen aus Homburg, Klagenfurt (je 100 %) und Regensburg (93,3 %). Den höchsten Anteil der Publikationen mit ausschließlich Kollaborationspartnerschaften außerhalb des D‑A-CH-Raums hatten Publikationen aus Basel (64,1 %), Genf (60,0 %) und Luzern (57,1 %, Tab. ). Die drei häufigsten Kollaborationen waren zwischen den Städten Köln und Witten (21), Berlin und Hannover (18) sowie Berlin und Köln (17) (Abb. ). Eine interaktive Kartenversion ist online unter https://www.kinderanaesthesie-talk.de/szientometrie verfügbar. Während Publikationen aus Deutschland am häufigsten in der Fachzeitschrift Die Anaesthesiologie erschienen ( n = 154), wurden Publikationen aus Österreich und der Schweiz am häufigsten in Pediatric Anesthesia veröffentlicht ( n = 39 bzw. n = 99, Tab. ). Die Publikationsaktivität in der Kinderanästhesiologie in Deutschland, Österreich und der Schweiz nahm zwischen 2001 und 2020 jährlich um 3 % zu, wobei besonders Kollaborationen von wachsender Bedeutung sind. Dies spiegelt sich sowohl in einer mehr als doppelt so hohen Zunahme der Publikationen mit mehr als 2 kollaborierenden Institutionen als auch in der steigenden Anzahl an Co-Autorenschaften bei Publikationen mit Korrespondenz außerhalb von D‑A-CH-Raum wider. Außerdem kollaborieren die D‑A-CH-Staaten sehr stark miteinander. Wissenschaftliches Arbeiten wird durch diverse rechtliche und organisatorische Anforderungen sowie Ressourcenknappheit zunehmend komplexer und aufwendiger . Daher ist ein hohes Maß an Expertise und Fachwissen erforderlich, um den ansteigenden Anforderungen mehr und mehr gerecht werden zu können. Eine zunehmende Vernetzung und Bündelung von Ressourcen eröffnet die Möglichkeit, bestehende Evidenzlücken gezielt(er) zu schließen und besonders „schwierige Probleme“ gemeinsam angehen zu können . Dies wird am besten durch Kollaborationen erreicht, was Adams als Grundpfeiler der aktuellen Forschungsepoche tituliert . Besonders über Institutionsgrenzen hinaus haben Kollaborationen eine steigende Bedeutung: Sie bündeln Expertise und Ressourcen, ermöglichen größere Fallzahlen, erzeugen eine größere Resonanz, bringen „frische“ Ideen in bestehende Teams und tragen zur Dissemination von Fachwissen bei . Kollaborationen mit all den genannten Aspekten sind daher für die Kinderanästhesiologie wesentlich, wie rezente Studien wie APRICOT oder NECTARINE, woran Wissenschaftler*innen aus 18 bzw. 30 Staaten mitwirkten, durch ihren Impact praxisrelevant darlegen. Es verwundert demnach nicht, dass der Anteil der durch Kollaborationen entstandenen, kinderanästhesiologischen Publikationen aus dem D‑A-CH-Raum überproportional angestiegen ist und knapp die Hälfte aller Publikationen mindestens eine Kollaboration aufweist. Die Zusammenarbeit findet überwiegend zwischen Institutionen innerhalb des D‑A-CH-Raums statt, was sicherlich durch die geografische und sprachliche Nähe begünstigt ist. Auffallend ist dabei ein deutlich höherer Anteil der internationalen Kollaborationen von Schweizer Institutionen als von Deutschen oder Österreichischen. Internationalität scheint in der schweizerischen Kinderanästhesiologie-Forschung eine größere Rolle zu spielen, womöglich aufgrund der geringeren Zahl der wissenschaftlich tätigen Institutionen. Dies würde zwar auf Österreich auch zutreffen, jedoch ist dort die Publikationsaktivität generell geringer und die Vernetzung mit Deutschland stärker. Österreichische und schweizerische Institutionen publizieren, relativ gesehen, häufiger in internationalen Fachzeitschriften wie Pediatric Anesthesia. Deutsche Institutionen hingegen wählen am häufigsten deutschsprachige Fachzeitschriften – allen voran Die Anaesthesiologie , welche aber auch für Österreich und Schweiz eine häufig gewählte Fachzeitschrift ist. Trotz Zunahme der Publikationsaktivität ist das jährliche Wachstum im D‑A-CH-Raum etwas geringer als das Weltweite, das im selben 20-Jahres-Zeitraum 7,6 % betrug und v. a. auf die teilweise hohen Wachstumsraten einiger Länder wie China und Indien zurückzuführen ist. Dies spiegelt sich auch in einem seit 2016 erkennbaren Abrutsch der D‑A-CH-Staaten im länderspezifischen Ranking der Korrespondenzautorenschaften wider und ist in ähnlicher Weise auch auf dem Gebiet der gesamten Anästhesiologie zu beobachten . Dennoch gehören D‑A-CH zu den in den letzten beiden Dekaden am häufigsten kinderanästhesiologisch publizierenden Staaten. Bezüglich der Verteilung fällt die Ähnlichkeit zu einer generalisierten Pareto-Verteilung auf , da ca. 80 % der Institutionen weniger als 20 Publikationen hatten. Sehr wenige Institutionen sind also für einen Großteil der Publikationen verantwortlich, was als Konzentrierung der Korrespondenzen gesehen werden kann und damit eine Spezialisierung in der kinderanästhesiologischen Publikationslandschaft indiziert. Mehr als die Hälfte der wissenschaftlich aktiven Institutionen sind zwar an Publikationen beteiligt, waren aber selbst nie als Korrespondenz benannt, also vermutlich nicht federführend. Dies spiegelt sich auch anhand der steigenden Anzahl an Co-Autorenschaften pro Publikation sowohl in unseren Daten und auch in der Anästhesiologie gesamt wider . Allerdings steigt nicht nur die Anzahl an Autorenschaften, sondern auch die Anzahl an verschiedenen, an einer Publikation beteiligten Institutionen und damit der Grad an Vernetzung. Im Gegenzug sinkt der Anteil jener Publikationen, die von einer einzigen Institution ohne jegliche Kollaborationen ausgehen. Dies zeigt einen eindeutigen Trend zur Vernetzung auf breiterer Basis, könnte aber auch ein Indikator für eine Zunahme der wissenschaftlichen Komplexität sein. Bezüglich einer weiteren Vernetzung auf Ebene des D‑A-CH-Raums kommt dem Wissenschaftlichen Arbeitskreis Kinderanästhesie der DGAI sicherlich eine tragende Rolle bei der Ermöglichung von Kollaborationen zu. Auf europäischer Ebene wurde bei der European Society of Anaesthesiology and Intensive Care (ESAIC) das Paediatric Anaesthesia Research Network (ESAIC PARNet) mit dem Ziel eingerichtet, interessierten Wissenschaftler*innen Kollaborationen unter dem Schirm dieser Institution zu ermöglichen. Szientometrische Analysen lassen jedoch einige Aspekte offen: Hinter bloßen Zahlen stecken oft Parameter, die nicht final beantwortet werden können . Sind alle Autorenschaften gerechtfertigt? Haben alle Beteiligten gleich viel beigetragen? Ist viel gut oder ist weniger mehr? Welche Ressourcen stecken hinter einer Publikation? Die berichteten Zahlen sind zumindest ein Indikator für die Ableitung eines longitudinalen Trends, da die Verwendung eines geeigneten Nenners die Verzerrung reduziert . Limitationen Wir sind uns mehrerer Limitationen bewusst: Erstens kann das Abfrageschema zu einer Überschätzung der Publikationsaktivität geführt haben, da die Kombination aus kinderbezogenen Themen und Zugehörigkeit zu einer anästhesiologischen Institution nicht zwangsläufig ausschließlich kinderanästhesiologisch spezifische Publikationen erfasst. Dies gilt z. B. für kinderintensivmedizinische Publikationen. Da es im D‑A-CH-Raum (und auch außerhalb) nur wenige eigenständige Abteilungen für Kinderanästhesiologie gibt, steht kein adäquateres Abfrageschema zur Vermeidung falsch-positiver Erfassungen zur Verfügung . Zumindest waren bei den erfassten Publikationen anästhesiologisch affiliierte Personen Teil des Teams. Zudem lässt die Verteilung auf die identifizierten Fachzeitschriften auf eine hohe Sensitivität für kinderanästhesiologisch relevante Themen schließen. Zweitens wurden nur vollständig genannte Autorenschaften gezählt; die noch nicht lange bestehenden „collaborative authorships“ wurden durch das Abfrageschema nicht erfasst. Dies könnte die Anzahl der Kollaborationen sogar noch unterschätzt haben. Drittens ist die Unterscheidung zwischen Institution und Stadt nicht immer scharf trennbar, da es manche Institutionen gibt, die einer anderen Stadt zugeordnet sind und daher zu Doppelt- oder Falschnennungen führen können. Wir haben uns dabei auf die jeweils angegebene Zugehörigkeit gestützt. Viertens sind Analysen über das Affiliation field auf eine korrekte Angabe der Zugehörigkeitsfelder durch Wissenschaftler*innen sowie konsekutiv Fachzeitschriften und Datenbanken angewiesen. Fehlerhafte oder unzureichende Eingaben, wie sie v. a. bei PubMed immer wieder vorkommen , können bei Analysen nicht korrigiert werden. Wir sind uns mehrerer Limitationen bewusst: Erstens kann das Abfrageschema zu einer Überschätzung der Publikationsaktivität geführt haben, da die Kombination aus kinderbezogenen Themen und Zugehörigkeit zu einer anästhesiologischen Institution nicht zwangsläufig ausschließlich kinderanästhesiologisch spezifische Publikationen erfasst. Dies gilt z. B. für kinderintensivmedizinische Publikationen. Da es im D‑A-CH-Raum (und auch außerhalb) nur wenige eigenständige Abteilungen für Kinderanästhesiologie gibt, steht kein adäquateres Abfrageschema zur Vermeidung falsch-positiver Erfassungen zur Verfügung . Zumindest waren bei den erfassten Publikationen anästhesiologisch affiliierte Personen Teil des Teams. Zudem lässt die Verteilung auf die identifizierten Fachzeitschriften auf eine hohe Sensitivität für kinderanästhesiologisch relevante Themen schließen. Zweitens wurden nur vollständig genannte Autorenschaften gezählt; die noch nicht lange bestehenden „collaborative authorships“ wurden durch das Abfrageschema nicht erfasst. Dies könnte die Anzahl der Kollaborationen sogar noch unterschätzt haben. Drittens ist die Unterscheidung zwischen Institution und Stadt nicht immer scharf trennbar, da es manche Institutionen gibt, die einer anderen Stadt zugeordnet sind und daher zu Doppelt- oder Falschnennungen führen können. Wir haben uns dabei auf die jeweils angegebene Zugehörigkeit gestützt. Viertens sind Analysen über das Affiliation field auf eine korrekte Angabe der Zugehörigkeitsfelder durch Wissenschaftler*innen sowie konsekutiv Fachzeitschriften und Datenbanken angewiesen. Fehlerhafte oder unzureichende Eingaben, wie sie v. a. bei PubMed immer wieder vorkommen , können bei Analysen nicht korrigiert werden. Die Anzahl der Publikationen im Bereich Kinderanästhesiologie aus dem D‑A-CH-Raum nahm zwischen 2001 und 2020 zu. Kollaborationen spielten dabei eine zunehmend wichtigere Rolle, was durch die überproportionale Steigerung an Publikationen mit mehreren Institutionen angezeigt wird. Vorwiegend wurde innerhalb des D‑A-CH-Raums kooperiert; nur in der Schweiz war der Grad der internationalen Kollaboration deutlich höher. Der Grad der Vernetzung bei kinderanästhesiologischen Publikationen nahm ebenfalls zu, zeigte jedoch eine Konzentrierung an federführenden Institutionen. Es bleibt zu wünschen, dass dies in einer Verbesserung der Evidenzlage in der Kinderanästhesie resultiert. |
Making medical missions your mission | a6d6abfb-9a80-4f82-aea7-bcca0a9094b1 | 11307023 | Pediatrics[mh] | A medical mission is a medical trip, typically run by a non-governmental organization (NGO) to provide short- or long-term medical care in a developing country. It may be done by one or more individual medical providers or by a whole team with a single mission (e.g., providing surgery for a specific condition). It may involve a variety of medical and non-medical personnel. It is not a substitute for locally based services which are always there. Those who come in from the outside (ex-pats) will not “cure” the problems you have come to address. And outsiders will go home after days or weeks or years. Who will be there when the ex-pats leave? You do not know better than the people in country X what they need and want. Do a “needs and wants” survey and try to help with the items the people you are working with want to be addressed. Be realistic in what can be accomplished in the time you are there. There are very few physiatrists in developing countries (especially in Africa) and even fewer pediatric physiatrists. Most pediatric rehabilitation is done by a combination of neurologists, orthopedists, pediatricians, and maybe nurses or therapists. And frequently rehabilitation is not done at all. There are a variety of ways to find a mission that fits with your skills, interests, and timing. Word of mouth from colleagues is a frequent way to find a mission. It may be sponsored by an organization you work for, belong to, or know about. You may start your own program or organization or you may find a mission on the internet that interests you. Things to consider in deciding on a mission trip: Where do you want to go? What do you want to do? How long do you want to spend on the mission? Do you want to travel or be part of a big or small team? Do you want to organize the trip or have someone do it for you? Much of the world does not understand what a rehabilitation physician does. You may have to convince an organization that you have something to contribute. And even though you are a pediatric physiatrist, you may end up being a pediatrician, neurologist, or non-operative orthopedist. Or maybe even an engineer, architect for barrier-free design, etc. Have you ever been to a developing country (low- to middle-income country [LMIC]) before? If not, there can be a “shock” factor the first time you encounter living conditions you have not previously seen and lack of commonly available resources (think soap, alcohol gel, disposable gloves, running water in clinic, privacy ...). Although you may want to show your way of doing rehabilitation (or surgery, etc.), all the equipment and supplies you have are usually not available in LMICs. And it is hard to go back home to a paucity of supplies and equipment and translate what you have learned if you are a professional from a developing country. There are also cultural factors that are different in each country which may change the way you practice. There are too many well-trained professionals from LMIC’s who now work in the US or other upper income countries. I have had the honor of doing medical missions in a variety of countries. These have included information gathering to help our processes, providing rehabilitation care, setting up programs, and teaching both trainees and practitioners, including orthopedic residents, nurses, and therapists. I have also supported parents as they learn to become advocates for their children in the community. My favorite missions have been in Kenya, where I have been going since 2001. Service has included all of the above. Most exciting is that the hospital I have worked in has gone from being staffed primarily by ex-pats (mostly Americans) to fully staffed by Africans. It is so exciting to see a resident I worked with go from residency to staff to chief of staff. And the nurse I taught has gone on to teach other nurses and run a program for children with spina bifida. And I have seen parents advocate for their children with spina bifida to attend regular schools even though their children might use wheelchairs and be on an intermittent catheterization program. But most exciting is seeing a former patient with spina bifida become a professional advocate and help with programs in Kenya and internationally. |
Virtual Interviews and the Pediatric Emergency Medicine Match Geography: A National Survey | 32add411-c46e-4a1d-9712-2d763d38ad51 | 11000550 | Pediatrics[mh] | Since 2020, virtual interviews (VI) have been preferred for trainee recruitment. With the benefits of lower cost and greater equity, it is likely to remain a permanent part of recruitment, despite a general preference for face-to-face interviews. – The VI process and associated perceptions have been described in the literature. , , – The inability to visit a program in person can impact decision-making during ranking, , – and an increased number of applications could create undue strain on programs. – Geographic location, sense of “fit,” and program leadership were described as major contributors to applicants’ rank preference. A national cohort of pediatric emergency medicine program directors (PEM PD), in a joint statement, raised concern that VI could lead applicants to apply to more programs and to programs farther away than they may be willing or able to travel. We conducted this study to determine whether PEM fellowship applicants would apply to a larger number of programs and in different geographic patterns with VI (2020 and 2021) as compared to in-person interviews (2018 and 2019). Design and Participants This was an anonymous, self-administered, cross-sectional, web-based survey of PEM fellows in the United States. Participation was voluntary, and no incentive was provided for completion. The study was exempted by the institutional review board at Yale University, with informed consent implied by completion of the survey by participants. Survey Development The survey questionnaire was developed through iterative feedback and a modified Delphi process to determine item importance. Thirteen PEM PDs with expertise in performance and evaluation participated in multiple rounds of revisions and editing. Pilot testing was conducted with two pediatric hospital medicine fellows who had applied to the match during VIs and two pediatric chief residents who were also interviewing for fellowships using VI, at the lead institution. Revisions were made based on pilot feedback (survey provided in ). The survey included multiple-choice questions about location of residency, states applied to and interviewed for fellowship, preferred location for fellowship, states visited in person for the purpose of the match, and state matched in. It also asked fellows to indicate states of residence of immediate family (parents, siblings, or partners) and about compelling reasons (other than family) that may have led fellows to favor a state or region (free text). Geographic regions were defined as Northeast, Southeast, Midwest, Southwest, Rocky Mountain, and Pacific regions. Survey Distribution The survey was reviewed and approved by the American Academy of Pediatrics (AAP) Section on Emergency Medicine (SOEM) PD survey subcommittee prior to distribution on Qualtrics (Qualtrics, Provo, UT) to all PEM PDs, via the AAP SoEM PD Committee listserv. The PDs forwarded the survey link to their current and incoming fellows (those recently matched to start in July 2022). Each PD completed a separate questionnaire indicating the total number of current and recently matched fellows to whom they forwarded the survey. Analysis Participants were divided into two groups: VI (2020 or 2021) and in person (2018 or 2019). We performed descriptive statistics including frequencies, percentages, means with standard deviations, and medians with interquartile range (IQR). Chi-square tests compared categorical variables and t-tests, continuous variables with 95% confidence intervals (CI). We considered a two-tailed alpha of <0.05 to be statistically significant. We conducted analyses in IBM SPSS Statistics version 28 (IBM Corporation, Armonk, NY). This was an anonymous, self-administered, cross-sectional, web-based survey of PEM fellows in the United States. Participation was voluntary, and no incentive was provided for completion. The study was exempted by the institutional review board at Yale University, with informed consent implied by completion of the survey by participants. The survey questionnaire was developed through iterative feedback and a modified Delphi process to determine item importance. Thirteen PEM PDs with expertise in performance and evaluation participated in multiple rounds of revisions and editing. Pilot testing was conducted with two pediatric hospital medicine fellows who had applied to the match during VIs and two pediatric chief residents who were also interviewing for fellowships using VI, at the lead institution. Revisions were made based on pilot feedback (survey provided in ). The survey included multiple-choice questions about location of residency, states applied to and interviewed for fellowship, preferred location for fellowship, states visited in person for the purpose of the match, and state matched in. It also asked fellows to indicate states of residence of immediate family (parents, siblings, or partners) and about compelling reasons (other than family) that may have led fellows to favor a state or region (free text). Geographic regions were defined as Northeast, Southeast, Midwest, Southwest, Rocky Mountain, and Pacific regions. The survey was reviewed and approved by the American Academy of Pediatrics (AAP) Section on Emergency Medicine (SOEM) PD survey subcommittee prior to distribution on Qualtrics (Qualtrics, Provo, UT) to all PEM PDs, via the AAP SoEM PD Committee listserv. The PDs forwarded the survey link to their current and incoming fellows (those recently matched to start in July 2022). Each PD completed a separate questionnaire indicating the total number of current and recently matched fellows to whom they forwarded the survey. Participants were divided into two groups: VI (2020 or 2021) and in person (2018 or 2019). We performed descriptive statistics including frequencies, percentages, means with standard deviations, and medians with interquartile range (IQR). Chi-square tests compared categorical variables and t-tests, continuous variables with 95% confidence intervals (CI). We considered a two-tailed alpha of <0.05 to be statistically significant. We conducted analyses in IBM SPSS Statistics version 28 (IBM Corporation, Armonk, NY). The PDs reported that they forwarded the survey to 406 current fellows and 144 incoming fellows. The response rate for current fellows was 35% (143/406) and for incoming fellows, 61% (88/144). Overall, the response rate was 42% (231/550). Of the total respondents, 62% (143/231) were current fellows and 38% (88/231) incoming. Two fellows (1%) did not complete residency in the US, and 12 (5%) applied to PEM fellowship more than once. All incoming fellows had undergone VI, whereas 48% of the current fellows had undergone VI (69/143). Overall, 32% of respondents (74/231) interviewed in person and 68% (157/213) virtually. There was no statistical difference in the number of programs applied to during in-person vs VI (mean difference (95% CI): .72 [−2.8, 4.2]) . Data describing the geographic training and location preference of participants are presented in the table in . Fellows applied to a median of four of the six geographic regions (IQR 2, 5). Most participants applied for fellowship in the same geographic region as their residency (216, 93%) and outside their residency region as well (192, 83%). Only the Pacific region saw a statistically significant increase in applicants during VI (59.9% vs 43.2%, P = 0.02) . Less than half of respondents had immediate family members living in the same state as residency (N = 111, 48%), fellowship (N = 90, 39%), or their preferred match state (N = 95, 41%). Compelling reasons to apply to an area included familiarity with location (N = 128, 55%); similar location to residency (N = 65, 28%); and a desire to train in a new area (N = 53, 23%). Partner’s employment was an important factor for 89 (38%), salary and cost of living for 76 (33%), and school for children for 20 (9%). Our results show that VI may allow some candidates to explore and consider regions they may not have otherwise due to logistical or financial constraints, without increasing the number of programs, regions or states they apply to. These results are consistent with the 2021 NRMP survey where 52% reported no impact of the VI on the number of programs applied to. Residency programs have reported an increase in matched internal candidates during VI. , , , In PEM, a pre-pandemic study of PDs showed that 29% of fellows completed residency at the same institution. While we did not have data at the institutional level, there was no significant increase in fellows matching within the state of their residency program with VI. This suggests that VI were not a significant detriment to applicants ranking programs and geographic areas, despite the absence of opportunities to meet in person and visit programs. This also allows programs to have access to a larger and potentially more diverse pool of candidates. Proximity to family was not a significant consideration for most applicants and was not impacted by VI. Residency applicants reported geography, quality of life, case variety, curriculum, institutional reputation, expertise in areas of interest, and program size as key factors. Applicants to PEM highlighted familiarity with the region or wanting to explore a new area as factors for exploring programs in different regions. Limitations of this study include the smaller response rate of the current fellows as compared to the incoming fellows. This low response rate limited the sample size of the in-person cohort, impacting the statistical significance of our results. This differential response from the incoming fellows may have been due to desirability bias where this cohort of applicants may have tended to state that they matched in their preferred state. To minimize this, we designed our study to be fully anonymous and self-administered, and the questions were worded to retain objectivity of the answers. Respondents may also have experienced recall bias regarding the states and programs to which they applied. This bias could potentially have contributed to the lower response rate among the current fellows who had interviewed in 2018/2019, 3–4 years prior to the survey date, compared to the more recent applicants who had a more recent recollection of the questions asked in the survey. Another limitation is that we didn’t explicitly ask the total number of fellows in each class cohort; however, since the PEM fellowship class size in the US doesn’t vary significantly from year to year (by virtue of the approved fellowship positions available), the denominator is expected to be relatively constant. This study was not designed to look at the rates of applications to individual programs nor assess the post-match opinions of programs and fellows regarding the results of the match. This information would provide a deeper insight into the impact of the recruitment process; however, it is also prone to bias as fellows only experience training at a single institution. We also did not take into consideration the concentration of PEM programs by region or the available fellowship slots per program or region. However, the objective of this study was to look at the differences before and during VIs, and there was not a significant change in available fellowship slots or programs during these years. As the number of pediatric fellowship applicants rises, further investigation into the impact of VIs is necessary to gain a deeper understanding of its implications and to optimize this process both for applicants and programs. While more PEM fellowship applicants applied outside the geographic area where their residency was and to the Pacific region, there was no overall increase in the number of programs or geographic areas that PEM applicants applied to during VI during the first two years of its institution, as compared to in-person interview seasons. Ongoing monitoring of the interview and match seasons will help identify future trends and impact of VIs. |
Clinical practice guidelines for uterine corpus cancer: an update to the Korean Society of Gynecologic Oncology guidelines | d2ddd24f-6c49-4cc6-bdc2-149075f3f05f | 11790997 | Internal Medicine[mh] | Endometrial cancer, also known as uterine corpus cancer, is a significant global health concern. In 2022, 420,368 new cases were reported worldwide, reflecting their growing impact . Its incidence is rising owing to factors such as aging populations, increasing obesity rates, and changes in reproductive patterns . Advances in molecular classification and diagnostic techniques are promising for improving treatment outcomes . This rising trend underscores the urgent need for updated clinical practice guidelines to optimize patient care and improve survival outcomes. Recognizing the importance of standardized treatment protocols, the Korean Society of Gynecologic Oncology (KSGO) has been actively developing and updating practice guidelines for endometrial cancer since 2006. The previous version 5.0, published in March 2024, provided comprehensive evidence-based recommendations covering a wide range of diagnostic and therapeutic approaches . However, rapid advancements in endometrial cancer research, particularly in targeted therapies, immune checkpoint inhibitors, and poly(ADP-ribose) polymerase (PARP) inhibitors, have necessitated an expedited revision of these guidelines. The newly updated version 5.1 of the KSGO guideline incorporates the most recent high-quality evidence from randomized controlled trials (RCTs) to address critical questions in the management of endometrial cancer. This version includes the revision of key questions from version 5.0 and introduces new questions that reflect advancements in therapeutic strategies. Through this update, the KSGO aims to provide clinicians with actionable evidence-based recommendations to support decision-making in routine clinical practice. By addressing both established and emerging therapies, updated guidelines seek to enhance the standard of care for patients with endometrial cancer in Korea. This effort reaffirms the KSGO’s commitment to improving patient outcomes and advancing the field of gynecologic oncology. 1. Developing the recommendations The KSGO developed the 5.1 version of the guideline for the management of endometrial cancer based on the most recent RCTs and relevant clinical evidence. This update aimed to reflect advancements in research and clinical practice, while addressing newly emerging key questions to guide optimal patient care. Unlike version 5.0, which included systematic reviews and meta-analyses based on comprehensive literature searches, the 5.1 guideline primarily relied on evidence from recently published RCTs. While the 5.0 guideline involved processes such as detailed literature searches, data extraction, and meta-analyses to generate recommendations, the 5.1 version focused on integrating high-quality, large-scale RCTs that directly addressed the revised and new key questions. The updates to version 5.1 included: 1. Revising existing key questions. 2. Adding 2 new key questions to address emerging evidence in the diagnosis, treatment, and management of endometrial cancer. 2. Key question development The KSGO Uterine Corpus Cancer Committee developed and refined the key questions through multiple discussions . These key questions were formulated using the Population, Intervention, Comparison, and Outcome (PICO) framework to ensure clinical relevance and applicability. The new and revised key questions focus on addressing recent advancements in treatment modalities, including the integration of immune checkpoint inhibitors and targeted therapies. 3. Literature selection The recommendations in version 5.1 were based on recent evidence from well-known RCTs directly addressing the updated key questions. Only peer-reviewed RCTs published in English that reported clear outcomes related to the key questions were included. Studies unrelated to endometrial cancer, case reports, observational studies, and duplicate data from overlapping patient populations were also excluded. 4. Quality of evidence The quality of evidence supporting the recommendations of this guideline was graded using the levels defined in . Level I evidence represents findings from at least one large, randomized, controlled trial of good methodological quality (with low potential for bias) or meta-analyses of well-conducted randomized trials without heterogeneity. Level II evidence includes small randomized trials, large randomized trials with potential biases, or meta-analyses of such trials with demonstrated heterogeneity. Levels III, IV, and V correspond to progressively lower levels of evidence, ranging from prospective cohort studies (Level III) to retrospective studies, case reports, or expert opinions (Level V). This grading system ensures transparency and reliability in linking recommendations to the strength of underlying evidence. 5. Grades of recommendation The grades of recommendation were assigned based on the quality of evidence, the balance of benefits and harms, and clinical relevance . Grade A indicates strong evidence of efficacy with substantial clinical benefit, and such interventions are strongly recommended. Grade B signifies strong or moderate evidence of efficacy, although with limited clinical benefit, making the intervention generally recommended. Grade C is applied when there is insufficient evidence for efficacy or when benefits do not clearly outweigh risks, making the intervention optional. Grade D indicates moderate evidence against efficacy or concerns for adverse outcomes, resulting in a general recommendation against intervention. Grade E reflects strong evidence against efficacy or significant adverse outcomes, with interventions never being recommended. This grading system provides clinicians with clear evidence-based guidance for informed decision making in clinical practice. 6. Consensus process The final recommendations were formulated and agreed upon by the KSGO Uterine Corpus Cancer Committee. Multiple rounds of discussion were conducted to resolve differences in the interpretation or application of the evidence. All recommendations were finalized during the consensus meeting of committee members. The KSGO developed the 5.1 version of the guideline for the management of endometrial cancer based on the most recent RCTs and relevant clinical evidence. This update aimed to reflect advancements in research and clinical practice, while addressing newly emerging key questions to guide optimal patient care. Unlike version 5.0, which included systematic reviews and meta-analyses based on comprehensive literature searches, the 5.1 guideline primarily relied on evidence from recently published RCTs. While the 5.0 guideline involved processes such as detailed literature searches, data extraction, and meta-analyses to generate recommendations, the 5.1 version focused on integrating high-quality, large-scale RCTs that directly addressed the revised and new key questions. The updates to version 5.1 included: 1. Revising existing key questions. 2. Adding 2 new key questions to address emerging evidence in the diagnosis, treatment, and management of endometrial cancer. The KSGO Uterine Corpus Cancer Committee developed and refined the key questions through multiple discussions . These key questions were formulated using the Population, Intervention, Comparison, and Outcome (PICO) framework to ensure clinical relevance and applicability. The new and revised key questions focus on addressing recent advancements in treatment modalities, including the integration of immune checkpoint inhibitors and targeted therapies. The recommendations in version 5.1 were based on recent evidence from well-known RCTs directly addressing the updated key questions. Only peer-reviewed RCTs published in English that reported clear outcomes related to the key questions were included. Studies unrelated to endometrial cancer, case reports, observational studies, and duplicate data from overlapping patient populations were also excluded. The quality of evidence supporting the recommendations of this guideline was graded using the levels defined in . Level I evidence represents findings from at least one large, randomized, controlled trial of good methodological quality (with low potential for bias) or meta-analyses of well-conducted randomized trials without heterogeneity. Level II evidence includes small randomized trials, large randomized trials with potential biases, or meta-analyses of such trials with demonstrated heterogeneity. Levels III, IV, and V correspond to progressively lower levels of evidence, ranging from prospective cohort studies (Level III) to retrospective studies, case reports, or expert opinions (Level V). This grading system ensures transparency and reliability in linking recommendations to the strength of underlying evidence. The grades of recommendation were assigned based on the quality of evidence, the balance of benefits and harms, and clinical relevance . Grade A indicates strong evidence of efficacy with substantial clinical benefit, and such interventions are strongly recommended. Grade B signifies strong or moderate evidence of efficacy, although with limited clinical benefit, making the intervention generally recommended. Grade C is applied when there is insufficient evidence for efficacy or when benefits do not clearly outweigh risks, making the intervention optional. Grade D indicates moderate evidence against efficacy or concerns for adverse outcomes, resulting in a general recommendation against intervention. Grade E reflects strong evidence against efficacy or significant adverse outcomes, with interventions never being recommended. This grading system provides clinicians with clear evidence-based guidance for informed decision making in clinical practice. The final recommendations were formulated and agreed upon by the KSGO Uterine Corpus Cancer Committee. Multiple rounds of discussion were conducted to resolve differences in the interpretation or application of the evidence. All recommendations were finalized during the consensus meeting of committee members. 1. KQ1. Does combination therapy with trabectedin improve the survival of patients with metastatic or recurrent unresectable leiomyosarcoma? One randomized phase 3 clinical trial was included in the analysis for this key question. The LMS-04 trial by Pautier et al. in 2024 provided primary evidence to support the efficacy of trabectedin. This multicenter, randomized, open-label, phase 3 trial was conducted across 20 centers in France and compared doxorubicin monotherapy with doxorubicin plus trabectedin, followed by trabectedin maintenance therapy, in patients with metastatic or unresectable leiomyosarcoma. Randomization was stratified based on the tumor origin (uterine vs. soft tissue) and disease stage (locally advanced vs. metastatic). Progression-free survival (PFS) & overall survival (OS) The LMS-04 trial enrolled 150 patients, with 74 randomized to the doxorubicin–trabectedin group and 76 to the doxorubicin group. The median PFS was significantly longer in the doxorubicin-trabectedin group (12 months; 95% confidence interval [CI]=10–16) than in the doxorubicin group (6 months; 95% CI=4–7), with an adjusted hazard ratio (HR) for progression or death of 0.37 (95% CI=0.26–0.53). Similarly, the median OS was significantly improved in the doxorubicin-trabectedin group (33 months; 95% CI=26–48) compared to the doxorubicin group (24 months; 95% CI=19–31), with an adjusted HR for death of 0.65 (95% CI=0.44–0.95). Adverse events (grade 3≤) Adverse events of grade 3 or higher were more frequent in the doxorubicin–trabectedin group (97%) than in the doxorubicin group (56%). Common adverse events in the doxorubicin-trabectedin group included neutropenia, anemia, thrombocytopenia, and febrile neutropenia. Despite the higher toxicity, 81% of the patients in the combination group completed all 6 cycles of induction therapy. Although no treatment-related deaths were reported in the doxorubicin-trabectedin group, 1 treatment-related death occurred in the doxorubicin group, as detailed in the study. Based on the above results, the following was recommended: Doxorubicin/trabectedin combination therapy is recommended as first-line treatment for patients with metastatic, recurrent, or unresectable leiomyosarcoma to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) 2. KQ2. Does combination therapy with immune checkpoint inhibitors and PARP inhibitors improve the survival of patients with metastatic or recurrent endometrial cancer? One randomized phase 3 clinical trial was included in the analysis for this key question. The DUO-E trial, published by Westin et al. in 2024 , served as the primary evidence supporting the efficacy of combination therapy with immune checkpoint inhibitors and PARP inhibitors. This multicenter, randomized, open-label Phase 3 trial was conducted across 20 centers in France and compared doxorubicin monotherapy with doxorubicin plus durvalumab, followed by maintenance durvalumab with or without olaparib, in patients with metastatic or unresectable endometrial cancer. Randomization was stratified based on the tumor origin (uterine vs. soft tissue) and disease stage (locally advanced vs. metastatic). PFS & OS The DUO-E trial enrolled 718 patients, with 239 randomized to the durvalumab + olaparib arm, 238 to the durvalumab arm, and 241 to the control arm. The median PFS was significantly longer in the durvalumab + olaparib group (15.1 months; 95% CI=12.6–20.7) compared to the control group (9.6 months; 95% CI=9.0–9.9), with an adjusted hazard ratio for progression or death of 0.55 (95% CI=0.43–0.69). The trial also reported a positive trend in OS, favoring the durvalumab + olaparib arm. The HR for death was 0.59 (95% CI=0.42–0.83; p=0.003) compared to the control arm. However, the OS data were not fully mature at the time of the analysis. The interim results suggested a potential survival benefit with combination therapy, but further follow-up is required to confirm these findings. Adverse events (grade 3≤) Grade 3≤ adverse events were more frequent in the durvalumab + olaparib group (67.2%) than in the control group (56.4%). During the maintenance phase, the frequency of grade 3 or higher adverse events was notably higher in the durvalumab + olaparib group (41.1%) than that in the control group (16.6%). The most common grade 3 or higher adverse events in the durvalumab + olaparib group included neutropenia (26.0%) and anemia (23.5%), whereas the control group reported neutropenia (23.3%) and anemia (14.4%) as the most frequent events. Serious adverse events were observed in 35.7% of patients in the durvalumab + olaparib group compared with 30.9% in the control group. Fatal adverse events occurred in 2.1% and 3.4% of patients in the durvalumab + olaparib and control groups, respectively. Notably, rare but significant adverse events, such as pneumonitis (5.0%) and pure red cell aplasia (1.6%), were reported in the durvalumab + olaparib group, some of which led to treatment discontinuation. The rate of treatment discontinuation due to adverse events was higher in the durvalumab + olaparib group (24.4%) than that in the control group (18.6%). Most adverse events were managed with dose modifications. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and PARP inhibitors is recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: B, Consensus) 3. KQ3. Does combination therapy with immune checkpoint inhibitors improve survival in patients with advanced or recurrent endometrial cancer? Two randomized phase 3 clinical trials were included in the analysis of this key question. The NRG-GY018 trial and RUBY trial provided substantial evidence supporting the use of immune checkpoint inhibitors in combination with chemotherapy for advanced or recurrent endometrial cancer. The NRG-GY018 trial evaluated pembrolizumab combined with carboplatin and paclitaxel versus placebo plus carboplatin and paclitaxel in a global double-blind randomized trial . The study enrolled 816 patients stratified according to their mismatch repair (MMR) status. The RUBY trial assessed dostarlimab in combination with carboplatin and paclitaxel compared with placebo plus carboplatin and paclitaxel in 494 patients, similarly stratified based on MMR status . PFS & OS In the NRG-GY018 trial, pembrolizumab plus chemotherapy demonstrated significant PFS benefits in both deficient and proficient mismatch repairs (dMMR and pMMR) subgroups . Patients with dMMR tumors experienced significant PFS benefits with pembrolizumab plus chemotherapy (median PFS not reached vs. 7.6 months; HR=0.30; 95% CI=0.19–0.48) compared to the control group. In the pMMR population, the combination therapy demonstrated a median PFS of 13.1 months (95% CI=10.8–15.4) compared to 8.7 months (95% CI=7.5–10.1) in the control group (HR=0.54; 95% CI=0.41–0.71). In the RUBY trial, dostarlimab plus chemotherapy demonstrated significant PFS improvements across the overall population and the dMMR and pMMR subgroups . In the overall population, the 24-month PFS rate was 36.1% (95% CI=29.3–42.9) in the dostarlimab group compared with 18.1% (95% CI=13.0–23.9) in the placebo group, with a HR of 0.64 (95% CI=0.51–0.80; p<0.001). Among patients with dMMR tumors, the 24-month PFS rate was 61.4% (95% CI=46.3–73.4) in the dostarlimab group and 15.7% (95% CI=7.2–27.0) in the placebo group (HR=0.28; 95% CI=0.16–0.50; p<0.001). In the pMMR subgroup, the 24-month PFS rate was 28.4% (95% CI=21.2–36.0) in the dostarlimab group compared with 18.8% (95% CI=12.8–25.7) in the placebo group, with an HR of 0.76 (95% CI=0.59–0.98; p=0.033). The NRG-GY018 trial did not report mature OS data at the time of publication. Although PFS results provided strong evidence for pembrolizumab efficacy, OS data were pending and are expected in future analyses . In contrast, the RUBY trial provided updated OS data, demonstrating significant improvements in the dostarlimab plus chemotherapy group across the overall population and dMMR subgroup . In the overall population, the 24-month OS rate was 70.1% (95% CI=63.8–75.5) in the dostarlimab group compared with 54.3% (95% CI=47.8–60.3) in the placebo group, with a HR of 0.69 (95% CI=0.54–0.89; p=0.002). Among patients with dMMR tumors, the 24-month OS rate was 82.8% (95% CI=69.5–90.7) in the dostarlimab group and 57.5% (95% CI=44.4–68.6) in the placebo group (HR=0.32; 95% CI=0.17–0.63; nominal p=0.0002). In the pMMR subgroup, the OS benefit was less pronounced, with a 24-month OS rate of 66.5% (95% CI=59.2–72.8) in the dostarlimab group compared with 53.2% (95% CI=45.6–60.2) in the placebo group (HR=0.79; 95% CI=0.60–1.04; nominal p=0.0493). Adverse events (grade 3≤) In the NRG-GY018 trial, the incidence of grade 3 or higher adverse events was higher in the pembrolizumab plus chemotherapy group than in the placebo plus chemotherapy group in both the dMMR and pMMR cohorts . In the dMMR cohort, 63.3% of patients in the pembrolizumab group experienced grade 3 or higher adverse events compared to 47.2% in the placebo group. Common grade 3 or higher adverse events included anemia and neutropenia. Anemia occurred in 19.3% of patients in the pembrolizumab group compared to 10.4% in the placebo group, while neutropenia was observed at a lower rate in the pembrolizumab group (11.9%) than in the placebo group (17.0%). This unexpected trend did not appear to affect the overall safety profile of the treatment. In the RUBY trial, the incidence of grade 3 or higher adverse events was also higher in the dostarlimab plus chemotherapy group than in the placebo group . Among the overall population, 72.2% of patients in the dostarlimab group experienced grade 3 or higher adverse events compared with 60.2% in the placebo group. Anemia was reported in 14.9% of patients in the dostarlimab group compared to 16.7% in the placebo group, while neutropenia occurred in 9.5% of patients in the dostarlimab group compared to 9.3% in the placebo group. Both trials showed that the addition of immune checkpoint inhibitors to chemotherapy increased the incidence of grade 3 or higher adverse events. However, these events were generally manageable with standard supportive care and no unexpected safety signals were identified. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and chemotherapy is strongly recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) One randomized phase 3 clinical trial was included in the analysis for this key question. The LMS-04 trial by Pautier et al. in 2024 provided primary evidence to support the efficacy of trabectedin. This multicenter, randomized, open-label, phase 3 trial was conducted across 20 centers in France and compared doxorubicin monotherapy with doxorubicin plus trabectedin, followed by trabectedin maintenance therapy, in patients with metastatic or unresectable leiomyosarcoma. Randomization was stratified based on the tumor origin (uterine vs. soft tissue) and disease stage (locally advanced vs. metastatic). Progression-free survival (PFS) & overall survival (OS) The LMS-04 trial enrolled 150 patients, with 74 randomized to the doxorubicin–trabectedin group and 76 to the doxorubicin group. The median PFS was significantly longer in the doxorubicin-trabectedin group (12 months; 95% confidence interval [CI]=10–16) than in the doxorubicin group (6 months; 95% CI=4–7), with an adjusted hazard ratio (HR) for progression or death of 0.37 (95% CI=0.26–0.53). Similarly, the median OS was significantly improved in the doxorubicin-trabectedin group (33 months; 95% CI=26–48) compared to the doxorubicin group (24 months; 95% CI=19–31), with an adjusted HR for death of 0.65 (95% CI=0.44–0.95). Adverse events (grade 3≤) Adverse events of grade 3 or higher were more frequent in the doxorubicin–trabectedin group (97%) than in the doxorubicin group (56%). Common adverse events in the doxorubicin-trabectedin group included neutropenia, anemia, thrombocytopenia, and febrile neutropenia. Despite the higher toxicity, 81% of the patients in the combination group completed all 6 cycles of induction therapy. Although no treatment-related deaths were reported in the doxorubicin-trabectedin group, 1 treatment-related death occurred in the doxorubicin group, as detailed in the study. Based on the above results, the following was recommended: Doxorubicin/trabectedin combination therapy is recommended as first-line treatment for patients with metastatic, recurrent, or unresectable leiomyosarcoma to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) The LMS-04 trial enrolled 150 patients, with 74 randomized to the doxorubicin–trabectedin group and 76 to the doxorubicin group. The median PFS was significantly longer in the doxorubicin-trabectedin group (12 months; 95% confidence interval [CI]=10–16) than in the doxorubicin group (6 months; 95% CI=4–7), with an adjusted hazard ratio (HR) for progression or death of 0.37 (95% CI=0.26–0.53). Similarly, the median OS was significantly improved in the doxorubicin-trabectedin group (33 months; 95% CI=26–48) compared to the doxorubicin group (24 months; 95% CI=19–31), with an adjusted HR for death of 0.65 (95% CI=0.44–0.95). Adverse events of grade 3 or higher were more frequent in the doxorubicin–trabectedin group (97%) than in the doxorubicin group (56%). Common adverse events in the doxorubicin-trabectedin group included neutropenia, anemia, thrombocytopenia, and febrile neutropenia. Despite the higher toxicity, 81% of the patients in the combination group completed all 6 cycles of induction therapy. Although no treatment-related deaths were reported in the doxorubicin-trabectedin group, 1 treatment-related death occurred in the doxorubicin group, as detailed in the study. Based on the above results, the following was recommended: Doxorubicin/trabectedin combination therapy is recommended as first-line treatment for patients with metastatic, recurrent, or unresectable leiomyosarcoma to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) One randomized phase 3 clinical trial was included in the analysis for this key question. The DUO-E trial, published by Westin et al. in 2024 , served as the primary evidence supporting the efficacy of combination therapy with immune checkpoint inhibitors and PARP inhibitors. This multicenter, randomized, open-label Phase 3 trial was conducted across 20 centers in France and compared doxorubicin monotherapy with doxorubicin plus durvalumab, followed by maintenance durvalumab with or without olaparib, in patients with metastatic or unresectable endometrial cancer. Randomization was stratified based on the tumor origin (uterine vs. soft tissue) and disease stage (locally advanced vs. metastatic). PFS & OS The DUO-E trial enrolled 718 patients, with 239 randomized to the durvalumab + olaparib arm, 238 to the durvalumab arm, and 241 to the control arm. The median PFS was significantly longer in the durvalumab + olaparib group (15.1 months; 95% CI=12.6–20.7) compared to the control group (9.6 months; 95% CI=9.0–9.9), with an adjusted hazard ratio for progression or death of 0.55 (95% CI=0.43–0.69). The trial also reported a positive trend in OS, favoring the durvalumab + olaparib arm. The HR for death was 0.59 (95% CI=0.42–0.83; p=0.003) compared to the control arm. However, the OS data were not fully mature at the time of the analysis. The interim results suggested a potential survival benefit with combination therapy, but further follow-up is required to confirm these findings. Adverse events (grade 3≤) Grade 3≤ adverse events were more frequent in the durvalumab + olaparib group (67.2%) than in the control group (56.4%). During the maintenance phase, the frequency of grade 3 or higher adverse events was notably higher in the durvalumab + olaparib group (41.1%) than that in the control group (16.6%). The most common grade 3 or higher adverse events in the durvalumab + olaparib group included neutropenia (26.0%) and anemia (23.5%), whereas the control group reported neutropenia (23.3%) and anemia (14.4%) as the most frequent events. Serious adverse events were observed in 35.7% of patients in the durvalumab + olaparib group compared with 30.9% in the control group. Fatal adverse events occurred in 2.1% and 3.4% of patients in the durvalumab + olaparib and control groups, respectively. Notably, rare but significant adverse events, such as pneumonitis (5.0%) and pure red cell aplasia (1.6%), were reported in the durvalumab + olaparib group, some of which led to treatment discontinuation. The rate of treatment discontinuation due to adverse events was higher in the durvalumab + olaparib group (24.4%) than that in the control group (18.6%). Most adverse events were managed with dose modifications. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and PARP inhibitors is recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: B, Consensus) The DUO-E trial enrolled 718 patients, with 239 randomized to the durvalumab + olaparib arm, 238 to the durvalumab arm, and 241 to the control arm. The median PFS was significantly longer in the durvalumab + olaparib group (15.1 months; 95% CI=12.6–20.7) compared to the control group (9.6 months; 95% CI=9.0–9.9), with an adjusted hazard ratio for progression or death of 0.55 (95% CI=0.43–0.69). The trial also reported a positive trend in OS, favoring the durvalumab + olaparib arm. The HR for death was 0.59 (95% CI=0.42–0.83; p=0.003) compared to the control arm. However, the OS data were not fully mature at the time of the analysis. The interim results suggested a potential survival benefit with combination therapy, but further follow-up is required to confirm these findings. Grade 3≤ adverse events were more frequent in the durvalumab + olaparib group (67.2%) than in the control group (56.4%). During the maintenance phase, the frequency of grade 3 or higher adverse events was notably higher in the durvalumab + olaparib group (41.1%) than that in the control group (16.6%). The most common grade 3 or higher adverse events in the durvalumab + olaparib group included neutropenia (26.0%) and anemia (23.5%), whereas the control group reported neutropenia (23.3%) and anemia (14.4%) as the most frequent events. Serious adverse events were observed in 35.7% of patients in the durvalumab + olaparib group compared with 30.9% in the control group. Fatal adverse events occurred in 2.1% and 3.4% of patients in the durvalumab + olaparib and control groups, respectively. Notably, rare but significant adverse events, such as pneumonitis (5.0%) and pure red cell aplasia (1.6%), were reported in the durvalumab + olaparib group, some of which led to treatment discontinuation. The rate of treatment discontinuation due to adverse events was higher in the durvalumab + olaparib group (24.4%) than that in the control group (18.6%). Most adverse events were managed with dose modifications. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and PARP inhibitors is recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: B, Consensus) Two randomized phase 3 clinical trials were included in the analysis of this key question. The NRG-GY018 trial and RUBY trial provided substantial evidence supporting the use of immune checkpoint inhibitors in combination with chemotherapy for advanced or recurrent endometrial cancer. The NRG-GY018 trial evaluated pembrolizumab combined with carboplatin and paclitaxel versus placebo plus carboplatin and paclitaxel in a global double-blind randomized trial . The study enrolled 816 patients stratified according to their mismatch repair (MMR) status. The RUBY trial assessed dostarlimab in combination with carboplatin and paclitaxel compared with placebo plus carboplatin and paclitaxel in 494 patients, similarly stratified based on MMR status . PFS & OS In the NRG-GY018 trial, pembrolizumab plus chemotherapy demonstrated significant PFS benefits in both deficient and proficient mismatch repairs (dMMR and pMMR) subgroups . Patients with dMMR tumors experienced significant PFS benefits with pembrolizumab plus chemotherapy (median PFS not reached vs. 7.6 months; HR=0.30; 95% CI=0.19–0.48) compared to the control group. In the pMMR population, the combination therapy demonstrated a median PFS of 13.1 months (95% CI=10.8–15.4) compared to 8.7 months (95% CI=7.5–10.1) in the control group (HR=0.54; 95% CI=0.41–0.71). In the RUBY trial, dostarlimab plus chemotherapy demonstrated significant PFS improvements across the overall population and the dMMR and pMMR subgroups . In the overall population, the 24-month PFS rate was 36.1% (95% CI=29.3–42.9) in the dostarlimab group compared with 18.1% (95% CI=13.0–23.9) in the placebo group, with a HR of 0.64 (95% CI=0.51–0.80; p<0.001). Among patients with dMMR tumors, the 24-month PFS rate was 61.4% (95% CI=46.3–73.4) in the dostarlimab group and 15.7% (95% CI=7.2–27.0) in the placebo group (HR=0.28; 95% CI=0.16–0.50; p<0.001). In the pMMR subgroup, the 24-month PFS rate was 28.4% (95% CI=21.2–36.0) in the dostarlimab group compared with 18.8% (95% CI=12.8–25.7) in the placebo group, with an HR of 0.76 (95% CI=0.59–0.98; p=0.033). The NRG-GY018 trial did not report mature OS data at the time of publication. Although PFS results provided strong evidence for pembrolizumab efficacy, OS data were pending and are expected in future analyses . In contrast, the RUBY trial provided updated OS data, demonstrating significant improvements in the dostarlimab plus chemotherapy group across the overall population and dMMR subgroup . In the overall population, the 24-month OS rate was 70.1% (95% CI=63.8–75.5) in the dostarlimab group compared with 54.3% (95% CI=47.8–60.3) in the placebo group, with a HR of 0.69 (95% CI=0.54–0.89; p=0.002). Among patients with dMMR tumors, the 24-month OS rate was 82.8% (95% CI=69.5–90.7) in the dostarlimab group and 57.5% (95% CI=44.4–68.6) in the placebo group (HR=0.32; 95% CI=0.17–0.63; nominal p=0.0002). In the pMMR subgroup, the OS benefit was less pronounced, with a 24-month OS rate of 66.5% (95% CI=59.2–72.8) in the dostarlimab group compared with 53.2% (95% CI=45.6–60.2) in the placebo group (HR=0.79; 95% CI=0.60–1.04; nominal p=0.0493). Adverse events (grade 3≤) In the NRG-GY018 trial, the incidence of grade 3 or higher adverse events was higher in the pembrolizumab plus chemotherapy group than in the placebo plus chemotherapy group in both the dMMR and pMMR cohorts . In the dMMR cohort, 63.3% of patients in the pembrolizumab group experienced grade 3 or higher adverse events compared to 47.2% in the placebo group. Common grade 3 or higher adverse events included anemia and neutropenia. Anemia occurred in 19.3% of patients in the pembrolizumab group compared to 10.4% in the placebo group, while neutropenia was observed at a lower rate in the pembrolizumab group (11.9%) than in the placebo group (17.0%). This unexpected trend did not appear to affect the overall safety profile of the treatment. In the RUBY trial, the incidence of grade 3 or higher adverse events was also higher in the dostarlimab plus chemotherapy group than in the placebo group . Among the overall population, 72.2% of patients in the dostarlimab group experienced grade 3 or higher adverse events compared with 60.2% in the placebo group. Anemia was reported in 14.9% of patients in the dostarlimab group compared to 16.7% in the placebo group, while neutropenia occurred in 9.5% of patients in the dostarlimab group compared to 9.3% in the placebo group. Both trials showed that the addition of immune checkpoint inhibitors to chemotherapy increased the incidence of grade 3 or higher adverse events. However, these events were generally manageable with standard supportive care and no unexpected safety signals were identified. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and chemotherapy is strongly recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) In the NRG-GY018 trial, pembrolizumab plus chemotherapy demonstrated significant PFS benefits in both deficient and proficient mismatch repairs (dMMR and pMMR) subgroups . Patients with dMMR tumors experienced significant PFS benefits with pembrolizumab plus chemotherapy (median PFS not reached vs. 7.6 months; HR=0.30; 95% CI=0.19–0.48) compared to the control group. In the pMMR population, the combination therapy demonstrated a median PFS of 13.1 months (95% CI=10.8–15.4) compared to 8.7 months (95% CI=7.5–10.1) in the control group (HR=0.54; 95% CI=0.41–0.71). In the RUBY trial, dostarlimab plus chemotherapy demonstrated significant PFS improvements across the overall population and the dMMR and pMMR subgroups . In the overall population, the 24-month PFS rate was 36.1% (95% CI=29.3–42.9) in the dostarlimab group compared with 18.1% (95% CI=13.0–23.9) in the placebo group, with a HR of 0.64 (95% CI=0.51–0.80; p<0.001). Among patients with dMMR tumors, the 24-month PFS rate was 61.4% (95% CI=46.3–73.4) in the dostarlimab group and 15.7% (95% CI=7.2–27.0) in the placebo group (HR=0.28; 95% CI=0.16–0.50; p<0.001). In the pMMR subgroup, the 24-month PFS rate was 28.4% (95% CI=21.2–36.0) in the dostarlimab group compared with 18.8% (95% CI=12.8–25.7) in the placebo group, with an HR of 0.76 (95% CI=0.59–0.98; p=0.033). The NRG-GY018 trial did not report mature OS data at the time of publication. Although PFS results provided strong evidence for pembrolizumab efficacy, OS data were pending and are expected in future analyses . In contrast, the RUBY trial provided updated OS data, demonstrating significant improvements in the dostarlimab plus chemotherapy group across the overall population and dMMR subgroup . In the overall population, the 24-month OS rate was 70.1% (95% CI=63.8–75.5) in the dostarlimab group compared with 54.3% (95% CI=47.8–60.3) in the placebo group, with a HR of 0.69 (95% CI=0.54–0.89; p=0.002). Among patients with dMMR tumors, the 24-month OS rate was 82.8% (95% CI=69.5–90.7) in the dostarlimab group and 57.5% (95% CI=44.4–68.6) in the placebo group (HR=0.32; 95% CI=0.17–0.63; nominal p=0.0002). In the pMMR subgroup, the OS benefit was less pronounced, with a 24-month OS rate of 66.5% (95% CI=59.2–72.8) in the dostarlimab group compared with 53.2% (95% CI=45.6–60.2) in the placebo group (HR=0.79; 95% CI=0.60–1.04; nominal p=0.0493). In the NRG-GY018 trial, the incidence of grade 3 or higher adverse events was higher in the pembrolizumab plus chemotherapy group than in the placebo plus chemotherapy group in both the dMMR and pMMR cohorts . In the dMMR cohort, 63.3% of patients in the pembrolizumab group experienced grade 3 or higher adverse events compared to 47.2% in the placebo group. Common grade 3 or higher adverse events included anemia and neutropenia. Anemia occurred in 19.3% of patients in the pembrolizumab group compared to 10.4% in the placebo group, while neutropenia was observed at a lower rate in the pembrolizumab group (11.9%) than in the placebo group (17.0%). This unexpected trend did not appear to affect the overall safety profile of the treatment. In the RUBY trial, the incidence of grade 3 or higher adverse events was also higher in the dostarlimab plus chemotherapy group than in the placebo group . Among the overall population, 72.2% of patients in the dostarlimab group experienced grade 3 or higher adverse events compared with 60.2% in the placebo group. Anemia was reported in 14.9% of patients in the dostarlimab group compared to 16.7% in the placebo group, while neutropenia occurred in 9.5% of patients in the dostarlimab group compared to 9.3% in the placebo group. Both trials showed that the addition of immune checkpoint inhibitors to chemotherapy increased the incidence of grade 3 or higher adverse events. However, these events were generally manageable with standard supportive care and no unexpected safety signals were identified. Based on the above results, the following was recommended: Combination therapy with immune checkpoint inhibitors and chemotherapy is strongly recommended as first-line treatment for patients with advanced or recurrent endometrial cancer to improve survival outcomes. (Level of Evidence: I, Grade of Recommendation: A, Consensus) The updated version 5.1 of the KSGO guidelines for the management of endometrial cancer reflects significant advancements in clinical evidence and demonstrates an adaptive approach to guideline development tailored to current needs. Unlike the previous version 5.0, which incorporated systematic reviews and meta-analyses as part of its development process, version 5.1 was based primarily on high-quality RCTs. This methodological shift allowed the guidelines to incorporate the most current and robust clinical data, ensuring their relevance in a rapidly evolving therapeutic landscape. Moreover, the recommendations were carefully tailored to align with Korea’s unique medical environment, considering factors such as insurance coverage and treatment accessibility to enhance feasibility. One of the notable updates in version 5.1 is the inclusion of recommendations for trabectedin in the treatment of metastatic or recurrent unresectable leiomyosarcoma. Based on evidence from the LMS-04 trial, doxorubicin/trabectedin combination therapy demonstrated significant improvements in PFS and OS compared to doxorubicin monotherapy . Although combination therapy was associated with a higher frequency of adverse events, these were manageable with supportive care, and the treatment showed substantial clinical benefits. Given its demonstrated efficacy and approval for use as a first-line therapy in Korea under specific indications, this recommendation received strong grade A. The alignment between clinical evidence and practical applicability underscores the importance of integrating this therapy into routine practice for eligible patients. Another major update is the introduction of recommendations for combination therapies involving immune checkpoint inhibitors and PARP inhibitors for advanced or recurrent endometrial cancer. The DUO-E trial provided high-quality evidence that combining durvalumab and olaparib significantly improved PFS with early indications of potential OS benefits . While OS data remain immature, the robust results from this large-scale trial qualify as level I evidence. However, this therapy has received only partial Food and Drug Administration approval for use in dMMR populations and is not yet available in Korea . Consequently, the guideline assigns a grade B recommendation, reflecting the promising efficacy of this combination, while acknowledging the current regulatory and accessibility limitations. This recommendation highlights the potential of biomarker-driven therapies to optimize patient outcomes, while emphasizing the need for further validation and expanded accessibility. Significant revisions have been made to the recommendations for immune checkpoint inhibitors in combination with chemotherapy for advanced or recurrent endometrial cancer. While version 5.0 provided only a weak or conditional recommendation due to limited accessibility in Korea, the updated guidelines strongly recommend (Grade A) pembrolizumab or dostarlimab combined with platinum-based chemotherapy. This shift is supported by new evidence from pivotal RCTs, including the NRG-GY018 and RUBY trials, which demonstrated substantial improvements in both PFS and OS across both dMMR and pMMR populations . The increased availability of these therapies in Korea further supports this recommendation, making them central to modern endometrial cancer treatment. The updated guidelines underscore KSGO’s commitment to integrating emerging global evidence with Korea’s healthcare realities. While recommendations are grounded in high-quality RCTs, their strength was carefully adjusted to reflect domestic factors, such as insurance policies and treatment reimbursement. For instance, the strong recommendation for trabectedin acknowledges its demonstrated efficacy and current approval status in Korea, whereas the general recommendation for durvalumab and olaparib reflects limited domestic accessibility despite robust evidence. By incorporating these updates, version 5.1 addresses critical unmet needs in the management of advanced and recurrent endometrial cancer. The emphasis on evidence-based actionable recommendations ensures that the guidelines remain practical for clinicians while advancing the standard of care. Moving forward, the KSGO remains committed to continuous updates that reflect the latest scientific advancements and adapts to the evolving needs of Korea’s healthcare system. |
Global proteomics reveals pathways of mesenchymal stem cells altered by | 56ae23ea-c4ed-47e1-9a00-ea9dd2640f17 | 11680934 | Biochemistry[mh] | In spite of the tremendous efforts, control of tuberculosis (TB) still remains a challenging task. Moreover, the onset of COVID-19 pandemic in 2020 has negatively impacted the progress made towards TB elimination in the past few years. According to WHO, in 2022, an estimated 10.6 million people fell ill with TB globally, out of which 1.3 million people died due to the disease . Apart from this, one-fourth of the world’s population is infected with dormant M. tb , which is at a lifetime risk of reactivation into active disease . M. tb displays a remarkable tendency to modulate its active metabolic state to dormant state in the host and hides in various unconventional niches evading host immune surveillance, stressful environment as well as antibiotic treatment . Therefore, in order to target these dormant bacteria, there is a need to understand the mechanisms of survival and persistence of dormant M. tb in such unconventional niches. One such niche is bone marrow mesenchymal stem cells (BM-MSCs), wherein bacteria can persist without getting eliminated by anti-TB drugs posing a threat for reactivation – . Our laboratory has previously demonstrated that M. tb when residing inside BM-MSCs was unresponsive to the action of anti-TB drugs as compared to when residing inside THP-1 macrophages, owing to the upregulation of host ABCG2 efflux pumps resulting in an enhanced efflux of the anti-TB drugs . Since, M. tb and other pathogenic organisms are known to hijack host machinery and modulate the host cellular pathways for their own survival advantage, a detailed understanding of such mechanisms/pathways altered in hBM-MSCs by M. tb infection would help us to design novel strategies to target M. tb residing inside hBM-MSCs and eliminate this pathogen reservoir. Several studies have been conducted in macrophages where proteomics-based approach was employed for comprehensive study of the host proteome. Menon et al. have employed quantitative proteomics to understand the importance of lipid metabolism and host defence mechanisms in tackling bacterial infection . Another study has showed that the exposure of mycobacterial cell wall lipids induces differential expression of several proteins in macrophages belonging to immune response, vesicle transport, oxidation and reduction and many more cellular processes . These studies highlight the importance of proteomics-based strategies for the identification of various novel proteins and pathways that help in better understanding of host-pathogen interactions. In this study, we focused on identification of the changes induced by pathogenic M. tb in the proteome of human BM-MSCs to favour its own survival and further protect the pathogen from antibiotic assault and immune response by using global label-free proteomics approach. For this, to identify various proteins and pathways of hBM-MSCs that are modulated specifically with virulent M. tb infection, proteomics study was conducted with hBM-MSCs infected with the virulent as well as the avirulent M. tb strains. It is known that both M. tb H37Rv (virulent) and M. tb H37Ra (avirulent) are closely related strains of mycobacteria which differ mainly in their virulence potential . Despite having equivalent MIC values for anti-TB drugs, these strains differ at their genetic and protein levels . M. tb H37Ra bears a mutation in the phoP gene that encodes for a response regulator of the PhoP/PhoR two-component system. PhoP is essential for the virulence and is known to regulate several downstream genes including ESX-1 secretion system . In the absence of ESX-1 secretion system, the pathogen is unable to release mycobacterial effector proteins into the host which might contribute to its avirulent nature. Moreover, it has been shown that M. tb H37Ra infects lungs and other organs with lower bacterial loads as compared to M. tb H37Rv, which fails to cause disease . Apart from this, it has been previously demonstrated that infection with virulent or avirulent strain of M. tb invokes different expression profile in macrophages, suggesting the existence of different immunity mechanisms . Uncovering the pathways that work differently in the virulent and avirulent infection highlights their importance in the host defence. and thus makes them potential targets for host-directed therapeutic approach for the elimination of the pathogen from the host.
Propagation of hBM-MSCs The hBM-MSCs were procured commercially and were successfully cultured and propagated. The cells achieved a confluency of ~ 80–90% in 6–7 days of revival and it was observed that passaging of the cells at less than 60–70% confluency resulted in extremely slow proliferation of the cells, thereby, suggesting the importance of cell-cell contact during expansion of hBM-MSCs in ex vivo culture. Figure shows the images of the cells during propagation, wherein, long spindle-shaped and flattened cells were observed in the culture dishes, which is a characteristic morphological feature of the mesenchymal stem cells. Figure A represents cells observed at 3–4 days post culturing, whereas Fig. B, represents cells observed after 6–7 days post culturing. It was noted that the cells grew in a healthy manner till passage 2, however, subsequently their growth rate was decreased. Hence, passage 2 cells were employed for all the studies. Confocal microscopy of hBM-MSCs infected with M. tb To verify the infection of cultured hBM-MSCs with M. tb , we performed confocal microscopy to visualize GFP expressing M. tb in hBM-MSCs after infection. Briefly, the cells were infected with M. tb H37Rv-GFP strain by employing the protocol described in the ‘methods’ section. The cells were fixed post infection and were stained with PKH26 dye and DAPI to label the cell membrane and the nucleus of the cells, respectively. It was observed that the bacteria were intracellularly localised inside hBM-MSCs as observed by GFP fluorescence in the cells (Fig. C,D). Thus, this confirmed the localisation of the M. tb inside hBM-MSCs and provided a validation for the infection protocol. Virulent M. tb persists inside hBM-MSCs In order to perform a global proteomics study of hBM-MSCs infected with M. tb , it was required that the sample for proteomics analysis comprised of a high number of M. tb infected viable cells. For this, we conducted a preliminary infection experiment wherein hBM-MSCs were infected with two different MOIs (1:30 and 1:50) and evaluated the percent infection of hBM-MSCs at each of the two MOIs. We observed that an infection with MOI of 1:50 resulted in ~ 62% infection without any significant loss of cellular viability, while an MOI of 1:30 led to ~ 49% infection (Fig. E,F). Since, the aim of the study was to identify the differential proteomic profile of BM-MSCs in response to infection, hence, the MOI of 1:50 for M. tb infection of hBM-MSCs for conducting proteomic study was selected. MSCs have been shown earlier to provide a protective niche to M. tb . It was shown that M. tb possesses the ability to survive and persist inside BM-MSCs by evading the immune surveillance and antibiotic treatment, however, the mechanisms responsible for the same are poorly understood. Therefore, we performed an untargeted global LC-MS/MS based proteomics which would reflect the dynamic state of the cellular proteome and will provide accurate overall protein signatures of a genome. Identifying various host proteins/pathways that are altered in hBM-MSCs by M. tb infection would help in bridging the gaps in the understanding of the mechanism(s) of pathogen’s survival inside hBM-MSCs. Moreover, along with the virulent M. tb strain, we have also employed the avirulent M. tb H37Ra strain to specifically identify the proteins/pathways modulated inside hBM-MSCs upon infection with virulent M. tb. Towards this, a growth kinetic study was carried out for both the strains of M. tb i.e., virulent M. tb H37Rv and aviruent M. tb H37Ra, in order to determine the growth rates of these strains inside hBM-MSCs. It was observed that the virulent M. tb H37Rv strain was able to replicate inside hBM-MSCs till day 4 and thereafter, bacteria remained viable in a non-replicative manner albeit constantly maintaining the bacterial CFU. This observation corroborated with the earlier observation of M. tb reaching a dormant state in hBM-MSCs , . However, the avirulent M. tb H37Ra strain, replicated initially till day 4 inside hBM-MSCs with a subsequent decline in the bacterial CFU from day 6 onwards. At day 10, the avirulent strain exhibited ~ 0.5 log reduced CFU as compared to the virulent strain (Fig. G). Thus, the virulent M. tb is able to adapt more efficiently and remains dormant and in non-replicating state inside hBM-MSCs as compared to the avirulent M. tb , wherein, the host is able to combat the infection as observed by a decline in the CFU of avirulent M. tb . This differential ability of the host can be understood by global proteome profiling of virulent versus avirulent M. tb infected hBM-MSCs to delineate the mechanisms hijacked specifically by virulent M. tb for its own advantage and survival. M. tb infection drives global cellular proteomic remodelling in hBM-MSCs Figure A shows the design of the experimental protocol followed to conduct the proteomics study. We detected 2476 proteins in H37Rv infected hBM-MSCs lysate; whereas 2519 proteins were identified in H37Ra infected hBM-MSC lysate and a total of 2503 proteins were detected in uninfected control sample. This represented ~ 12.5% of the total human proteins that were detected in our investigation. Before further analysis, various statistical models were employed (2D-PCA and correlation matrix) in the study to determine the uniformity, robustness and reproducibility of the protein abundance levels obtained after MS (Fig. B–D) – . Downstream analysis of expressed proteome using amica showed significant reproducibility among the independent replicates. We observed varied global profiles in the protein data sets across different groups ( M. tb H37Rv-infected, M. tb H37Ra-infected and uninfected hBM-MSCs) with less variation among the three independent replicates of a particular group (Fig. B,C). This suggested that the independent replicates were highly reproducible and the overall proteome of the hBM-MSCs altered significantly after infection as compared to uninfected state. As expected, we also observed that the virulent and avirulent strains of the bacteria evoke different protein expression outcomes in the host. After establishing the reproducibility between the replicates, the proteomes of M. tb H37Rv-infected and M. tb H37Ra-infected hBM-MSCs were thoroughly analysed to determine the differentially expressed proteins (DEPs) induced as a result of bacterial infection. For this, three analysis groups were employed, namely, M. tb H37Rv-infected hBM-MSCs versus uninfected hBM-MSCs control (Rv Vs UI), M. tb H37Ra-infected hBM-MSCs versus uninfected hBM-MSCs control (Ra Vs UI) and M. tb H37Rv-infected hBM-MSCs versus M. tb H37Ra-infected hBM-MSCs (Rv Vs Ra) (Supplementary information S1). Critical evaluation of the differentially expressed proteins (DEPs) (> log2FC, pValue < 0.05) by visualizing the volcano plots and unsupervised hierarchical clusters showed notable and reproducible pattern of enriched and depleted proteins (Fig. ). Volcano plots and Heat map analysis for comparison of the relative protein expression profiles amongst the three analysis groups reflected that the levels of majority of the host proteins altered upon virulent M. tb H37Rv infection in hBM-MSCs had decreased expression in comparison to the DEPs of hBM-MSCs infected with avirulent M. tb H37Ra strain (Fig. A–F; Table ). In the Venn diagram-based distribution analysis of differentially expressed proteins (DEPs) among different groups, we found that a total of 200 proteins were altered upon M. tb H37Rv infection as compared to uninfected hBM-MSCs, out of which 72 proteins were overexpressed and 128 proteins had decreased expression (Fig. G,H). However, in the case of M. tb H37Ra-infected hBM-MSCs versus uninfected group, 168 host proteins were found to be altered after infection with avirulent strain of bacteria. Out of these 168 proteins, there were 95 host proteins with increased expression and 73 proteins with decreased expression. Further, comparison of DEPs of M. tb H37Rv infected versus M. tb H37Ra infected hBM-MSCs led to the identification of 141 distinct host proteins whose expression levels were altered exclusively by virulent M. tb infection. Out of these, the expression levels of 33 proteins were increased and the levels of 108 proteins were decreased significantly in the hBM-MSCs. These results clearly indicate that the changes in protein profile after infection with virulent M. tb H37Rv strain as compared to avirulent and uninfected group, were more towards translational inhibition (downregulation of proteome) rather than increased synthesis (upregulation of proteome). Moreover, the Venn diagram depicts the intersection of various DEPs across these groups (Fig. G,H). Thus, these results suggested that virulent M. tb infection reshapes the host machinery and cellular pathways resulting in suppression of the levels of several proteins in order to survive inside the host BM-MSCs. There can be various mechanisms of reduction in protein levels such as activation of ubiquitin mediated protein degradation pathways, epigenetic modifications (histone modification and DNA methylation), regulation of expression by long non-coding RNAs or miRNA, manipulation of mRNA processing, changes in the mRNA stability and degradation etc., which would require further investigations . Gene ontology (GO) and pathway analysis-insights into specific cellular changes in host upon infection To elucidate the functional and biological relevance of the bacterial infection derived DEPs of hBM-MSCs, all the DEPs were subjected to identification of key gene ontology (GO) and pathways that were enriched harboring the DEPs in a statistically significant manner (Supplementary information S2). Clustering of enriched GO and pathways was performed and visualized as Balloon plot. A total of 19 GO and pathways were identified such as amino acid biosynthesis, calcium signaling, cell adhesion, cell adhesion and migration, collagen, extracellular matrix (ECM), host-pathogen interaction, immune response, lipoproteins, mitochondrial electron transport function, mitochondrial function, ROS response, proteases, protein ubiquitination, protein folding, vesicle trafficking, secretory protein transport, translation, and splicing (Fig. A,B). Moreover, it was observed that most of the altered proteins whether it showed increased or decreased expression in any of the infected groups, belonged to the pathways related to host-pathogen interactions, collagen/cell adhesion, immune response, mitochondrial function, lipoproteins, splicing/translation, and vesicle trafficking (Fig. A,B). On further analysis, we observed that in the case of avirulent M. tb H37Ra infected hBM-MSCs versus uninfected hBM-MSCs, proteins belonging to pathways such as ROS response, ubiquitin proteolysis pathway, mitochondrial electron transport function (bioenergetics) and lipoproteins were found to be enriched, whereas proteins of these pathways were either unchanged or exhibited decreased expression in the M. tb H37Rv infected cells versus uninfected cells (Fig. A,B). The enrichment of these specific pathway proteins in host hBM-MSCs infected with avirulent M. tb suggests their involvement in the host mechanisms to kill M. tb H37Ra, whereas, alterations in the levels of these proteins in the virulent M. tb infected hBM-MSCs, further substantiates that these proteins are required by the host cells to combat infection. In the case of analysis group virulent M. tb H37Rv infected hBM-MSCs versus uninfected, it was observed that proteins belonging to pathways related to vesicle trafficking, cell adhesion and migration, collagen, host-pathogen interactions, proteases, protein transport, and mitochondrial function were depleted, which were mostly unchanged in avirulent M. tb infected host cells, again pointing out to the fact that the virulent M. tb infection suppressed various pathways. This was interesting to note that there was an overall shutdown/suppression of the various key pathways by virulent M. tb infection that might act as a possible strategy contributing to the survival of the pathogen in the host cells and cause rewiring of these host immune-protective mechanisms for its own advantage. These enriched GO and pathways were considered as bridges and DEPs were considered as the nodes that connect the bridges. All the DEPs along with their biological role (GO and pathways) that was provided as input to RegNet algorithm (Theomics international Pvt. Ltd.) resulted in the modeling of protein: protein, protein: pathway, and protein: ontology along with the fold change and p-value (Student’s t-test) for each of the DEP. The nodes were coloured according to their log 2 ratios (abundance ratio) for each group. The bridge file output of the algorithm was visualized using Cytoscape v 2.8.3 to resolve the core protein network encompassing the DEPs like IL1B, COL1A1, CTGF, COL1A2, COL3A1, CXCL8, COL5A1, MMP14, MMP13, THBS2, COL12A1, CXCL1, LAMB1, APOE etc., that regulates host-pathogen interaction, immune response, collagen, ECM, cell adhesion and migration, and mitochondrial function (Fig. C–E). The DEPs of pathways such as collagen, ECM, cell adhesion, proteases were strongly clustered and inter-related while host-pathogen interaction and immunity related DEPs formed another strong cluster. Most of the proteins found in ‘Rv Vs UI’ were altered as against their basal levels in uninfected cells suggesting that the proteome profile of hBM-MSCs was severely modulated by M. tb infection (Fig. C) while the same proteins were mostly unchanged in case of infection with avirulent M. tb H37Ra infection (Fig. D). Moreover, in the most critical network analysis group (Rv Vs Ra), the repressed protein nodes were of utmost importance because these proteins were suppressed in the host cells due to M. tb H37Rv infection, but were either unchanged or enriched in M. tb H37Ra infected hBM-MSCs (Fig. E). Therefore, they might represent the specific protein players involved in bacterial killing mechanism by the host. The pathways altered upon infection with virulent M. tb strain were further categorized into seven categories namely, RNA binding/alternate splicing, autophagy/vesicle fusion, ubiquinone synthesis/mitochondrial bioenergetics, metalloproteases, phagosome-endosome fusion, immune response related, and collagen/ECM/cell adhesion (Fig. F). Supplementary information S1 lists the DEPs associated with these pathways. Thus, the proteins regulating these pathways offer a chance for further investigation to target virulent bacteria residing inside the hBM-MSCs. Expression analysis for genes encoding DEPs To experimentally validate the proteomics results, we performed real time PCR analysis. For this, 8 genes namely, cxcl-10 , mmp13 , col1a2 , clecb3 , grem-1 , uqcrh , gpx-1 , and hnrnpk were selected that belonged to five of the majorly altered pathways as given in Fig. F (immunity related pathways, metalloproteases, ECM/collagen/stemness related, mitochondrial bioenergetics and RNA binding/alternate splicing pathway). For the analysis, 1–2 genes were randomly selected from these pathways. For this, the total RNA was isolated from hBM-MSCs infected with virulent/avirulent M. tb strains/uninfected cells and was converted into cDNA by using the protocol mentioned in the ‘methods’ section. Real time PCR was conducted for each sample by employing gene specific primers (Table ) followed by determination of ΔCt values after normalising the Ct values with gapdh and further log2 fold change values were calculated by using ΔΔCt method (Fig. G,H). It was found that the mRNA levels of cxcl-10 , clecb3 , mmp13 and grem-1 were upregulated and the expression levels of uqcrh , col1a2 , gpx-1 and hnrnpk were downregulated in virulent M. tb infected hBM-MSCs as compared to avirulent M. tb infected and uninfected cells (Fig. G,H). The observed fold changes in the mRNA levels of various genes in the virulent M. tb infected cells in comparison to avirulent infected cells were consistent with the protein abundance levels of these genes products in the proteomics results (Fig. H). Hence, these results substantiated our observations that infection with M. tb indeed alters the relative protein quantities in hBM-MSCs.
The hBM-MSCs were procured commercially and were successfully cultured and propagated. The cells achieved a confluency of ~ 80–90% in 6–7 days of revival and it was observed that passaging of the cells at less than 60–70% confluency resulted in extremely slow proliferation of the cells, thereby, suggesting the importance of cell-cell contact during expansion of hBM-MSCs in ex vivo culture. Figure shows the images of the cells during propagation, wherein, long spindle-shaped and flattened cells were observed in the culture dishes, which is a characteristic morphological feature of the mesenchymal stem cells. Figure A represents cells observed at 3–4 days post culturing, whereas Fig. B, represents cells observed after 6–7 days post culturing. It was noted that the cells grew in a healthy manner till passage 2, however, subsequently their growth rate was decreased. Hence, passage 2 cells were employed for all the studies.
M. tb To verify the infection of cultured hBM-MSCs with M. tb , we performed confocal microscopy to visualize GFP expressing M. tb in hBM-MSCs after infection. Briefly, the cells were infected with M. tb H37Rv-GFP strain by employing the protocol described in the ‘methods’ section. The cells were fixed post infection and were stained with PKH26 dye and DAPI to label the cell membrane and the nucleus of the cells, respectively. It was observed that the bacteria were intracellularly localised inside hBM-MSCs as observed by GFP fluorescence in the cells (Fig. C,D). Thus, this confirmed the localisation of the M. tb inside hBM-MSCs and provided a validation for the infection protocol.
M. tb persists inside hBM-MSCs In order to perform a global proteomics study of hBM-MSCs infected with M. tb , it was required that the sample for proteomics analysis comprised of a high number of M. tb infected viable cells. For this, we conducted a preliminary infection experiment wherein hBM-MSCs were infected with two different MOIs (1:30 and 1:50) and evaluated the percent infection of hBM-MSCs at each of the two MOIs. We observed that an infection with MOI of 1:50 resulted in ~ 62% infection without any significant loss of cellular viability, while an MOI of 1:30 led to ~ 49% infection (Fig. E,F). Since, the aim of the study was to identify the differential proteomic profile of BM-MSCs in response to infection, hence, the MOI of 1:50 for M. tb infection of hBM-MSCs for conducting proteomic study was selected. MSCs have been shown earlier to provide a protective niche to M. tb . It was shown that M. tb possesses the ability to survive and persist inside BM-MSCs by evading the immune surveillance and antibiotic treatment, however, the mechanisms responsible for the same are poorly understood. Therefore, we performed an untargeted global LC-MS/MS based proteomics which would reflect the dynamic state of the cellular proteome and will provide accurate overall protein signatures of a genome. Identifying various host proteins/pathways that are altered in hBM-MSCs by M. tb infection would help in bridging the gaps in the understanding of the mechanism(s) of pathogen’s survival inside hBM-MSCs. Moreover, along with the virulent M. tb strain, we have also employed the avirulent M. tb H37Ra strain to specifically identify the proteins/pathways modulated inside hBM-MSCs upon infection with virulent M. tb. Towards this, a growth kinetic study was carried out for both the strains of M. tb i.e., virulent M. tb H37Rv and aviruent M. tb H37Ra, in order to determine the growth rates of these strains inside hBM-MSCs. It was observed that the virulent M. tb H37Rv strain was able to replicate inside hBM-MSCs till day 4 and thereafter, bacteria remained viable in a non-replicative manner albeit constantly maintaining the bacterial CFU. This observation corroborated with the earlier observation of M. tb reaching a dormant state in hBM-MSCs , . However, the avirulent M. tb H37Ra strain, replicated initially till day 4 inside hBM-MSCs with a subsequent decline in the bacterial CFU from day 6 onwards. At day 10, the avirulent strain exhibited ~ 0.5 log reduced CFU as compared to the virulent strain (Fig. G). Thus, the virulent M. tb is able to adapt more efficiently and remains dormant and in non-replicating state inside hBM-MSCs as compared to the avirulent M. tb , wherein, the host is able to combat the infection as observed by a decline in the CFU of avirulent M. tb . This differential ability of the host can be understood by global proteome profiling of virulent versus avirulent M. tb infected hBM-MSCs to delineate the mechanisms hijacked specifically by virulent M. tb for its own advantage and survival.
infection drives global cellular proteomic remodelling in hBM-MSCs Figure A shows the design of the experimental protocol followed to conduct the proteomics study. We detected 2476 proteins in H37Rv infected hBM-MSCs lysate; whereas 2519 proteins were identified in H37Ra infected hBM-MSC lysate and a total of 2503 proteins were detected in uninfected control sample. This represented ~ 12.5% of the total human proteins that were detected in our investigation. Before further analysis, various statistical models were employed (2D-PCA and correlation matrix) in the study to determine the uniformity, robustness and reproducibility of the protein abundance levels obtained after MS (Fig. B–D) – . Downstream analysis of expressed proteome using amica showed significant reproducibility among the independent replicates. We observed varied global profiles in the protein data sets across different groups ( M. tb H37Rv-infected, M. tb H37Ra-infected and uninfected hBM-MSCs) with less variation among the three independent replicates of a particular group (Fig. B,C). This suggested that the independent replicates were highly reproducible and the overall proteome of the hBM-MSCs altered significantly after infection as compared to uninfected state. As expected, we also observed that the virulent and avirulent strains of the bacteria evoke different protein expression outcomes in the host. After establishing the reproducibility between the replicates, the proteomes of M. tb H37Rv-infected and M. tb H37Ra-infected hBM-MSCs were thoroughly analysed to determine the differentially expressed proteins (DEPs) induced as a result of bacterial infection. For this, three analysis groups were employed, namely, M. tb H37Rv-infected hBM-MSCs versus uninfected hBM-MSCs control (Rv Vs UI), M. tb H37Ra-infected hBM-MSCs versus uninfected hBM-MSCs control (Ra Vs UI) and M. tb H37Rv-infected hBM-MSCs versus M. tb H37Ra-infected hBM-MSCs (Rv Vs Ra) (Supplementary information S1). Critical evaluation of the differentially expressed proteins (DEPs) (> log2FC, pValue < 0.05) by visualizing the volcano plots and unsupervised hierarchical clusters showed notable and reproducible pattern of enriched and depleted proteins (Fig. ). Volcano plots and Heat map analysis for comparison of the relative protein expression profiles amongst the three analysis groups reflected that the levels of majority of the host proteins altered upon virulent M. tb H37Rv infection in hBM-MSCs had decreased expression in comparison to the DEPs of hBM-MSCs infected with avirulent M. tb H37Ra strain (Fig. A–F; Table ). In the Venn diagram-based distribution analysis of differentially expressed proteins (DEPs) among different groups, we found that a total of 200 proteins were altered upon M. tb H37Rv infection as compared to uninfected hBM-MSCs, out of which 72 proteins were overexpressed and 128 proteins had decreased expression (Fig. G,H). However, in the case of M. tb H37Ra-infected hBM-MSCs versus uninfected group, 168 host proteins were found to be altered after infection with avirulent strain of bacteria. Out of these 168 proteins, there were 95 host proteins with increased expression and 73 proteins with decreased expression. Further, comparison of DEPs of M. tb H37Rv infected versus M. tb H37Ra infected hBM-MSCs led to the identification of 141 distinct host proteins whose expression levels were altered exclusively by virulent M. tb infection. Out of these, the expression levels of 33 proteins were increased and the levels of 108 proteins were decreased significantly in the hBM-MSCs. These results clearly indicate that the changes in protein profile after infection with virulent M. tb H37Rv strain as compared to avirulent and uninfected group, were more towards translational inhibition (downregulation of proteome) rather than increased synthesis (upregulation of proteome). Moreover, the Venn diagram depicts the intersection of various DEPs across these groups (Fig. G,H). Thus, these results suggested that virulent M. tb infection reshapes the host machinery and cellular pathways resulting in suppression of the levels of several proteins in order to survive inside the host BM-MSCs. There can be various mechanisms of reduction in protein levels such as activation of ubiquitin mediated protein degradation pathways, epigenetic modifications (histone modification and DNA methylation), regulation of expression by long non-coding RNAs or miRNA, manipulation of mRNA processing, changes in the mRNA stability and degradation etc., which would require further investigations .
To elucidate the functional and biological relevance of the bacterial infection derived DEPs of hBM-MSCs, all the DEPs were subjected to identification of key gene ontology (GO) and pathways that were enriched harboring the DEPs in a statistically significant manner (Supplementary information S2). Clustering of enriched GO and pathways was performed and visualized as Balloon plot. A total of 19 GO and pathways were identified such as amino acid biosynthesis, calcium signaling, cell adhesion, cell adhesion and migration, collagen, extracellular matrix (ECM), host-pathogen interaction, immune response, lipoproteins, mitochondrial electron transport function, mitochondrial function, ROS response, proteases, protein ubiquitination, protein folding, vesicle trafficking, secretory protein transport, translation, and splicing (Fig. A,B). Moreover, it was observed that most of the altered proteins whether it showed increased or decreased expression in any of the infected groups, belonged to the pathways related to host-pathogen interactions, collagen/cell adhesion, immune response, mitochondrial function, lipoproteins, splicing/translation, and vesicle trafficking (Fig. A,B). On further analysis, we observed that in the case of avirulent M. tb H37Ra infected hBM-MSCs versus uninfected hBM-MSCs, proteins belonging to pathways such as ROS response, ubiquitin proteolysis pathway, mitochondrial electron transport function (bioenergetics) and lipoproteins were found to be enriched, whereas proteins of these pathways were either unchanged or exhibited decreased expression in the M. tb H37Rv infected cells versus uninfected cells (Fig. A,B). The enrichment of these specific pathway proteins in host hBM-MSCs infected with avirulent M. tb suggests their involvement in the host mechanisms to kill M. tb H37Ra, whereas, alterations in the levels of these proteins in the virulent M. tb infected hBM-MSCs, further substantiates that these proteins are required by the host cells to combat infection. In the case of analysis group virulent M. tb H37Rv infected hBM-MSCs versus uninfected, it was observed that proteins belonging to pathways related to vesicle trafficking, cell adhesion and migration, collagen, host-pathogen interactions, proteases, protein transport, and mitochondrial function were depleted, which were mostly unchanged in avirulent M. tb infected host cells, again pointing out to the fact that the virulent M. tb infection suppressed various pathways. This was interesting to note that there was an overall shutdown/suppression of the various key pathways by virulent M. tb infection that might act as a possible strategy contributing to the survival of the pathogen in the host cells and cause rewiring of these host immune-protective mechanisms for its own advantage. These enriched GO and pathways were considered as bridges and DEPs were considered as the nodes that connect the bridges. All the DEPs along with their biological role (GO and pathways) that was provided as input to RegNet algorithm (Theomics international Pvt. Ltd.) resulted in the modeling of protein: protein, protein: pathway, and protein: ontology along with the fold change and p-value (Student’s t-test) for each of the DEP. The nodes were coloured according to their log 2 ratios (abundance ratio) for each group. The bridge file output of the algorithm was visualized using Cytoscape v 2.8.3 to resolve the core protein network encompassing the DEPs like IL1B, COL1A1, CTGF, COL1A2, COL3A1, CXCL8, COL5A1, MMP14, MMP13, THBS2, COL12A1, CXCL1, LAMB1, APOE etc., that regulates host-pathogen interaction, immune response, collagen, ECM, cell adhesion and migration, and mitochondrial function (Fig. C–E). The DEPs of pathways such as collagen, ECM, cell adhesion, proteases were strongly clustered and inter-related while host-pathogen interaction and immunity related DEPs formed another strong cluster. Most of the proteins found in ‘Rv Vs UI’ were altered as against their basal levels in uninfected cells suggesting that the proteome profile of hBM-MSCs was severely modulated by M. tb infection (Fig. C) while the same proteins were mostly unchanged in case of infection with avirulent M. tb H37Ra infection (Fig. D). Moreover, in the most critical network analysis group (Rv Vs Ra), the repressed protein nodes were of utmost importance because these proteins were suppressed in the host cells due to M. tb H37Rv infection, but were either unchanged or enriched in M. tb H37Ra infected hBM-MSCs (Fig. E). Therefore, they might represent the specific protein players involved in bacterial killing mechanism by the host. The pathways altered upon infection with virulent M. tb strain were further categorized into seven categories namely, RNA binding/alternate splicing, autophagy/vesicle fusion, ubiquinone synthesis/mitochondrial bioenergetics, metalloproteases, phagosome-endosome fusion, immune response related, and collagen/ECM/cell adhesion (Fig. F). Supplementary information S1 lists the DEPs associated with these pathways. Thus, the proteins regulating these pathways offer a chance for further investigation to target virulent bacteria residing inside the hBM-MSCs.
To experimentally validate the proteomics results, we performed real time PCR analysis. For this, 8 genes namely, cxcl-10 , mmp13 , col1a2 , clecb3 , grem-1 , uqcrh , gpx-1 , and hnrnpk were selected that belonged to five of the majorly altered pathways as given in Fig. F (immunity related pathways, metalloproteases, ECM/collagen/stemness related, mitochondrial bioenergetics and RNA binding/alternate splicing pathway). For the analysis, 1–2 genes were randomly selected from these pathways. For this, the total RNA was isolated from hBM-MSCs infected with virulent/avirulent M. tb strains/uninfected cells and was converted into cDNA by using the protocol mentioned in the ‘methods’ section. Real time PCR was conducted for each sample by employing gene specific primers (Table ) followed by determination of ΔCt values after normalising the Ct values with gapdh and further log2 fold change values were calculated by using ΔΔCt method (Fig. G,H). It was found that the mRNA levels of cxcl-10 , clecb3 , mmp13 and grem-1 were upregulated and the expression levels of uqcrh , col1a2 , gpx-1 and hnrnpk were downregulated in virulent M. tb infected hBM-MSCs as compared to avirulent M. tb infected and uninfected cells (Fig. G,H). The observed fold changes in the mRNA levels of various genes in the virulent M. tb infected cells in comparison to avirulent infected cells were consistent with the protein abundance levels of these genes products in the proteomics results (Fig. H). Hence, these results substantiated our observations that infection with M. tb indeed alters the relative protein quantities in hBM-MSCs.
Mycobacterium tuberculosis causes tuberculosis in humans and is one of the most successful pathogens. Its success lies in its ability to withstand the host mounted defences and to also undergo physiological adaptations by switching its metabolic state from active to latent state and vice-versa. Regardless of the presence of effective anti-TB drugs and a vaccine, M. tb continues to remain a global menace. Therefore, to fight the battle against this pathogen, designing of novel improved interventions is imperative. BM-MSCs have been found as a niche for dormant M. tb . However, the mechanism(s) by which the pathogen survives and persists inside these mesenchymal stem cells is poorly understood. Hence, knowledge of the key regulatory pathways/proteins of the host that are hijacked by M. tb post infection for its own persistence would be extremely useful in formulating novel approaches to kill these hidden bacteria and eliminate TB. Thus, in this study, changes in the proteomics profile of hBM-MSCs as a result of infection with virulent M. tb H37Rv/avirulent H37Ra strains was investigated by using a high throughput tandem MS-based proteomics approach. We demonstrated that unlike the virulent M. tb , avirulent strain of the bacteria is susceptible to host-mediated killing pathways and therefore, their viability starts to decline inside hBM-MSCs, however, the former strain continues to persist. This observation was in agreement with other studies, where the authors have demonstrated that the attenuated strain of M. tb gets killed by the action of cathelicidin inside BM-MSCs, whereas M. tb H37Rv could resist and therefore, was able to survive and persist inside these cells . Further, we conducted a label-free MS-based proteomic analysis of M. tb H37Rv-infected, M. tb H37Ra-infected and uninfected hBM-MSCs, separately, where M. tb H37Ra-infected hBM-MSCs and uninfected cells were considered as reference controls for identifying M. tb H37Rv induced specific alterations in hBM-MSCs at the proteome level. It was found that the data generated by LC-MS/MS was reproducible (as assessed by 2D-PCA plot and correlation matrix) across all the three biological replicates of the 3 groups. Various DEPs of hBM-MSCs were identified whose expression levels were altered upon M. tb infection as compared to uninfected control. Further, comparison of DEPs of M. tb H37Rv infected versus M. tb H37Ra infected hBM-MSCs led to the identification of 141 distinct host proteins whose expression levels were altered exclusively by virulent M. tb infection. Out of these, the expression levels of 33 proteins were increased and the levels of 108 proteins were decreased significantly in the hBM-MSCs. Enrichment analysis of GO and pathways harbouring differential proteome revealed that M. tb H37Rv infection when compared to M. tb H37Ra infection causes modulation of host proteins involved in major cellular processes such as RNA binding and splicing, immune response, mitochondrial function, vesicle trafficking, collagen related, ECM/cell adhesion etc. A very large complex network between DEPs was observed suggesting functional inter-connections between various pathways emphasizing on the overall reprogramming of several processes of hBM-MSCs by virulent M. tb for its survival and persistence. Several studies have also demonstrated similar reprogramming and modulations of pathways in macrophage cells (primary host niche) after infection with M. tb . Various mechanistic strategies adopted by the pathogen have also been elucidated based on these studies conducted in infected macrophages such as, downregulation of autophagy, changes in cytoskeleton for pathogen’s movement and dissemination in the host cell and alteration in the cytokine profile of macrophage resulting in reduced innate immune response – . Our study shows that M. tb can manipulate and modulate hBM-MSCs and some of the key pathways and proteins involved in the process are described below. It has been observed that the factors such as, EIF5B, EIF4G2, RPS27, RPS3, SRSF2, SRRM2, HNRNPK, and RNPS1 involved in RNA binding, translation, and splicing process showed significant depletion exclusively upon virulent M. tb infection. EIF4G2 and EIF5B are eukaryotic translation initiation factors that are known to dictate synthesis of proteins involved in various crucial processes . A study showed that low-level of EIF5B is responsible for suppressed cell growth and proliferation and alters the cellular pathways associated with stress responses . Similarly, EIF4G2 silencing also led to cellular growth inhibition, suppression of metastasis and tumorigenesis by inhibiting ERK signalling pathway in the case of hepatocellular carcinomas , signifying the importance of initiation factors in the cell proliferation. We also observed reduced levels of RNA binding factor RPS27, which is known to be associated with several biological processes such as proliferation, apoptosis, protein synthesis, alternate splicing , . Various investigators have shown the involvement of RPS27 in mediating innate immunity by activation of NF-κB signaling pathway , . RPS3, another ribosomal protein, that is induced by oxidative stress and bacterial infection has been shown to be involved in NF-κB mediated transcription of pro-inflammatory cytokines , . Hence, modulation in the expression levels of these proteins suggests that virulent M. tb targets ribosomal proteins to inhibit the host immune defence mechanisms, which is well suited for its survival in this niche. Alternative splicing is another crucial process that has been shown to be altered by various pathogens . Infection of macrophages with virulent M. tb has been shown to affect alternate splicing resulting in various spliced or truncated versions of various genes . We observed a decline in the levels of splicing proteins SRSF2 and SRRM2. The gene encoding for SRSF2 was also found to be downregulated in THP-1 macrophages after M. tb infection . Penn et al. demonstrated physical interaction of splicing proteins including SRSF2 and SRRM2 with M. tb secreted protein Rv1827, highlighting a crucial role of host-pathogen interactions resulting in dynamic reprogramming of the host transcriptome . We also observed that several proteins involved in mitochondrial function and bioenergetics (UQCRH, NDUFA8, SLC25A11, SLC25A4, OXCT-1, GPX-1) were significantly decreased in virulent M. tb infected hBM-MSCs. In the case of macrophages infected with M. tb , a metabolic shift in the host energy metabolism is observed that is directly related to the cellular immune responses against the pathogen invasion , . However, it is known for stem cells that a reduction in oxidative phosphorylation and mitochondrial respiration has been linked with maintenance of their stemness properties and reduced differentiation abilities , . Thus, we believe that virulent M. tb drives hBM-MSCs towards a state of quiescence by maintaining stemness of the cells, reducing cell differentiation and proliferation pathways. Thus, decrease in the proteins involved in oxidative phosphorylation and ATP production appears to be useful for M. tb survival and evasion to keep this host cell niche in an undifferentiated quiescent state. However, further investigations will be required to validate this. In addition to this, we observed that proteins belonging to ECM and collagen family (COL3A1, COL1A2, COL5A1, GREM-1, FBLN-1, THBS2, NID2) were highly altered upon M. tb infection. Previous studies have shown that during host infection, M. tb secretes factors that induce various host matrix metalloproteases to degrade ECM and collagen proteins and thereby, ensures their invasion and establishment of infection inside the cells , . Moreover, it has been known that in mesenchymal stem cells, collagen and ECM proteins regulate their differentiation and proliferation properties – . In our study, we observed that various collagen proteins like COL3A1, COL1A2 were significantly reduced, whereas COL5A1 was enriched. These proteins are known to have a direct role in the differentiation of MSCs, as higher levels of COL3A1 and COL1A2 promote osteogenic differentiation of MSCs , , whereas higher levels of COL5A1 inhibits osteogenic differentiation capacity of the multipotent stem cells . Similarly, we observed high expression of GREM-1 (Gremlin-1) which is an antagonist of BMP (bone morphogenetic protein, involved in osteogenic differentiation of stem cells) . GREM-1 has been demonstrated to inhibit osteogenic differentiation and senescence in stem cells . Apart from this, we observed increase levels of thrombospondin (THBS2), which is known to inhibit osteogenic differentiation and MSCs proliferation – . Moreover, the levels of proteins such as filbulin-1 (FBLN-1) and nidogen-2 (NID2), that induces osteogenic differentiation, were also found to be reduced in our study – . Hence, the specific alterations in these proteins indicated a reduction in the differentiation of stem cells suggesting that the pathogen restricts the stem cells from differentiation and maintains their stemness, keeping them in an undifferentiated state that may be required for its own benefit to survive longer in this BM-MSC niche. However, a further detailed investigation into this phenomenon of M. tb survival will be required. We also observed alterations in the proteins belonging to vesicular trafficking and protein transport. It has been previously demonstrated that autophagy can be an intrinsic mechanism for fusion of mycobacterial phagosome to lysosomes to kill intracellular M. tb . Hence, reducing the autophagy and vesicular trafficking pathways could be a strategy for M. tb to persist in MSCs. Along the same lines, we observed a significant reduction in the expression of RAB5B and RAB5C, which are known regulatory GTPases and function in endocytic pathway of phagocytic cells , . Moreover, various dynein motor proteins involved in vesicle transport (DYNC1I2, DYNLL1) were also found to be decreased in hBM-MSCs upon M. tb infection. These proteins have been earlier shown to be involved in directing phagosomes towards lysosomes, and thus, are involved in promoting phagosome-lysosome fusion and pathogen killing . Moreover, various proteins of vacuolar protein sorting complexes were found to be modulated by M. tb inside hBM-MSCs, such as VPS26A, VPS45, and VPS36. These are known to be involved in autophagy, cargo binding and selectivity and trafficking of vacuolar cargo – . Hence, downregulation of these proteins suggests that M. tb subverts the vesicular trafficking, autophagic response and protein transport for its survival. Additionally, our data showed that proteins involved in immune responses such as CXCL-1, CXCL-6, CXCL-8 and CXCL-10, were increased upon M. tb infection in hBM-MSCs which is in accordance with the vital role of these pro-inflammatory cytokines in fighting against invading pathogens and attracting various immune cells like neutrophils, monocytes, T cells and B cells at the site of injury/inflammation . Therefore, upregulation of these cytokines involved in innate immune response can be directly correlated to the hBM-MSCs response towards bacterial antigens – . Taken together, our analysis revealed that M. tb modifies the host cellular dynamics extensively by altering key regulatory proteins and hijacking major functional pathways for its persistence and survival inside hBM-MSCs. Based on these results, we speculate that M. tb attempts to drive hBM-MSCs towards a state of quiescence by maintaining stemness of the cells, reducing cell differentiation and proliferation pathways; suppressing proteins involved in splicing and translation; and decreasing the intracellular vesicular trafficking and autophagy (Fig. ). We believe that by modulating these host pathways, M. tb creates an inert environment for itself to thrive and perpetuate inside unconventional niche of hBM-MSCs. However, further investigations are needed to confirm these proposed strategies/mechanisms. This is the first study to report the proteomics profile of M. tb infected hBM-MSCs that compares changes in the abundance levels of proteins induced by virulent versus avirulent M. tb infection inside hBM-MSCs. Thus, this study has led to an increased understanding of the changes induced by pathogenic M. tb in the proteome of hBM-MSCs to favour its own survival, which paves the way for design and development of new host-directed therapeutic targets to kill this dormant population of M. tb from the host niches and prevent the problem of TB reactivation.
Bacterial culture and growth conditions M. tb strains (virulent M. tb H37Rv and avirulent M. tb H37Ra, obtained from All India Institute of Medical sciences (AIIMS), Delhi, India from Prof. Jaya Tyagi’s lab) were grown in Middlebrook 7H9 broth medium (Becton Dickinson) supplemented with ADC (Albumin- Dextrose-Catalase) (Becton Dickinson), 0.5% glycerol and 0.2% Tween 80 with constant shaking at 200 rpm, 37 °C. Recombinant M. tb GFP strain was grown in the same conditions in the presence of 25 µg/ml kanamycin. Culturing of cells Human bone marrow mesenchymal stem cells (hBM-MSCs) were procured commercially from Thermo Fisher Scientific (catalog number-A15652) and were propagated in MesenPRO RS ™ basal medium supplemented with MesenPRO RS ™ growth supplement (Gibco, catalog number- 12746012). Briefly, the cells were revived by thawing a stock vial at 37 °C in a humidified 5% CO 2 incubator followed by addition of 1 ml supplemented media to the vial. The contents were transferred to a T-25 flask and incubated at 37 °C in a humidified 5% CO 2 incubator. After 24 h, the culture medium was replaced with fresh media and the cells were cultured for ~ 6–7 days till they reached a confluency of 70–80%. Further, the cells were split (ratio 1:2) in two T-25 flasks after trypsinization with 0.025% trypsin (CTS ™ trypLE ™ select enzyme, Thermo Fisher Scientific). The cells were propagated till passage 2 and then employed for conducting all the experiments. Infection of hBM-MSCs with M. tb The hBM-MSCs were infected with M. tb H37Rv-GFP expressing strain for confocal microscopy studies. hBM-MSCs were seeded on circular coverslips washed with 70% Ethanol and dulbecco’s phosphate buffer saline (DPBS) and were incubated at 37 °C, 5% CO 2 for 16 h. A logarithmic phase culture of M. tb H37Rv-GFP cells was harvested, washed with 7H9 media, and employed for single cell preparation by using a previously published protocol . Subsequently, the hBM-MSCs were infected with M. tb H37Rv-GFP bacteria at an multiplicity of infection (MOI) of 1:10 (hBM-MSCs: bacteria) for 8 h followed by amikacin (200 µg/ml) treatment for 1 h to remove the extracellular bacteria. The cells membrane were then stained with 2 µM PKH26 dye (Merck) for 15 min at room temperature (RT). The cells were then fixed with 4% paraformaldehyde (PFA) for 1 h followed by mounting of the coverslips onto the glass slides by using DAPI (4’,6-diamidino-2-phenylindole) antifade stain (Invitrogen) followed by sealing of the coverslips. The cells were visualized by using Leica TCS SP8 confocal laser scanning microscope (Leica Microsystems). Growth kinetics of M. tb inside hBM-MSCs hBM-MSCs were infected with M. tb H37Rv (virulent) and M. tb H37Ra (avirulent) strains, separately at an MOI of 1:5 by using the protocol as mentioned above and incubated at 37 °C in 5% CO 2 . The bacterial burden inside the cells was evaluated by CFU enumeration at various time points (day 0, 2, 4, 6, and 10). For this, the cells were lysed by the addition of 0.025% sodium dodecyl sulfate (SDS) solution for 15 min at 37 °C and the lysate was subjected to centrifugation at 12,000 rpm for 10 min at 4 °C. The supernatant was discarded and the pellet was resuspended in 100 µl 7H9 medium. Appropriate dilutions of the samples were plated onto 7H11 agar plates and the plates were incubated at 37 °C for 3–4 weeks. Quantification of M. tb infection by using flow cytometry The optimum MOI with highest percentage of infected cells was determined for conducting the proteomics study. Briefly, the hBM-MSCs were grown till passage 2 and seeded in a 6-well plate for overnight at a density of 2 × 10 5 cells/well. The cells were infected with M. tb H37Rv-GFP at different MOIs of 1:30 and 1:50 (hBM-MSCs: bacteria) by employing the protocol as mentioned above. After infection, the cells were retrieved, fixed by using 4% PFA solution for 30 min, and washed with DPBS for further evaluation by FACS for percent infection. The uninfected cells were employed to set voltages for forward scattering (FSC) and side scattering (SSC) in the plot. The infected cells were run at fluorescein iosothiocyanate (FITC) channel to obtain the values of percent infection. The cell viability was also checked by flow cytometer by using 7AAD staining which is a fluorescent marker for determining the cellular viability. For this, the cells were immediately mixed with 2 µl of the staining solution before acquisition in the flow cytometer. The cell counts were also determined by trypan blue staining. Label free mass spectrometry based proteomics The hBM-MSCs were seeded in a 6 well flat bottom plate at a density of 1 × 10 6 cells per well in triplicates (independent triplicates from 3 different passages of cells) and were infected with M. tb H37Rv and M. tb H37Ra cells, separately at an MOI of 1:50 (hBM-MSC: bacteria) for 48 h at 37 °C in a humidified 5% CO 2 atmosphere. After 48 h of infection, culture medium was aspirated from each well. Uninfected hBM-MSCs were employed as control. All wells were washed with 1 ml DPBS to remove any residual media components. The adherent cells were scraped and resuspended in G-buffer [0.1 M tris (pH 8.5) and 6 M guanidine hydrochloride] preheated at 70 °C, supplemented with 1X protease inhibitor cocktail (Roche). The lysed cell mixture was subjected to centrifugation at 14,000 rpm for 10 min at RT. The supernatant containing all the cellular proteins was collected, quantified and ~ 100 µg of protein sample was employed for proteome analysis. For performing mass spectrometry, proteins in the cell lysates were reduced with 20 mM dithiothreitol (DTT) and incubated at 95 °C for 10 min. Further, the sample was alkylated with 40 mM iodoacetamide in dark for 30 min to block free cysteine residues. The alkylation reaction was quenched by adding 10 mM DTT. Trypsin was added at a ratio of 1:50 (trypsin: lysate) and the samples were incubated at 37 °C overnight. Digested sample was cleaned by using a C18 silica cartridge column to remove the salt followed by drying using a speed vac vacuum concentrator at RT. Peptides (~ 2 µg) from each sample were analyzed by reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer (Thermo Fisher Scientific). Samples were loaded onto a packed 75 cm x 50 cm PepMap RSLC C18 2 μm column (Thermo fisher scientific) by using mobile phase A (2% Acetonitrile + 98% water with 0.1% Formic acid) and mobile phase B (80% Acetonitrile + 20% water with 0.1% Formic acid). All samples were eluted from the analytical column at a flow rate of 300 nL/min by using a linear gradient of 5% solvent B to 45% solvent B over a duration of 104 min, followed by linear gradient of 45–90% of solvent B for 1 min. The column was regenerated by washing with 90% solvent B for 10 min and re-equilibrated with 5% solvent B for 3 min. Mass spectrometry data was acquired by using a data-dependent acquisition procedure and intact peptides were detected in the orbitrap at a resolution of 70,000 and a scan range of 350 − 2000 m/z. Peptides were selected for MS/MS and ion fragments were detected in the orbitrap at a resolution of 17,500 in a scan range of 200−2000 m/z. Quantitative and qualitative identification of all the expressed proteins upon infection was performed using Proteome Discoverer 2.4 (Thermo Fisher Scientific). The output file with protein levels represented by Sequest HT along with its annotation from UNIPROT database (for Homo sapiens , 202,195 entries, October 2021) was subjected to normalization and differential proteome identification. Trypsin was employed as a protease with a maximum of two missed cleavage sites allowed. The mass tolerance for peptides was set to 10ppm and mass tolerance for fragment ions was set to 20mmu. Carbamidomethylation of cysteines was used as fixed modification, and oxidation of methionines, acetylation of lysine and histidine were used as variable modification. Peptides with only high confidence (target peptide FDR- 0.01) were used and minimum of one unique peptide was considered for successful protein identification. Quantitative proteomics analysis was carried out by using amica web-based tool for quality control, differential expression, biological network and over-representation analysis. The replicate experiment data was analyzed for reproducibility by PCA and unsupervised correlation condition tree. Further, the differential proteome analysis was performed by comparing infected with uninfected proteome as well as Rv infected proteome with Ra infected proteome profiles. edgeR was used to perform DPA (differential proteome analysis) with a fold change of 2 and above with a FDR (false discovery rate) of pValue < 0.05. Unsupervised hierarchical clustering of DEPs was performed by using Cluster 3.0 and visualized using java tree view to identify the up and down-regulated protein clusters across the conditions compared. The DEPs were also visualized using volcano plot to understand the magnitude of change in protein expression as induction or repression. The DEPs were further subjected to GO and pathway analysis using DAVID online tool with a FDR criterion of pValue < 0.05 to identify enriched pathways and gene ontology categories. SRPlot was used to plot the DEP results for better understanding of the experimental changes. Statistically significant and biologically relevant gene ontology terms and pathways along with protein-protein interaction data of the DEPs were provided as input to RegNet al.gorithm (Theomics International Pvt. Ltd.). RegNet algorithm identifies the connecting nodes and edges from the raw input and derives the list of connections (gene-pathway-condition), enriched in the overall experiment. Further, this information was provided as an input to CytoScape V 2.8.2 (National Institute of General Medical Sciences by National Institutes of Health) to visualize the network. Force-directed spring-embedded layout algorithm was applied to the network and nodes were sized based on their connectivity score with larger nodes bearing the highest score. Real-time PCR Total RNA was isolated from all the three groups employed in the study ( M. tb H37Rv infected hBM-MSCs, M. tb H37Ra infected hBM-MSCs and uninfected hBM-MSCs) by using Direct-zol RNA Miniprep kit (Zymo research) as per the manufacturer’s protocol. Briefly, 1 ml TRIzol reagent (Invitrogen) was added into the wells to lyse the cells followed by loading of the entire lysate onto the RNA columns. The columns were washed by using RNA pre-wash and the samples were eluted from the columns in DNA/RNA-free water. The integrity of RNA was evaluated by using nano-drop machine. Total RNA (~ 2 µg) was converted to cDNA by using SuperScript IV VILO reverse transcription kit (Thermo Fisher Scientific) according to the manufacturer’s protocol and gene specific primers for all the candidate genes were designed by using ‘Primer 3’ software (the primer sequences are mentioned in Table ). Primers were procured (Merck) and the real time PCR reaction assays were performed in a total reaction volume of 10 µl by using PowerUp SYBR Green Master Mix (Applied Biosystems). The qPCR cycles were carried out under standard cycling conditions (stage 1: initial denaturation at 95 °C for 10 min, stage 2: consisting of 40 cycles of denaturation at 95 °C, for 15 s followed by annealing, extension and fluorescence reading at 60 °C for 1 min and stage 3: hold at 4 °C). The experiment was performed by using independent replicates. The gene expression in each group was normalized to GAPDH and the data is represented as ∆Ct values. The differential expression was analyzed by using the ∆∆Ct method and relative expression level (log2 fold change) of various genes was plotted. Statistical significance MS-based proteome analysis were performed for three groups ( M. tb H37Rv infected hBM-MSCs, M. tb H37Ra cells infected hBM-MSCs and uninfected cells) separately in three independent replicates. The total of nine samples were processed and analyzed by a reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer. Further, qualitative and quantitative identification of all the expressed proteins was performed using Proteome Discoverer (version 2.0) and amica web-based tool. edgeR was used for differential proteome analysis, GO and pathway analysis was performed using DAVID online tool and protein-protein interaction was studied using RegNet algorithm. Statistical significance was performed by using Student’s t test and a fold change of 2 and above with a false discovery rate of p Value < 0.05 was defined as cutoff in all analyses. The growth kinetics of M. tb H37Rv and M. tb H37Ra was analysed by plotting a graph using GraphPad Prism. The data is represented as the mean ± SEM (error bars) of at least two independent experiments (*, p < 0.05; (**, p < 0.01; ***, p < 0.001, two-way ANOVA, Bonferroni post-tests).
M. tb strains (virulent M. tb H37Rv and avirulent M. tb H37Ra, obtained from All India Institute of Medical sciences (AIIMS), Delhi, India from Prof. Jaya Tyagi’s lab) were grown in Middlebrook 7H9 broth medium (Becton Dickinson) supplemented with ADC (Albumin- Dextrose-Catalase) (Becton Dickinson), 0.5% glycerol and 0.2% Tween 80 with constant shaking at 200 rpm, 37 °C. Recombinant M. tb GFP strain was grown in the same conditions in the presence of 25 µg/ml kanamycin.
Human bone marrow mesenchymal stem cells (hBM-MSCs) were procured commercially from Thermo Fisher Scientific (catalog number-A15652) and were propagated in MesenPRO RS ™ basal medium supplemented with MesenPRO RS ™ growth supplement (Gibco, catalog number- 12746012). Briefly, the cells were revived by thawing a stock vial at 37 °C in a humidified 5% CO 2 incubator followed by addition of 1 ml supplemented media to the vial. The contents were transferred to a T-25 flask and incubated at 37 °C in a humidified 5% CO 2 incubator. After 24 h, the culture medium was replaced with fresh media and the cells were cultured for ~ 6–7 days till they reached a confluency of 70–80%. Further, the cells were split (ratio 1:2) in two T-25 flasks after trypsinization with 0.025% trypsin (CTS ™ trypLE ™ select enzyme, Thermo Fisher Scientific). The cells were propagated till passage 2 and then employed for conducting all the experiments.
M. tb The hBM-MSCs were infected with M. tb H37Rv-GFP expressing strain for confocal microscopy studies. hBM-MSCs were seeded on circular coverslips washed with 70% Ethanol and dulbecco’s phosphate buffer saline (DPBS) and were incubated at 37 °C, 5% CO 2 for 16 h. A logarithmic phase culture of M. tb H37Rv-GFP cells was harvested, washed with 7H9 media, and employed for single cell preparation by using a previously published protocol . Subsequently, the hBM-MSCs were infected with M. tb H37Rv-GFP bacteria at an multiplicity of infection (MOI) of 1:10 (hBM-MSCs: bacteria) for 8 h followed by amikacin (200 µg/ml) treatment for 1 h to remove the extracellular bacteria. The cells membrane were then stained with 2 µM PKH26 dye (Merck) for 15 min at room temperature (RT). The cells were then fixed with 4% paraformaldehyde (PFA) for 1 h followed by mounting of the coverslips onto the glass slides by using DAPI (4’,6-diamidino-2-phenylindole) antifade stain (Invitrogen) followed by sealing of the coverslips. The cells were visualized by using Leica TCS SP8 confocal laser scanning microscope (Leica Microsystems).
M. tb inside hBM-MSCs hBM-MSCs were infected with M. tb H37Rv (virulent) and M. tb H37Ra (avirulent) strains, separately at an MOI of 1:5 by using the protocol as mentioned above and incubated at 37 °C in 5% CO 2 . The bacterial burden inside the cells was evaluated by CFU enumeration at various time points (day 0, 2, 4, 6, and 10). For this, the cells were lysed by the addition of 0.025% sodium dodecyl sulfate (SDS) solution for 15 min at 37 °C and the lysate was subjected to centrifugation at 12,000 rpm for 10 min at 4 °C. The supernatant was discarded and the pellet was resuspended in 100 µl 7H9 medium. Appropriate dilutions of the samples were plated onto 7H11 agar plates and the plates were incubated at 37 °C for 3–4 weeks.
M. tb infection by using flow cytometry The optimum MOI with highest percentage of infected cells was determined for conducting the proteomics study. Briefly, the hBM-MSCs were grown till passage 2 and seeded in a 6-well plate for overnight at a density of 2 × 10 5 cells/well. The cells were infected with M. tb H37Rv-GFP at different MOIs of 1:30 and 1:50 (hBM-MSCs: bacteria) by employing the protocol as mentioned above. After infection, the cells were retrieved, fixed by using 4% PFA solution for 30 min, and washed with DPBS for further evaluation by FACS for percent infection. The uninfected cells were employed to set voltages for forward scattering (FSC) and side scattering (SSC) in the plot. The infected cells were run at fluorescein iosothiocyanate (FITC) channel to obtain the values of percent infection. The cell viability was also checked by flow cytometer by using 7AAD staining which is a fluorescent marker for determining the cellular viability. For this, the cells were immediately mixed with 2 µl of the staining solution before acquisition in the flow cytometer. The cell counts were also determined by trypan blue staining.
The hBM-MSCs were seeded in a 6 well flat bottom plate at a density of 1 × 10 6 cells per well in triplicates (independent triplicates from 3 different passages of cells) and were infected with M. tb H37Rv and M. tb H37Ra cells, separately at an MOI of 1:50 (hBM-MSC: bacteria) for 48 h at 37 °C in a humidified 5% CO 2 atmosphere. After 48 h of infection, culture medium was aspirated from each well. Uninfected hBM-MSCs were employed as control. All wells were washed with 1 ml DPBS to remove any residual media components. The adherent cells were scraped and resuspended in G-buffer [0.1 M tris (pH 8.5) and 6 M guanidine hydrochloride] preheated at 70 °C, supplemented with 1X protease inhibitor cocktail (Roche). The lysed cell mixture was subjected to centrifugation at 14,000 rpm for 10 min at RT. The supernatant containing all the cellular proteins was collected, quantified and ~ 100 µg of protein sample was employed for proteome analysis. For performing mass spectrometry, proteins in the cell lysates were reduced with 20 mM dithiothreitol (DTT) and incubated at 95 °C for 10 min. Further, the sample was alkylated with 40 mM iodoacetamide in dark for 30 min to block free cysteine residues. The alkylation reaction was quenched by adding 10 mM DTT. Trypsin was added at a ratio of 1:50 (trypsin: lysate) and the samples were incubated at 37 °C overnight. Digested sample was cleaned by using a C18 silica cartridge column to remove the salt followed by drying using a speed vac vacuum concentrator at RT. Peptides (~ 2 µg) from each sample were analyzed by reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer (Thermo Fisher Scientific). Samples were loaded onto a packed 75 cm x 50 cm PepMap RSLC C18 2 μm column (Thermo fisher scientific) by using mobile phase A (2% Acetonitrile + 98% water with 0.1% Formic acid) and mobile phase B (80% Acetonitrile + 20% water with 0.1% Formic acid). All samples were eluted from the analytical column at a flow rate of 300 nL/min by using a linear gradient of 5% solvent B to 45% solvent B over a duration of 104 min, followed by linear gradient of 45–90% of solvent B for 1 min. The column was regenerated by washing with 90% solvent B for 10 min and re-equilibrated with 5% solvent B for 3 min. Mass spectrometry data was acquired by using a data-dependent acquisition procedure and intact peptides were detected in the orbitrap at a resolution of 70,000 and a scan range of 350 − 2000 m/z. Peptides were selected for MS/MS and ion fragments were detected in the orbitrap at a resolution of 17,500 in a scan range of 200−2000 m/z. Quantitative and qualitative identification of all the expressed proteins upon infection was performed using Proteome Discoverer 2.4 (Thermo Fisher Scientific). The output file with protein levels represented by Sequest HT along with its annotation from UNIPROT database (for Homo sapiens , 202,195 entries, October 2021) was subjected to normalization and differential proteome identification. Trypsin was employed as a protease with a maximum of two missed cleavage sites allowed. The mass tolerance for peptides was set to 10ppm and mass tolerance for fragment ions was set to 20mmu. Carbamidomethylation of cysteines was used as fixed modification, and oxidation of methionines, acetylation of lysine and histidine were used as variable modification. Peptides with only high confidence (target peptide FDR- 0.01) were used and minimum of one unique peptide was considered for successful protein identification. Quantitative proteomics analysis was carried out by using amica web-based tool for quality control, differential expression, biological network and over-representation analysis. The replicate experiment data was analyzed for reproducibility by PCA and unsupervised correlation condition tree. Further, the differential proteome analysis was performed by comparing infected with uninfected proteome as well as Rv infected proteome with Ra infected proteome profiles. edgeR was used to perform DPA (differential proteome analysis) with a fold change of 2 and above with a FDR (false discovery rate) of pValue < 0.05. Unsupervised hierarchical clustering of DEPs was performed by using Cluster 3.0 and visualized using java tree view to identify the up and down-regulated protein clusters across the conditions compared. The DEPs were also visualized using volcano plot to understand the magnitude of change in protein expression as induction or repression. The DEPs were further subjected to GO and pathway analysis using DAVID online tool with a FDR criterion of pValue < 0.05 to identify enriched pathways and gene ontology categories. SRPlot was used to plot the DEP results for better understanding of the experimental changes. Statistically significant and biologically relevant gene ontology terms and pathways along with protein-protein interaction data of the DEPs were provided as input to RegNet al.gorithm (Theomics International Pvt. Ltd.). RegNet algorithm identifies the connecting nodes and edges from the raw input and derives the list of connections (gene-pathway-condition), enriched in the overall experiment. Further, this information was provided as an input to CytoScape V 2.8.2 (National Institute of General Medical Sciences by National Institutes of Health) to visualize the network. Force-directed spring-embedded layout algorithm was applied to the network and nodes were sized based on their connectivity score with larger nodes bearing the highest score.
Total RNA was isolated from all the three groups employed in the study ( M. tb H37Rv infected hBM-MSCs, M. tb H37Ra infected hBM-MSCs and uninfected hBM-MSCs) by using Direct-zol RNA Miniprep kit (Zymo research) as per the manufacturer’s protocol. Briefly, 1 ml TRIzol reagent (Invitrogen) was added into the wells to lyse the cells followed by loading of the entire lysate onto the RNA columns. The columns were washed by using RNA pre-wash and the samples were eluted from the columns in DNA/RNA-free water. The integrity of RNA was evaluated by using nano-drop machine. Total RNA (~ 2 µg) was converted to cDNA by using SuperScript IV VILO reverse transcription kit (Thermo Fisher Scientific) according to the manufacturer’s protocol and gene specific primers for all the candidate genes were designed by using ‘Primer 3’ software (the primer sequences are mentioned in Table ). Primers were procured (Merck) and the real time PCR reaction assays were performed in a total reaction volume of 10 µl by using PowerUp SYBR Green Master Mix (Applied Biosystems). The qPCR cycles were carried out under standard cycling conditions (stage 1: initial denaturation at 95 °C for 10 min, stage 2: consisting of 40 cycles of denaturation at 95 °C, for 15 s followed by annealing, extension and fluorescence reading at 60 °C for 1 min and stage 3: hold at 4 °C). The experiment was performed by using independent replicates. The gene expression in each group was normalized to GAPDH and the data is represented as ∆Ct values. The differential expression was analyzed by using the ∆∆Ct method and relative expression level (log2 fold change) of various genes was plotted.
MS-based proteome analysis were performed for three groups ( M. tb H37Rv infected hBM-MSCs, M. tb H37Ra cells infected hBM-MSCs and uninfected cells) separately in three independent replicates. The total of nine samples were processed and analyzed by a reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer. Further, qualitative and quantitative identification of all the expressed proteins was performed using Proteome Discoverer (version 2.0) and amica web-based tool. edgeR was used for differential proteome analysis, GO and pathway analysis was performed using DAVID online tool and protein-protein interaction was studied using RegNet algorithm. Statistical significance was performed by using Student’s t test and a fold change of 2 and above with a false discovery rate of p Value < 0.05 was defined as cutoff in all analyses. The growth kinetics of M. tb H37Rv and M. tb H37Ra was analysed by plotting a graph using GraphPad Prism. The data is represented as the mean ± SEM (error bars) of at least two independent experiments (*, p < 0.05; (**, p < 0.01; ***, p < 0.001, two-way ANOVA, Bonferroni post-tests).
Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6 Supplementary Material 7
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Advances in paediatrics in 2019: current practices and challenges in allergy, endocrinology, gastroenterology, public health, neonatology, nutrition, nephrology, neurology, respiratory diseases and rheumatic diseases | 2fc444ae-6a1a-4598-a967-f66338785bfc | 7325159 | Pediatrics[mh] | This paper summarizes main advances that were reported in the field of allergy, endocrinology, gastroenterology, neonatology, nutrition, nephrology, neurology, public health, respiratory diseases and rheumatology over the first semester of 2019 in the Italian Journal of Pediatrics. The most accessed papers have been carefully selected and put in the context of studies that appeared in other journals.
Allergy. 1-food allergy; 2-severe asthma; 3-vernal Keratoconjunctivitis There is a continuous effort to improve the management of allergic diseases. Pathophysiology of food allergy is IgE-mediated, non IgE-mediated (cell-mediated), or mixed (IgE and cell-mediated). Manifestations of IgE-mediated reactions include rhinoconjunctivitis, asthma, rash, angioedema, urticaria, nausea, vomiting, abdominal pain, diarrhea, anaphylaxis. Trigger food is identified by medical history, IgE tests (skin prick tests and/or serum specific IgE antibodies) and oral food challenge that is the gold standard . Avoidance of culprit food is the cornerstone of food allergy treatment. Oral immunotherapy (OIT) to cow’s milk, hen’s egg or peanut allergy is promising. However, it has been shown that OIT is not able to induce total or partial food tolerance in about 30% of children. Furthermore, the frequency of adverse events is high and duration of effectiveness unclear. Crisafulli G et al. investigated the efficacy of add-on therapy with omalizumab a monoclonal anti-IgE antibody during OIT in 5 children with cow’s milk allergy. A combination treatment (OIT plus omalizumab) preceded by a pretreatment with omalizumab in 3 cases, was beneficial in most children and tolerability was good. Omalizumab is that has been approved for the treatment of severe persistent allergic uncontrolled asthma and spontaneous chronic urticaria. It has also been shown to be successful in chronic rhinosinusitis . Among allergies with a mixed (IgE and cell-mediated) pathophysiology, omalizumab could be helpful in improving atopic dermatitis that shares with asthma, inflammatory mediators and the response to allergen immunotherapy but it did not improve eosinophilic esophagitis . In asthmatic children, the prevention of recurrent symptoms is based on long-term therapy and avoidance of triggering factors including aeroallergens, food allergens , physical exercise, passive smoking, pollutants. Asthma control has been shown to be enhanced by communication interventions. However, almost all the asthmatic children are not enough engaged in discussions on management . The SOUND project published a consensus for improving the communication to children and adolescents with severe asthma and their parents . Recommendations are given to physicians on how welcome they have made children and parents. The knowledge of the context would be facilitated by asking questions on goal of the visit, daily life (diet, physical activity, relation with family members and school advancement), by understanding the view of the child, and by using child’s drawings to recognize his thoughts. Advices are given on management of emotions, and on how keeping relationships between the visits. It is recommended to avoid prohibitions since they can cause suffering and undesirably disturb the relationship. Vernal keratoconjunctivitis (VKC) is an underestimate severe seasonal chronic inflammation that can lead to persistent damages . A systematic review has addressed the definition of diagnostic criteria and scoring system. A lack of standards for diagnosis was found. This mainly hampers the differentiation from seasonal allergic conjunctivitis that is often due to grass pollens . This is even more difficult since VKC can coexist with sensitization to seasonal pollens. Furthermore, a great variation in clinical score have been showed. So, continue efforts are needed by the scientific community to have a common language on diagnostic criteria, management and treatment. It is also advisable the development of homogeneous scoring system to be routinely used. Endocrinology. 1- growth in preterm infants; 2- syndrome of inappropriate secretion of antidiuretic hormone; 3- adrenal hemorrhage; 4- type 1 diabetes Since early postnatal growth of preterm infants is an important clue in clinical setting, Zhang et al. studied the postnatal growth patterns in a sample of Chinese healthy late preterm infants. Until they reached a term corrected age. Through bivariate, multivariate linear regression analyses and final stepwise regression models, interesting characteristics of postnatal growth have been assessed. Among the most relevant emerge; an extremely low rate (3%) of weight catch down growth, a prevalent weight (46.2%) vs length (30.7%) catch up growth, a faster postnatal weight and length catch up growth in males versus females, as well as in twins versus singletons, a superior weight growth in SGA and AGA versus LGA infants, and a faster length growth velocity in infants of 36 versus 34 and 35 weeks PMA at birth. The results of this study show a better global postnatal growth pattern in late preterm infants than previously described . Thus, the authors underline the necessity to consider in follow-up studies the difference in feeding and adopted nutrition strategies, as well as regional, local, ethical and traditional factors that can contribute to the divergence in postnatal growth patterns . The acronym SIADH (syndrome of inappropriate secretion of antidiuretic hormone) indicates a non-physiological secretion of ADH as it occurs independently from effective serum osmolality or circulating blood volume that normally regulates it. ADH stimulates water reabsorption through binding to V2 receptors located in the renal tubules, which mediates the concentration of urine, with relative water excess in plasma leading to hyponatremia. Inappropriate antidiuresis may also result from a gain-of-function mutation in its type 2 receptor. Therefore, some Authors prefer to use the term “syndrome of inappropriate antidiuresis (SIAD)” including both situations. SIADH can be idiopathic or due to multiple causes (neurological, pulmonary, malignant diseases, medications, acute conditions as stress, pain, general anesthesia) because various non-osmotic stimuli may cause AVP release. The classic criteria for diagnosis are those found in the clinical case described by Pintaldi et al. (hyponatremia, high urinary osmolarity, high urinary sodium concentration, absence of edema or clinical signs of volume depletion). However, it is important to remember that the diagnosis of SIADH requires a normal renal, cardiac, hepatic, adrenal and thyroid function . In other words, it is a diagnosis of exclusion, In particular, hypothyroidism (extremely rare) and adrenal insufficiency (AI) must be excluded. AI may be due to ACTH/CRH insufficiency (secondary and tertiary form particularly important in patients who present with neurosurgical conditions, such as traumatic brain injury, subarachnoid hemorrhage and intracranial tumors) or due to a primitive alteration of the adrenal gland which could be congenital or acquired . In fact, in the above mentioned clinical case the analysis of the functional parameters of the ACTH / Cortisol axis led to change the initial diagnosis to the final one of an autoimmune adrenalitis (Addison’s disease) which is considered,after the congenital adrenal hyperplasia (CAH), the second more frequent cause of primary AI. Finally, it is interesting to underline the similarities of the case described by Pintaldi with others reported in Literature . In particular, the initial normality of the values of potassium which would be assumed to be high in case of adrenal insufficiency but which were normal, probably due to the vomiting presented by the patients and in addition, the presence of some slight hyperpigmentation of the skin creases and gingival pigmentations which may be useful for diagnostic orientation during clinical evaluation. Neonatal adrenal hemorrhage (NAH) is uncommon (0.2–0.55%) . In most cases is asymptomatic and death is rare . Ultrasonographic examination is commonly performed since it is immediate, accurate and safe . In NAH, according to pathological anatomical evolution, temporal modification of echostructure is highly specific. The hemorrhagic adrenal gland is enlarged and homogeneously hyperechoic in newborns. Subsequently, the lysis of the clot increases hypoechoic structure and after 1 or 2 weeks cystic-colliquative feature emerges. Sometimes, shell calcification then appears . An involuted complex structure small mass, partly calcified without vascularization can residue. NAH can regress without relics in a period ranging from 20 days to 5–6 months. Most neonatal supra-renal masses are identified as congenital neuroblastoma (NBL) or adrenal hemorrhage . The histologic examination of tumor tissue or blood marrow besides elevated levels of catecholamine metabolites in urine or serum, is necessary for diagnosis of NBL. Ultrasonographic examination may be useful in assessing adrenal NBL. NBL may appear as a defined small mass within the adrenal gland or an infiltrative complex mass, lobulated with hemorrhagic zones. It is often solid, occasionally with calcific punctate areas in newborns . In NAH, the calcification appears generally later. Ultrasonography differentiation between cystic NAH and cystic NBL may be difficult, especially when catecholamine metabolite values are low. Color Doppler ultrasound examination seems to have most significance in providing a correct diagnosis. In NAH, a nonvascular flow and a regression of lesion over time are observed . In NBL, blood supply is essential for its own growth. This tumor gives rise to characteristic high velocity Doppler shifts. The usual follow-up time for the resolution of the hemorrhage should be within 90 days. NBL should be suspected if the mass does not resolve in 3 months. Adrenal NBL often spontaneously resolve. Therefore, a watchful waiting rather than an interventional approach is suggested . Hypophosphatemia can be one of the consequences of diabetic acidosis (DKA). In most cases of DKA the decrease in blood levels of phosphates is mild, it is not considered responsible for specific pathologies and it does not require correction as various prospective studies have shown no clinical benefit. Phosphate replacement is instead indicated in the severe forms (blood phosphate levels < 1 mg /dL/0.32 mmol / L) with the appearance of symptoms . They can in fact be responsible for clinical manifestations mainly respiratory, neuromuscular, cardiac and hematologic . As regards the cardiac involvement and in particular the arrhythmias, there are no precise epidemiological data but, on the basis of recent patient series, they appear infrequent compared to other complications . In that context, the clinical case described by Miszczuk et al. is an interesting one in particular in two respects: 1) ventricular bigeminy and trigeminy have not been previously described among arrhythmias and although their origin may be multifactorial the fact that they disappear with the phosphate supplementation indicates an important pathogenetic role; 2) the patient studied had blood levels of phosphate slightly higher than the limit considered diagnostic for severe forms, but a set of elements rightly suggest that an intracellular phosphate depletion had been created in the body. In other words, the intracellular phosphate level is primarily responsible for clinical manifestations. Concerning clinical practice, the recent ISPAD consensus concludes: “although administration of phosphate is associated with a risk of hypocalcemia, an IV solution that contains a 50:50 mixture of potassium phosphate and another suitable potassium salt (potassium chloride or potassium acetate), generally permits adequate phosphate replacement while avoiding clinically significant hypocalcemia.” Mauriac’s syndrome (MS) was initially described in 1930 and it is being characterized by growth failure, delayed puberty, cushingoid appearance, hepatomegaly with abnormal liver enzymes, and hypercholesterolemia. Such a syndrome has been mainly reported in brittle type 1 diabetes (DM1) and very rarely in DM2. In the last few decades, the improvement of diabetes therapy (education, use of insulin and /or its analogues and delivery technology) may have suggested that MS was about the past in the history of diabetes. On the contrary, the most recent reviews in Literature tell us that MS still exists especially in adolescent who do not always accept the rules that a good control of diabetes requires and in patients who live in socially and culturally backward environments where there may be objective difficulties in managing the disease . On the other hand, it should be kept in mind that the hepatomegaly (due to an overloading of hepatocytes with glycogen) represents one of the major signs of MS and it may be the only feature present both in children / adolescents and in adults. It has been defined in various ways: liver glycogen storage, hepatic or liver glycogenosis, DM-associated glycogen storage hepatomegaly and lately “glycogenic hepatopathy” (GH). Real incidence and prevalence of GH are unknown, commonly being misdiagnosed or underdiagnosed . However, if we consider some series of patients, we find that about 10% of diabetic children had hepatic hyperechogeneity decreasing after a period of several months of better adherence to therapy . In other words, hepatomegaly does not seem as rare as generally thought and should be sought in the follow up of diabetic patients. When present, the blood level of transaminases should be assessed, and other causes of liver disease excluded. If there is still a diagnostic doubt, liver biopsy is the gold standard. According to some AA, it would be useful above all to differentiate liver glycogen storage from nonalcoholic fatty liver disease (NAFLD), considering that the former is generally transient and with a benign prognosis while the latter (much more frequent in DM2) can evolve towards forms of cirrhosis and cancer . Global and public health. 1-violence Violence against children, adolescent and young adults shows, all over the world, a dramatic and still unsolved concern for the health, the connected social and legal problems. Globally it is estimated that up to1 billion children aged 2–17 years, have experienced physical, sexual, or emotional violence or neglect in one year (as cited in and that in the WHO European Region violence affects over 55 million victims . That can occur in various forms . In Europe we consider prevalences from 9.6% for sexual abuse, 16.3% for physical neglect, 18.4% for emotional neglect, and 2.9% for physical abuse, to 29.6% for emotional abuse . We must also keep in mind that the general prevalence is often underestimated due to the difficulty in various States for fully collecting data. Numerous studies have then highlighted the long-term consequences of the violence suffered. The victims are in fact at greater risk of developing both chronic diseases and behavioural and relational alterations . There are many factors that can facilitate violence both at an individual level (such as lower levels of education, low income, having a disability or mental health problems) and at community level (such as settings with weak governance and poor law enforcement) and with many of such it is possible to act with an appropriate prevention aimed in particular at family and school which are known to be the places where maltreatment occurs most frequently. On the other hand, the importance of prevention has been considered a priority by WHO which in connection with other international agencies has recently proposed the INSPIRE program ( www.who.int › inspire-package) based on seven strategies towards reducing and eliminating violence against children. With regard to the school environment in particular, many studies and resulting preventive recommendations have taken into consideration bullying or cyberbullying phenomena which are certainly the most frequent. On the basis of the data collected in Italy by Ferrara et al. and of a recent review of the international literature , it is useful to point out that studies about the violent teacher-student relationship are very rare and that this phenomenon, certainly less frequent than the previous one, would deserve greater attention both at the epidemiological level and for establishing setting methods and action to prevent that. Neonatology. 1-preterm birth; 2-infant mortality; 3-vitamin K deficiency; 4-Lotus birth Preterm birth is a public health concern and it represents the leading cause of neonatal mortality . Preterm newborns also present neurological impairment, respiratory, renal and gastrointestinal complications. All these conditions may seriously affect the neurocognitive outcome and cause severe disability. The highest mortality rates of preterm birth have been found in developing countries . In an observational study conducted in Ethiopia, the mortality rate of preterm newborns was 28.8% . Neonatal deaths occurred within the first 24 h in 11.4% of cases and within the first 7 days in 85.23% of instances. Perinatal asphyxia was the major cause of death followed by hyaline membrane disease, jaundice, clinical sepsis and apnoea. Griffin et al. proposed a model for reducing preterm mortality based on WHO recommendations. He pointed out that combined interventions lead to the greatest impact on preterm mortality. The most effective single interventions are oxygen/CPAP, cord care, breastfeeding, and antibiotics. New efforts are needed to prompt identify potential preterm births in order to provide a proper intervention. Granese R et al. found that vaginal/urinary infections, underweight, obesity, unmarried status, uterine anomalies, poly/oligohydramnios, hypertension, diabetes, a history of preterm birth and a short cervix length in the second trimester were the main risk factors for preterm birth. Of note, a short cervix predicted early preterm and very early preterm delivery while the other factors should be considered in late preterm cases. This study indicates that cervix length evaluation during the midtrimester should be performed not only in women at high risk of preterm birth but in all cases since it may early detect high-risk pregnancies and guarantee progesterone administration that diminishes the risk of preterm birth and reduces neonatal morbidity. Socioeconomical factors and health development play a role in the neonatal mortality. In Italy, the overall neonatal mortality rate is 2 per one thousand live births, that is one of the lowest infant mortality rates of all countries. However, there still are differences among areas of the country (North-Centre-South) that should be linked to inadequate care level and organization of perinatal care . Of note, mortality index among immigrants were higher than among Italians. Accordingly, in England ethnic minority newborns had twice risk of adverse events at birth than British infants . Several explanations may be offered to explain these findings. This could be associated with socioeconomical conditions. Language and cultural differences between minority and majority groups can create barriers to access or benefit from information. Newborns, whose parents have a low level of education, are more likely to die in early life . The late onset type of vitamin K deficiency can occur with cerebral haemorrhage. Ceratto and Savino reported a healthy newborn who developed intracranial bleeding due to vitamin K deficiency at the end of the first week of life. She received oral vitamin K at birth because she had no risk factor. These findings can suggest that intramuscular vitamin K may be useful for all newborns because of unpredictable risk factors at birth (malabsorption or cholestasis) other than preterm birth . The American Academy of Pediatrics, the Canadian Pediatric Society and the ESPGHAN Committee on Nutrition recommend the intramuscular administration of the first dose of vitamin K at birth since it would be linked with less failure mainly for late bleeding than oral route administration, due to minor abnormalities of absorption . In many countries, national recommendations on this issue are lacking. There is a need of consistent indications about optimal dose and routes of administration of vitamin K prophylaxis in newborns. Lotus birth is the practice of umbilical nonseverance, leaving the umbilical cord and the placenta intact and attached until it detaches spontaneously after 3–10 days. Meanwhile, the placenta is put in a bowl with salt and herbs . Clinical risks, bioethical and medico legal aspects of this controversial procedure have been analysed by Bonsignore et al. . From the health side, studies about this particular practice are inconsistent, of poor quality and with small sample. There is no clear evidence that having placenta connected to the baby for many days provides benefits to him/her. On the other hand, there is a potential risk for reduced neonatal perfusion and clot formation. In a recent case report series, no infections occurred after lotus birth and mothers expressed interest in repeat lotus birth in the future . However, the dead tissue attached to the newborn may be affected by bacteria and possible complications related to this practice such as omphalitis or other infections have been described . From the medico-legal side, the question arises whether placenta belongs to the mother or to the baby and no clear statement assess the juridical availability of placenta. Therefore, when the mother requests the placenta, she should be allowed to have it, unless a public health issue arises. Families should be adequately updated about the risk/benefit ratio of Lotus birth and informed forms should be used. Overall, Bonsignore et al. consider Lotus birth inadvisable from both medical and rational point of view. Nutrition. 1-vitamin D; 2-malnutrition Vitamin D subclinical deficiency or insufficiency continue to be a common finding . Vitamin D is useful for bone health and it has been investigated for preventing cancer, cardiovascular disease, type 2 diabetes mellitus, neurologic disorders, autoimmune disorders, infectious disease also by increasing the function of gastrointestinal microbiota which may have a role in preventing infectious diseases . Vitamin D supplementation is a matter of debate. It is usually recommended when children have risk factors for deficiency of vitamin D such as inadequate intake, limited skin exposure to sunlight, dark skin, malabsorption, drug intake (anticonvulsants, systemic glucocorticoids, antiretroviral therapy), liver or kidney diseases, obesity). In Italy, the recommended supplementation in children from 1 to 17 years is 600–1000 IU/day vitamin D3 and children with risk factors should receive 1000–1500/UI vitamin D3 per day . To prevent the deficiency of vitamin D, it was conducted a study on the effect of vitamin D3 1500 IU/day from November to April versus no supplementation . In the intervention group, there was no side effect and the 25-hydroxyvitamin D maximum serum level was 71 ng/ml. In adolescents with vitamin D insufficiency, there was only a slight increase in mean 25-hydroxyvitamin D serum level so it is possible that this age range would receive a higher dose of vitamin D3. No consensus has been reached about the period of the administration of vitamin D supplementation . In this study, the intervention group had normal serum value of 25-hydroxyvitamin D all the year except in May. In the control group vitamin D deficiency were found in 4 months out of 6 at the beginning of the year and vitamin D insufficiency in the other 2 months. So, it would be reasonable to extend vitamin D supplementation. Undernutrition is still a leading cause of morbidity and mortality in children and in some developing countries. Both acute and chronic forms (wasting and stunting) represent a public health challenge. They are strongly inversely correlated with the wealth of nations. In Sub-Saharan Africa and in South Asia , risk factors for wasting and stunting in children are low birth weight, low mother’s BMI, small birth size, low parental education, young mother, increasing child’s age, male, inadequate food supply, unhealthy living environments. In the slums of Nairobi (Kenia), 26.30% of children under 12 months of age was stunted, 6.3% wasted and 13.16% underweight . Wasting was more frequently associated with infectious diseases such as cough and rapid breathing and diarrhea, probably due to the acute loss of weight. Regarding mortality, it has been estimated that 45% of deaths in children under 5 years of age in the world is due to undernutrition . Mid-upper arm circumference (MUAC) and weight-for-height/length Z-score (WHZ) are used to identify children with severe acute malnutrition (SAM) but they are affected by gender, region and age bias . Therefore, the burden of SAM can be higher than that reported. Moreover, SAM is a risk factor for growth retardation and impaired psychosocial and cognitive development. Fikrie et al. studied Ethiopian hospitalized children with malnutrition assessed by mid-upper arm circumference (MUAC), weight-for-height/length Z-score (WHZ), edema. All children presented co-morbidities, including pneumonia, diarrhea, anaemia, tuberculosis. They found that the recovery rate was 69.4%, which was below the minimum accepted international standard of 75% and the mortality rate was 10%. Weight gain and length of staying were in line with the international standard and Ethiopian protocol for management of SAM. These results are concordant with those of a similar research conducted in Northwest Ethiopia . Comorbidities in the enrolled population may elucidate the low recovery rate . Other explanations may be related to therapeutic milk intake and high rates of mortality. Finally, relapse after discharge was 7.1% of all cases. This highlights that standardized protocols for SAM follow-up after discharge are always needed. Nephrology. 1-congenital anomalies; 2-Hypophosphatemic rickets Congenital anomalies of the kidney and urinary tract (CAKUTs) include structural and functional abnormalities of the kidney, collecting system, bladder, and urethral abnormalities, and are some of the most common birth defects in newborns. Li and collaborators conducted a retrospective study in China’s Zhejiang Province, including all births and all ascertained patients with CAKUTs registered from 2010 to 2016. There were enrolled 2790 patients identified among 1,748,038 births . Authors observed that males (OR 1.28, 95% CI 1.18–1.38), multiple births (OR 1.53, 95% CI 1.21–1.92) and births in urban areas (OR 1.27, 95% CI 1.18–1.37) presented a higher risk of CAKUTs. Instead, CAKUTs were poorly associated with maternal age. Overall, 22.69% of births with CAKUTs had associated malformations, especially heart defects. The most frequent CAKUT was hydronephrosis, (31.79%), followed by polycystic kidney, renal agenesis, renal ectopia, and renal duplication. In this study, the prevalence of CAKUTs was much lower than in reports from Copenhagen, Russia, and western areas of Saudi Arabia, maybe explained by differences in sociodemographic background, malformation inclusion criteria. In Murmansk County, a population-based birth registry recorded anomalies diagnosed from 22 weeks of gestation to hospital discharge . Those authors admitted that some figures had been overestimated owing to the lack of strict diagnostic criteria for pyelectasis, hydronephrosis, and unspecified anomalies . In Saudi Arabia, the high rate of consanguineous marriage within the local population might increase the rate of CAKUTs . The study in Denmark followed up a birth cohort for 8 years . Finally, the authors evaluated that the prevalence of CAKUTs doubled from 2010 to 2016, which might be owing to increased screening, developments in ultrasound technology, and improved birth defect surveillance. X-linked hypophosphatemic rickets (XLH) is a rare disease caused by mutations in the PHEX gene, this disease is poorly known, and diagnosis is frequently delayed. Emma et al. collected data by means of a questionnaire on XLH epidemiology, diagnosis and treatment, from 10 Italian centres on 175 patients, followed between 1998 and 2017 . The diagnosis was made before the age of 1 and between 1 and 5 years in 11 and 50% of cases, respectively. Clinically apparent bone deformities were present in 95% of patients. Other frequent complications included bone pain (40%), dental abscesses (33%), and dental malpositions (53%). Treatment protocols varied substantially among centres. Nephrocalcinosis, a complication of conventional treatment, was observed in 34% of patients. Tertiary hyperparathyroidism developed in 6% of patients. Overall, nephrocalcinosis has been reported in the literature in 30–70% of patients . The present study was conducted to evaluate the current status in the diagnosis and treatment of XLH in Italy. Overall, results are in line with available data in the literature, although with some noticeable differences. The prevalence of XLH is estimated between 1.2–3.0/60,000 . In this survey the number is lower than expected, indicating that the disease is either underdiagnosed. Neurology. 1-PANDAS syndrome; 2-headache Guido et al. showed the successful results of the eye movement desensitisation and reprocessing (EMDR) therapy associated with parent management training (PMT) in a 11-year-old boy who presented with simple and complex vocal tics, motor tics, obsessive-compulsive traits and irritability from the age of 6 years, diagnosed as paediatric autoimmune neuropsychiatric disorder associated with streptococcus (PANDAS) . These results indicate the possibility of improving the treatment outcomes of patients with PANDAS by a combined approach using both antibiotic and EMDR therapies. According to the most recent guidelines , elective evidence-based therapies for the treatment of PANDAS include Cognitive Behavioural Therapy, parent training and drug therapy. EMDR therapy had never been utilised before in patients with PANDAS syndrome , this method works on the present and not on the past. The explanatory model underlying these considerations is the Adaptive Information Processing model, in which previously stored dysfunctionally without proper assimilation within of a wider adaptive network present in the patient . Migraine is one of the most prevalent chronic pain manifestations of childhood, affecting up to 10% of children between the ages of 5 and 15 years and up to 28% of adolescents aged from 15 to 19 years . Moreover, parents are often concerned about chronic therapies and even clinicians prefer to avoid prescription of prophylactic therapies in children, due to the poor evidence of efficacy and significant potential adverse effects in this population . Moscano et al. conducted an observational multicenter study performed in 91 children with migraine, with (MO) or without aura (MA), or tension-type headache (TTH) . A fixed-dose of Partena® tablets (a combination of Mg2+ 169 mg, CoQ10 20 mg, VitB2 4,8 mg, Feverfew 150 mg-1,2 mg Parthenolides and Andrographis paniculata 100 mg), was administered for 16 weeks. The herbal supplement significantly reduced the frequency of headaches in TTH patients during treatment period, maintaining the efficacy after 16 weeks of treatment withdrawal. A significant effect was observed also in the MO and MA groups during treatment. These results are according several epidemiologic, preclinical and clinical evidence supporting the usefulness of other active principles of Partena® in prophylactic treatment of migraine currently available in Europe and USA as dietary supplements . The most recent randomized controlled trial, using a stable extract, add some positive evidence about the efficacy of in the prophylactic treatment of migraine . Studies on Feverfew efficacy in children and adolescents with migraine are lacking. Gastroenterology. 1-celiac disease; 2-Alagille syndrome An increased prevalence of celiac disease (CD) has been observed in several cohorts of cystic fibrosis (CF) patients. A recent study indicates that the gluten/gliadin-derived peptide (P31–43) can cause the cystic fibrosis transmembrane conductance regulator (CFTR) channel protein inhibition in intestinal epithelial cells, thus causing a local stress response that contributes to the immunopathology of CD. Mauri et al. speculated that P31–43-induced CFTR inhibition elicits the danger signals that ignite the epithelial stress response and perturb epithelial proteostasis . Importantly, potentiators of CFTR channel gating, such as the FDA-approved drug Ivacaftor, prevent P31–43 driven CFTR inhibition and suppress the gliadin-induced stress response in cells from celiac patients, as well as the immunopathology developing in gliadin-sensitive mice. Altogether these findings demonstrate that gliadin induced CFTR malfunction is at the apex of the pathogenic cascade leading to CD . Paucity of interlobular bile ducts is an important observation at liver biopsy in the diagnostic work-up of neonatal cholestasis. To date, other than in the Alagille syndrome, syndromic paucity of interlobular bile ducts has been documented in four cholestatic neonates with HFN1β mutations. A syndromic phenotype, known as renal cysts and diabetes syndrome (RCAD), has been identified. Pinon et al. reported a novel case of 5-week-old boy affected by paucity of interlobular bile ducts due to an HFN1β defect . He was admitted for cholestatic jaundice with increased gamma-glutamyl transpeptidase and an unremarkable clinical examination, characterized by cholestatic disease, hyperechogenic kidneys with multiple bilateral cortical cysts at ultrasound examination, associated with moderately impaired renal function with proteinuria, polyuria and metabolic acidosis, paucity of interlobular bile ducts at liver biopsy, thus the diagnosis of Alagille syndrome (AGS) was considered, but excluded. Although genetic tests for liver cholestatic diseases were performed with negative results for Alagille syndrome (JAG1 and NOTCH2), a de-novo missense mutation of HNF1β gene was detected. To date, only others 5 cases of neonatal cholestasis are reported in literature as associated to HNF1β mutations, in most cases de-novo deletions, with similar clinical course . HFN1β defects should be considered in neonates with cholestasis and renal impairment, especially in SGA and IUGR newborns with a family history of renal disease or diabetes, in addition to AGS. Respiratory diseases. 1- recurrent wheezing; 2- Bronchopulmonary dysplasia; 3- cystic fibrosis Recurrent wheezing and/or asthma are common chronic respiratory disease in children. Studies have demonstrated that children hospitalized for RSV bronchiolitis during infancy were more likely to have subsequent episodes of wheezing . Also, eosinophil-derived neurotoxin (EDN), contained in eosinophil cytotoxic granule proteins has been considered to be involved in the recurrent wheezing and asthma development in later life . Zhai et al. followed-up for 1-year 145 children of 3 years old or younger, who were hospitalized with wheezing, in order to analyse factors that may predict recurrent wheezing . The authors demonstrated that eczema, respiratory syncytial virus (RSV) infection, eosinophil count and eosinophil-derived neurotoxin (EDN) concentration were all risk factors related to recurrent wheezing, speculating that the combination of eosinophil count and serum EDN quantification may be served as one of the biomarkers to predict the recurrent wheezing in clinical practice. This data are confirmed by a double-blind randomized, placebo-controlled study, where the parallel comparison of montelukast and placebo administered for 3 months in 200 infants (age, 6–24 months), who were hospitalized with their first episode of acute RSV bronchiolitis, showed that serum EDN levels correlated significantly with the total number of wheezing episodes at 12 months in both groups of treated with placebo or leukotriene receptor antagonist . There are not standard criteria for weaning from continuous positive airways pressure (CPAP) and/or oxygen therapy the premature babies. Vento et al. wanted to verify if a physiologic test, modified respect to that developed by Walsh and collaborators for estimating bronchopulmonary dysplasia (BPD) rate, can be used as a clinical tool for weaning the premature babies from CPAP and/or oxygen therapy . They tested 23 neonates with body weight (BW) 500–1250 g and gestational age (GA) ≤ 32 weeks, receiving FiO2 ≤ 0.30 by hood or CPAP, monitoring transcutaneous partial pressure of CO2 (TcPCO2) and SpO2, at 28 days of life and at 36 weeks of postmenstrual age, in 3 steps: baseline, challenge (FiO2 and CPAP reduction to room air) and post-test (room air). Six of 23 tested babies (26%) passed the challenge at 28 days of life, 4 of 10 tested babies (40%) passed the challenge at 36 weeks. Median values of SpO2 were significantly higher in the neonates passing the test, respect to the failing patients. At the same time median values of TcPCO2 were significantly higher in the latter babies. The authors speculated that TcPCO2 monitoring appeared to be a new useful parameter for failure prediction of weaning. These data are confirmed in a multicentre study conducted by Kaempf et al., where pCO2 and SpO2 values appears to be reasonably good markers of lung injury, median pCO2 values were significantly higher in infants with BPD compared to controls . Vitamin D plays an important role in inflammatory responses after antigen exposure. T helper 17 cells produce Il-17A promoted by Il-23 and bind it to its receptor on the T cell membrane. They are both critical for neutrophil recruitment in a chronic P. aeruginosa pulmonary infection . Olszowiec-Chlebna et al. . conducted a randomized, placebo-controlled, double-blind, cross-over trial in 23 patients with cystic fibrosis (CF), chronically infected by P. aeruginosa , and randomly assigned to calcitriol or cholecalciferol groups. The results showed that both analogs of vitamin D revealed their anti-inflammatory effect, reducing the level of Il-17A and Il-23 in the airway of CF patients with chronic P. aeruginosa infection, and that calcitriol improve calcium phosphorus metabolism after supplementation without adverse effects. Pincikova et al. randomized CF patients to receive 35,000–50,000 IU vitamin D per week for 3 months and observed that this supplementation has pleiotropic immunomodulatory effects in CF in a dose-dependent manner, demonstrated that free serum 25 OH D level correlated positively with anti-inflammatory soluble immunological parameters . Instead, Olszowiec-Chlebna et al. did not observe any statistically significant changes of 25OHD serum level due to the supplementation with cholecalciferol 1000 IU per day. This is probably related to low dose of administered cholecalciferol. Rheumatic diseases Thrombotic thrombocytopenic purpura (TTP) is a disorder of the blood-coagulation system. Although TTP in patients with systemic lupus erythematosis (SLE) is rare, TTP-SLE has high mortality, ranging from 34 to 62.5% . TTP-SLE is related to endothelial injury or platelet aggregation that lead to vascular injury or autoimmune response. Li et al. want to report the clinical features of patients with TTP-SLE and enrolled 25 paediatric patients (median age 14 years old) . They observed that all patients had decreased platelet count and microangiopathic haemolytic anemia. Fever, rash, edema and neurological symptoms were the main clinical symptoms. Nineteen patients (76%) had impaired renal function, with a lupus nephritis class IV (20%) and thrombotic microangiopathy (20%) at renal biopsy, in line with the observations in adult TTP-SLE patients . Thirteen patients (52%) were treated with glucocorticoids in combination with immunosuppressive agent, and 10 patients (40%) were treated with plasma exchange combined with glucocorticoids plus immunosuppressive agent. One patient died due to lung infection; others had disease remission. These data showed that TTP-SLE often had a moderate to severe lupus disease activity, as confirmed in literature . Testing of LDH level and blood smear should be performed when kidney and neurological symptoms arise in children with SLE. The use of combination therapy, glucocorticoids plus immunosuppressive agent, provided satisfactory clinical outcome. Patients with refractory TTP-SLE will also need plasma exchange therapy.
There is a continuous effort to improve the management of allergic diseases. Pathophysiology of food allergy is IgE-mediated, non IgE-mediated (cell-mediated), or mixed (IgE and cell-mediated). Manifestations of IgE-mediated reactions include rhinoconjunctivitis, asthma, rash, angioedema, urticaria, nausea, vomiting, abdominal pain, diarrhea, anaphylaxis. Trigger food is identified by medical history, IgE tests (skin prick tests and/or serum specific IgE antibodies) and oral food challenge that is the gold standard . Avoidance of culprit food is the cornerstone of food allergy treatment. Oral immunotherapy (OIT) to cow’s milk, hen’s egg or peanut allergy is promising. However, it has been shown that OIT is not able to induce total or partial food tolerance in about 30% of children. Furthermore, the frequency of adverse events is high and duration of effectiveness unclear. Crisafulli G et al. investigated the efficacy of add-on therapy with omalizumab a monoclonal anti-IgE antibody during OIT in 5 children with cow’s milk allergy. A combination treatment (OIT plus omalizumab) preceded by a pretreatment with omalizumab in 3 cases, was beneficial in most children and tolerability was good. Omalizumab is that has been approved for the treatment of severe persistent allergic uncontrolled asthma and spontaneous chronic urticaria. It has also been shown to be successful in chronic rhinosinusitis . Among allergies with a mixed (IgE and cell-mediated) pathophysiology, omalizumab could be helpful in improving atopic dermatitis that shares with asthma, inflammatory mediators and the response to allergen immunotherapy but it did not improve eosinophilic esophagitis . In asthmatic children, the prevention of recurrent symptoms is based on long-term therapy and avoidance of triggering factors including aeroallergens, food allergens , physical exercise, passive smoking, pollutants. Asthma control has been shown to be enhanced by communication interventions. However, almost all the asthmatic children are not enough engaged in discussions on management . The SOUND project published a consensus for improving the communication to children and adolescents with severe asthma and their parents . Recommendations are given to physicians on how welcome they have made children and parents. The knowledge of the context would be facilitated by asking questions on goal of the visit, daily life (diet, physical activity, relation with family members and school advancement), by understanding the view of the child, and by using child’s drawings to recognize his thoughts. Advices are given on management of emotions, and on how keeping relationships between the visits. It is recommended to avoid prohibitions since they can cause suffering and undesirably disturb the relationship. Vernal keratoconjunctivitis (VKC) is an underestimate severe seasonal chronic inflammation that can lead to persistent damages . A systematic review has addressed the definition of diagnostic criteria and scoring system. A lack of standards for diagnosis was found. This mainly hampers the differentiation from seasonal allergic conjunctivitis that is often due to grass pollens . This is even more difficult since VKC can coexist with sensitization to seasonal pollens. Furthermore, a great variation in clinical score have been showed. So, continue efforts are needed by the scientific community to have a common language on diagnostic criteria, management and treatment. It is also advisable the development of homogeneous scoring system to be routinely used.
Since early postnatal growth of preterm infants is an important clue in clinical setting, Zhang et al. studied the postnatal growth patterns in a sample of Chinese healthy late preterm infants. Until they reached a term corrected age. Through bivariate, multivariate linear regression analyses and final stepwise regression models, interesting characteristics of postnatal growth have been assessed. Among the most relevant emerge; an extremely low rate (3%) of weight catch down growth, a prevalent weight (46.2%) vs length (30.7%) catch up growth, a faster postnatal weight and length catch up growth in males versus females, as well as in twins versus singletons, a superior weight growth in SGA and AGA versus LGA infants, and a faster length growth velocity in infants of 36 versus 34 and 35 weeks PMA at birth. The results of this study show a better global postnatal growth pattern in late preterm infants than previously described . Thus, the authors underline the necessity to consider in follow-up studies the difference in feeding and adopted nutrition strategies, as well as regional, local, ethical and traditional factors that can contribute to the divergence in postnatal growth patterns . The acronym SIADH (syndrome of inappropriate secretion of antidiuretic hormone) indicates a non-physiological secretion of ADH as it occurs independently from effective serum osmolality or circulating blood volume that normally regulates it. ADH stimulates water reabsorption through binding to V2 receptors located in the renal tubules, which mediates the concentration of urine, with relative water excess in plasma leading to hyponatremia. Inappropriate antidiuresis may also result from a gain-of-function mutation in its type 2 receptor. Therefore, some Authors prefer to use the term “syndrome of inappropriate antidiuresis (SIAD)” including both situations. SIADH can be idiopathic or due to multiple causes (neurological, pulmonary, malignant diseases, medications, acute conditions as stress, pain, general anesthesia) because various non-osmotic stimuli may cause AVP release. The classic criteria for diagnosis are those found in the clinical case described by Pintaldi et al. (hyponatremia, high urinary osmolarity, high urinary sodium concentration, absence of edema or clinical signs of volume depletion). However, it is important to remember that the diagnosis of SIADH requires a normal renal, cardiac, hepatic, adrenal and thyroid function . In other words, it is a diagnosis of exclusion, In particular, hypothyroidism (extremely rare) and adrenal insufficiency (AI) must be excluded. AI may be due to ACTH/CRH insufficiency (secondary and tertiary form particularly important in patients who present with neurosurgical conditions, such as traumatic brain injury, subarachnoid hemorrhage and intracranial tumors) or due to a primitive alteration of the adrenal gland which could be congenital or acquired . In fact, in the above mentioned clinical case the analysis of the functional parameters of the ACTH / Cortisol axis led to change the initial diagnosis to the final one of an autoimmune adrenalitis (Addison’s disease) which is considered,after the congenital adrenal hyperplasia (CAH), the second more frequent cause of primary AI. Finally, it is interesting to underline the similarities of the case described by Pintaldi with others reported in Literature . In particular, the initial normality of the values of potassium which would be assumed to be high in case of adrenal insufficiency but which were normal, probably due to the vomiting presented by the patients and in addition, the presence of some slight hyperpigmentation of the skin creases and gingival pigmentations which may be useful for diagnostic orientation during clinical evaluation. Neonatal adrenal hemorrhage (NAH) is uncommon (0.2–0.55%) . In most cases is asymptomatic and death is rare . Ultrasonographic examination is commonly performed since it is immediate, accurate and safe . In NAH, according to pathological anatomical evolution, temporal modification of echostructure is highly specific. The hemorrhagic adrenal gland is enlarged and homogeneously hyperechoic in newborns. Subsequently, the lysis of the clot increases hypoechoic structure and after 1 or 2 weeks cystic-colliquative feature emerges. Sometimes, shell calcification then appears . An involuted complex structure small mass, partly calcified without vascularization can residue. NAH can regress without relics in a period ranging from 20 days to 5–6 months. Most neonatal supra-renal masses are identified as congenital neuroblastoma (NBL) or adrenal hemorrhage . The histologic examination of tumor tissue or blood marrow besides elevated levels of catecholamine metabolites in urine or serum, is necessary for diagnosis of NBL. Ultrasonographic examination may be useful in assessing adrenal NBL. NBL may appear as a defined small mass within the adrenal gland or an infiltrative complex mass, lobulated with hemorrhagic zones. It is often solid, occasionally with calcific punctate areas in newborns . In NAH, the calcification appears generally later. Ultrasonography differentiation between cystic NAH and cystic NBL may be difficult, especially when catecholamine metabolite values are low. Color Doppler ultrasound examination seems to have most significance in providing a correct diagnosis. In NAH, a nonvascular flow and a regression of lesion over time are observed . In NBL, blood supply is essential for its own growth. This tumor gives rise to characteristic high velocity Doppler shifts. The usual follow-up time for the resolution of the hemorrhage should be within 90 days. NBL should be suspected if the mass does not resolve in 3 months. Adrenal NBL often spontaneously resolve. Therefore, a watchful waiting rather than an interventional approach is suggested . Hypophosphatemia can be one of the consequences of diabetic acidosis (DKA). In most cases of DKA the decrease in blood levels of phosphates is mild, it is not considered responsible for specific pathologies and it does not require correction as various prospective studies have shown no clinical benefit. Phosphate replacement is instead indicated in the severe forms (blood phosphate levels < 1 mg /dL/0.32 mmol / L) with the appearance of symptoms . They can in fact be responsible for clinical manifestations mainly respiratory, neuromuscular, cardiac and hematologic . As regards the cardiac involvement and in particular the arrhythmias, there are no precise epidemiological data but, on the basis of recent patient series, they appear infrequent compared to other complications . In that context, the clinical case described by Miszczuk et al. is an interesting one in particular in two respects: 1) ventricular bigeminy and trigeminy have not been previously described among arrhythmias and although their origin may be multifactorial the fact that they disappear with the phosphate supplementation indicates an important pathogenetic role; 2) the patient studied had blood levels of phosphate slightly higher than the limit considered diagnostic for severe forms, but a set of elements rightly suggest that an intracellular phosphate depletion had been created in the body. In other words, the intracellular phosphate level is primarily responsible for clinical manifestations. Concerning clinical practice, the recent ISPAD consensus concludes: “although administration of phosphate is associated with a risk of hypocalcemia, an IV solution that contains a 50:50 mixture of potassium phosphate and another suitable potassium salt (potassium chloride or potassium acetate), generally permits adequate phosphate replacement while avoiding clinically significant hypocalcemia.” Mauriac’s syndrome (MS) was initially described in 1930 and it is being characterized by growth failure, delayed puberty, cushingoid appearance, hepatomegaly with abnormal liver enzymes, and hypercholesterolemia. Such a syndrome has been mainly reported in brittle type 1 diabetes (DM1) and very rarely in DM2. In the last few decades, the improvement of diabetes therapy (education, use of insulin and /or its analogues and delivery technology) may have suggested that MS was about the past in the history of diabetes. On the contrary, the most recent reviews in Literature tell us that MS still exists especially in adolescent who do not always accept the rules that a good control of diabetes requires and in patients who live in socially and culturally backward environments where there may be objective difficulties in managing the disease . On the other hand, it should be kept in mind that the hepatomegaly (due to an overloading of hepatocytes with glycogen) represents one of the major signs of MS and it may be the only feature present both in children / adolescents and in adults. It has been defined in various ways: liver glycogen storage, hepatic or liver glycogenosis, DM-associated glycogen storage hepatomegaly and lately “glycogenic hepatopathy” (GH). Real incidence and prevalence of GH are unknown, commonly being misdiagnosed or underdiagnosed . However, if we consider some series of patients, we find that about 10% of diabetic children had hepatic hyperechogeneity decreasing after a period of several months of better adherence to therapy . In other words, hepatomegaly does not seem as rare as generally thought and should be sought in the follow up of diabetic patients. When present, the blood level of transaminases should be assessed, and other causes of liver disease excluded. If there is still a diagnostic doubt, liver biopsy is the gold standard. According to some AA, it would be useful above all to differentiate liver glycogen storage from nonalcoholic fatty liver disease (NAFLD), considering that the former is generally transient and with a benign prognosis while the latter (much more frequent in DM2) can evolve towards forms of cirrhosis and cancer .
Violence against children, adolescent and young adults shows, all over the world, a dramatic and still unsolved concern for the health, the connected social and legal problems. Globally it is estimated that up to1 billion children aged 2–17 years, have experienced physical, sexual, or emotional violence or neglect in one year (as cited in and that in the WHO European Region violence affects over 55 million victims . That can occur in various forms . In Europe we consider prevalences from 9.6% for sexual abuse, 16.3% for physical neglect, 18.4% for emotional neglect, and 2.9% for physical abuse, to 29.6% for emotional abuse . We must also keep in mind that the general prevalence is often underestimated due to the difficulty in various States for fully collecting data. Numerous studies have then highlighted the long-term consequences of the violence suffered. The victims are in fact at greater risk of developing both chronic diseases and behavioural and relational alterations . There are many factors that can facilitate violence both at an individual level (such as lower levels of education, low income, having a disability or mental health problems) and at community level (such as settings with weak governance and poor law enforcement) and with many of such it is possible to act with an appropriate prevention aimed in particular at family and school which are known to be the places where maltreatment occurs most frequently. On the other hand, the importance of prevention has been considered a priority by WHO which in connection with other international agencies has recently proposed the INSPIRE program ( www.who.int › inspire-package) based on seven strategies towards reducing and eliminating violence against children. With regard to the school environment in particular, many studies and resulting preventive recommendations have taken into consideration bullying or cyberbullying phenomena which are certainly the most frequent. On the basis of the data collected in Italy by Ferrara et al. and of a recent review of the international literature , it is useful to point out that studies about the violent teacher-student relationship are very rare and that this phenomenon, certainly less frequent than the previous one, would deserve greater attention both at the epidemiological level and for establishing setting methods and action to prevent that.
Preterm birth is a public health concern and it represents the leading cause of neonatal mortality . Preterm newborns also present neurological impairment, respiratory, renal and gastrointestinal complications. All these conditions may seriously affect the neurocognitive outcome and cause severe disability. The highest mortality rates of preterm birth have been found in developing countries . In an observational study conducted in Ethiopia, the mortality rate of preterm newborns was 28.8% . Neonatal deaths occurred within the first 24 h in 11.4% of cases and within the first 7 days in 85.23% of instances. Perinatal asphyxia was the major cause of death followed by hyaline membrane disease, jaundice, clinical sepsis and apnoea. Griffin et al. proposed a model for reducing preterm mortality based on WHO recommendations. He pointed out that combined interventions lead to the greatest impact on preterm mortality. The most effective single interventions are oxygen/CPAP, cord care, breastfeeding, and antibiotics. New efforts are needed to prompt identify potential preterm births in order to provide a proper intervention. Granese R et al. found that vaginal/urinary infections, underweight, obesity, unmarried status, uterine anomalies, poly/oligohydramnios, hypertension, diabetes, a history of preterm birth and a short cervix length in the second trimester were the main risk factors for preterm birth. Of note, a short cervix predicted early preterm and very early preterm delivery while the other factors should be considered in late preterm cases. This study indicates that cervix length evaluation during the midtrimester should be performed not only in women at high risk of preterm birth but in all cases since it may early detect high-risk pregnancies and guarantee progesterone administration that diminishes the risk of preterm birth and reduces neonatal morbidity. Socioeconomical factors and health development play a role in the neonatal mortality. In Italy, the overall neonatal mortality rate is 2 per one thousand live births, that is one of the lowest infant mortality rates of all countries. However, there still are differences among areas of the country (North-Centre-South) that should be linked to inadequate care level and organization of perinatal care . Of note, mortality index among immigrants were higher than among Italians. Accordingly, in England ethnic minority newborns had twice risk of adverse events at birth than British infants . Several explanations may be offered to explain these findings. This could be associated with socioeconomical conditions. Language and cultural differences between minority and majority groups can create barriers to access or benefit from information. Newborns, whose parents have a low level of education, are more likely to die in early life . The late onset type of vitamin K deficiency can occur with cerebral haemorrhage. Ceratto and Savino reported a healthy newborn who developed intracranial bleeding due to vitamin K deficiency at the end of the first week of life. She received oral vitamin K at birth because she had no risk factor. These findings can suggest that intramuscular vitamin K may be useful for all newborns because of unpredictable risk factors at birth (malabsorption or cholestasis) other than preterm birth . The American Academy of Pediatrics, the Canadian Pediatric Society and the ESPGHAN Committee on Nutrition recommend the intramuscular administration of the first dose of vitamin K at birth since it would be linked with less failure mainly for late bleeding than oral route administration, due to minor abnormalities of absorption . In many countries, national recommendations on this issue are lacking. There is a need of consistent indications about optimal dose and routes of administration of vitamin K prophylaxis in newborns. Lotus birth is the practice of umbilical nonseverance, leaving the umbilical cord and the placenta intact and attached until it detaches spontaneously after 3–10 days. Meanwhile, the placenta is put in a bowl with salt and herbs . Clinical risks, bioethical and medico legal aspects of this controversial procedure have been analysed by Bonsignore et al. . From the health side, studies about this particular practice are inconsistent, of poor quality and with small sample. There is no clear evidence that having placenta connected to the baby for many days provides benefits to him/her. On the other hand, there is a potential risk for reduced neonatal perfusion and clot formation. In a recent case report series, no infections occurred after lotus birth and mothers expressed interest in repeat lotus birth in the future . However, the dead tissue attached to the newborn may be affected by bacteria and possible complications related to this practice such as omphalitis or other infections have been described . From the medico-legal side, the question arises whether placenta belongs to the mother or to the baby and no clear statement assess the juridical availability of placenta. Therefore, when the mother requests the placenta, she should be allowed to have it, unless a public health issue arises. Families should be adequately updated about the risk/benefit ratio of Lotus birth and informed forms should be used. Overall, Bonsignore et al. consider Lotus birth inadvisable from both medical and rational point of view.
Vitamin D subclinical deficiency or insufficiency continue to be a common finding . Vitamin D is useful for bone health and it has been investigated for preventing cancer, cardiovascular disease, type 2 diabetes mellitus, neurologic disorders, autoimmune disorders, infectious disease also by increasing the function of gastrointestinal microbiota which may have a role in preventing infectious diseases . Vitamin D supplementation is a matter of debate. It is usually recommended when children have risk factors for deficiency of vitamin D such as inadequate intake, limited skin exposure to sunlight, dark skin, malabsorption, drug intake (anticonvulsants, systemic glucocorticoids, antiretroviral therapy), liver or kidney diseases, obesity). In Italy, the recommended supplementation in children from 1 to 17 years is 600–1000 IU/day vitamin D3 and children with risk factors should receive 1000–1500/UI vitamin D3 per day . To prevent the deficiency of vitamin D, it was conducted a study on the effect of vitamin D3 1500 IU/day from November to April versus no supplementation . In the intervention group, there was no side effect and the 25-hydroxyvitamin D maximum serum level was 71 ng/ml. In adolescents with vitamin D insufficiency, there was only a slight increase in mean 25-hydroxyvitamin D serum level so it is possible that this age range would receive a higher dose of vitamin D3. No consensus has been reached about the period of the administration of vitamin D supplementation . In this study, the intervention group had normal serum value of 25-hydroxyvitamin D all the year except in May. In the control group vitamin D deficiency were found in 4 months out of 6 at the beginning of the year and vitamin D insufficiency in the other 2 months. So, it would be reasonable to extend vitamin D supplementation. Undernutrition is still a leading cause of morbidity and mortality in children and in some developing countries. Both acute and chronic forms (wasting and stunting) represent a public health challenge. They are strongly inversely correlated with the wealth of nations. In Sub-Saharan Africa and in South Asia , risk factors for wasting and stunting in children are low birth weight, low mother’s BMI, small birth size, low parental education, young mother, increasing child’s age, male, inadequate food supply, unhealthy living environments. In the slums of Nairobi (Kenia), 26.30% of children under 12 months of age was stunted, 6.3% wasted and 13.16% underweight . Wasting was more frequently associated with infectious diseases such as cough and rapid breathing and diarrhea, probably due to the acute loss of weight. Regarding mortality, it has been estimated that 45% of deaths in children under 5 years of age in the world is due to undernutrition . Mid-upper arm circumference (MUAC) and weight-for-height/length Z-score (WHZ) are used to identify children with severe acute malnutrition (SAM) but they are affected by gender, region and age bias . Therefore, the burden of SAM can be higher than that reported. Moreover, SAM is a risk factor for growth retardation and impaired psychosocial and cognitive development. Fikrie et al. studied Ethiopian hospitalized children with malnutrition assessed by mid-upper arm circumference (MUAC), weight-for-height/length Z-score (WHZ), edema. All children presented co-morbidities, including pneumonia, diarrhea, anaemia, tuberculosis. They found that the recovery rate was 69.4%, which was below the minimum accepted international standard of 75% and the mortality rate was 10%. Weight gain and length of staying were in line with the international standard and Ethiopian protocol for management of SAM. These results are concordant with those of a similar research conducted in Northwest Ethiopia . Comorbidities in the enrolled population may elucidate the low recovery rate . Other explanations may be related to therapeutic milk intake and high rates of mortality. Finally, relapse after discharge was 7.1% of all cases. This highlights that standardized protocols for SAM follow-up after discharge are always needed.
Congenital anomalies of the kidney and urinary tract (CAKUTs) include structural and functional abnormalities of the kidney, collecting system, bladder, and urethral abnormalities, and are some of the most common birth defects in newborns. Li and collaborators conducted a retrospective study in China’s Zhejiang Province, including all births and all ascertained patients with CAKUTs registered from 2010 to 2016. There were enrolled 2790 patients identified among 1,748,038 births . Authors observed that males (OR 1.28, 95% CI 1.18–1.38), multiple births (OR 1.53, 95% CI 1.21–1.92) and births in urban areas (OR 1.27, 95% CI 1.18–1.37) presented a higher risk of CAKUTs. Instead, CAKUTs were poorly associated with maternal age. Overall, 22.69% of births with CAKUTs had associated malformations, especially heart defects. The most frequent CAKUT was hydronephrosis, (31.79%), followed by polycystic kidney, renal agenesis, renal ectopia, and renal duplication. In this study, the prevalence of CAKUTs was much lower than in reports from Copenhagen, Russia, and western areas of Saudi Arabia, maybe explained by differences in sociodemographic background, malformation inclusion criteria. In Murmansk County, a population-based birth registry recorded anomalies diagnosed from 22 weeks of gestation to hospital discharge . Those authors admitted that some figures had been overestimated owing to the lack of strict diagnostic criteria for pyelectasis, hydronephrosis, and unspecified anomalies . In Saudi Arabia, the high rate of consanguineous marriage within the local population might increase the rate of CAKUTs . The study in Denmark followed up a birth cohort for 8 years . Finally, the authors evaluated that the prevalence of CAKUTs doubled from 2010 to 2016, which might be owing to increased screening, developments in ultrasound technology, and improved birth defect surveillance. X-linked hypophosphatemic rickets (XLH) is a rare disease caused by mutations in the PHEX gene, this disease is poorly known, and diagnosis is frequently delayed. Emma et al. collected data by means of a questionnaire on XLH epidemiology, diagnosis and treatment, from 10 Italian centres on 175 patients, followed between 1998 and 2017 . The diagnosis was made before the age of 1 and between 1 and 5 years in 11 and 50% of cases, respectively. Clinically apparent bone deformities were present in 95% of patients. Other frequent complications included bone pain (40%), dental abscesses (33%), and dental malpositions (53%). Treatment protocols varied substantially among centres. Nephrocalcinosis, a complication of conventional treatment, was observed in 34% of patients. Tertiary hyperparathyroidism developed in 6% of patients. Overall, nephrocalcinosis has been reported in the literature in 30–70% of patients . The present study was conducted to evaluate the current status in the diagnosis and treatment of XLH in Italy. Overall, results are in line with available data in the literature, although with some noticeable differences. The prevalence of XLH is estimated between 1.2–3.0/60,000 . In this survey the number is lower than expected, indicating that the disease is either underdiagnosed.
Guido et al. showed the successful results of the eye movement desensitisation and reprocessing (EMDR) therapy associated with parent management training (PMT) in a 11-year-old boy who presented with simple and complex vocal tics, motor tics, obsessive-compulsive traits and irritability from the age of 6 years, diagnosed as paediatric autoimmune neuropsychiatric disorder associated with streptococcus (PANDAS) . These results indicate the possibility of improving the treatment outcomes of patients with PANDAS by a combined approach using both antibiotic and EMDR therapies. According to the most recent guidelines , elective evidence-based therapies for the treatment of PANDAS include Cognitive Behavioural Therapy, parent training and drug therapy. EMDR therapy had never been utilised before in patients with PANDAS syndrome , this method works on the present and not on the past. The explanatory model underlying these considerations is the Adaptive Information Processing model, in which previously stored dysfunctionally without proper assimilation within of a wider adaptive network present in the patient . Migraine is one of the most prevalent chronic pain manifestations of childhood, affecting up to 10% of children between the ages of 5 and 15 years and up to 28% of adolescents aged from 15 to 19 years . Moreover, parents are often concerned about chronic therapies and even clinicians prefer to avoid prescription of prophylactic therapies in children, due to the poor evidence of efficacy and significant potential adverse effects in this population . Moscano et al. conducted an observational multicenter study performed in 91 children with migraine, with (MO) or without aura (MA), or tension-type headache (TTH) . A fixed-dose of Partena® tablets (a combination of Mg2+ 169 mg, CoQ10 20 mg, VitB2 4,8 mg, Feverfew 150 mg-1,2 mg Parthenolides and Andrographis paniculata 100 mg), was administered for 16 weeks. The herbal supplement significantly reduced the frequency of headaches in TTH patients during treatment period, maintaining the efficacy after 16 weeks of treatment withdrawal. A significant effect was observed also in the MO and MA groups during treatment. These results are according several epidemiologic, preclinical and clinical evidence supporting the usefulness of other active principles of Partena® in prophylactic treatment of migraine currently available in Europe and USA as dietary supplements . The most recent randomized controlled trial, using a stable extract, add some positive evidence about the efficacy of in the prophylactic treatment of migraine . Studies on Feverfew efficacy in children and adolescents with migraine are lacking.
An increased prevalence of celiac disease (CD) has been observed in several cohorts of cystic fibrosis (CF) patients. A recent study indicates that the gluten/gliadin-derived peptide (P31–43) can cause the cystic fibrosis transmembrane conductance regulator (CFTR) channel protein inhibition in intestinal epithelial cells, thus causing a local stress response that contributes to the immunopathology of CD. Mauri et al. speculated that P31–43-induced CFTR inhibition elicits the danger signals that ignite the epithelial stress response and perturb epithelial proteostasis . Importantly, potentiators of CFTR channel gating, such as the FDA-approved drug Ivacaftor, prevent P31–43 driven CFTR inhibition and suppress the gliadin-induced stress response in cells from celiac patients, as well as the immunopathology developing in gliadin-sensitive mice. Altogether these findings demonstrate that gliadin induced CFTR malfunction is at the apex of the pathogenic cascade leading to CD . Paucity of interlobular bile ducts is an important observation at liver biopsy in the diagnostic work-up of neonatal cholestasis. To date, other than in the Alagille syndrome, syndromic paucity of interlobular bile ducts has been documented in four cholestatic neonates with HFN1β mutations. A syndromic phenotype, known as renal cysts and diabetes syndrome (RCAD), has been identified. Pinon et al. reported a novel case of 5-week-old boy affected by paucity of interlobular bile ducts due to an HFN1β defect . He was admitted for cholestatic jaundice with increased gamma-glutamyl transpeptidase and an unremarkable clinical examination, characterized by cholestatic disease, hyperechogenic kidneys with multiple bilateral cortical cysts at ultrasound examination, associated with moderately impaired renal function with proteinuria, polyuria and metabolic acidosis, paucity of interlobular bile ducts at liver biopsy, thus the diagnosis of Alagille syndrome (AGS) was considered, but excluded. Although genetic tests for liver cholestatic diseases were performed with negative results for Alagille syndrome (JAG1 and NOTCH2), a de-novo missense mutation of HNF1β gene was detected. To date, only others 5 cases of neonatal cholestasis are reported in literature as associated to HNF1β mutations, in most cases de-novo deletions, with similar clinical course . HFN1β defects should be considered in neonates with cholestasis and renal impairment, especially in SGA and IUGR newborns with a family history of renal disease or diabetes, in addition to AGS.
Recurrent wheezing and/or asthma are common chronic respiratory disease in children. Studies have demonstrated that children hospitalized for RSV bronchiolitis during infancy were more likely to have subsequent episodes of wheezing . Also, eosinophil-derived neurotoxin (EDN), contained in eosinophil cytotoxic granule proteins has been considered to be involved in the recurrent wheezing and asthma development in later life . Zhai et al. followed-up for 1-year 145 children of 3 years old or younger, who were hospitalized with wheezing, in order to analyse factors that may predict recurrent wheezing . The authors demonstrated that eczema, respiratory syncytial virus (RSV) infection, eosinophil count and eosinophil-derived neurotoxin (EDN) concentration were all risk factors related to recurrent wheezing, speculating that the combination of eosinophil count and serum EDN quantification may be served as one of the biomarkers to predict the recurrent wheezing in clinical practice. This data are confirmed by a double-blind randomized, placebo-controlled study, where the parallel comparison of montelukast and placebo administered for 3 months in 200 infants (age, 6–24 months), who were hospitalized with their first episode of acute RSV bronchiolitis, showed that serum EDN levels correlated significantly with the total number of wheezing episodes at 12 months in both groups of treated with placebo or leukotriene receptor antagonist . There are not standard criteria for weaning from continuous positive airways pressure (CPAP) and/or oxygen therapy the premature babies. Vento et al. wanted to verify if a physiologic test, modified respect to that developed by Walsh and collaborators for estimating bronchopulmonary dysplasia (BPD) rate, can be used as a clinical tool for weaning the premature babies from CPAP and/or oxygen therapy . They tested 23 neonates with body weight (BW) 500–1250 g and gestational age (GA) ≤ 32 weeks, receiving FiO2 ≤ 0.30 by hood or CPAP, monitoring transcutaneous partial pressure of CO2 (TcPCO2) and SpO2, at 28 days of life and at 36 weeks of postmenstrual age, in 3 steps: baseline, challenge (FiO2 and CPAP reduction to room air) and post-test (room air). Six of 23 tested babies (26%) passed the challenge at 28 days of life, 4 of 10 tested babies (40%) passed the challenge at 36 weeks. Median values of SpO2 were significantly higher in the neonates passing the test, respect to the failing patients. At the same time median values of TcPCO2 were significantly higher in the latter babies. The authors speculated that TcPCO2 monitoring appeared to be a new useful parameter for failure prediction of weaning. These data are confirmed in a multicentre study conducted by Kaempf et al., where pCO2 and SpO2 values appears to be reasonably good markers of lung injury, median pCO2 values were significantly higher in infants with BPD compared to controls . Vitamin D plays an important role in inflammatory responses after antigen exposure. T helper 17 cells produce Il-17A promoted by Il-23 and bind it to its receptor on the T cell membrane. They are both critical for neutrophil recruitment in a chronic P. aeruginosa pulmonary infection . Olszowiec-Chlebna et al. . conducted a randomized, placebo-controlled, double-blind, cross-over trial in 23 patients with cystic fibrosis (CF), chronically infected by P. aeruginosa , and randomly assigned to calcitriol or cholecalciferol groups. The results showed that both analogs of vitamin D revealed their anti-inflammatory effect, reducing the level of Il-17A and Il-23 in the airway of CF patients with chronic P. aeruginosa infection, and that calcitriol improve calcium phosphorus metabolism after supplementation without adverse effects. Pincikova et al. randomized CF patients to receive 35,000–50,000 IU vitamin D per week for 3 months and observed that this supplementation has pleiotropic immunomodulatory effects in CF in a dose-dependent manner, demonstrated that free serum 25 OH D level correlated positively with anti-inflammatory soluble immunological parameters . Instead, Olszowiec-Chlebna et al. did not observe any statistically significant changes of 25OHD serum level due to the supplementation with cholecalciferol 1000 IU per day. This is probably related to low dose of administered cholecalciferol.
Thrombotic thrombocytopenic purpura (TTP) is a disorder of the blood-coagulation system. Although TTP in patients with systemic lupus erythematosis (SLE) is rare, TTP-SLE has high mortality, ranging from 34 to 62.5% . TTP-SLE is related to endothelial injury or platelet aggregation that lead to vascular injury or autoimmune response. Li et al. want to report the clinical features of patients with TTP-SLE and enrolled 25 paediatric patients (median age 14 years old) . They observed that all patients had decreased platelet count and microangiopathic haemolytic anemia. Fever, rash, edema and neurological symptoms were the main clinical symptoms. Nineteen patients (76%) had impaired renal function, with a lupus nephritis class IV (20%) and thrombotic microangiopathy (20%) at renal biopsy, in line with the observations in adult TTP-SLE patients . Thirteen patients (52%) were treated with glucocorticoids in combination with immunosuppressive agent, and 10 patients (40%) were treated with plasma exchange combined with glucocorticoids plus immunosuppressive agent. One patient died due to lung infection; others had disease remission. These data showed that TTP-SLE often had a moderate to severe lupus disease activity, as confirmed in literature . Testing of LDH level and blood smear should be performed when kidney and neurological symptoms arise in children with SLE. The use of combination therapy, glucocorticoids plus immunosuppressive agent, provided satisfactory clinical outcome. Patients with refractory TTP-SLE will also need plasma exchange therapy.
The first semester of year 2019 was a remarkable time in the field of paediatrics. We have described developments that have improved our knowledge across many areas. They covered mechanisms and clinical management of diseases. We look forward to additional thought-provoking facts in the future.
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A novel automated IHC staining system for quality control application in ALK immunohistochemistry testing | 4c4dea0f-f71f-4d16-b081-6fea5bfbcdab | 11864879 | Anatomy[mh] | The identification of aberrantly activated tyrosine kinases in a subset of non–small cell lung cancer (NSCLC) has accelerated the approval of ALK tyrosine kinase inhibitors, which have improved the progression-free survival for patients. Approximately 3%–5% of the NSCLC cases harbor an echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) rearrangement and may respond to targeted therapy . ALK status is clinically pivotal in determining eligibility for ALK-directed targeted therapy. Laboratory tests to detect EML4-ALK rearrangement should be robust, reliable, rapid, and cost–effective. The fluorescence in situ hybridization (FISH) method to detect ALK rearrangement was approved by the U.S. Food and Drug Administration (FDA) in 2011 . The VENTANA ALK IHC assay, which uses the rabbit monoclonal antibody D5F3 to detect ALK rearrangement, has been authorized by the U.S. FDA as a companion diagnostic for the ALK tyrosine kinase inhibitor Ceritinib . Because of the low throughput of FISH, the IHC assay usually plays the role of routine screening of ALK-rearranged NSCLC. The precise detection of low ALK expression mainly depends on the affinity of the antibody, the sensitivity of the detection system, and the quality control . In this study, a novel ALK antibody (clone BP616) performed on an IHC staining system called LYNX480 PLUS was evaluated in a large cohort of NSCLC specimens, to determine its reliability for the detection of ALK rearrangements compared to the D5F3/VENTANA system. The ALK controls in liquid form (CLFs) prepared from genetically modified cell lines applied by the quality control (QC) module of the LYNX480 PLUS have a high-success rate of quality control setting. These novel controls in liquid form could be applied as the quality controls in the IHC staining process to monitor the variation of staining conditions such as antibody dilution rate and antigen retrieval. The auto-QC function of the LYNX480 PLUS combined with the novel CLFs provides a reliable, effective, and donor tissue–saving method of quality control in IHC testing.
Tumor samples and controls Archival formalin-fixed paraffin-embedded (FFPE) tumor samples from 87 patients with stage I–III NSCLC were retrospectively selected from the Laboratory of Clinical and Experimental Pathology at the First Affiliated Hospital, Zhejiang University School of Medicine between 2021 and 2022. The individual patient data is listed in . In total, 47 ALK-positive specimens and 40 ALK-negative specimens were concurrently confirmed by fluorescence in situ hybridization (FISH), qRT-PCR, or IHC in the previous study. All tumor speciments in previous studies were collected, stored, and used with informed written consent of the patients. The study was approved by the local ethics committee (Human Research Ethics Committee, the First Affiliated Hospital, Zhejiang University School of Medicine). An optimized IHC protocol was established by using 3 of the 87 lung adenocarcinoma samples. Controls in liquid form (CLFs) CLFs are a type of cell suspensin prepared from genetically modified cell lines. ALK positive CLF (Catalog Number: BX30026P, Biolynx) and ALK negative CLF (Catalog Number: BX30026N) both were prepared from genetically modified cell lines which could/could not express ALK. CLFs can be applied on slides by pipette or by an automated pipetting system, the QC module in the LYNX480 PLUS while using. The staining pattern and application method for ALK CLFs were validated before use on the 87 tumor samples, by adding CLFs to empty slides and staining these slides with an optimized staining protocol on LYNX480 PLUS. The shape and location of control droplets and the staining patterns of CLFs were compared between automatic and manual applications. The one with better droplet shape, cell distribution, and stable staining patterns was selected as the CLFs application method for further research. Automated IHC staining and QC system The LYNX480 PLUS System (catalog number: I50080B, Biolynx) is an automated immunohistochemistry staining system with a quality control function. The system includes a staining module and an IHC QC module. The IHC quality control module can batch-process 60 slides by adding corresponding CLFs controls before the IHC staining procedure. Automatic cap opening/closing and sampling probe washing can effectively prevent CLFs evaporation and contamination. By scanning the quick response code of CLFs with the scanner in the QC module, the controls in liquid form can be automatically dripped onto the target slides. The applied CLFs droplet can be dried and fixed to the slide in minutes using a heater. Four independent chambers in the staining module can support both IHC and ISH staining simultaneously. The entire QC procedure and information, including patient clinical information, QC, and staining records, can be recorded and tracked. Immunohistochemistry The VENTANA ALK (Clone D5F3) CDx Kit on the VENTANA BenchMark XT platform was performed according to the manufacturer’s recommendations. The rabbit monoclonal anti-ALK antibody BP6165 (catalog number: I1153, Biolynx) assay was performed using the LYNX480 PLUS System with conventional 3,3′-diaminobenzidine (DAB) staining (no amplification). IHC was performed on 3-μm formalin-fixed paraffin-embedded tissue sections. Preparation steps, which included deparaffinization, rehydration, antigen retrieval, and peroxidase block along with IHC staining processes were all performed on the LYNX 480 PLUS platform with correlated reagents from the BXV visualization system (catalog number: I2003, Biolynx). Antigen retrieval and peroxidase blocking were performed by using the retrieval solution (EDTA) at PH 9.0 for 60 min at 100°C and the peroxidase blocking solution for 5 min. After that, the specimens were incubated with primary antibody (BP6165) for 30 min at room temperature, at the dilution ratio of 1:200. The specimens were then incubated with post-primary antibody for 15 min and secondary antibody-horseradish peroxidase compound for 20 min at room temperature. DAB chromogen concentrate was diluted with DAB diluent at a ratio of 1:20, and the diluted DAB was then applied to each specimen and allowed to react for 10 min. The specimens were then counterstained with hematoxylin. Dehydration was conducted before the specimens were mounted with coverslips. The entire described steps were followed by washes with buffer (TBS) or distilled water. IHC results were evaluated in a blinded manner. Criteria to assess ALK staining as optimal in the lung adenocarcinoma included: 1) An at least weak to moderate granular cytoplasmic staining reaction of virtually all neoplastic cells in the lung adenocarcinoma with EML-ALK translocation. 2) No staining of neoplastic cells in the lung adenocarcinoma without ALK rearrangement. Interpretation of immunohistochemistry staining results Five independent pathologists from the First Affiliated Hospital, Zhejiang University School of Medicine blindly reviewed each stained slide. Prior to analysis, three lung adenocarcinomas with known ALK status stained with each antibody were reviewed by each pathologist, which allowed them to assess the level of nonspecific or background staining characteristic of the individual reagents. In the vast majority of the tumor cells, the expression of positive ALK protein was defined as that tumor-specific cytoplasmic staining of any intensity was found to be superior to background staining. Statistical analysis Statistical analysis was performed using the SPSS Statistics 22.0 software for Windows (IBM Corporation, NY, United States). Considering how interobserver variability may have impacted the etiologic risk estimates, a Cohen’s Kappa statistic was used to compare the interobserver diagnostic variability among the five different pathologists. A 95% confidence interval (CI) was used to estimate the range of values of a parameter.
Archival formalin-fixed paraffin-embedded (FFPE) tumor samples from 87 patients with stage I–III NSCLC were retrospectively selected from the Laboratory of Clinical and Experimental Pathology at the First Affiliated Hospital, Zhejiang University School of Medicine between 2021 and 2022. The individual patient data is listed in . In total, 47 ALK-positive specimens and 40 ALK-negative specimens were concurrently confirmed by fluorescence in situ hybridization (FISH), qRT-PCR, or IHC in the previous study. All tumor speciments in previous studies were collected, stored, and used with informed written consent of the patients. The study was approved by the local ethics committee (Human Research Ethics Committee, the First Affiliated Hospital, Zhejiang University School of Medicine). An optimized IHC protocol was established by using 3 of the 87 lung adenocarcinoma samples.
CLFs are a type of cell suspensin prepared from genetically modified cell lines. ALK positive CLF (Catalog Number: BX30026P, Biolynx) and ALK negative CLF (Catalog Number: BX30026N) both were prepared from genetically modified cell lines which could/could not express ALK. CLFs can be applied on slides by pipette or by an automated pipetting system, the QC module in the LYNX480 PLUS while using. The staining pattern and application method for ALK CLFs were validated before use on the 87 tumor samples, by adding CLFs to empty slides and staining these slides with an optimized staining protocol on LYNX480 PLUS. The shape and location of control droplets and the staining patterns of CLFs were compared between automatic and manual applications. The one with better droplet shape, cell distribution, and stable staining patterns was selected as the CLFs application method for further research.
The LYNX480 PLUS System (catalog number: I50080B, Biolynx) is an automated immunohistochemistry staining system with a quality control function. The system includes a staining module and an IHC QC module. The IHC quality control module can batch-process 60 slides by adding corresponding CLFs controls before the IHC staining procedure. Automatic cap opening/closing and sampling probe washing can effectively prevent CLFs evaporation and contamination. By scanning the quick response code of CLFs with the scanner in the QC module, the controls in liquid form can be automatically dripped onto the target slides. The applied CLFs droplet can be dried and fixed to the slide in minutes using a heater. Four independent chambers in the staining module can support both IHC and ISH staining simultaneously. The entire QC procedure and information, including patient clinical information, QC, and staining records, can be recorded and tracked.
The VENTANA ALK (Clone D5F3) CDx Kit on the VENTANA BenchMark XT platform was performed according to the manufacturer’s recommendations. The rabbit monoclonal anti-ALK antibody BP6165 (catalog number: I1153, Biolynx) assay was performed using the LYNX480 PLUS System with conventional 3,3′-diaminobenzidine (DAB) staining (no amplification). IHC was performed on 3-μm formalin-fixed paraffin-embedded tissue sections. Preparation steps, which included deparaffinization, rehydration, antigen retrieval, and peroxidase block along with IHC staining processes were all performed on the LYNX 480 PLUS platform with correlated reagents from the BXV visualization system (catalog number: I2003, Biolynx). Antigen retrieval and peroxidase blocking were performed by using the retrieval solution (EDTA) at PH 9.0 for 60 min at 100°C and the peroxidase blocking solution for 5 min. After that, the specimens were incubated with primary antibody (BP6165) for 30 min at room temperature, at the dilution ratio of 1:200. The specimens were then incubated with post-primary antibody for 15 min and secondary antibody-horseradish peroxidase compound for 20 min at room temperature. DAB chromogen concentrate was diluted with DAB diluent at a ratio of 1:20, and the diluted DAB was then applied to each specimen and allowed to react for 10 min. The specimens were then counterstained with hematoxylin. Dehydration was conducted before the specimens were mounted with coverslips. The entire described steps were followed by washes with buffer (TBS) or distilled water. IHC results were evaluated in a blinded manner. Criteria to assess ALK staining as optimal in the lung adenocarcinoma included: 1) An at least weak to moderate granular cytoplasmic staining reaction of virtually all neoplastic cells in the lung adenocarcinoma with EML-ALK translocation. 2) No staining of neoplastic cells in the lung adenocarcinoma without ALK rearrangement.
Five independent pathologists from the First Affiliated Hospital, Zhejiang University School of Medicine blindly reviewed each stained slide. Prior to analysis, three lung adenocarcinomas with known ALK status stained with each antibody were reviewed by each pathologist, which allowed them to assess the level of nonspecific or background staining characteristic of the individual reagents. In the vast majority of the tumor cells, the expression of positive ALK protein was defined as that tumor-specific cytoplasmic staining of any intensity was found to be superior to background staining.
Statistical analysis was performed using the SPSS Statistics 22.0 software for Windows (IBM Corporation, NY, United States). Considering how interobserver variability may have impacted the etiologic risk estimates, a Cohen’s Kappa statistic was used to compare the interobserver diagnostic variability among the five different pathologists. A 95% confidence interval (CI) was used to estimate the range of values of a parameter.
Clinicopathologic characteristics of patients Of the 87 patients with lung adenocarcinoma, the median age was 52 years in the current cohort. There were 35 men and 52 women. The pathologic stages were stage I in 40 patients, stage II in 38 patients, and stage III in 9 patients. According to the IALSC/ATS/ERS classification, the most prevalent subtype was acinar adenocarcinoma (37.93%), followed by minimally invasive adenocarcinoma (26.44%), papillary predominant (9.20%), adenocarcinoma in situ (6.90%), solid predominant (6.90%), lepidic predominant (6.90%), variants of invasive adenocarcinoma (4.60%) and micropapillary predominant (1.15%). The clinicopathologic characteristics of the patients are listed in . Comparison between rabbit monoclonal anti-ALK antibody BP6165 and ALK (D5F3) CDx Kit Three lung adenocarcinoma samples with known EML4-ALK status as determined by qRT-PCR and FISH were analyzed for ALK protein expression using the D5F3/VENTANA and BP6165/LYNX480 PLUS immunohistochemical assays, respectively. According to the optimized protocol introduced by the manufacturer (Biolynx, China), staining patterns on lung adenocarcinoma samples using the BP6165 concentrated antibody on the LYNX480 PLUS platform showed weaker specific cytoplasmic signals and less background than staining patterns with the ALK (D5F3) CDx Kit on the VENTANA BenchMark XT platform . Evaluation of the LYNX480 PLUS platform agreement versus the gold standard A total of 87 lung adenocarcinoma samples were then used to study the concordance of the BP6165 antibody assay on the LYNX480 PLUS platform with the D5F3 CDx Kit on the VENTANA BenchMark XT platform. The BP6165 antibody assay identified all 47 ALK-rearranged tumors as assessed by five independent pathologists based on the ALK (D5F3) CDx binary scoring algorithm. The average positive percentage agreement (PPA) was 98.30% . The diagnostic results of the two platforms as assessed by five independent pathologists showed good agreement (kappa > 0.80) . ALK rearrangement was confirmed by FISH in all tumors and two of the cases with weak staining intensity. Of the 47 ALK-positive cases, 45 were undoubtedly scored as positive. Two of 47 cases were scored as negative with the possible reason that these two cases were weakly expressed around the low limit of detection level, and the BP6165-480 PLUS Assay had weaker staining than the D5F3-VENTANA Assay as mentioned in the ‘Comparison between rabbit monoclonal anti-ALK antibody BP6165 and ALK (D5F3) CDx Kit’ section of the Results section. The diagnostic results as assessed by five independent pathologists are provided in . CLFs application to slides To meet the requirements of setting quality control in ALK testing, CLFs prepared from cell lines was selected and tested to determine whether it could be used as a control. When appropriate IHC protocol was used, 80%–95% of ALK-positive cells were presented as moderate to strong staining on the cytoplasm, while no positive staining was present on ALK-negative cells---this pattern was defined as the standard staining pattern for ALK CLFs defined by the manufacturer. Both ALK-positive cells and negative CLFs were vortexed for 10–15 s and then 1–2 μL were manually applied to the slide by five technicians. All staining showed the same pattern according to the manufacturer’s interpretation guidelines, in which the positive showed 80%–95% cytoplasm staining and the negative showed no positive staining . Cellular structures such as cell membranes, cytoplasmic, and nuclear details, were also well preserved. However, the shape of all the droplets was very different from one to another, as shown in , only A1 and A4 are in circle shape but still with different diameters. The cell distribution of some droplets was also found to be uneven, especially in negative cell droplets. Comparison of automated and manual application of CLFs The same bottles of ALK CLFs were performed in an automated way on the QC module in LYNX480 PLUS platform to see whether the droplets shape and diameter could be similar and cell distribution could be even. The negative or positive CLFs was mixed and added automatically by the LYNX480 PLUS to five slides. The staining results showed the standard staining pattern of ALK CLFs. Besides, compared to the manual application, the control droplet applied by the automated method had a more regular circular shape and better cell distribution, as shown in . The reason might be that, as an automated instrument LYNX480 PLUS’s sample adding probe could give a consistent liquid adding force and adding speed, so the CLFs droplet’s diameter and the cell density in each droplet can be highly uniform. Therefore, automatic application by the LYNX480 PLUS platform might be an accurate and labor-saving way to add CLFs. Determination of the CLFs setting scheme on the LYNX480 PLUS system We also tested two control setting schemes to evaluate whether the different setting positions of CLFs could influence the staining results and to determine the better application area on the slide. One was setting the CLFs away from the label end of the slide . The other was near the label . After mounting the tissue sections and baking the slides, we applied these two schemes at the same time to the 87 lung adenocarcinoma sample slides using the LYNX480 PLUS platform. The CLFs PPA and NPA results were calculated in , based on the standard staining pattern of ALK CLFs described in Results Section of the Results section. When the controls were set near the label end, the negative percentage agreement (NPA) was 98.8% while the PPA reached 100%, with a total agreement of 99.4%. However, it was only 89.7% for NPA and 90.8% for PPA when the controls were set far away from the label end, with a total agreement of 90.2%, significantly lower than the other control setting scheme. The results of IHC staining are shown in . After observation, we found that on some slides, the control droplets placed away from the label end were uneven. The reason for this was probably that, the gravitationally-guided melting wax during the slide baking procedure may have flowed through part of the slide space away from the label end. A control droplet was then added there, partially covering the re-solidified wax and affecting the droplet shape during the dewaxing procedure. The same phenomenon was not observed when the controls were set near the label end of the slide. Therefore, we will apply CLFs near the label end for our further study. CLFs staining pattern changes in IHC The processing time of antigen retrieval and the dilution of antibodies could be the main factors influencing the results of ALK staining. Whether CLFs could detect the variation of antigen retrieval and antibody dilution in IHC was verified on the LYNX480 PLUS platform. The confirmed EML4-ALK lung adenocarcinoma samples were used as tissue controls containing positive tumor cells negative lymphocytes and interstitial fiber cells. It was also tested whether CLFs could play the same quality control role as tissue control. ALK-positive and negative CLFs were applied simultaneously to 15 slides by an automatic staining device before antigen retrieval. Each slide contained both CLFs droplets and a confirmed EML4-ALK tissue specimen. Staining of CLFs and tissue on five slides treated with proper antigen retrieval time (60 min) showed the standard IHC staining pattern . Without antigen retrieval or insufficient treating time (20 min used in this study), positive CLFs showed negative staining or only weak cytoplasmic staining, which was consistent with the staining results of the control tissue specimen . Therefore, CLFs can be a quality control material to monitor the effect of antigen retrieval. CLFs with confirmed EML4-ALK tissue controls were also stained with different concentrations of ALK BP6165 antibody. The optimal dilution of BP6165 tested previously was 1:200. As shown in , all lung adenocarcinoma samples, ALK positive and negative cell control showed a standard staining pattern when the antibody dilution rate was 1:200 . When a higher concentration antibody with a dilution rate of 1:25 was applied, the lymphocytes in the lung adenocarcinoma samples showed nonspecific staining and negative cell control showed “background staining” . When an antibody dilution of 1:1,600 was applied, lung adenocarcinoma samples showed weaker staining and the positive cell control showed a lower positive rate . When a 1:6400 dilution ratio of BP6165 was applied, both lung adenocarcinoma samples and the positive cell control showed even weaker staining . Therefore, CLFs and lung adenocarcinoma samples have a high consistency of variation when the antibody concentration changes, indicating that CLFs can be a type of quality control material used to monitor the change in antibody concentration.
Of the 87 patients with lung adenocarcinoma, the median age was 52 years in the current cohort. There were 35 men and 52 women. The pathologic stages were stage I in 40 patients, stage II in 38 patients, and stage III in 9 patients. According to the IALSC/ATS/ERS classification, the most prevalent subtype was acinar adenocarcinoma (37.93%), followed by minimally invasive adenocarcinoma (26.44%), papillary predominant (9.20%), adenocarcinoma in situ (6.90%), solid predominant (6.90%), lepidic predominant (6.90%), variants of invasive adenocarcinoma (4.60%) and micropapillary predominant (1.15%). The clinicopathologic characteristics of the patients are listed in .
Three lung adenocarcinoma samples with known EML4-ALK status as determined by qRT-PCR and FISH were analyzed for ALK protein expression using the D5F3/VENTANA and BP6165/LYNX480 PLUS immunohistochemical assays, respectively. According to the optimized protocol introduced by the manufacturer (Biolynx, China), staining patterns on lung adenocarcinoma samples using the BP6165 concentrated antibody on the LYNX480 PLUS platform showed weaker specific cytoplasmic signals and less background than staining patterns with the ALK (D5F3) CDx Kit on the VENTANA BenchMark XT platform .
A total of 87 lung adenocarcinoma samples were then used to study the concordance of the BP6165 antibody assay on the LYNX480 PLUS platform with the D5F3 CDx Kit on the VENTANA BenchMark XT platform. The BP6165 antibody assay identified all 47 ALK-rearranged tumors as assessed by five independent pathologists based on the ALK (D5F3) CDx binary scoring algorithm. The average positive percentage agreement (PPA) was 98.30% . The diagnostic results of the two platforms as assessed by five independent pathologists showed good agreement (kappa > 0.80) . ALK rearrangement was confirmed by FISH in all tumors and two of the cases with weak staining intensity. Of the 47 ALK-positive cases, 45 were undoubtedly scored as positive. Two of 47 cases were scored as negative with the possible reason that these two cases were weakly expressed around the low limit of detection level, and the BP6165-480 PLUS Assay had weaker staining than the D5F3-VENTANA Assay as mentioned in the ‘Comparison between rabbit monoclonal anti-ALK antibody BP6165 and ALK (D5F3) CDx Kit’ section of the Results section. The diagnostic results as assessed by five independent pathologists are provided in .
To meet the requirements of setting quality control in ALK testing, CLFs prepared from cell lines was selected and tested to determine whether it could be used as a control. When appropriate IHC protocol was used, 80%–95% of ALK-positive cells were presented as moderate to strong staining on the cytoplasm, while no positive staining was present on ALK-negative cells---this pattern was defined as the standard staining pattern for ALK CLFs defined by the manufacturer. Both ALK-positive cells and negative CLFs were vortexed for 10–15 s and then 1–2 μL were manually applied to the slide by five technicians. All staining showed the same pattern according to the manufacturer’s interpretation guidelines, in which the positive showed 80%–95% cytoplasm staining and the negative showed no positive staining . Cellular structures such as cell membranes, cytoplasmic, and nuclear details, were also well preserved. However, the shape of all the droplets was very different from one to another, as shown in , only A1 and A4 are in circle shape but still with different diameters. The cell distribution of some droplets was also found to be uneven, especially in negative cell droplets.
The same bottles of ALK CLFs were performed in an automated way on the QC module in LYNX480 PLUS platform to see whether the droplets shape and diameter could be similar and cell distribution could be even. The negative or positive CLFs was mixed and added automatically by the LYNX480 PLUS to five slides. The staining results showed the standard staining pattern of ALK CLFs. Besides, compared to the manual application, the control droplet applied by the automated method had a more regular circular shape and better cell distribution, as shown in . The reason might be that, as an automated instrument LYNX480 PLUS’s sample adding probe could give a consistent liquid adding force and adding speed, so the CLFs droplet’s diameter and the cell density in each droplet can be highly uniform. Therefore, automatic application by the LYNX480 PLUS platform might be an accurate and labor-saving way to add CLFs.
We also tested two control setting schemes to evaluate whether the different setting positions of CLFs could influence the staining results and to determine the better application area on the slide. One was setting the CLFs away from the label end of the slide . The other was near the label . After mounting the tissue sections and baking the slides, we applied these two schemes at the same time to the 87 lung adenocarcinoma sample slides using the LYNX480 PLUS platform. The CLFs PPA and NPA results were calculated in , based on the standard staining pattern of ALK CLFs described in Results Section of the Results section. When the controls were set near the label end, the negative percentage agreement (NPA) was 98.8% while the PPA reached 100%, with a total agreement of 99.4%. However, it was only 89.7% for NPA and 90.8% for PPA when the controls were set far away from the label end, with a total agreement of 90.2%, significantly lower than the other control setting scheme. The results of IHC staining are shown in . After observation, we found that on some slides, the control droplets placed away from the label end were uneven. The reason for this was probably that, the gravitationally-guided melting wax during the slide baking procedure may have flowed through part of the slide space away from the label end. A control droplet was then added there, partially covering the re-solidified wax and affecting the droplet shape during the dewaxing procedure. The same phenomenon was not observed when the controls were set near the label end of the slide. Therefore, we will apply CLFs near the label end for our further study.
The processing time of antigen retrieval and the dilution of antibodies could be the main factors influencing the results of ALK staining. Whether CLFs could detect the variation of antigen retrieval and antibody dilution in IHC was verified on the LYNX480 PLUS platform. The confirmed EML4-ALK lung adenocarcinoma samples were used as tissue controls containing positive tumor cells negative lymphocytes and interstitial fiber cells. It was also tested whether CLFs could play the same quality control role as tissue control. ALK-positive and negative CLFs were applied simultaneously to 15 slides by an automatic staining device before antigen retrieval. Each slide contained both CLFs droplets and a confirmed EML4-ALK tissue specimen. Staining of CLFs and tissue on five slides treated with proper antigen retrieval time (60 min) showed the standard IHC staining pattern . Without antigen retrieval or insufficient treating time (20 min used in this study), positive CLFs showed negative staining or only weak cytoplasmic staining, which was consistent with the staining results of the control tissue specimen . Therefore, CLFs can be a quality control material to monitor the effect of antigen retrieval. CLFs with confirmed EML4-ALK tissue controls were also stained with different concentrations of ALK BP6165 antibody. The optimal dilution of BP6165 tested previously was 1:200. As shown in , all lung adenocarcinoma samples, ALK positive and negative cell control showed a standard staining pattern when the antibody dilution rate was 1:200 . When a higher concentration antibody with a dilution rate of 1:25 was applied, the lymphocytes in the lung adenocarcinoma samples showed nonspecific staining and negative cell control showed “background staining” . When an antibody dilution of 1:1,600 was applied, lung adenocarcinoma samples showed weaker staining and the positive cell control showed a lower positive rate . When a 1:6400 dilution ratio of BP6165 was applied, both lung adenocarcinoma samples and the positive cell control showed even weaker staining . Therefore, CLFs and lung adenocarcinoma samples have a high consistency of variation when the antibody concentration changes, indicating that CLFs can be a type of quality control material used to monitor the change in antibody concentration.
Given the daily increasing use of IHC staining as a companion diagnostic tool, the use of positive and negative controls for IHC is essential for process standardization and repeatability . FFPE tissue samples pre-confirmed for the presence or absence of specific target antigens have been widely used as positive and negative controls . The preparation of tissue controls has doubled the IHC workload, which is both time-consuming and tissue material-intensive. Moreover, ALK-positive lung adenocarcinoma samples are clinically scarce, making it difficult to meet the demand for an adequate supply of controls. Here a novel ALK antibody with clone number BP6165 and CLFs produced by genetically modified cell lines and the IHC staining system LYNX480 PLUS with QC setting and recording function was developed. IHC staining with BP6165 antibody was performed by a non-signal-enhancing staining procedure. The staining of lung cancer specimens using the BP6165/LYNX480 PLUS system was highly concordant with the D5F3/VENTANA system. The sensitivity of the BP6165 assay was 98.30%. The specificity of the BP6165/LYNX480 PLUS was 100%. Other studies reported a sensitivity of 95% with 5A4/VENTANA , 83%–100% with D5F3/VENTANA and 100% with 1A4/VENTANA . The specificity of D5F3/VENTANA and 1A4/VENTANA was reported to be 98% each, respectively . The D5F3/VENTANA assay produced a more intense cytoplasmic signal than BP6165 but with higher background and focal staining. These results may be due to the tyramide signal amplification step in the D5F3/VENTANA system, which requires trained staining and experienced evaluation. CLFs were successfully applied by the LYNX480 PLUS system, with an increased success rate of ALK-positive control setting when compared to that of tissue control, which is free of tissue consumption and has improved efficiency. The benefits of an automated IHC Staining System with QC function include avoiding human operation error and spontaneous QC operation information recording. When conditions such as antibody dilution and antigen retrieval in a IHC testing changed, the staning results of both CLFs and tissue samples would change accordingly, for both form of IHC controls the changes in staining intensity and positive rate were varied identically. The limitation of this approach is that pathologists may not be familiar with CLFs without tissue morphology. This will limit the application of the new controls in IHC testing. Moreover, to test whether ALK CLFs could work well under more staining conditions, a larger scale of tests using different antibodies and staining platforms is needed. These results suggest that CLFs can be an alternative to traditional ALK tissue quality control, and is reliable, convenient in operation, and saves tissue material, which can further promote the success rate of IHC QC setting and improve the productivity of pathology laboratories. The availability of standardized protocols for ALK rearrangement detection using the BP6165 concentrated antibody on the LYNX480 PLUS platform will expand the number of laboratories that can determine the eligibility of patients with lung adenocarcinoma for treatment with ALK tyrosine kinase inhibitors in a reliable and concordant manner. Automated application of CLFs via LYNX480 PLUS has a more even distribution than manual application. By comparing the tissue positive control, CLFs can not only monitor the running condition of the IHC staining system and protocol sensitivity but also ensure that the correct antibody and antigen retrieval conditions are applied. The LYNX480 PLUS platform combined with CLFs provides a fast, low-cost solution without the consumption of scarce tissue quality controls for IHC testing in day-to-day pathological practice.
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The Colonic Vitamin D Receptor and Inflammatory Bowel Disease: No Correlation to Histologic or Endoscopic Inflammation | b2317e7f-4acf-406c-bb89-0f3e9c78fbf9 | 11744339 | Anatomy[mh] | Introduction Inflammatory bowel disease (IBD), a disease entity comprised of ulcerative colitis (UC) and Crohn's disease (CD), has a complex and incompletely mapped pathogenesis. IBD is thought to occur when the delicate immunological balance of the gastrointestinal (GI) tract is disturbed, with a vicious circle of inappropriate immune response to a disrupted gut bacterial microbiome with resulting inflammatory response leading to disturbed epithelial cell tight junction function, which in turn results in increased bacterial translocation from the GI lumen, triggering further inflammatory response . The incidence of IBD has increased markedly over the last decades and is associated with economic development , suggesting environmental risk factors as the cause. Several potential factors have been studied, one such being vitamin D deficiency . Vitamin D is, beyond its classical role in calcium homeostasis, also a potent immunomodulator . Vitamin D deficiency has been implicated in several autoinflammatory diseases, such as for example type 1 diabetes mellitus, and multiple sclerosis . There is a clear north–south gradient in the incidence of IBD . The ‘modern’ lifestyle entails a lower exposure to UVB‐sunlight with subsequent reduction in vitamin D synthesis and increased risk of vitamin D deficiency. Up to 40% of the population of Europe can be considered vitamin D insufficient . Vitamin D deficiency is relatively common among IBD patients . The direct effects of vitamin D deficiency and supplementation on the prognosis and histopathological picture of IBD have recently come under scrutiny. Several studies have correlated vitamin D deficiency to IBD disease severity . The effects of vitamin D supplementation on the prognosis and clinical outcome of IBD have also been studied intensely in recent years with equivocal results . The immunomodulatory effects of vitamin D have been well described through in vitro and animal studies. The vitamin D receptor (VDR) is a nuclear receptor that acts as a transcription factor, mainly located in the cytoplasm in its inactive form. Active vitamin D (1,25 (OH) 2D) binds to and activates VDR in the cytoplasm, which forms a heterodimer with the retinoid X receptor. This heterodimer enters the cell nucleus and binds to vitamin D response elements on cellular DNA, leading to several changes in gene expression . Activated VDR can thus be described as vitamin D's intracellular mechanism of action. VDR polymorphisms are associated with IBD and knockout of VDR results in increased severity of chemically induced colitis in mice . VDR has been well described in in vitro and animal studies and is considered to play an important immunomodulatory role by promoting the integrity of the intestinal barrier—both by down‐regulating enterocyte apoptosis and by increasing the production of claudins and cadherins . In addition, VDR also downregulates NF‐κB signalling, a crucial mediator in immune activation of particular importance in CD . VDR also regulates the autophagy‐related gene ATG16L1 and has been shown to promote secretion of antimicrobial peptides by Paneth cells . In immune cells, VDR inhibits differentiation of naïve CD4+ T cells into proinflammatory Th17 cells in favour of anti‐inflammatory Tregs, while inducing the development of tolerogenic dendritic cells . Some histopathological studies have suggested a relationship between intestinal inflammation in IBD and low immunohistochemical expression of VDR , with VDR expression being lower in IBD patients and inversely correlating with histologic inflammatory score, but there is a paucity of studies with much to be elucidated. Studies are also conflicting regarding the relationship between circulating vitamin D status and VDR expression in the intestine, with some studies showing correlation and others not . It is therefore theoretically possible that dysregulation of VDR plays a role in IBD pathogenesis, either in conjunction with vitamin D deficiency or independent of circulatory vitamin D status. Our aim was to retrospectively study how immunohistochemical VDR expression correlated to IBD disease severity as evaluated through endoscopic and histopathological inflammation, as well as clinical and laboratory correlates, over time in the same patients. Materials and Methods 2.1 Patients and Tissue Specimens Putative patients were selected from a list comprised of patients admitted to the in‐patient ward or the out‐patient clinic at the Department of Gastroenterology at Skåne University Hospital, Malmö from January 2019 to June 2021. Out of 491 patients with colonic CD or UC, 57 patients could be selected. Inclusion criteria were Caucasian ethnicity (as pigmentation affects vitamin D synthesis) and ≥ 2 colonoscopies with biopsy taking in the last 10 years, with at least one colonoscopy with biopsies in completely inactive disease (defined by no microscopic evidence of inflammation from terminal ileum to rectum) and at least one colonoscopy with biopsies from active disease. An exclusion criterion was colorectal surgery prior to biopsy taking. The selection process is outlined in Figure . After sampling and evaluation, biopsies are stored at the Department of Pathology, Skåne University Hospital for one decade. Two biopsies were selected per patient, taken from the same anatomic region in the colon but on different dates and disease activity. Diagnosis, disease localisation and behaviour according to the Montreal classification were registered. Symptoms and findings (abdominal pain, diarrhoea and bloody stools at the time of colonoscopy) and routine lab tests (calprotectin, CRP, haemoglobin and albumin) registered within 1 month and serum 25(OH) vitamin D within 3 months of the corresponding colonoscopy were registered. This permissive time frame of serum 25(OH) vitamin D sampling was allowed due to vitamin D being a fat‐soluble vitamin. Data concerning medications (including vitamin D and/or other multivitamin supplements) and extraintestinal manifestations of IBD was also registered. Macroscopic picture during colonoscopy was graded based on original endoscopic assessment as normal mucosa or active colitis, ranging from mild to severe. For analysis of VDR expression in non‐IBD patients, we included 12 anonymised non‐IBD controls from random patients operated on for colorectal cancer, where a section was taken from normal colon for tissue microarray (TMA). 2.2 Immunohistochemistry and Histologic Evaluation Three μm sections were cut from each tissue block and mounted on coated slides at the Department of Pathology, Malmö, Sweden and the Department of Pathology, Aalborg, Denmark, from patients and controls, respectively. Two sections were mounted on each slide, representing the inflamed and uninflamed states from each patient, respectively. The mounted slides were sent to the Department of Pathology, Aalborg, Denmark. Slides were baked at 60°C for at least 30 min and then placed in the automated BenchMark Ultra instrument (Ventana). The slides were deparaffinised on board and submitted to heat‐induced epitope retrieval (HIER) in buffer (CC1, pH 8.5) at 99°C. Following endogenous peroxidase blocking, the primary antibody (Rabbit polyclonal VDR antibody, Sino Biological product no. 101024‐T10) was applied for 32 min at 36°C. After a wash in buffer, the visualisation system (Optiview DAB, Ventana) was applied, and the slides were finally developed with chromogen and counterstained with haematoxylin II. Staining intensity for VDR was independently scored by two pathologists (C.T. and M.B.) who were blinded regarding all other information about the samples. In cases of discrepancies between initial evaluations, a consensus was reached through discussion using a double‐headed microscope. The epithelium and stroma were scored separately as negative (0), low (1), moderate (2), or high expression (3). Weak to moderate staining reaction in less than half of the cells in each compartment were categorised as low expression, weak to moderate staining in most of the cells were categorised as moderate expression, while moderate to strong staining in almost all cells were categorised as high expression. Examples of the scoring entities are shown in Figure . The original HE‐stained slides of the biopsies were graded semi‐quantitatively by an experienced gastrointestinal pathologist (A.W.) for inflammatory activity according to GI‐KVAST (score 0–3) . 2.3 Statistics Differences in immunohistochemical VDR expression between active and inactive mucosa were tested for statistical significance using the paired samples Wilcoxon test. For comparison of the control group against active and inactive mucosa, respectively, the Mann‐Whitney U test was used. Correlation between VDR expression, histological inflammation, clinical symptoms, and laboratory measures was determined using Pearson's correlation coefficient for parametric data and Spearman's coefficient for nonparametric data. Statistical analysis was performed using SPSS version 27. A p ‐value of ≤ 0.05 was considered statistically significant. To account for multiple comparisons when comparing VDR expression between groups, a Bonferroni correction was used, giving an adjusted significance level of p ≤ 0.017 (α/ n comparisons = 0.05/3 ≈ 0.017). 2.4 Ethics This study was approved by the Swedish Regional Review Authority (Dnr 2021‐02219) and Region Skåne Consultative Board for Quality Registers, Health care Registers and Preparation (registration number 159‐21). Written informed consent was obtained from all patients before inclusion. Patients and Tissue Specimens Putative patients were selected from a list comprised of patients admitted to the in‐patient ward or the out‐patient clinic at the Department of Gastroenterology at Skåne University Hospital, Malmö from January 2019 to June 2021. Out of 491 patients with colonic CD or UC, 57 patients could be selected. Inclusion criteria were Caucasian ethnicity (as pigmentation affects vitamin D synthesis) and ≥ 2 colonoscopies with biopsy taking in the last 10 years, with at least one colonoscopy with biopsies in completely inactive disease (defined by no microscopic evidence of inflammation from terminal ileum to rectum) and at least one colonoscopy with biopsies from active disease. An exclusion criterion was colorectal surgery prior to biopsy taking. The selection process is outlined in Figure . After sampling and evaluation, biopsies are stored at the Department of Pathology, Skåne University Hospital for one decade. Two biopsies were selected per patient, taken from the same anatomic region in the colon but on different dates and disease activity. Diagnosis, disease localisation and behaviour according to the Montreal classification were registered. Symptoms and findings (abdominal pain, diarrhoea and bloody stools at the time of colonoscopy) and routine lab tests (calprotectin, CRP, haemoglobin and albumin) registered within 1 month and serum 25(OH) vitamin D within 3 months of the corresponding colonoscopy were registered. This permissive time frame of serum 25(OH) vitamin D sampling was allowed due to vitamin D being a fat‐soluble vitamin. Data concerning medications (including vitamin D and/or other multivitamin supplements) and extraintestinal manifestations of IBD was also registered. Macroscopic picture during colonoscopy was graded based on original endoscopic assessment as normal mucosa or active colitis, ranging from mild to severe. For analysis of VDR expression in non‐IBD patients, we included 12 anonymised non‐IBD controls from random patients operated on for colorectal cancer, where a section was taken from normal colon for tissue microarray (TMA). Immunohistochemistry and Histologic Evaluation Three μm sections were cut from each tissue block and mounted on coated slides at the Department of Pathology, Malmö, Sweden and the Department of Pathology, Aalborg, Denmark, from patients and controls, respectively. Two sections were mounted on each slide, representing the inflamed and uninflamed states from each patient, respectively. The mounted slides were sent to the Department of Pathology, Aalborg, Denmark. Slides were baked at 60°C for at least 30 min and then placed in the automated BenchMark Ultra instrument (Ventana). The slides were deparaffinised on board and submitted to heat‐induced epitope retrieval (HIER) in buffer (CC1, pH 8.5) at 99°C. Following endogenous peroxidase blocking, the primary antibody (Rabbit polyclonal VDR antibody, Sino Biological product no. 101024‐T10) was applied for 32 min at 36°C. After a wash in buffer, the visualisation system (Optiview DAB, Ventana) was applied, and the slides were finally developed with chromogen and counterstained with haematoxylin II. Staining intensity for VDR was independently scored by two pathologists (C.T. and M.B.) who were blinded regarding all other information about the samples. In cases of discrepancies between initial evaluations, a consensus was reached through discussion using a double‐headed microscope. The epithelium and stroma were scored separately as negative (0), low (1), moderate (2), or high expression (3). Weak to moderate staining reaction in less than half of the cells in each compartment were categorised as low expression, weak to moderate staining in most of the cells were categorised as moderate expression, while moderate to strong staining in almost all cells were categorised as high expression. Examples of the scoring entities are shown in Figure . The original HE‐stained slides of the biopsies were graded semi‐quantitatively by an experienced gastrointestinal pathologist (A.W.) for inflammatory activity according to GI‐KVAST (score 0–3) . Statistics Differences in immunohistochemical VDR expression between active and inactive mucosa were tested for statistical significance using the paired samples Wilcoxon test. For comparison of the control group against active and inactive mucosa, respectively, the Mann‐Whitney U test was used. Correlation between VDR expression, histological inflammation, clinical symptoms, and laboratory measures was determined using Pearson's correlation coefficient for parametric data and Spearman's coefficient for nonparametric data. Statistical analysis was performed using SPSS version 27. A p ‐value of ≤ 0.05 was considered statistically significant. To account for multiple comparisons when comparing VDR expression between groups, a Bonferroni correction was used, giving an adjusted significance level of p ≤ 0.017 (α/ n comparisons = 0.05/3 ≈ 0.017). Ethics This study was approved by the Swedish Regional Review Authority (Dnr 2021‐02219) and Region Skåne Consultative Board for Quality Registers, Health care Registers and Preparation (registration number 159‐21). Written informed consent was obtained from all patients before inclusion. Results 3.1 Patients and Disease Characteristics After the selection process, 28 patients could be included in the study (Figure ) with 56 biopsies in total that were analysed. The selected group consisted of 21 patients with UC and 7 with CD in the colon, which were compared with 12 non‐IBD controls. The UC and CD groups were of a similar average age and gender representation. The majority of CD patients had non‐stricturing, non‐penetrating disease, whereas most UC patients had extensive colitis. Two out of 7 CD patients had undergone ileocecal resection before the biopsies were taken. Disease characteristics of the patients and IBD medications at the time of each colonoscopy are outlined in Tables and , respectively. Routine laboratory tests and vitamin D status are presented in Table . 3.2 Equal VDR Expression Was Seen Throughout the Colon VDR immunohistochemical staining is exemplified in Figure . Immunohistochemical staining of VDR showed staining in both epithelium (mean 2.04 ± 0.63) and stromal cells (mean 1.68 ± 0.54), with significantly more staining in epithelium ( p < 0.005). There was no significant difference in VDR expression between different segments of the colon ( p = 0.62 for epithelium and p = 0.75 for stroma) (Figure ). 3.3 VDR Does Not Differ in Active Versus Inactive IBD and Without Any Correlation to Histologic Inflammation Mean VDR expression in active IBD was 1.96 ± 0.64 for epithelium and 1.75 ± 0.59 for stroma. VDR expression in inactive IBD was 2.11 ± 0.63 for epithelium and 1.61 ± 0.50 for stroma. In non‐IBD controls, VDR expression was 2.42 ± 0.52 for epithelium and 2.08 ± 0.52 for stroma. There was no significant difference in VDR expression between active and inactive biopsies ( p = 0.40 for epithelium and p = 0.29 for stroma). When comparing non‐IBD controls and inactive IBD mucosa, there was no difference in VDR expression in epithelium ( p = 0.22), but a trend for significantly more intense stromal VDR staining in controls was observed ( p = 0.042) (Figure ). However, this result did not reach the Bonferroni‐corrected significance threshold of 0.017. There was a trend but no significant difference in VDR expression between non‐IBD controls and active IBD in epithelium ( p = 0.074) but no significant difference for stroma ( p = 0.163). Furthermore, no significant difference was found in VDR staining intensity between UC and CD ( p = 0.22 for epithelium and p = 0.16 for stroma). No significant correlation was found between VDR expression and histologic inflammation ( r = −0.19, p = 0.89 for epithelium and r = 0.13, p = 0.35 for stroma) (Figure ), colonoscopic inflammation ( r = −0.33, p = 0.81 for epithelium and r = 0.17, p = 0.22 for stroma) or any other clinical or laboratory parameters, including serum 25(OH) vitamin D ( r = −0.91, p = 0.82 for epithelium and r = −0.18, p = 0.64 for stroma). Serum 25(OH) vitamin D did not correlate significantly to any clinical or laboratory parameter (data not shown). Patients and Disease Characteristics After the selection process, 28 patients could be included in the study (Figure ) with 56 biopsies in total that were analysed. The selected group consisted of 21 patients with UC and 7 with CD in the colon, which were compared with 12 non‐IBD controls. The UC and CD groups were of a similar average age and gender representation. The majority of CD patients had non‐stricturing, non‐penetrating disease, whereas most UC patients had extensive colitis. Two out of 7 CD patients had undergone ileocecal resection before the biopsies were taken. Disease characteristics of the patients and IBD medications at the time of each colonoscopy are outlined in Tables and , respectively. Routine laboratory tests and vitamin D status are presented in Table . Equal VDR Expression Was Seen Throughout the Colon VDR immunohistochemical staining is exemplified in Figure . Immunohistochemical staining of VDR showed staining in both epithelium (mean 2.04 ± 0.63) and stromal cells (mean 1.68 ± 0.54), with significantly more staining in epithelium ( p < 0.005). There was no significant difference in VDR expression between different segments of the colon ( p = 0.62 for epithelium and p = 0.75 for stroma) (Figure ). VDR Does Not Differ in Active Versus Inactive IBD and Without Any Correlation to Histologic Inflammation Mean VDR expression in active IBD was 1.96 ± 0.64 for epithelium and 1.75 ± 0.59 for stroma. VDR expression in inactive IBD was 2.11 ± 0.63 for epithelium and 1.61 ± 0.50 for stroma. In non‐IBD controls, VDR expression was 2.42 ± 0.52 for epithelium and 2.08 ± 0.52 for stroma. There was no significant difference in VDR expression between active and inactive biopsies ( p = 0.40 for epithelium and p = 0.29 for stroma). When comparing non‐IBD controls and inactive IBD mucosa, there was no difference in VDR expression in epithelium ( p = 0.22), but a trend for significantly more intense stromal VDR staining in controls was observed ( p = 0.042) (Figure ). However, this result did not reach the Bonferroni‐corrected significance threshold of 0.017. There was a trend but no significant difference in VDR expression between non‐IBD controls and active IBD in epithelium ( p = 0.074) but no significant difference for stroma ( p = 0.163). Furthermore, no significant difference was found in VDR staining intensity between UC and CD ( p = 0.22 for epithelium and p = 0.16 for stroma). No significant correlation was found between VDR expression and histologic inflammation ( r = −0.19, p = 0.89 for epithelium and r = 0.13, p = 0.35 for stroma) (Figure ), colonoscopic inflammation ( r = −0.33, p = 0.81 for epithelium and r = 0.17, p = 0.22 for stroma) or any other clinical or laboratory parameters, including serum 25(OH) vitamin D ( r = −0.91, p = 0.82 for epithelium and r = −0.18, p = 0.64 for stroma). Serum 25(OH) vitamin D did not correlate significantly to any clinical or laboratory parameter (data not shown). Discussion In this study, we have shown that VDR is expressed similarly in colonic epithelium and stroma, regardless of IBD disease activity. VDR expression did not change in active disease compared to inactive disease in the same patient. No correlation was found between VDR expression and histological inflammation, endoscopic inflammatory severity, or any laboratory findings. While there was a trend for more intense stromal VDR staining in non‐IBD controls compared to non‐inflamed IBD patients, and epithelial VDR staining in controls compared to inflamed IBD biopsies, no such trend was found between controls and inactive IBD in epithelium or controls and active IBD in stroma. When adjusting with a Bonferroni correction, statistical significance was not reached, suggesting that these trends could reflect a type I error owing to multiple comparisons. However, our group of control biopsies was small ( n : 12) compared to IBD biopsies ( n : 28 × 2), so this part of the statistical analysis might have been inadequately powered, hiding a true but minor significant difference in VDR levels. A potential subtle decrease in VDR levels in IBD cannot thus be entirely rejected, and more well‐powered studies might be of interest in future research. We consider our patient group to be fairly representative of the standard IBD population in terms of age and disease distribution through the colon, with the exception of a relatively higher prevalence of ulcerative pancolitis (extensive colitis) of 67%, compared to the typical relative prevalence of 15%–25% . A possible explanation for this is the fact that we recruited patients who had probably undergone more colonoscopies than the average IBD patient, as our inclusion criteria was at least 2 colonoscopies in recent years. There is a paucity of studies in the field, with results in previous studies being conflicting regarding VDR expression in non‐inflamed versus inflamed colon . Abreu‐Delgado et al. saw no difference in VDR expression between inflamed and non‐inflamed colon in the individual patient and no difference in VDR between controls and IBD, but with VDR still weakly correlating to inflammatory severity in inflamed lesions. Meanwhile, Garg et al. reported significant differences in VDR expression between inflamed and non‐inflamed colon, with VDR being reduced in inflamed portions of the colon and correlating inversely with histologic inflammation, but also with no difference in VDR levels between IBD patients and controls. Liu et al. reported significantly lower VDR expression in IBD patients compared to controls, while also demonstrating a protective role of epithelial VDR expression against chemically induced colitis. These findings tentatively suggested the emerging role of VDR as an immunological factor in IBD pathology, with VDR as an immunomodulator being locally suppressed in inflamed parts of the colon by unclear mechanisms, resulting in compromised mucosal integrity and hyperinflammation . Indeed, TNF‐α has been experimentally shown to suppress VDR expression in colon cancer cells . While this is a tempting hypothesis, we failed to reproduce similar results in this study. We believe that these prior significant findings of the aforementioned studies must be interpreted with caution. Abreu‐Delgado et al. analysed 10 IBD patients (UC:3, CD:7) with 10 controls. They found a significant inverse correlation between VDR and histologic inflammation, although very weak with an r 2 = 0.19 and a small sample size . While Liu et al. found a highly significant reduction in VDR levels in IBD patients compared to controls, information in their article is lacking regarding to numbers of patients and basic patient and disease characteristics, making it difficult to put their results in context . The study by Garg et al. was more well‐powered with 20 CD patients and 15 UC patients . However, the correlation they found between VDR mRNA levels and histologic inflammation was r 2 = 0.45 for UC and r 2 = 0.34 for CD, which is modest at best. VDR levels were similar between IBD and non‐IBD controls. They also found a small, but statistically significant, difference in VDR IHC between inflamed and non‐inflamed IBD by digital image analysis (DIA). DIA is more reproducible and precise than our manual scoring, and they scored the staining percentage, which altogether allows detection of more subtle differences. Their measured difference was of small magnitude and hence of questionable relevance. Of note, our study had a significantly larger proportion of UC patients (21 out of 28 patients) than Abreu‐Delgado et al. and Garg et al. Our patient population was similar in terms of age distribution. In this study, we found no correlation between serum 25(OH)D levels and VDR expression. There are numerous studies on the relationship between circulating 25(OH)D levels and intestinal VDR expression. A large study of 230 UC patients found a small but significant correlation between serum 25(OH)D level and immunohistochemical VDR expression . In the previously mentioned studies, Abreu‐Delgado et al. also found a positive correlation between serum 25(OH)D level and VDR expression in non‐inflamed IBD and control biopsies, but notably not in inflamed IBD biopsies. However, Garg et al. and Liu et al. found no significant correlation between 25(OH)D and VDR expression, concurring with our results. Our findings support the idea that intestinal VDR expression is regulated independently of circulating 25(OH)D. Due to our very low numbers of adequate vitamin D samples, this finding of our study must however be interpreted with great caution. Our study has limitations. Firstly, this is a retrospective study with resulting difficulties in consistently acquiring patient laboratory and clinical data. Many of our patients lacked data in one or more laboratory or clinical parameters, thus likely lowering statistical power in analysis of these variables. For example, we only had seven 25(OH) vitamin D samples. As outlined in Section , there could have been up to 1 month between blood/stool samples and the colonoscopy and up to 3 months for 25(OH) vitamin D. Secondly, vitamin D supplements are widely sold ‘over the counter’ outside the purview of the physician and not always disclosed by patients, rendering data regarding vitamin D supplements difficult to collect retrospectively. It is conceivable that concurrent vitamin D supplementation might affect VDR status, being a possible confounder. Thirdly, our method of analysing VDR expression with immunohistochemistry has limitations. It is a semiquantitative method unlike, for example, Western blotting for quantification of VDR expression. There are also numerous strengths to this study. Previous studies on VDR and IBD have been cross‐sectional and thus unable to prospectively follow patients regarding inflammatory activity and VDR expression. Using our model, we were able to prospectively follow patients over time using retrospectively collected data and thus compare active to completely inactive IBD. Our method thus differs from previous studies that mainly compared inactive to active lesions in active disease from the same colonoscopy at a single point in time, by instead comparing completely inactive IBD to active disease on an individual patient basis, which has advantages. It is possible that active IBD in one area of the colon could result in altered expression of VDR across the colon. Indeed, Garg et al. demonstrated significantly higher VDR expression in non‐inflamed IBD biopsies compared to biopsies from non‐IBD controls, and paradoxically no significant difference in VDR expression between active IBD and controls. As mentioned previously, Abreu‐Delgado et al. saw no difference in VDR expression between inflamed colon and non‐inflamed colon. We believe our model provides a more accurate picture of VDR status in IBD, as we have analysed this receptor at two different points in time in the same patient. Finally, our patient group was ethnically homogeneous (Caucasian), limiting a possible confounder of skin colour, which has been shown to affect vitamin D synthesis . Conclusions In this study, we found that VDR immunohistochemical expression does not change in active IBD compared to inactive disease, analysing biopsies from 28 IBD patients taken both in inactive and active disease (in every patient). VDR expression was equal in both UC and CD and stained equally throughout the colon. A trend for greater VDR levels in controls was partly found, but did not reach statistical significance when correcting for multiple comparisons. No significant correlation was found between VDR expression and 25(OH) vitamin D status. VDR expression did not correlate with histologic inflammation, colonoscopic inflammatory severity, clinical symptoms of IBD, or inflammatory laboratory parameters. The results in the present study differ from previous studies that have found significant inverse relationships between IBD inflammation and VDR expression. However, there are very few studies on humans with previously tentative results. Our study is, as far as we are aware, the first of its kind to analyse biopsies taken from IBD patients at two different points in time, in both active and entirely inactive IBD. In conclusion, our results do not support the hypothesis that VDR dysregulation correlates with IBD disease severity. Due to the conflicting results in different studies, a prospective study design with different phenotypes and measurement of activated VDR (with analysis of mRNA) is indicated to be able to determine whether any differences in expression do exist and, in that case, could be due to, for example, differences in regulation in different subgroups. Also, comparing VDR levels in non‐IBD to IBD on a greater study population might be of interest. This study was approved by the Swedish Regional Review Authority (Dnr 2021‐02219) and Region Skåne Consultative Board for Quality Registers, Health care Registers and Preparation (registration number 159‐21). Written informed consent was obtained from all patients before inclusion. The authors declare no conflicts of interest. |
Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA | 7e350856-8c35-4f34-a612-a00e4d541e35 | 11139991 | Microbiology[mh] | Fungi are one of the most diverse and ecologically important yet unexplored kingdoms of life . From a practical perspective, fungi are infamously hard to sample and characterize . Recent advancements in DNA-based survey methods have revolutionized studies on fungal diversity, especially its large-scale patterns – . Given that fungi occur in nearly every possible environment and substrate, current sampling campaigns and estimates of fungal diversity tend to rely explicitly on substrate-specific sampling . Sampling of soil has been popular given the relative ease with which the mycobiome of any handful of soil can be characterized through metabarcoding . Yet, whether biogeographic patterns from those substrates broadly reflect patterns in fungal taxa or biodiversity in general is unclear. Additionally, there are significant biases in the geographic areas represented in global studies , , although there have been recent efforts to expand the coverage of understudied regions . A recent methodological breakthrough for surveying fungi uses a cyclone sampler to capture fungal spores from the air, followed by DNA sequencing and sequence-based species identification . Air sampling has revealed high diversity and stronger ecological signals in community composition of fungi than soil sampling . Air sampling captures any fragments of fungi floating in the air, including the wind-dispersed spores of fungi and fragments of hyphae as well as fungal structures attached to other organisms. Consequently, air sampling detects fungal dispersal at high temporal resolution. In addition to fungal surveys, the sampling of airborne DNA has proved effective in acquiring comprehensive inventories of regional diversity of many other taxa . Here we present a global-scale database assembled by the Global Spore Sampling Project (GSSP) that was initiated in 2018–2019 . The GSSP involves 47 sampling locations distributed across all continents except Antarctica, with each location collecting two 24-hr samples per week, in most cases over a period of one year or more (Fig. ). Sampling is conducted with a cyclone sampler, which orients itself in the direction of the wind. It collects particles >1 μm in size from the air directly into a sampling tube with a single reverse-flow cyclone. For DNA sequencing, we targeted part of the nuclear ribosomal internal transcribed spacer (ITS) region, which is the universal molecular barcode for fungi . To generate semi-quantitative estimates of DNA content (in units of ng of fungal DNA per m 3 of air), we applied a spiking approach (Fig. ). To convert the sequence data into species data, we began by denoising the sequence yield into amplicon sequence variants (ASV ). We then applied probabilistic taxonomic placement using Protax-fungi , to assign ASVs to taxa at ranks from phylum to species. Finally, we used a new constrained clustering approach (see Methods ) guided by the taxonomic annotations from Protax-fungi to group ASVs into species-level operational taxonomic units (OTUs ). This clustering allowed us to assign OTUs to previously known and unknown taxa (Fig. ). Using a threshold of >90% probability of correct assignment, this resulted in 27,954 species-level OTUs, of which 1,392 could be reliably assigned to known species. The GSSP data are highly complementary to the Global Soil Mycobiome consortium (GSMc) data , as among the 10 top ranking orders in the GSSP data, only 5 were found in the 10 top ranking orders of the GSMc data (Table ).
Data acquisition The Global Spore Sampling Project (GSSP) consists of a globally distributed network of 47 sampling sites collecting two 24-hr air samples per week over one to two years (Fig. ). Each sampling site was equipped with a cyclone sampler (Burkard Cyclone Sampler for Field Operation, Burkard Manufacturing Co Ltd; http://burkard.co.uk/product/cyclone-sampler-for-field-operation ). The sampling sites represent varying climatic zones and altitudes. Most sampling sites were located in natural environments, with a few in urban settings. Due to logistical reasons, we could not start the global sampling fully synchronously. In some locations, sampling had to stop earlier than expected due to external reasons (e.g., storms breaking the equipment or restrictions caused by COVID-19 lockdown). See Fig. for realized sampling periods per site. In October and November 2017, prior to the start of global sampling, a field test was performed in a grassy area at the University of Helsinki Viikki campus (60.2278 N, 25.01653E) to evaluate the quantity of fungal DNA collected over different time frames and in field blanks handled with and without the use of gloves on the part of the human handler. In total we collected seven 24-hour samples, three one-hour samples, and three 10-minute samples, in addition to four field blanks handled with gloves and five field blanks handled without gloves. For field blanks, Eppendorf vials were installed in the cyclone sampler in the field, but the sampler was not activated. The vials were then removed after one minute and sealed. Based on the results of these field tests (see Technical Validation ), we decided to use a 24-hr sampling period, and to instruct the participating teams to handle the samples with gloves. The functioning of the cyclone sampler and sample preparation procedure is described in detail in Ovaskainen et al . . The cyclone samplers were placed at ground level to ensure free airflow through the sampler. The sampler collected particles >1 µm in size from the air directly into a sterile Eppendorf vial. The sampler’s average throughput of air was 16.5 L per minute for a total of 23,800 L (23.8 m 3 ) during each 24-hour sampling period. After sampling, the vial was removed from the cyclone sampler, the lid was closed, and the vials were labelled with the site code and week number. We also recorded the time and duration of the sampling, along with notes on the presence of rainwater or larger objects (e.g., arthropods) in the sampling vial. To avoid contamination, gloves were used while handling the samples and the device. Participants were instructed to clean the cyclone part of the device monthly with water and soap and to rinse it with ethanol, or to sterilize it with dry-heat, chlorine, or UV when such equipment was available. The samples were stored at −20 °C until shipped to the University of Helsinki, Finland. Shipping was done at room temperature. We do not expect much bias across samples due to this approach, as the shipping time was relatively short and most shipments were received with a similar delay. In Helsinki, the samples were separated from visible arthropods. To avoid losing fungal spores attached to arthropod bodies, the surface of any arthropod present in the sample was rinsed by adding sterile water into the sample tube and vortexing. After washing, the arthropods were removed with sterile tweezers. Samples containing any rainwater were dried in a vacuum drier (24 h). Prior to drying, each sample was covered with a porous Parafilm to avoid cross-contamination between samples. After drying, all samples were sent to the University of Guelph, Canada, for DNA extraction and sequencing. DNA extraction, sequencing, and quantifying DNA amount A detailed description of DNA extraction, primers, and sequencing is given in Ovaskainen et al . . In brief, the target genetic marker, i.e., the ITS2 region of the rRNA operon, was amplified using the polymerase chain reaction (PCR) for 20 cycles with fusion primers ITS_S2F , ITS3, and ITS4 tailed with Illumina adapters, and sequenced on Illumina MiSeq with 2 × 300 bp paired end reads. ITS_S2F was included as a second forward primer to specifically amplify plant DNA, in order to include pollen as well as fungal spores in the analysis. However, only a small fraction of reads resulted from the ITS_S2F-ITS4 amplicon, and so these were removed in the early stages of the analysis and not further considered. To quantify the amount of fungal DNA, we applied a spike-in approach , using nine positive control plasmids prepared from synthetic sequences. These sequences were designed to be generally consistent with fungal ITS sequences, but different from all known natural sequences . The positive synthetic control (0.01 ng/μl) containing nine plasmids was spiked into the PCR master mix at a ratio of 1:100 for the first 336 samples. For the remaining 2,432 samples, we used a 1:1000 ratio, since the 1:100 ratio produced an unnecessarily high proportion of the sequences representing the spikes. This could have compromised the sequencing depth of the targeted fungal sequences. We converted the ratio of the non-spike vs. spike-sequences into semi-quantitative estimates of DNA amount in units of ng of DNA per m 3 of air as described previously . The resulting estimates of DNA abundance correlated well with a qPCR-based estimate of DNA amount. Each MiSeq run included 84 study samples, one negative control sample introduced in the DNA extraction step, and two negative controls introduced in the PCR step. The only exceptions were two runs (CCDB-35004 and CCDB-35005) which included three extraction negative controls and no PCR negative controls. The same master mix as used for the study samples, including synthetic positive controls, was also used for the negative controls. For the field test samples, DNA was extracted following the same protocol, except that 300 µL of ILB extraction buffer was used instead of 270 µL, and the final DNA extract was eluted into 35 µL of Tris buffer instead of 45 µL. Two extraction blanks were also included. A fungal DNA standard was extracted from Fleischmann’s Baker’s commercial yeast. Then, approximately one-half package of the commercial yeast was added to 50 mL warm water and proofed with sugar until the formation of active foam. Yeast DNA was extracted using an abbreviated version of the protocol described above, which omitted the initial ILB extraction buffer and homogenization in the TissueLyzer. Instead, six aliquots of 300 µL of yeast suspension were directly transferred to 900 µL each of 5 M GuSCN binding buffer, incubated at 56 °C for 1 hour in an orbital shaker, and then at 65 °C for 1 hour. The six eluates were pooled and quantified using a Qubit fluorometer with the DS DNA high sensitivity kit. The extract, which had a DNA concentration of 2.77 ng/µL, was then diluted to form standards of 1 ng/µL, 0.1 ng/µL, 0.01 ng/µL, 0.001 ng/µL, and 0.0001 ng/µL. The test samples were quantified by real-time PCR (RT-PCR) on a LightCycler96 (Roche) as described in Ovaskainen et al . , with two replicates of each of the standards for calibration. Bioinformatic processing Demultiplexed paired-end reads were first trimmed using Cutadapt version 4.2 . Because of low-quality base-calls at the 5′ end of R2 reads, we removed the first 16 bases from all R2 reads. We then trimmed the 3′ end of both reads with a quality threshold of 2 (i.e., remove only N’s), and the 5′ end of R2 with a quality threshold of 10. Reads were then trimmed to the ITS3-ITS4 amplicon, with a minimum 10 bp overlap and error tolerance of 0.2. Primers at the 3′ ends of both reads were optional but read pairs where the 5′ primer was not detected (including reads originating from the ITS_S2F-ITS4 amplicon) were removed. Pairs were discarded after trimming if either read was less than 100 bases or contained ambiguous bases. Reads were then further processed using DADA2 version 1.18.0 . First, all pairs where either read matched to the PhiX genome were removed, along with reads where R1 contained more than 3 expected errors or R2 contained more than 5 expected errors. Reads were denoised using separate error profiles fit for each MiSeq run with default parameters, and denoised read pairs were merged to form ASVs with a minimum overlap of 10 bp and a maximum mismatch of 1 bp. An initial de novo chimera check was performed on the merged ASV table using the DADA2 “consensus” method . A second reference-based chimera check was then performed using the “uchime_ref” option in VSEARCH version 2.22.1 with reference Sanger sequences from the UNITE v9database , as used by the PlutoF Species Hypothesis matching pipeline . The synthetic spike sequences were also included as references. Non-chimeric ASVs that were identical except for end gaps were combined, with the most abundant ASV sequence taken as representative. ASVs with a sequence similarity greater than 0.9 to SynMock spike sequences were identified using the “-usearch_global” command in VSEARCH 2.22.1 and labelled as spike sequences. Non-spike sequences were aligned using Infernal 1.1.4 to the covariance model for the combined 5.8 S and 28 S rRNA genes from the FunGene pipeline which was truncated to include only the region between the ITS3 and ITS4 primer sites. Sequences that did not match the full length of the model, or which scored less than 50, were discarded. This resulted in a 65,912 ASVs × 2,768 samples matrix, with entries representing read abundance. A taxonomic affiliation was assigned to each non-spike ASV sequence using Protax-fungi . This procedure gives assignments at each taxonomic rank from phylum to species, along with a calibrated probability that the assignment at each rank is correct. We used the 90% probability threshold for taxonomic assignments. Additionally, because Protax-fungi does not include non-fungi in its reference database, we matched ASVs to the same UNITE Sanger sequences mentioned above using the “usearch_global” command of VSEARCH 2.22.1 , with a sequence similarity threshold of 0.8. Sequences whose best match was annotated as belonging to a kingdom other than Fungi , or which had no match at the given threshold, were annotated as potential non-fungi but retained for the next clustering step. Due to frequent intraspecific sequence variants for the ITS region, ITS-based ASVs are not suitable proxies for fungal species . Consequently, we developed a taxonomically-guided clustering approach using the taxonomic annotations from Protax-fungi to group ASVs into approximately species-level OTUs. Our approach also groups sequences, including those without existing taxonomic annotations, into clusters approximating each taxonomic rank. First, we calculated optimal single-linkage clustering thresholds for each combination of a known taxon at a rank higher than species (henceforth, the “supertaxon”) and a taxonomic rank lower than that taxon (“subrank”) using multi-class F-measure optimization as described for the tool Dnabarcoder . However, instead of using BLAST to calculate pairwise distances, as in Dnabarcoder, we based our clusters on a sparse pairwise sequence distance matrix generated by the -calc_distmx command in USEARCH 11.0.667 , with an initial kmer dissimilarity threshold of 0.4, maximum global alignment dissimilarity of 0.6, and a gap penalty of 1. For each supertaxon-subrank combination where there were at least five subtaxa represented by a total of at least ten reference sequences, we chose the clustering threshold that generated clusters most closely corresponding to the reference identifications. This match was assessed by the multi-class F-measure. Thus, we generated optimal thresholds for clustering all fungi into ranks from phylum to species; for clustering each phylum into ranks from class to species, and so on. The ASVs were then clustered in three stages for each taxonomic rank from phylum to species, with the species-level clusters forming the final OTUs. In the first step, cluster cores were formed by the ASVs which had been assigned to taxa at that rank by Protax-fungi. These cluster cores were used as a reference for a closed-reference clustering stage, in which unassigned ASVs were matched to the closest cluster core using the optimized sequence similarity threshold for that rank and the nearest enclosing supertaxon. To this aim, we applied the “-usearch_global command” in VSEARCH version 2.22.1 . We used the same alignment penalties for closed-reference clustering as for the threshold optimization clustering above to ensure that distance calculations were comparable. Iterations were performed until no new matches were found, generating approximately single-linkage clusters without merging cluster cores. Finally, in the third step, remaining unclustered ASVs at each rank were clustered using de novo single-linkage clustering using distances calculated by USEARCH as above, and again using the optimized sequence similarity threshold for the rank and nearest supertaxon. These de novo clusters, which we refer to as “pseudotaxa”, were assigned placeholder taxonomic names of the form “pseudo{rank}_{number}” (e.g., “pseudogenus_0216” for a cluster at genus rank). At each taxonomic rank after phylum, the three clustering stages were performed within the clusters generated at higher taxonomic ranks. Thus, two ASVs that were assigned to, for instance, different phyla by Protax-fungi, could not be clustered together into the same pseudoclass, even when their sequence similarity was greater than the class-level threshold determined for one or both phyla. Because the current version of Protax-fungi is trained only to identify fungi and not all eukaryotes, the non-fungal sequences were generally unidentified at the phylum level and were grouped into a large number of pseudophyla. We used the kingdom-level results from matching to the UNITE Sanger references (see above) to classify ASVs as “known fungi”, “known non-fungi”, or “unknown kingdom”, and removed pseudotaxa containing more known non-fungal ASVs than known fungal ASVs. At the phylum level, pseudotaxa containing only ASVs of unknown kingdoms were also removed. The final result of this process was a 27,954 species-level OTUs × 2,768 samples read abundance matrix, along with taxonomic annotations at each rank from phylum to species, including pseudotaxon placeholders. The bioinformatics pipeline was implemented using the Targets package version 1.3 in R version 4.2.2.
The Global Spore Sampling Project (GSSP) consists of a globally distributed network of 47 sampling sites collecting two 24-hr air samples per week over one to two years (Fig. ). Each sampling site was equipped with a cyclone sampler (Burkard Cyclone Sampler for Field Operation, Burkard Manufacturing Co Ltd; http://burkard.co.uk/product/cyclone-sampler-for-field-operation ). The sampling sites represent varying climatic zones and altitudes. Most sampling sites were located in natural environments, with a few in urban settings. Due to logistical reasons, we could not start the global sampling fully synchronously. In some locations, sampling had to stop earlier than expected due to external reasons (e.g., storms breaking the equipment or restrictions caused by COVID-19 lockdown). See Fig. for realized sampling periods per site. In October and November 2017, prior to the start of global sampling, a field test was performed in a grassy area at the University of Helsinki Viikki campus (60.2278 N, 25.01653E) to evaluate the quantity of fungal DNA collected over different time frames and in field blanks handled with and without the use of gloves on the part of the human handler. In total we collected seven 24-hour samples, three one-hour samples, and three 10-minute samples, in addition to four field blanks handled with gloves and five field blanks handled without gloves. For field blanks, Eppendorf vials were installed in the cyclone sampler in the field, but the sampler was not activated. The vials were then removed after one minute and sealed. Based on the results of these field tests (see Technical Validation ), we decided to use a 24-hr sampling period, and to instruct the participating teams to handle the samples with gloves. The functioning of the cyclone sampler and sample preparation procedure is described in detail in Ovaskainen et al . . The cyclone samplers were placed at ground level to ensure free airflow through the sampler. The sampler collected particles >1 µm in size from the air directly into a sterile Eppendorf vial. The sampler’s average throughput of air was 16.5 L per minute for a total of 23,800 L (23.8 m 3 ) during each 24-hour sampling period. After sampling, the vial was removed from the cyclone sampler, the lid was closed, and the vials were labelled with the site code and week number. We also recorded the time and duration of the sampling, along with notes on the presence of rainwater or larger objects (e.g., arthropods) in the sampling vial. To avoid contamination, gloves were used while handling the samples and the device. Participants were instructed to clean the cyclone part of the device monthly with water and soap and to rinse it with ethanol, or to sterilize it with dry-heat, chlorine, or UV when such equipment was available. The samples were stored at −20 °C until shipped to the University of Helsinki, Finland. Shipping was done at room temperature. We do not expect much bias across samples due to this approach, as the shipping time was relatively short and most shipments were received with a similar delay. In Helsinki, the samples were separated from visible arthropods. To avoid losing fungal spores attached to arthropod bodies, the surface of any arthropod present in the sample was rinsed by adding sterile water into the sample tube and vortexing. After washing, the arthropods were removed with sterile tweezers. Samples containing any rainwater were dried in a vacuum drier (24 h). Prior to drying, each sample was covered with a porous Parafilm to avoid cross-contamination between samples. After drying, all samples were sent to the University of Guelph, Canada, for DNA extraction and sequencing.
A detailed description of DNA extraction, primers, and sequencing is given in Ovaskainen et al . . In brief, the target genetic marker, i.e., the ITS2 region of the rRNA operon, was amplified using the polymerase chain reaction (PCR) for 20 cycles with fusion primers ITS_S2F , ITS3, and ITS4 tailed with Illumina adapters, and sequenced on Illumina MiSeq with 2 × 300 bp paired end reads. ITS_S2F was included as a second forward primer to specifically amplify plant DNA, in order to include pollen as well as fungal spores in the analysis. However, only a small fraction of reads resulted from the ITS_S2F-ITS4 amplicon, and so these were removed in the early stages of the analysis and not further considered. To quantify the amount of fungal DNA, we applied a spike-in approach , using nine positive control plasmids prepared from synthetic sequences. These sequences were designed to be generally consistent with fungal ITS sequences, but different from all known natural sequences . The positive synthetic control (0.01 ng/μl) containing nine plasmids was spiked into the PCR master mix at a ratio of 1:100 for the first 336 samples. For the remaining 2,432 samples, we used a 1:1000 ratio, since the 1:100 ratio produced an unnecessarily high proportion of the sequences representing the spikes. This could have compromised the sequencing depth of the targeted fungal sequences. We converted the ratio of the non-spike vs. spike-sequences into semi-quantitative estimates of DNA amount in units of ng of DNA per m 3 of air as described previously . The resulting estimates of DNA abundance correlated well with a qPCR-based estimate of DNA amount. Each MiSeq run included 84 study samples, one negative control sample introduced in the DNA extraction step, and two negative controls introduced in the PCR step. The only exceptions were two runs (CCDB-35004 and CCDB-35005) which included three extraction negative controls and no PCR negative controls. The same master mix as used for the study samples, including synthetic positive controls, was also used for the negative controls. For the field test samples, DNA was extracted following the same protocol, except that 300 µL of ILB extraction buffer was used instead of 270 µL, and the final DNA extract was eluted into 35 µL of Tris buffer instead of 45 µL. Two extraction blanks were also included. A fungal DNA standard was extracted from Fleischmann’s Baker’s commercial yeast. Then, approximately one-half package of the commercial yeast was added to 50 mL warm water and proofed with sugar until the formation of active foam. Yeast DNA was extracted using an abbreviated version of the protocol described above, which omitted the initial ILB extraction buffer and homogenization in the TissueLyzer. Instead, six aliquots of 300 µL of yeast suspension were directly transferred to 900 µL each of 5 M GuSCN binding buffer, incubated at 56 °C for 1 hour in an orbital shaker, and then at 65 °C for 1 hour. The six eluates were pooled and quantified using a Qubit fluorometer with the DS DNA high sensitivity kit. The extract, which had a DNA concentration of 2.77 ng/µL, was then diluted to form standards of 1 ng/µL, 0.1 ng/µL, 0.01 ng/µL, 0.001 ng/µL, and 0.0001 ng/µL. The test samples were quantified by real-time PCR (RT-PCR) on a LightCycler96 (Roche) as described in Ovaskainen et al . , with two replicates of each of the standards for calibration.
Demultiplexed paired-end reads were first trimmed using Cutadapt version 4.2 . Because of low-quality base-calls at the 5′ end of R2 reads, we removed the first 16 bases from all R2 reads. We then trimmed the 3′ end of both reads with a quality threshold of 2 (i.e., remove only N’s), and the 5′ end of R2 with a quality threshold of 10. Reads were then trimmed to the ITS3-ITS4 amplicon, with a minimum 10 bp overlap and error tolerance of 0.2. Primers at the 3′ ends of both reads were optional but read pairs where the 5′ primer was not detected (including reads originating from the ITS_S2F-ITS4 amplicon) were removed. Pairs were discarded after trimming if either read was less than 100 bases or contained ambiguous bases. Reads were then further processed using DADA2 version 1.18.0 . First, all pairs where either read matched to the PhiX genome were removed, along with reads where R1 contained more than 3 expected errors or R2 contained more than 5 expected errors. Reads were denoised using separate error profiles fit for each MiSeq run with default parameters, and denoised read pairs were merged to form ASVs with a minimum overlap of 10 bp and a maximum mismatch of 1 bp. An initial de novo chimera check was performed on the merged ASV table using the DADA2 “consensus” method . A second reference-based chimera check was then performed using the “uchime_ref” option in VSEARCH version 2.22.1 with reference Sanger sequences from the UNITE v9database , as used by the PlutoF Species Hypothesis matching pipeline . The synthetic spike sequences were also included as references. Non-chimeric ASVs that were identical except for end gaps were combined, with the most abundant ASV sequence taken as representative. ASVs with a sequence similarity greater than 0.9 to SynMock spike sequences were identified using the “-usearch_global” command in VSEARCH 2.22.1 and labelled as spike sequences. Non-spike sequences were aligned using Infernal 1.1.4 to the covariance model for the combined 5.8 S and 28 S rRNA genes from the FunGene pipeline which was truncated to include only the region between the ITS3 and ITS4 primer sites. Sequences that did not match the full length of the model, or which scored less than 50, were discarded. This resulted in a 65,912 ASVs × 2,768 samples matrix, with entries representing read abundance. A taxonomic affiliation was assigned to each non-spike ASV sequence using Protax-fungi . This procedure gives assignments at each taxonomic rank from phylum to species, along with a calibrated probability that the assignment at each rank is correct. We used the 90% probability threshold for taxonomic assignments. Additionally, because Protax-fungi does not include non-fungi in its reference database, we matched ASVs to the same UNITE Sanger sequences mentioned above using the “usearch_global” command of VSEARCH 2.22.1 , with a sequence similarity threshold of 0.8. Sequences whose best match was annotated as belonging to a kingdom other than Fungi , or which had no match at the given threshold, were annotated as potential non-fungi but retained for the next clustering step. Due to frequent intraspecific sequence variants for the ITS region, ITS-based ASVs are not suitable proxies for fungal species . Consequently, we developed a taxonomically-guided clustering approach using the taxonomic annotations from Protax-fungi to group ASVs into approximately species-level OTUs. Our approach also groups sequences, including those without existing taxonomic annotations, into clusters approximating each taxonomic rank. First, we calculated optimal single-linkage clustering thresholds for each combination of a known taxon at a rank higher than species (henceforth, the “supertaxon”) and a taxonomic rank lower than that taxon (“subrank”) using multi-class F-measure optimization as described for the tool Dnabarcoder . However, instead of using BLAST to calculate pairwise distances, as in Dnabarcoder, we based our clusters on a sparse pairwise sequence distance matrix generated by the -calc_distmx command in USEARCH 11.0.667 , with an initial kmer dissimilarity threshold of 0.4, maximum global alignment dissimilarity of 0.6, and a gap penalty of 1. For each supertaxon-subrank combination where there were at least five subtaxa represented by a total of at least ten reference sequences, we chose the clustering threshold that generated clusters most closely corresponding to the reference identifications. This match was assessed by the multi-class F-measure. Thus, we generated optimal thresholds for clustering all fungi into ranks from phylum to species; for clustering each phylum into ranks from class to species, and so on. The ASVs were then clustered in three stages for each taxonomic rank from phylum to species, with the species-level clusters forming the final OTUs. In the first step, cluster cores were formed by the ASVs which had been assigned to taxa at that rank by Protax-fungi. These cluster cores were used as a reference for a closed-reference clustering stage, in which unassigned ASVs were matched to the closest cluster core using the optimized sequence similarity threshold for that rank and the nearest enclosing supertaxon. To this aim, we applied the “-usearch_global command” in VSEARCH version 2.22.1 . We used the same alignment penalties for closed-reference clustering as for the threshold optimization clustering above to ensure that distance calculations were comparable. Iterations were performed until no new matches were found, generating approximately single-linkage clusters without merging cluster cores. Finally, in the third step, remaining unclustered ASVs at each rank were clustered using de novo single-linkage clustering using distances calculated by USEARCH as above, and again using the optimized sequence similarity threshold for the rank and nearest supertaxon. These de novo clusters, which we refer to as “pseudotaxa”, were assigned placeholder taxonomic names of the form “pseudo{rank}_{number}” (e.g., “pseudogenus_0216” for a cluster at genus rank). At each taxonomic rank after phylum, the three clustering stages were performed within the clusters generated at higher taxonomic ranks. Thus, two ASVs that were assigned to, for instance, different phyla by Protax-fungi, could not be clustered together into the same pseudoclass, even when their sequence similarity was greater than the class-level threshold determined for one or both phyla. Because the current version of Protax-fungi is trained only to identify fungi and not all eukaryotes, the non-fungal sequences were generally unidentified at the phylum level and were grouped into a large number of pseudophyla. We used the kingdom-level results from matching to the UNITE Sanger references (see above) to classify ASVs as “known fungi”, “known non-fungi”, or “unknown kingdom”, and removed pseudotaxa containing more known non-fungal ASVs than known fungal ASVs. At the phylum level, pseudotaxa containing only ASVs of unknown kingdoms were also removed. The final result of this process was a 27,954 species-level OTUs × 2,768 samples read abundance matrix, along with taxonomic annotations at each rank from phylum to species, including pseudotaxon placeholders. The bioinformatics pipeline was implemented using the Targets package version 1.3 in R version 4.2.2.
The database has been deposited to Zenodo and the sequence data are available at ENA European Nucleotide Archive . The database is organized in five datasets in a csv format (columns separated by commas): (1) metadata providing the location, date, and time for each sample, along with sequencing depth and other essential information (Table ); (2) species-level OTU tables per sample describing the number of sequences assigned to each species (Table ); (3) taxonomic classification of each species-level OTU (Table ); (4) closest matching sequences and their taxonomy for ASVs in putatively fungal pseudophyla, which are included in (2) and (3) (Table ); and (5) closest matching sequences and their taxonomy for ASVs in putatively non-fungal pseudophyla, which are not included in the other datasets (Table ). The first four datasets can be linked to each other using the unique sample codes and the unique identifiers for species-level OTUs.
Field tests and negative controls The median DNA amount measured by RT-PCR in the seven 24-hour test samples was 14 fg of DNA. The median DNA content measured in 1-hour samples was 8 fg, and the median for 10-minute samples, as well as for field blanks handled without gloves, were less than 3 fg. The median DNA quantity measured in the field blanks handled with gloves and the extraction blanks were approximately 0.7 fg, and the DNA quantity in the PCR blank was approximately 0.1 fg (Fig. ). As these values were standardized using genomic DNA extracted from yeast, they cannot be directly translated to other fungi due to varying genome size and ITS copy number. Nonetheless, we note that 24-hour field samples had almost 5 times more ITS copies than blank samples handled without gloves, and twenty times more than blank samples handled with gloves. In the actual study, all samples were handled with gloves. Of the 99 negative controls, 89% of samples (i.e., 88 samples) did not yield any reads of fungal origin at the end of the bioinformatic analysis. For all sequencing runs, at least one negative control sample contained 0 fungal reads, indicating that the reagents were uncontaminated. The 9 negative control samples that did produce fungal reads yielded fewer fungal reads than the study samples (Fig. ), and, in most cases, these reads belonged to only one or two OTUs. OTUs found in negative control samples were all relatively common in the study. They were no more common in the sequencing runs which contained the negative controls than in other sequencing runs. This suggests that the most likely source of these reads was infrequent cross-contamination from study samples to negative controls. Among the negative controls, sample CCDB-35071NEGPCR2 yielded the highest read count: 2,668 fungal reads. All 18 OTUs detected in this sample were also found in sample COR_41A with abundances 7–60 times as high as in the negative control. Samples CCDB-35071NEGPCR2 and COR_41A were processed in the same sequencing run, indicating that the sample COR_41A was likely the source of cross-contamination. Sufficiency of sequencing depth The mean sequencing depth among the samples was 86,845, and the median sequencing depth was 79,396. We recommend conducting analyses with samples yielding at least 10,000 sequencing reads, which corresponds to discarding 50 samples and thus 1.8% of the samples (Fig. ). If rarefying all samples to 10,000 sequence reads, a minor loss of species-level OTU richness is observed for the most diverse samples (Fig. ). Nonetheless, even the most diverse samples were likely sequenced to an adequate depth, as illustrated by the well-saturating rarefaction curves (Fig. ). Validation of automated taxonomic classifications by manual expert evaluation Molecular taxonomic identification of fungi from environmental samples is challenging for several reasons . First, the diversity of fungi is enormous, and most species are still unknown to science. Second, reference sequences are available only for a subset of the scientifically described species. Third, the systematics of fungi remains partially or even largely unresolved and undergoes continuous revisions. Fourth, the reference sequences in standard databases contain errors, and a substantial proportion of the reference sequences are mislabelled. Fifth, unlike the COI region used for molecular identification of animals, the ITS region does not allow for alignment at deep phylogenetic scales (much above the genus level), making sequence comparison more challenging. PROTAX-fungi explicitly accounts for all these sources of uncertainty while performing probabilistic taxonomic classification, and its validity has been tested by cross-validation experiments . Given the taxonomic breadth of the data and the unexplored nature of airborne fungal diversity, we evaluated the validity of the PROTAX classifications by comparing them to taxonomic classifications carried out by independent experts. To do so, we first clustered the sequences with 97% similarity threshold and selected the most common sequence in each cluster as its representative. We then selected a total of 500 clusters (and their corresponding representatives) as follows: (i) 200 sequences that PROTAX could not reliably (with at least 90% probability) classify to any known phylum, in which case they are unlikely to belong to the fungal kingdom; (ii) 50 sequences that PROTAX reliably classified to a known phylum but an unknown class; (iii) 50 sequences that were reliably classified to a known class but an unknown order; (iv) 50 sequences reliably classified to a known order but an unknown family; (v) 50 sequences reliably classified to a known family but an unknown genus; (vi) 50 sequences reliably classified to a known genus but an unknown species; and (vii) 50 sequences reliably classified to a known species. Within each category, we selected clusters that achieved the highest prevalence (i.e., that occurred in the highest proportions of the samples) in the GSSP data. Two authors with fungal taxonomic expertise (Otto Miettinen and Anton Savchenko) then manually performed the taxonomic classification of these 500 sequences, up to the taxonomic resolution that they considered possible to reliably achieve. The expert assessment was based on the first 100 BLAST hits between the query sequence and reference sequences in publicly available gene databases, thus incorporating a larger body of information than just a few top hits. In their assessment, the experts accounted for the quality issues in the reference sequences, such as divergent tail regions in poorly trimmed Sanger sequences, or chimeric sequences. Furthermore, naming of the sequences varies wildly, and experts used their judgement on which sequences to trust as the reference, and to what degree. There might be equally good hits under several names, in which case the experts judged which one was most likely correct. The best hit might refer to a name that is a collective, not allowing species-level identification with certainty. An important criterion in judging the reliability of reference sequences was related to the perceived trustworthiness of the sequence authors based on their taxonomic expertise (i.e., their standing in the field). As there is no published, up-to-date taxonomy for all fungal taxa, in many cases the experts had access to more up-to-date information (e.g., unpublished sources) about the classification, and then used this information when deciding on the correct naming at all taxonomic ranks. The taxonomic experts knew the criteria used to select the sequences, whereas the order in which the sequences were provided was randomized, so that the experts did not have a priori information about the PROTAX classifications. We compared the classifications achieved by PROTAX versus the experts by computing the numbers of consistent and inconsistent classifications for each taxonomic level. The consistent and inconsistent classifications were counted separately for each of the following four confidence levels of PROTAX identifications: reliable identifications (i.e., those with at least 90% probability of correct classification), plausible identifications (those with at least 50% but less than 90% probability of correct classification), best hits (the classification with highest probability, where the highest probability is at least 1% but less than 50%), and no hits (those for which PROTAX did not yield any classification with at least 1% probability). PROTAX-fungi classifications and expert classifications were highly consistent (Fig. ). Most importantly, out of those 861 cases where PROTAX yielded a reliable classification at a given rank, the classification differed from that of the experts in only three cases (0.35% of the cases). Out of the 247 cases for which PROTAX yielded a plausible classification, the classification differed from that of the experts in 9% of the cases. Out of the 154 cases where PROTAX yielded merely a best hit, the classification differed from that of the experts in 21% of the cases. Out of those 189 cases that the experts classified as belonging to groups other than fungi (48 cases of Viridiplantae and 14 cases of Metazoa) or found impossible to reliably classify as fungi, PROTAX never produced a reliable phylum-level classification. Figure shows only cases where the experts classified the sequences to at least the same taxonomic level as did PROTAX. However, there were also 29 cases for which the experts considered it possible to reliably classify the sequence up to the genus level, but PROTAX provided a reliable classification to the species level. Out of these 29 cases, the experts gave an uncertain species-level classification for 15 cases. In each of these cases, the classification offered by the experts was consistent with the classification provided by PROTAX. In addition, there was one case in which the experts provided only a class-level classification and one case where the experts gave an order-level classification, but PROTAX considered it possible to reliably provide also more resolved classifications. Based on these results, we conclude that the taxonomic classifications provided by PROTAX are highly consistent with those carried out manually by experts, but that PROTAX is generally more conservative regarding the reliability of the classifications. The difference in the uncertainty assessment is at least partially due to the fact that PROTAX explicitly accounts for the possibility that the sequence represents an unknown taxon – and such taxa are likely to be common in the global aerial data. As the manual classifications involved only a negligible fraction of all the sequences, the classifications published in the database were conducted by PROTAX. Validation of automated taxonomic classifications by comparison with the Global Biodiversity Information Facility (GBIF) database To further validate the reliability of the automated taxonomic classifications, we compared the spatial distributions observed in this study to species occurrence records present in the Global Biodiversity Information Facility (GBIF) database. The motivation behind this comparison was to assess how likely the taxonomic classifications based on DNA barcoding match with classifications conducted by earlier research – as based mostly on morphological characters. To evaluate this consistency, we compared the spatial distributions of species recorded in this study to those recorded in the GBIF database. Cases where a difference in the distributions recorded suggested an error in the taxonomic classification were then examined in greater detail. To download occurrence records from GBIF, we used the function occ_download of the R-package rgbif v3.7.7 with R-version 4.3.1 for the 1,319 species that were reliably identified in our data, and for which occurrence data was available in GBIF (GBIF.org. 27 August 2023, GBIF Occurrence Download DOI 10.15468/dl.t8yn8x, with 6,189,602 occurrences). Quantifying the consistency between our GSSP data and GBIF data is not straightforward, because the GBIF data is presence-only in nature without a well-controlled observation effort. To avoid biasing the results due to uncontrolled variation in sampling effort among species and across space in the GBIF data, we applied a null-model approach. Here, we constructed a null distribution that described the consistency between the spatial distribution of each focal species in the GBIF database and of all non-focal species in the GSSP data. For GSSP data, we used the prevalence of a species p i (i.e., fraction of samples in which the species was present) as the measure of species abundance for each site i . For the GBIF data, we computed a GBIF-index g i describing how frequently the species was observed in the proximity of the site i for each of our sampling sites. To do so, we defined g i as the weighted sum over all GBIF occurrences where we weighted each occurrence by [12pt]{minimal}
$$ ()$$ exp − d 1000 , where d is the distance (in kilometers) between the focal site i and the location of the GBIF occurrence. As a measure of consistency between the spatial distributions in the two datasets, we then computed the correlation between p i and g i over the sites. For each focal species, the observed value is the consistency between the focal species in the GBIF data and the focal species in our data, whereas the null distribution encapsulates the consistencies between the focal species in the GBIF data and all non-focal species in the GSSP data. As an empirical p-value, we computed the proportion of the null distribution instances where the value exceeded the observed one. This comparison was carried out for 1,251 out of the 1,319 species, since for 68 species the number of datapoints was too low, resulting in a NA value for the correlation. Overall, the species distributions revealed by our study were consistent with their known distributions in the GBIF database – in the sense that their distributions in the GSSP data coincide more with the distributions in GBIF than with random distributions (Fig. ). This comparison also highlights the large number of species for which the match is no better than random (as revealed by p -values in the range from 0.05 to 0.95 in Fig. ). This lack of statistically significant matches was expected, as the GBIF data on most fungal species derive from opportunistic observations rather than from systematic surveys. The comparison further highlighted 14 species ( Cystobasidium minuta, Sphaerobolus ingoldii, Gaeumannomyces graminis, Phialemonium dimorphosporum, Xenasmatella ardosiaca, Zygoascus hellenicus, Meyerozyma guilliermondii, Candida intermedia, Trametes polyzona, Lodderomyces elongisporus, Hansfordia pulvinata, Physisporinus vitreus, Scopuloides rimosa and Phlebia subserialis ) for which the match was worse than expected by random (p-value > 0.95). While the proportion of such mismatches are less than expected by chance (since a uniform distribution of p-values would lead to 63 such cases), this list identifies candidates for misclassification and were thus examined manually in more detail. For two of the mismatches, the inconsistency was most likely explained by erroneous records in GBIF: OTUs classified here as Phlebia subserialis and Sphaerobolus ingoldii . The name P. subserialis is known to have been applied to multiple biological species of corticioid wood decay fungus that are morphologically similar but not very closely related , , likely creating erroneous records in GBIF (Fig. ). The wood-decaying fungus Sphaerobolus ingoldii was described in the 21 st century based on DNA evidence, and it is morphologically similar to S. stellatus . We thus assume that the old GBIF observations of S. stellatus in South Africa and Australia might be S. ingoldii instead. For three of the mismatches, we considered the name assigned in GSSP incorrect: OTUs classified here as Phialemonium dimorphosporum, Physisporinus vitreus , and Scopuloides rimosa . For these cases, there were either exactly matching reference sequences representing multiple species, or there was divergence among the PROTAX assignments of the ASVs that were included in the OTU. Thus, in these cases, the classification selected by our algorithm was somewhat ambiguous, even when at least one of the ASVs belonging to the OTU cluster achieved at least 90% probability of correct classification. For two of the mismatches ( Xenasmatella ardosiaca and Trametes polyzona ), our manual inspection revealed that we had accidentally imported an incorrect species from GBIF (or only partial data for the focal species), whereas the correct data from GBIF actually showed a good match with the GSSP records. Hence, only 12 (not 14) species in the end showed a mismatch between the two databases. However, to keep our technical validation transparent and to point out the range of errors that may take place in automated comparisons, we decided to report on these two apparent mismatches here. For the remaining seven mismatches ( Cystobasidium minuta, Gaeumannomyces graminis, Zygoascus hellenicus, Meyerozyma guilliermondii, Candida intermedia, Lodderomyces elongisporus , and Hansfordia pulvinatae ), our manual inspection suggested that there was indeed a mismatch between the GSSP and GBIF distributions, but it was difficult to judge whether the problem was in the GSSP classifications, in the GBIF records, or in both of these, highlighting another common issue in automated comparisons. From the comparison between GSSP and GBIF, we conclude that both molecular and morphological classifications of fungi are challenging. Both databases are indeed likely to have some level of error, especially at the species level. Yet, even at the species level, a high proportion of the cases supported the validity of both the GSSP and GBIF data by showing that they match better than expected at random. Only for 1% of the cases (12 out of 1,251) did we find a mismatch that was significant at the p < 0.05 level; the comparison thus supports the technical validity of the GSSP data. Affinity of sequences which could not be assigned to fungal phyla As described above, ASV sequences that could not be assigned to a fungal phylum either by Protax with probability >90% or by clustering with other ASVs which were so assigned by Protax were de novo clustered into “pseudophyla”. These pseudophyla are expected to contain real fungal sequences which lack close matches in the Protax reference database, as well as real non-fungal sequences and sequencing artifacts. Because we are unable to draw confident conclusions about the taxonomic affinity of these pseudophyla on the basis of the Protax results, we have included data tables providing, for each ASV in each pseudophylum, information on the closest matching species hypothesis (SH) in the Unite Sanger reference database , the sequence dissimilarity of that closest match as calculated by VSEARCH, and the taxonomy given in Unite (the “best-hit taxonomy”). Although we do not consider the best-hit taxonomy to be reliable without extensive manual validation, we also summarize the best-hit taxonomy at the phylum level for likely fungal pseudophyla (Table ) and at the kingdom level for likely non-fungal pseudophyla (Table ). In almost all cases, multiple pseudophyla share the same best-hit taxonomy; however, the best-hit taxonomy within each pseudophylum is quite consistent, as indicated by low numbers of “minority” ASVs, especially within the fungi. This suggests that pseudophyla (and presumably other pseudotaxa, at least at higher taxonomic ranks) are most likely underclustered, in the sense that two sequences which are in the same pseudophylum can be confidently assumed to belong to the same phylum, while sequences in different pseudophyla cannot be so confidently assumed to belong to different phyla. Although many pseudophyla include multiple ASVs that cluster into multiple pseudospecies, we note that the 738 pseudophyla with no match of less than 20% sequence dissimilarity (Table ) each contains exactly one pseudospecies, although in some cases these pseudospecies do consist of multiple ASVs. We suggest that the sequences included in these pseudophyla, which like the rest of the non- Fungi pseudophyla are not included in the main data tables, are particularly likely to be sequencing artifacts, although some highly divergent unknown taxa may also be included. Main sources of variation in the data To evaluate the types of ecological signals present in the data, we quantified the main sources of variation. We fitted a generalized linear model to a data set including each 485 species-level OTU that occurred at least 50 times in the data. We truncated the data to presence-absence and applied probit regression with the R-package Hmsc . As fixed effects, we included log(sequencing depth), the mean temperature of the site and its square, and the interaction between latitude and seasonality. We modelled “seasonality” with the periodic functions [12pt]{minimal}
$$ (2 )$$ sin 2 π d 365 and [12pt]{minimal}
$$ (2 )$$ cos 2 π d 365 , where d is the Julian day of the year. As latitude is positive for the Northern and negative for the Southern Hemisphere, we note that the interaction between seasonality and latitude appropriately assumes opposite patterns of seasonality in the two hemispheres. To capture spatial variation not captured by the annual mean air temperature of the site, we included the site as a random effect. We assumed the default prior distributions of Hmsc and fitted the models using the Markov Chain Monte Carlo (MCMC) procedure . We included four MCMC chains with 37,500 iterations in each, out of which we discarded 12,500 as transient and thinned the remaining iterations by 100, obtaining 250 posterior samples per chain and hence 1,000 posterior samples in total. We followed Tikhonov et al . to evaluate the models’ explanatory power with Tjur’s R 2 and AUC and partitioned the explained variation to its components explained by temperature, seasonality, sequencing depth, and the random effect of the site. The models achieved a satisfactory model fit, with mean (over the species) AUC = 0.91 and mean Tjur’s R 2 = 0.18. The annual mean air temperature of the site explained the largest portion of the variation (53%, averaged over the species), followed by the random effect of the site (29%), seasonality (12%), and sequencing depth (5%). These results suggest that the data contain a strong ecological signal, as species distributions are strongly structured by space – in particular by the annual mean air temperature of the site.
The median DNA amount measured by RT-PCR in the seven 24-hour test samples was 14 fg of DNA. The median DNA content measured in 1-hour samples was 8 fg, and the median for 10-minute samples, as well as for field blanks handled without gloves, were less than 3 fg. The median DNA quantity measured in the field blanks handled with gloves and the extraction blanks were approximately 0.7 fg, and the DNA quantity in the PCR blank was approximately 0.1 fg (Fig. ). As these values were standardized using genomic DNA extracted from yeast, they cannot be directly translated to other fungi due to varying genome size and ITS copy number. Nonetheless, we note that 24-hour field samples had almost 5 times more ITS copies than blank samples handled without gloves, and twenty times more than blank samples handled with gloves. In the actual study, all samples were handled with gloves. Of the 99 negative controls, 89% of samples (i.e., 88 samples) did not yield any reads of fungal origin at the end of the bioinformatic analysis. For all sequencing runs, at least one negative control sample contained 0 fungal reads, indicating that the reagents were uncontaminated. The 9 negative control samples that did produce fungal reads yielded fewer fungal reads than the study samples (Fig. ), and, in most cases, these reads belonged to only one or two OTUs. OTUs found in negative control samples were all relatively common in the study. They were no more common in the sequencing runs which contained the negative controls than in other sequencing runs. This suggests that the most likely source of these reads was infrequent cross-contamination from study samples to negative controls. Among the negative controls, sample CCDB-35071NEGPCR2 yielded the highest read count: 2,668 fungal reads. All 18 OTUs detected in this sample were also found in sample COR_41A with abundances 7–60 times as high as in the negative control. Samples CCDB-35071NEGPCR2 and COR_41A were processed in the same sequencing run, indicating that the sample COR_41A was likely the source of cross-contamination.
The mean sequencing depth among the samples was 86,845, and the median sequencing depth was 79,396. We recommend conducting analyses with samples yielding at least 10,000 sequencing reads, which corresponds to discarding 50 samples and thus 1.8% of the samples (Fig. ). If rarefying all samples to 10,000 sequence reads, a minor loss of species-level OTU richness is observed for the most diverse samples (Fig. ). Nonetheless, even the most diverse samples were likely sequenced to an adequate depth, as illustrated by the well-saturating rarefaction curves (Fig. ).
Molecular taxonomic identification of fungi from environmental samples is challenging for several reasons . First, the diversity of fungi is enormous, and most species are still unknown to science. Second, reference sequences are available only for a subset of the scientifically described species. Third, the systematics of fungi remains partially or even largely unresolved and undergoes continuous revisions. Fourth, the reference sequences in standard databases contain errors, and a substantial proportion of the reference sequences are mislabelled. Fifth, unlike the COI region used for molecular identification of animals, the ITS region does not allow for alignment at deep phylogenetic scales (much above the genus level), making sequence comparison more challenging. PROTAX-fungi explicitly accounts for all these sources of uncertainty while performing probabilistic taxonomic classification, and its validity has been tested by cross-validation experiments . Given the taxonomic breadth of the data and the unexplored nature of airborne fungal diversity, we evaluated the validity of the PROTAX classifications by comparing them to taxonomic classifications carried out by independent experts. To do so, we first clustered the sequences with 97% similarity threshold and selected the most common sequence in each cluster as its representative. We then selected a total of 500 clusters (and their corresponding representatives) as follows: (i) 200 sequences that PROTAX could not reliably (with at least 90% probability) classify to any known phylum, in which case they are unlikely to belong to the fungal kingdom; (ii) 50 sequences that PROTAX reliably classified to a known phylum but an unknown class; (iii) 50 sequences that were reliably classified to a known class but an unknown order; (iv) 50 sequences reliably classified to a known order but an unknown family; (v) 50 sequences reliably classified to a known family but an unknown genus; (vi) 50 sequences reliably classified to a known genus but an unknown species; and (vii) 50 sequences reliably classified to a known species. Within each category, we selected clusters that achieved the highest prevalence (i.e., that occurred in the highest proportions of the samples) in the GSSP data. Two authors with fungal taxonomic expertise (Otto Miettinen and Anton Savchenko) then manually performed the taxonomic classification of these 500 sequences, up to the taxonomic resolution that they considered possible to reliably achieve. The expert assessment was based on the first 100 BLAST hits between the query sequence and reference sequences in publicly available gene databases, thus incorporating a larger body of information than just a few top hits. In their assessment, the experts accounted for the quality issues in the reference sequences, such as divergent tail regions in poorly trimmed Sanger sequences, or chimeric sequences. Furthermore, naming of the sequences varies wildly, and experts used their judgement on which sequences to trust as the reference, and to what degree. There might be equally good hits under several names, in which case the experts judged which one was most likely correct. The best hit might refer to a name that is a collective, not allowing species-level identification with certainty. An important criterion in judging the reliability of reference sequences was related to the perceived trustworthiness of the sequence authors based on their taxonomic expertise (i.e., their standing in the field). As there is no published, up-to-date taxonomy for all fungal taxa, in many cases the experts had access to more up-to-date information (e.g., unpublished sources) about the classification, and then used this information when deciding on the correct naming at all taxonomic ranks. The taxonomic experts knew the criteria used to select the sequences, whereas the order in which the sequences were provided was randomized, so that the experts did not have a priori information about the PROTAX classifications. We compared the classifications achieved by PROTAX versus the experts by computing the numbers of consistent and inconsistent classifications for each taxonomic level. The consistent and inconsistent classifications were counted separately for each of the following four confidence levels of PROTAX identifications: reliable identifications (i.e., those with at least 90% probability of correct classification), plausible identifications (those with at least 50% but less than 90% probability of correct classification), best hits (the classification with highest probability, where the highest probability is at least 1% but less than 50%), and no hits (those for which PROTAX did not yield any classification with at least 1% probability). PROTAX-fungi classifications and expert classifications were highly consistent (Fig. ). Most importantly, out of those 861 cases where PROTAX yielded a reliable classification at a given rank, the classification differed from that of the experts in only three cases (0.35% of the cases). Out of the 247 cases for which PROTAX yielded a plausible classification, the classification differed from that of the experts in 9% of the cases. Out of the 154 cases where PROTAX yielded merely a best hit, the classification differed from that of the experts in 21% of the cases. Out of those 189 cases that the experts classified as belonging to groups other than fungi (48 cases of Viridiplantae and 14 cases of Metazoa) or found impossible to reliably classify as fungi, PROTAX never produced a reliable phylum-level classification. Figure shows only cases where the experts classified the sequences to at least the same taxonomic level as did PROTAX. However, there were also 29 cases for which the experts considered it possible to reliably classify the sequence up to the genus level, but PROTAX provided a reliable classification to the species level. Out of these 29 cases, the experts gave an uncertain species-level classification for 15 cases. In each of these cases, the classification offered by the experts was consistent with the classification provided by PROTAX. In addition, there was one case in which the experts provided only a class-level classification and one case where the experts gave an order-level classification, but PROTAX considered it possible to reliably provide also more resolved classifications. Based on these results, we conclude that the taxonomic classifications provided by PROTAX are highly consistent with those carried out manually by experts, but that PROTAX is generally more conservative regarding the reliability of the classifications. The difference in the uncertainty assessment is at least partially due to the fact that PROTAX explicitly accounts for the possibility that the sequence represents an unknown taxon – and such taxa are likely to be common in the global aerial data. As the manual classifications involved only a negligible fraction of all the sequences, the classifications published in the database were conducted by PROTAX.
To further validate the reliability of the automated taxonomic classifications, we compared the spatial distributions observed in this study to species occurrence records present in the Global Biodiversity Information Facility (GBIF) database. The motivation behind this comparison was to assess how likely the taxonomic classifications based on DNA barcoding match with classifications conducted by earlier research – as based mostly on morphological characters. To evaluate this consistency, we compared the spatial distributions of species recorded in this study to those recorded in the GBIF database. Cases where a difference in the distributions recorded suggested an error in the taxonomic classification were then examined in greater detail. To download occurrence records from GBIF, we used the function occ_download of the R-package rgbif v3.7.7 with R-version 4.3.1 for the 1,319 species that were reliably identified in our data, and for which occurrence data was available in GBIF (GBIF.org. 27 August 2023, GBIF Occurrence Download DOI 10.15468/dl.t8yn8x, with 6,189,602 occurrences). Quantifying the consistency between our GSSP data and GBIF data is not straightforward, because the GBIF data is presence-only in nature without a well-controlled observation effort. To avoid biasing the results due to uncontrolled variation in sampling effort among species and across space in the GBIF data, we applied a null-model approach. Here, we constructed a null distribution that described the consistency between the spatial distribution of each focal species in the GBIF database and of all non-focal species in the GSSP data. For GSSP data, we used the prevalence of a species p i (i.e., fraction of samples in which the species was present) as the measure of species abundance for each site i . For the GBIF data, we computed a GBIF-index g i describing how frequently the species was observed in the proximity of the site i for each of our sampling sites. To do so, we defined g i as the weighted sum over all GBIF occurrences where we weighted each occurrence by [12pt]{minimal}
$$ ()$$ exp − d 1000 , where d is the distance (in kilometers) between the focal site i and the location of the GBIF occurrence. As a measure of consistency between the spatial distributions in the two datasets, we then computed the correlation between p i and g i over the sites. For each focal species, the observed value is the consistency between the focal species in the GBIF data and the focal species in our data, whereas the null distribution encapsulates the consistencies between the focal species in the GBIF data and all non-focal species in the GSSP data. As an empirical p-value, we computed the proportion of the null distribution instances where the value exceeded the observed one. This comparison was carried out for 1,251 out of the 1,319 species, since for 68 species the number of datapoints was too low, resulting in a NA value for the correlation. Overall, the species distributions revealed by our study were consistent with their known distributions in the GBIF database – in the sense that their distributions in the GSSP data coincide more with the distributions in GBIF than with random distributions (Fig. ). This comparison also highlights the large number of species for which the match is no better than random (as revealed by p -values in the range from 0.05 to 0.95 in Fig. ). This lack of statistically significant matches was expected, as the GBIF data on most fungal species derive from opportunistic observations rather than from systematic surveys. The comparison further highlighted 14 species ( Cystobasidium minuta, Sphaerobolus ingoldii, Gaeumannomyces graminis, Phialemonium dimorphosporum, Xenasmatella ardosiaca, Zygoascus hellenicus, Meyerozyma guilliermondii, Candida intermedia, Trametes polyzona, Lodderomyces elongisporus, Hansfordia pulvinata, Physisporinus vitreus, Scopuloides rimosa and Phlebia subserialis ) for which the match was worse than expected by random (p-value > 0.95). While the proportion of such mismatches are less than expected by chance (since a uniform distribution of p-values would lead to 63 such cases), this list identifies candidates for misclassification and were thus examined manually in more detail. For two of the mismatches, the inconsistency was most likely explained by erroneous records in GBIF: OTUs classified here as Phlebia subserialis and Sphaerobolus ingoldii . The name P. subserialis is known to have been applied to multiple biological species of corticioid wood decay fungus that are morphologically similar but not very closely related , , likely creating erroneous records in GBIF (Fig. ). The wood-decaying fungus Sphaerobolus ingoldii was described in the 21 st century based on DNA evidence, and it is morphologically similar to S. stellatus . We thus assume that the old GBIF observations of S. stellatus in South Africa and Australia might be S. ingoldii instead. For three of the mismatches, we considered the name assigned in GSSP incorrect: OTUs classified here as Phialemonium dimorphosporum, Physisporinus vitreus , and Scopuloides rimosa . For these cases, there were either exactly matching reference sequences representing multiple species, or there was divergence among the PROTAX assignments of the ASVs that were included in the OTU. Thus, in these cases, the classification selected by our algorithm was somewhat ambiguous, even when at least one of the ASVs belonging to the OTU cluster achieved at least 90% probability of correct classification. For two of the mismatches ( Xenasmatella ardosiaca and Trametes polyzona ), our manual inspection revealed that we had accidentally imported an incorrect species from GBIF (or only partial data for the focal species), whereas the correct data from GBIF actually showed a good match with the GSSP records. Hence, only 12 (not 14) species in the end showed a mismatch between the two databases. However, to keep our technical validation transparent and to point out the range of errors that may take place in automated comparisons, we decided to report on these two apparent mismatches here. For the remaining seven mismatches ( Cystobasidium minuta, Gaeumannomyces graminis, Zygoascus hellenicus, Meyerozyma guilliermondii, Candida intermedia, Lodderomyces elongisporus , and Hansfordia pulvinatae ), our manual inspection suggested that there was indeed a mismatch between the GSSP and GBIF distributions, but it was difficult to judge whether the problem was in the GSSP classifications, in the GBIF records, or in both of these, highlighting another common issue in automated comparisons. From the comparison between GSSP and GBIF, we conclude that both molecular and morphological classifications of fungi are challenging. Both databases are indeed likely to have some level of error, especially at the species level. Yet, even at the species level, a high proportion of the cases supported the validity of both the GSSP and GBIF data by showing that they match better than expected at random. Only for 1% of the cases (12 out of 1,251) did we find a mismatch that was significant at the p < 0.05 level; the comparison thus supports the technical validity of the GSSP data.
As described above, ASV sequences that could not be assigned to a fungal phylum either by Protax with probability >90% or by clustering with other ASVs which were so assigned by Protax were de novo clustered into “pseudophyla”. These pseudophyla are expected to contain real fungal sequences which lack close matches in the Protax reference database, as well as real non-fungal sequences and sequencing artifacts. Because we are unable to draw confident conclusions about the taxonomic affinity of these pseudophyla on the basis of the Protax results, we have included data tables providing, for each ASV in each pseudophylum, information on the closest matching species hypothesis (SH) in the Unite Sanger reference database , the sequence dissimilarity of that closest match as calculated by VSEARCH, and the taxonomy given in Unite (the “best-hit taxonomy”). Although we do not consider the best-hit taxonomy to be reliable without extensive manual validation, we also summarize the best-hit taxonomy at the phylum level for likely fungal pseudophyla (Table ) and at the kingdom level for likely non-fungal pseudophyla (Table ). In almost all cases, multiple pseudophyla share the same best-hit taxonomy; however, the best-hit taxonomy within each pseudophylum is quite consistent, as indicated by low numbers of “minority” ASVs, especially within the fungi. This suggests that pseudophyla (and presumably other pseudotaxa, at least at higher taxonomic ranks) are most likely underclustered, in the sense that two sequences which are in the same pseudophylum can be confidently assumed to belong to the same phylum, while sequences in different pseudophyla cannot be so confidently assumed to belong to different phyla. Although many pseudophyla include multiple ASVs that cluster into multiple pseudospecies, we note that the 738 pseudophyla with no match of less than 20% sequence dissimilarity (Table ) each contains exactly one pseudospecies, although in some cases these pseudospecies do consist of multiple ASVs. We suggest that the sequences included in these pseudophyla, which like the rest of the non- Fungi pseudophyla are not included in the main data tables, are particularly likely to be sequencing artifacts, although some highly divergent unknown taxa may also be included.
To evaluate the types of ecological signals present in the data, we quantified the main sources of variation. We fitted a generalized linear model to a data set including each 485 species-level OTU that occurred at least 50 times in the data. We truncated the data to presence-absence and applied probit regression with the R-package Hmsc . As fixed effects, we included log(sequencing depth), the mean temperature of the site and its square, and the interaction between latitude and seasonality. We modelled “seasonality” with the periodic functions [12pt]{minimal}
$$ (2 )$$ sin 2 π d 365 and [12pt]{minimal}
$$ (2 )$$ cos 2 π d 365 , where d is the Julian day of the year. As latitude is positive for the Northern and negative for the Southern Hemisphere, we note that the interaction between seasonality and latitude appropriately assumes opposite patterns of seasonality in the two hemispheres. To capture spatial variation not captured by the annual mean air temperature of the site, we included the site as a random effect. We assumed the default prior distributions of Hmsc and fitted the models using the Markov Chain Monte Carlo (MCMC) procedure . We included four MCMC chains with 37,500 iterations in each, out of which we discarded 12,500 as transient and thinned the remaining iterations by 100, obtaining 250 posterior samples per chain and hence 1,000 posterior samples in total. We followed Tikhonov et al . to evaluate the models’ explanatory power with Tjur’s R 2 and AUC and partitioned the explained variation to its components explained by temperature, seasonality, sequencing depth, and the random effect of the site. The models achieved a satisfactory model fit, with mean (over the species) AUC = 0.91 and mean Tjur’s R 2 = 0.18. The annual mean air temperature of the site explained the largest portion of the variation (53%, averaged over the species), followed by the random effect of the site (29%), seasonality (12%), and sequencing depth (5%). These results suggest that the data contain a strong ecological signal, as species distributions are strongly structured by space – in particular by the annual mean air temperature of the site.
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Sensors: future tools for detecting young patient’s stress during a dental invasive versus a non-invasive dental treatment—a pilot study | 8904e5fa-6289-4325-bc7d-836a95d4fe1b | 11866936 | Dentistry[mh] | Non-invasive mobile health monitoring systems have been developed and utilised in the field of health promotion and medicine (Mao et al. ; Muzny et al. ; Liao et al. ; Murphy et al. ; Lu et al. ; Kamišalić et al. ). In addition, continuous monitoring and collecting of physiologic al variables via sensors have been tested, to facilitate medical diagnosis and individually tailored treatments (Murphy et al. ). A care-related area that would benefit from live monitoring patients’ physiological reactions, via a non-invasive device, is the paediatric dentistry field as: children and adolescents do not always have the ability, courage, or vocabulary to express their negative perceptions during dental procedures (Krekmanova and Robertson ). Furthermore, perceived anxiety, fear or pain may eventually lead to consequences, such as behavioural problems, dental fear, and non-attendance from subsequent dental care appointments (Klingberg and Broberg ; Ghanei et al. ). In addition, young dental patients with a shy, insecure or introvert temperament may need additional support to communicate their own needs. The inability of these young individuals to stand up for themselves is exemplified in a 5-year prospective study of 3–19-year-olds, a majority of whom cooperated with invasive dental procedures, despite experiencing fear and pain (Krekmanova and Robertson ; Ghanei et al. ). In the same study, patients reported the dental check-ups i.e. non-invasive treatment, to provoke significantly lower levels of fear and pain, than invasive procedures (Krekmanova and Robertson ; Ghanei et al. ). The results highlighted patient’s exposure in the dental setting and needless suffering during procedures such as oral injections and dental extractions. Seen from the dental care perspective, unexperienced dental staff's inadequate sensitivity to patient’s subtle reactions may increase a negatively perceived situation (Krekmanova et al. ). The above reasoning identifies an area in need of development. A desirable solution would be to visualise young patient’s reactions and so increase the dental staff’s sensitiveness, preferably by reading the patient’s physiological parameters during dental treatments. Thus, the physiological response would not depend on each patient’s ability to communicate, which broadens the clinical implementation. However, a clinical requirement would be to use a device that is easily manageable by dentists and effortlessly accepted among patients. Among commercially available devices on the market, the CE-marked Shimmer3 GSR + unit measures galvanic skin response (GSR), heart rate (HR) and hand movements, therefore, considered eligible to be tested for its ability to record physiological changes in the dental patient ( https://shimmersensing.com ). The aim was to evaluate the commercially available, CE marked, Shimmer3 GSR + unit’s ability to indicate for stress as a reaction of fear, regarding a non-invasive dental treatment (NI), and for an invasive dental treatment (I). Study design The study design was experimental, aiming to evaluate the Shimmer3 GSR + unit's ability to indicate the patient’s negative reactions during different dental interventions. Location of the study and patients The pilot study was conducted at the Public Dental Service. In addition, the survey was performed in collaboration between different cooperation partners (data blinded). Inclusion criteria *Patient listed at the specific Dental Public Clinic for the study performance. *Patient 14–16 years old, with no medical diagnoses or medications. *Patient and legal guardian fluent in the blinded language as each patient should be introduced to the validated scales: coloured analogue scale (CAS); 0 = no pain to 10 = most possible pain, for pain intensity, facial analogue scale (FAS); A = happy to I = crying, for the emotional state, and a fear scale; 0–4, 0 = not afraid to 4 = terrified, to enable to communicate the own experience. *An impending dental check-up. *An impending dental extraction of a permanent premolar, due to orthodontic indications. Exclusion criteria *Patient in need of sedatives or nitrous oxide sedation. Intervention groups Non-invasive treatment group (NI); an oral check-up. Invasive treatment group (I); a premolar extraction, maxilla, or mandible due to orthodontic indication. Study information and group allocation Patients with impending oral examinations/extractions who met the inclusion criteria were assigned to either group NI or group I. Patients were then introduced to the purpose of the study, and the anonymous data processing, both verbally and through written information. Written and verbal informed consent from the patient and guardian was required for study eligibility. Voluntariness was emphasised, highlighting that the participation could be withdrawn at any time during the study. No compensation was given to the informants. Sample size The sample size in this pilot study presumed that the participant number of 20 patients, in NI and I-group, would be sufficient to display differences between the groups. Based on clinical studies, it was anticipated that the I-group would show different physiological reactions compared to the NI-group. Shimmer GSR + unit Shimmer3 GSR + unit is a wireless sensor device that monitors skin conductivity, heart rate and hand movements (Fig. ). It provides connections and preamplification for one channel of GSR data acquisition. The GSR + unit measures the skin conductivity between two reusable electrodes attached to two fingers of the hand. Alternatively, the sensor is also compatible with disposable electrodes that can be attached to the palmar surface or any other part of the body. Shimmer3 GSR + also provides an additional channel that can capture the optical pulse or PPG (plethysmograph) signal to estimate the heart rate. It also has built-in motion sensors (accelerometer, gyroscope, and magnetometer) that can be used to capture hand movements and orientation. Designed to be wearable, the GSR + unit is free from wired constraints and provides reliable data via a wireless BLE transmitter. Reusable finger electrodes, disposable adhesive electrodes, and wrist strap are included. The study design was experimental, aiming to evaluate the Shimmer3 GSR + unit's ability to indicate the patient’s negative reactions during different dental interventions. The pilot study was conducted at the Public Dental Service. In addition, the survey was performed in collaboration between different cooperation partners (data blinded). *Patient listed at the specific Dental Public Clinic for the study performance. *Patient 14–16 years old, with no medical diagnoses or medications. *Patient and legal guardian fluent in the blinded language as each patient should be introduced to the validated scales: coloured analogue scale (CAS); 0 = no pain to 10 = most possible pain, for pain intensity, facial analogue scale (FAS); A = happy to I = crying, for the emotional state, and a fear scale; 0–4, 0 = not afraid to 4 = terrified, to enable to communicate the own experience. *An impending dental check-up. *An impending dental extraction of a permanent premolar, due to orthodontic indications. *Patient in need of sedatives or nitrous oxide sedation. Non-invasive treatment group (NI); an oral check-up. Invasive treatment group (I); a premolar extraction, maxilla, or mandible due to orthodontic indication. Patients with impending oral examinations/extractions who met the inclusion criteria were assigned to either group NI or group I. Patients were then introduced to the purpose of the study, and the anonymous data processing, both verbally and through written information. Written and verbal informed consent from the patient and guardian was required for study eligibility. Voluntariness was emphasised, highlighting that the participation could be withdrawn at any time during the study. No compensation was given to the informants. The sample size in this pilot study presumed that the participant number of 20 patients, in NI and I-group, would be sufficient to display differences between the groups. Based on clinical studies, it was anticipated that the I-group would show different physiological reactions compared to the NI-group. Shimmer3 GSR + unit is a wireless sensor device that monitors skin conductivity, heart rate and hand movements (Fig. ). It provides connections and preamplification for one channel of GSR data acquisition. The GSR + unit measures the skin conductivity between two reusable electrodes attached to two fingers of the hand. Alternatively, the sensor is also compatible with disposable electrodes that can be attached to the palmar surface or any other part of the body. Shimmer3 GSR + also provides an additional channel that can capture the optical pulse or PPG (plethysmograph) signal to estimate the heart rate. It also has built-in motion sensors (accelerometer, gyroscope, and magnetometer) that can be used to capture hand movements and orientation. Designed to be wearable, the GSR + unit is free from wired constraints and provides reliable data via a wireless BLE transmitter. Reusable finger electrodes, disposable adhesive electrodes, and wrist strap are included. Clinical setting and dentist calibration The pilot study was performed January through December 2023. A general dentist and dental assistant team executed all oral check-ups and premolar extractions. The general dentist (CJa) responsible for conducting the collection of the data was instructed and trained to use the Shimmer3 GSR + unit by author (CJo), and the clinical performance and protocol parameters by author (LK). Analogue and digital data All analogue data were collected during the NI and I dental appointments, using an intervention protocol for each group, respectively. Patient reactions for each included protocol item were time indicated and documented regarding emotion, pain intensity, and fear. The dentist CJa assessed patient cooperation on a four graded scale: 0 = physical resistance/crying, 1 = reluctant acceptance/mild protests, 2 = reluctant/indifferent acceptance, 3 = full acceptance (Rud and Kissling ). The digital parameters were continuously recorded and electronically stored. Patient preparation Prior to each NI and I treatment, the patient was introduced to the analogue scales regarding expressing anxiety, fear, and pain. The patient was then seated for 5 min before applying the Shimmer3 GSR + unit, to create a calm starting position. Non-invasive treatment group Patient was seated in the dental chair for 5 min. The Shimmer3 GSR + unit bracelet was then applied on the left or right wrist. The GSR electrodes were attached to two fingers, and the optical probe to one finger. The intervention was stepwise proceeded by the dentist CJa guiding each patient in accordance with the protocol: *Seated patient, *Lying patient, *Dentist fingers into the patient’s mouth, *Dental mirror usage, *Dental probe usage, *Oral radiograph (individual indication/not mandatory) and *Fluoride-varnish appliance (individual indication/not mandatory). After completion of treatment, the patient gave a self-report regarding CAS, FAS and regarding fear (0–4), for each protocol item. The dentist assessment regarding patient fear and cooperation (0–4) was included in the protocol. The clock time for each protocol step was observed and recorded by the assigned assistant, providing the opportunity to relate to a corresponding physiological value. Negative reactions of the patients were observed and addressed by CJa. In order to meet national recommendations, interventions were carried out in accordance with the Tell Show Do method (Holst and Ek ; Addleston ). Correspondingly, CJa would stop and communicate/adjust for the patient’s experience of discomfort. Patient was seated in the dental chair for 5 min. The Shimmer3 GSR + unit bracelet was then applied on the left or right wrist. The GSR electrodes were attached to two fingers, and the optical probe to one finger. The intervention was stepwise proceeded by the dentist CJa guiding each patient in accordance with the protocol: *Seated patient, *Lying patient, *Dentist fingers into the patient’s mouth, Dental mirror usage, *Dental probe usage (individual indication), *Topical anaesthesia (5 min) *Local anaesthesia, *Inferior Alveolar Nerve Block, *Trans papillary anaesthesia, *Dental luxation and *Dental extraction. The administration of local anaesthesia was standardised by making the protocol steps *Topical anaesthesia (5 min), *Local anaesthesia and *Transpapillary anaesthesia mandatory for every extraction procedure. After completion of treatment, the patient gave a self-report regarding CAS, FAS and regarding fear (0–4), for each protocol item. The dentist assessment regarding patient fear and cooperation (0–4) was included in the protocol. The clock time for each protocol step was observed and recorded by the assigned assistant, providing the opportunity to relate to a corresponding physiological value. Negative reactions of the patients were observed and addressed by CJa. In order to meet national recommendations, interventions were carried out in accordance with the Tell Show Do method. Correspondingly, CJa would stop and communicate/adjust for the patient’s experience of discomfort. Data readings The stored data readings from the Shimmer3 GSR + device were related to the NI and I protocol-variables, respectively. Each variable was correlated to the patient’s physiological response in time. After completion of treatment, each patient gave self-report on the CAS, FAS, and regarding fear, for each protocol item, respectively. The dentist assessment regarding patients fear and cooperation (0–3): 0 = no cooperation to 3 = full cooperation, was included in the protocol. Analogue patient data were collected in binders, while digital data were stored on a USB flash drive. All data were saved in a locked space. During the clinical study implementation, only the author CJa, LK had access to the locked space. All data were compiled and processed by CJa, CJo, and LK. Statistics Descriptive statistics has been performed for the NI and I-group, respectively, regarding the frequency (n) as to age, median, and gender of the patients. The physiological signals for heart rate, galvanic skin response and motion were analysed. The physiological signals for fear and pain at the beginning and end of each intervention were evaluated in relation to the equivalent analog protocol items. The hand movements were analysed correspondingly. The pilot study was performed January through December 2023. A general dentist and dental assistant team executed all oral check-ups and premolar extractions. The general dentist (CJa) responsible for conducting the collection of the data was instructed and trained to use the Shimmer3 GSR + unit by author (CJo), and the clinical performance and protocol parameters by author (LK). Analogue and digital data All analogue data were collected during the NI and I dental appointments, using an intervention protocol for each group, respectively. Patient reactions for each included protocol item were time indicated and documented regarding emotion, pain intensity, and fear. The dentist CJa assessed patient cooperation on a four graded scale: 0 = physical resistance/crying, 1 = reluctant acceptance/mild protests, 2 = reluctant/indifferent acceptance, 3 = full acceptance (Rud and Kissling ). The digital parameters were continuously recorded and electronically stored. All analogue data were collected during the NI and I dental appointments, using an intervention protocol for each group, respectively. Patient reactions for each included protocol item were time indicated and documented regarding emotion, pain intensity, and fear. The dentist CJa assessed patient cooperation on a four graded scale: 0 = physical resistance/crying, 1 = reluctant acceptance/mild protests, 2 = reluctant/indifferent acceptance, 3 = full acceptance (Rud and Kissling ). The digital parameters were continuously recorded and electronically stored. Prior to each NI and I treatment, the patient was introduced to the analogue scales regarding expressing anxiety, fear, and pain. The patient was then seated for 5 min before applying the Shimmer3 GSR + unit, to create a calm starting position. Patient was seated in the dental chair for 5 min. The Shimmer3 GSR + unit bracelet was then applied on the left or right wrist. The GSR electrodes were attached to two fingers, and the optical probe to one finger. The intervention was stepwise proceeded by the dentist CJa guiding each patient in accordance with the protocol: *Seated patient, *Lying patient, *Dentist fingers into the patient’s mouth, *Dental mirror usage, *Dental probe usage, *Oral radiograph (individual indication/not mandatory) and *Fluoride-varnish appliance (individual indication/not mandatory). After completion of treatment, the patient gave a self-report regarding CAS, FAS and regarding fear (0–4), for each protocol item. The dentist assessment regarding patient fear and cooperation (0–4) was included in the protocol. The clock time for each protocol step was observed and recorded by the assigned assistant, providing the opportunity to relate to a corresponding physiological value. Negative reactions of the patients were observed and addressed by CJa. In order to meet national recommendations, interventions were carried out in accordance with the Tell Show Do method (Holst and Ek ; Addleston ). Correspondingly, CJa would stop and communicate/adjust for the patient’s experience of discomfort. Patient was seated in the dental chair for 5 min. The Shimmer3 GSR + unit bracelet was then applied on the left or right wrist. The GSR electrodes were attached to two fingers, and the optical probe to one finger. The intervention was stepwise proceeded by the dentist CJa guiding each patient in accordance with the protocol: *Seated patient, *Lying patient, *Dentist fingers into the patient’s mouth, Dental mirror usage, *Dental probe usage (individual indication), *Topical anaesthesia (5 min) *Local anaesthesia, *Inferior Alveolar Nerve Block, *Trans papillary anaesthesia, *Dental luxation and *Dental extraction. The administration of local anaesthesia was standardised by making the protocol steps *Topical anaesthesia (5 min), *Local anaesthesia and *Transpapillary anaesthesia mandatory for every extraction procedure. After completion of treatment, the patient gave a self-report regarding CAS, FAS and regarding fear (0–4), for each protocol item. The dentist assessment regarding patient fear and cooperation (0–4) was included in the protocol. The clock time for each protocol step was observed and recorded by the assigned assistant, providing the opportunity to relate to a corresponding physiological value. Negative reactions of the patients were observed and addressed by CJa. In order to meet national recommendations, interventions were carried out in accordance with the Tell Show Do method. Correspondingly, CJa would stop and communicate/adjust for the patient’s experience of discomfort. The stored data readings from the Shimmer3 GSR + device were related to the NI and I protocol-variables, respectively. Each variable was correlated to the patient’s physiological response in time. After completion of treatment, each patient gave self-report on the CAS, FAS, and regarding fear, for each protocol item, respectively. The dentist assessment regarding patients fear and cooperation (0–3): 0 = no cooperation to 3 = full cooperation, was included in the protocol. Analogue patient data were collected in binders, while digital data were stored on a USB flash drive. All data were saved in a locked space. During the clinical study implementation, only the author CJa, LK had access to the locked space. All data were compiled and processed by CJa, CJo, and LK. Descriptive statistics has been performed for the NI and I-group, respectively, regarding the frequency (n) as to age, median, and gender of the patients. The physiological signals for heart rate, galvanic skin response and motion were analysed. The physiological signals for fear and pain at the beginning and end of each intervention were evaluated in relation to the equivalent analog protocol items. The hand movements were analysed correspondingly. Patient groups The NI-group consisted of 20 patients, 10 girls and 10 boys (14.6 ± 0.5 years), which underwent oral check-ups (Table ). The I-group consisted of 14 patients, 10 girls and 4 boys (15.3 ± 0.5 years), which underwent permanent premolar extractions (Table ). The number of the extracted teeth was 27. The distribution of the extracted teeth per patient was as follows: five patients; 1 tooth, four patients; 2 teeth, two patients; 3 teeth, two patients; 4 teeth. All 34 patients accepted and tolerated the Shimmer3 GSR + device well, without reporting being frightened by it. Analogue data of the protocols Patient mood, as reported by facial analogue scale, ranged between happy and being neutral for all protocol items during all dental sessions of the NI and I-group. Thus, no patient reported emotional distress. Fear was considerably more often reported by the I-group than by the NI-group. As reported for each protocol item in both groups, fear showed overall low gradings, 0–2/5. Pain reports were infrequent in both the I-group and NI-group. In the NI-group, pain was reported in 3/20 interventions, all occurring during the oral radiograph procedure. Pain intensity, as measured by the CAS for each protocol item in both the I and NI-groups, showed overall ratings < 3.5/10. Digital data The heart rate reading, based on photoplethysmography (PPG), was sensitive to the adjustment of the corresponding finger electrode. In numeral cases, the optical probe was misplaced, resulting in generally uninterpretable PPG reading. In total, PPG data could be read in 5 cases, of which increasing heart rate was noted in 3 cases linked to the injection procedure, I-group. The hand movements sensor data, as captured by the motion sensors (accelerometer, gyroscope, magnetometer), was interpreted as being adequate. In all I and NI patients, through all procedures, and at some time, hand movements were noted. Most frequently, these were noted during the application of the topical anaesthesia, a non-invasive procedure per se, of the I-group. The hand movements were equally frequent, during the injection performance. The galvanic skin response (GSR) data were interpreted as being adequate (Fig. ). In two I-group patients, the digital readings could not be detected due to technical problems. GSR ascended substantially in the I-group, at start and during 21 of the 27 injection procedures, and in 3 of the 27 extraction/luxation procedures (Fig. ). The physiological signals for the tooth extractions followed the same pattern as the tooth luxation. Patient compliance, as rated by the dentist: All patients of the I and NI-groups cooperated fully, grade 3, to all protocol items. The NI-group consisted of 20 patients, 10 girls and 10 boys (14.6 ± 0.5 years), which underwent oral check-ups (Table ). The I-group consisted of 14 patients, 10 girls and 4 boys (15.3 ± 0.5 years), which underwent permanent premolar extractions (Table ). The number of the extracted teeth was 27. The distribution of the extracted teeth per patient was as follows: five patients; 1 tooth, four patients; 2 teeth, two patients; 3 teeth, two patients; 4 teeth. All 34 patients accepted and tolerated the Shimmer3 GSR + device well, without reporting being frightened by it. Patient mood, as reported by facial analogue scale, ranged between happy and being neutral for all protocol items during all dental sessions of the NI and I-group. Thus, no patient reported emotional distress. Fear was considerably more often reported by the I-group than by the NI-group. As reported for each protocol item in both groups, fear showed overall low gradings, 0–2/5. Pain reports were infrequent in both the I-group and NI-group. In the NI-group, pain was reported in 3/20 interventions, all occurring during the oral radiograph procedure. Pain intensity, as measured by the CAS for each protocol item in both the I and NI-groups, showed overall ratings < 3.5/10. The heart rate reading, based on photoplethysmography (PPG), was sensitive to the adjustment of the corresponding finger electrode. In numeral cases, the optical probe was misplaced, resulting in generally uninterpretable PPG reading. In total, PPG data could be read in 5 cases, of which increasing heart rate was noted in 3 cases linked to the injection procedure, I-group. The hand movements sensor data, as captured by the motion sensors (accelerometer, gyroscope, magnetometer), was interpreted as being adequate. In all I and NI patients, through all procedures, and at some time, hand movements were noted. Most frequently, these were noted during the application of the topical anaesthesia, a non-invasive procedure per se, of the I-group. The hand movements were equally frequent, during the injection performance. The galvanic skin response (GSR) data were interpreted as being adequate (Fig. ). In two I-group patients, the digital readings could not be detected due to technical problems. GSR ascended substantially in the I-group, at start and during 21 of the 27 injection procedures, and in 3 of the 27 extraction/luxation procedures (Fig. ). The physiological signals for the tooth extractions followed the same pattern as the tooth luxation. Patient compliance, as rated by the dentist: All patients of the I and NI-groups cooperated fully, grade 3, to all protocol items. The main result indicated a significant increase in the galvanic skin responses (GSR), at the starting point and during the oral injection procedure, in the I-group. The GSR amplitudes persisted throughout and post the injection performance. The validity of the GSR readings for the I-group-data was reinforced by the corresponding analogue records, indicating the start of the oral injection. Accordingly, previous reports, among children and adolescents, have found injection to be the most fear and pain provoking dental procedure (Krekmanova and Robertson ). Moreover, most of the I-group patients consistently reported mild anxiety specifically connected to the protocol items, injection, dental luxation, and extraction, which the GSR signals supported. Because of the highest GSR signals during the injection, these reactions are interpreted as stress signs, most possibly induced by pain sensations. In contrast, for the NI protocol items as, using the dental mirror, or the dental probe, and dental radiograph no similar uniform pattern or high GSR amplitudes were produced. Among all detectable physiological stress responses such as heart rate, dilated pupils, and plasma cortisol levels, GSR may possibly be the most easily measurable sign (Rathmell and Fields ; Loscalzo et al. ; Yang ). Though, the possibility of vast interindividual range of physiological responses should be considered. In the NI-group, there was no unanimous high GSR response for specific items which point to overall different physiological reactions in comparison to the I-group. The fact that no patient, in either group, reported severe fear or pain could be the result of the small study population, as no of the invited patients declined participation. Another explanation could be that the dentist applied iatrosedation and thus influenced the patients’ experience in a positive way (Friedman ). A limitation of the pilot study was that the number of I-group participants did not match the NI-group. Therefore, nine of the I-group patients had more than one tooth extracted which could have influenced the physiological response during the succeeding visit. Consistently, Versloot et al. found that the pain that children perceived at the second dental injection was strongly influenced by the level of dental anxiety experienced at the first anaesthesia occasion (Versloot et al. ). Another limitation was that the pulse electrode could easily be misplaced on the finger, giving inadequate responses. Despite well-thought-out protocols, the Shimmer3 GSR + unit was applied after the patient was seated for 5 min to calm down, establishing only an analogue baseline. To our knowledge, there are no studies where patient physiological data have been retrieved with a digital device as in this pilot, recording invasive versus non-invasive dental procedures. Going forward, it is important to find a digital non-invasive method to objectively detect stress in young dental patients and prevent fear development. Most significant is that the method should be easily accepted by the young patients. An advantage in this study was that no patient discontinued the participation. A further advantage was that the applied device was well accepted by all participants. In the future, interdisciplinary research is essential for identifying optimal prevention of acute procedural pain in young dental patients. The Shimmer3 GSR + unit or a similar wearable sensor device could potentially provide a future solution. Considering the limitations of this study, the following conclusions can be made: the invasive treatment resulted in a specific unison GSR pattern, while the non-invasive procedure showed individually scattered GSR reactions. The commercially available CE-marked Shimmer3 GSR + device indicated the patient’s stress response triggered by the invasive anaesthetic procedure. |
Stereotypes and social representations associated with pediatric surgeons among medical students, residents and physicians: a cross-sectional study | 813dd4c2-897f-4a6c-acfb-4a85627d129b | 11789375 | Pediatrics[mh] | Pediatric surgery stands as a unique specialty practiced across many countries by surgeons from vanon-pediatric backgrounds encompassing general surgery, visceral surgery, orthopedic surgery, among others. Pediatric surgery was formally recognized in 2017 as a distinct residency in France divided into a visceral and an orthopedic sub-track while it was before regarded as a sub-specialty of visceral and orthopedic surgery before. Medical students in France undergo six years of general medical and surgical training, with part time hospital internships from the third to the sixth year. Students usually have to perform four part time 12 weeks internships per year, partly chosen by students depending on their individual preferences. A national competitive exam then ranks students allowing to access specialized residencies, among which pediatric surgery. Many factors influence residency choice, encompassing the social representation of the specialty, personal determinants, life fulfillment aspects such as a controllable lifestyle or the quality of working life, career considerations, and educational experiences, among others . Student social representation of medical specializations evolves from peer-to-peer interactions, a limited number of clinical rotations and classroom discussions with teachers who occasionally playfully reinforce stereotypes. Unfortunately, these stereotypes tend to persist from the onset of medical studies through to established medical practice . In pediatric surgery, studies have demonstrated the effects of gender and the effect of being part of a minority on career satisfaction and opportunities in pediatric surgery. Other authors tried to understand the determinants of satisfaction during residency in Saudi Arabia . However, literature examining perceptions and stereotypes specifically pertaining to pediatric surgery remains scant. For instance, in Turkey, the strongest reasons for selecting pediatric surgery residency in 2005 were the opportunity to perform surgery, working with children and experiencing strong emotional satisfaction, whereas other reasons, such as academic opportunities, were considered minor reasons . Notably, Ladha et al. demonstrated that in the U.S., medical students interested in surgical specialties were more motivated by salary and prestige than their counterparts interested in primary care . Yet, the perception of PS by peers remains largely unexplored, despite its potential impact on the specialty’s attractiveness for medical students and on the dialogue between pediatric surgeons and physicians from diverse medical specialties. Hence, the aim of this study is to elucidate the stereotypes and social representations (SRs) associated with pediatric surgery among French medical students, residents, and physicians. This nationwide, web-based survey on SRs and stereotypes regarding pediatric surgery was part of the largest project conducted by the French National Association of Medical Residents ( InterSyndicale Nationale des Internes) named StEreotypes Specialties Among Medical class (SESAME). The principal aim of which was to describe stereotypes and social representations of specialist physicians from all fields of medicine, to evaluate more precisely potential differences in attractiveness between the various specialties, thus to better understand how medical students choose their specialty for residency. The theory of social representations (SRs), elaborated by Serge Moscovici, comes from the field of social psychology . SRs are a cognitive and social set of beliefs, attitudes and opinions about a social object. This theory is based on the idea that social representations guide the actions of people. A link to an anonymous questionnaire ( , available in supplementary data) was posted on social networks and disseminated by e-mail by medical students and residents’ associations between March 15th and April 18th, 2021. Respondants had to assess they were following a medical curriculum. Here, we focused on SRs of French Pediatric surgeons among French medical students, residents and physicians. Respondents were required to be at least 18 years old, be enrolled or having completed medical curriculum (i.e., medical students, residents or physicians), be actually studying or practicing in France and had provided consent by signing the General Data Protection Regulation form. The questionnaire was based on the hierarchical evocation method, aiming not only to reveal shared representations within social groups but also to identify context-sensitive content. The same questionnaire was sent to residents in pediatric surgery to compare the results. The data were analyzed as previously published in the other medical specialties’ . Briefly, qualitative data were analyzed separately by two readers (CD and NH), with spelling correction and standardization of the writing (e.g., “meticulous”, “delicate”, “delicateness”, “precise” standardized under the word “meticulous”). The qualitative analysis was carried out according to the methods of Reinert , using the R interface for Multidimensional Analysis of Texts and Questionnaires (IRaMuteQ) . We explored the corpus of words by analyzing (i) descending hierarchical classification to identify different classes or themes of descriptions of pediatric surgery by medical class, (ii) constitution of a dendrogram to analyze how the themes were organized in relation to each other; each word of the corpus associated with a class was statistically linked to that class ( Chi 2 test p < 0.05). Graphical representation using correspondence factor analysis and (iii) an analysis of the structure of the word corpus by prototypical analysis, which assessed the corpus’s central core, i.e., the inseparable and universal part of the vision of PS. Then, each respondent’s SRs of PS were ranked from 1 to 5 by two independent raters (MP and CD, R²=0.86): 1: very positive SR, 2: positive SR, 3: neutral SR, 4: negative SR, and 5: very negative SR. A third reader (NH) was consulted in the event of disagreement. Graders were instructed that the rate should reflect the positivity or negativity of the set of words a respondent gave. Examples from the SESAME database outside the paediatric surgery database were taught to the graders. For qualitative data, all these analyses were made with the R interface for Multidimensional Analysis of Texts and Questionnaires (IRaMuteQ) in R software. For each class, a list of significant words for the class is generated based on the chi-square test according to Reinert method. The number of occurrences for each word considered significant satisfied the condition for use of the chi-square test. The number of participants sought to meet the recommendation of studies based on the theory of social representations of including more than 100 participants to generate these analyses. The quantitative statistical analyses were performed using SAS version 9.4 (SAS, Inc., Cary, NC, USA) and IBM SPSS statistics 25 (IBM, Inc., Armonk, NYC, USA). Multivariate regression was performed using R software version 4.2.2 (CRAN). Multivariate analysis was performed to decipher factors that had an effect on the willingness to become a PS (ranked from 1 to 5, totally agree to totally disagree ). Variables included in the analysis were SR grades (from 1 to 5), having performed an internship in pediatric surgery, having performed a pediatric surgery course, respondent gender, career status (student, resident, physician) and having someone in the family performing pediatric surgery. Reflexivity NH is a female doctor specialized in rehabilitation and has experience performing qualitative data. NH trained MP and CD to perform grading on the SESAME dataset. CD is a female pediatric surgeon and provided a surgical insight on the dataset while MP as a male resident in oncology provided an external point of view. NH is a female doctor specialized in rehabilitation and has experience performing qualitative data. NH trained MP and CD to perform grading on the SESAME dataset. CD is a female pediatric surgeon and provided a surgical insight on the dataset while MP as a male resident in oncology provided an external point of view. 278 medical students or physicians participated in the study, with 68.0% being female. Participants included students (30.9%), residents (44.2%) and physicians (24.8%), with ages ranging from 18 to 75 years (mean age 28.6 years, Table ). Verbatim responses yielded a total of 1078 words representing 234 unique forms (different words) (Fig. A). These words were first classified into 4 classes according to their lexical proximity (Fig. B). In Class 1 (30.8%), the words were mostly related to “human relations”, including the complex tripartite child‒parent-surgeon relationship; quite positive notions such as “empathy”, “emotion” and “softness”; alongside more nuanced words such as “stress” or “patience”. In Class 2 (27.6%), the words were mostly related to the “intensity” of pediatric surgery, either from a positive (“interesting”, “passion”, “polyvalent”, “valorizing”, “beautiful”) or negative descriptors (“difficult”, “time consuming”, “demanding”, risk”). Class 3 (15.2%) contained words related to the specificities of pediatric surgery (“hyperspecialized”, “specificities”, “unknown”). Finally, Class 4 (26.4%) words were related to the width of the PS specialty (“orthopedics”, “visceral”, “urology”, “family”, “malformations”, “cancer”). Words in the core zone (most frequent and highly ranked; Fig. C) are related to difficulties in the specialty, polyvalence and hyper-specialization, while words in the first periphery (frequent but low ranking) are related to the fact that specialty is perceived “stressful”, “time consuming”, “meticulous” and rather practiced in “university hospitals”. In comparison, another cohort of residents in pediatric surgery ( n = 30) seems to rather focus on the most positive sides of the specialty (“diversity”, “kindness”, “human”, “stimulating”), technicity (“growth”, “technical”, “complex”) and less frequently discuss the negative sides (“demographic issues”, “ time consuming” , “stress”). Only 3.6% of medical peers graded pediatric surgery as a specialty they strongly considered (10th out of 12 surgical specialties, Fig. A; Table ), while 57.5% of medical peers did not consider at all pediatric surgery (7th out of 12 surgical specialties “strongly disagree”, Fig. B). Pediatric surgery SR is rather intermediate and uniform, with a median grade of 3 [IQR 3–4] out of 5 (1 being very positive, 5 very negative). The SR of pediatric surgery was more positive for medical students (3 [IQR 3–4]) and physicians (3 [IQR 2–4]) than for residents (4 [IQR 3–4]). As expected, residents in pediatric surgery had a much better SR of the specialty (2 [IQR 2–2]). According to the multivariate analysis, the willingness to become a PS was associated with the SR of pediatric surgery ( p < 0.001) but also independently associated with having performed an internship in pediatric surgery ( p < 0.01) and having a family member practicing pediatric surgery ( p < 0.05). Interestingly, being a medical student, resident or physician had no significant effect ( p > 0.05), nor did attending to dedicated courses ( p = 0.65). Our study is the first to investigate the perspectives of medical students, residents, and physicians regarding pediatric surgery, although we published similar studies on other medical and surgical specialties . Only 3.6% of medical peers expressed a strong inclination toward choosing pediatric surgery as their specialty. While this percentage may seem small, it translates to approximately 320 medical students among the ± 9,000 medical students graduating annually. However, there were only 32 resident positions available in 2023 according to the French National Ranking Examination. Pediatric surgery may therefore be considered highly competitive as only about 10% of students strongly considering pediatric surgery may enter this residency (32 places out of 320 strongly considering the specialty). Pediatric surgery is considered by medical peers as a demanding, wide, and hyperspecialized surgical specialty that entails intricate complex human relationships with patients and their families, in our opinion fairly representing daily practice in PS. The primary negative perceptions associated with pediatric surgery revolve around its perceived difficulty, with descriptors such as “time-consuming” and “demanding,” often practiced in “university hospitals”. Although representative of daily practice in academic hospitals, PS begins to be practiced in non-academic and private settings with very different kind of practice. The rather negative notion of being a demanding specialty is also commonly associated to other surgical specialties in France. On the positive side, sentiments of “empathy”, “humanity”, “passion”, “beautiful[ness]” and “honorab[ility]” are attached to PS, while the technical part of PS is also valorized as “polyvalent[t]”, “meticulous” and “hyperspecialized”. One may expect that the technical aspects may also be attached to other surgical specialties, while the notion of empathy may not be shared by all surgical specialties. Despite its rather neutral social representation, pediatric surgery ranks 10th out of 12 surgical specialties considered, consistent with its rank in the national ranking exam in 2023. This is probably not explained by the fact that PS is a “rare” surgical specialty as other “rare” surgical specialties like ophthalmology are highly ranked. However, the possibility to practice in a private setting seems to be a major determinant as all highly ranked specialties are commonly practiced in the private setting in France (gynecology, ophthalmology and oto-rhino-laryngology) while all badly ranked are usually not performed in private settings (thoracic, neuro and pediatric surgery). A recent report from the National Office on Health Professionals’ Demography (ONDPS) published in 2021 revealed that pediatric surgery has the second-highest attrition rates among surgical specialties, with 17.4% of residents leaving the field, following thoracic and cardiac surgery and preceding neurosurgery. In contrast, ophthalmology and plastic surgery had the lowest attrition rates, at 2.4% and 5.4%, respectively. Additionally, the report indicated that 23% of pediatric surgeons who ceased practice had left the medical profession entirely, while 8% transitioned to another medical specialty . Informal discussions among residents in PS confirm that a large fraction of residents considered at least once leaving the specialty, mainly due to the negative aspects of this “time consuming” and “demanding” specialty. This exacerbates the shortage of pediatric surgeons, particularly in light of legislative changes in France that restrict the capacity of adult surgeons to conduct pediatric procedures . Nevertheless, in our study PS residents still have a very positive representation of the specialty, especially on aspects related to “diversity”, “kindness” or “passion”. We have demonstrated that regardless of social representation, factors affecting the inclination to pursue a career in pediatric surgery are completing an internship in pediatric surgery and having someone in the family practicing pediatric surgery, whereas attending courses on PS has no discernible effect. Only about 50% of medical peers had (or remembered having) a course on PS. This could be partially attributed to the limited number of pediatric surgery courses within the curriculum, resulting in the specialty being relatively unfamiliar to medical students. The fact that having a course was not statistically associated with a better SR of pediatric surgery also leaves room for improvement to PS courses. Medical peers represent < 1% of the French medical community but this was sufficient to include > 100 participants, a number deemed sufficient to generate a stable prototypical analysis . Our study encompassed a diverse array of medical peers from across the territory. This study may be biased by a selection bias as all responders participated voluntarily to this survey. Some parts of the analysis may partially suffer from a subjective bias because of some data analysis methods (i.e., grouping the synonymous words together or Likert scale of SR from 1 to 5). We employed a widely accepted method to analyze SRs, taking several precautions to mitigate bias through independent and blinded reviews . The social representation (SR) of pediatric surgery appears relatively neutral and is not highly regarded as a potential surgical specialty of interest among medical peers. Our findings indicate that the desire to pursue a career in pediatric surgery was positively influenced by completing an internship in the field, whereas attending courses had no significant impact. This discrepancy may be partly explained by the limited availability of courses on pediatric surgery, resulting in the specialty being relatively unknown to medical students. Therefore, efforts should be directed towards enhancing communication about the specialty, with a particular focus on innovative communication modalities to increase awareness and interest among medical students. Below is the link to the electronic supplementary material. Supplementary Material 1 |
Cognitive and psychophysiological impact of surgical mask use during university lessons | a5c10d09-1bc7-4147-bb5f-af69232f1dce | 7844352 | Physiology[mh] | Introduction Since the apparition of the SARS-Cov-2 in the city of Wuhan, (Hubei, China) in December 2019, governments around the world have taken unprecedented actions to respond and contain it . Countries are implementing different community, economic, and public health control measures to flatten the epidemic curve and avoid overload and possible collapse of their health systems. To date, the attenuation of reproduction/infection cases is given via suppression measures. This action aims to lead the R-naught of the virus below R1 with the use of non-pharmaceutical interventions till a vaccine is available, which according to recent data could be likely at least 12–18 months . Among the policies implemented we can highlighted the travel bans, social distancing, stay-at-home orders and general lockdowns, however while the conjunction of these measures have proven their efficacy, it has also shown severe impact and consequence for the economy and society . Since the pandemic seems to be lasting for a long time, governments need to find alternatives to severe measures as strict lockdowns . Given that the main pathway of transmission is via droplets (generally 5–10 μm) that have a short lifetime in the air and infect the upper respiratory tract, or finer aerosols, which may remain in the air for hours, the mandated use of mask seems like an effective non-pharmaceutical intervention to combat COVID-19 lockdowns . However, at the beginning of the pandemic, the World Health Organization did not recommend the use of face mask as a preventive measure . In the middle of the outbreak (May), there were not high-quality controlled trials addressing the question of wearing masks by the general population as a protective measure to contain COVID-19, and analogies were made with the influenza or SARS . Meanwhile, other health agencies as the centre of Disease and Prevention of the US (CDC), recommended the use of face masks, as an effective way to reduce the spread of the virus . In the same line, the European Center of Disease, Control and Prevention (ECDC), also highlighted the importance of its use whereas social distancing cannot be maintained . In general terms, countries are implementing the use of mandatory face mask at all time, independently of the context and situation while staying at public . This has risen a new question while some controversy is still rising about the chronic use of face masks. In this line, while the SARS outbreak, the prolonged use of face mask by healthcare workers, resulted in headaches , and adverse skins reactions such as rashes, acne, and itches . So on, recent research suggest that prolonged use of masks causes a host of physiologic and psychologic burdens and could decrease work efficiency .Indeed, authors stated that chronic use of FPII and surgical mask of healthcare workers in the actual pandemic lead to headaches, breathing difficulty, acne, skin breakdown, rashes, interferes with vision, communication, and thermal equilibrium . Despite most of the professions are subjected to telecommuting (mask-free), some sectors like education, are still face-to-face or combining online classes with traditional personal classes. Therefore, students and professors are a collective subjected to mandatory and chronic use of face mask for over 8 h (average duration of a school day). Yet, there are no studies focusing on this population, addressing the acute and chronic psychophysiological effects of face masks, as well as its impact on cognitive performance. Therefore, we conducted the present research with the aim of to analyze the impact of surgical mask use in cognitive and psychophysiological response of university students during a lesson. The initial hypothesis was that the use of surgical mask would increase the autonomic sympathetic modulation, decreasing cognitive performance and blood oxygen saturation.
Materials and methods 2.1 Participants We analyzed a total of 50 volunteers university students (age 20.2 ± 2.9). From those, 38 were male students (age 21.2 ± 1.6) and 12 female students (age 21.1 ± 1.1). The exclusion criteria were: presence of any medical condition, intake of any dietary supplement, stimulants or other ergogenic aids. Prior to participation, the experimental procedures were explained to all the participants, who gave their voluntary written informed consent in accordance with the Declaration of Helsinki. 2.2 Procedure To reach the study aim we analyzed the students in two different moments. i. personal face-to-face class in where the use of the mask is mandatory during the entire lecture time. Surgical masks used by students were distributed by the University, therefore all students used the same model with the same face-fit; ii. online class with student at home did not wearing the mask. Both lectures were given at 8:30 A.M and have a duration of 150 min. Both classes were regular magistral classes of biomedical students attending one theorical class. The following variables were measured before and immediately after both lectures. Blood oxygen saturation by an oximeter OXYM4000 (Quirumed, Madrid), placed in the index finger of the right arm. Heart Rate (HR) and Heart Rate Variability (HRV) were recorded before and after the lectures by a Polar V800 HR monitor (Kempele, Finland) in a prone position following the procedures of previous research in educational context (Ramírez-Adrados et al.,2020a;2020b). The V800 has a sampling frequency of 1000 Hz being able to register the RR intervals (time interval between R waves of the electrocardiogram) for the analysis of the HRV and the number of beats per minute for the HR analysis. Subsequently, the following parameters of the HRV domains were analysed using the Kubios HRV software program with no factor of correction, since the measures obtained were clean and free of noise (University of Kuopio, Kuopio, Finland): • Time-Domain (Nonspectral) Analysis. We recorded the Mean RR (ms) and the square root of the mean value of the sum of squared differences of all successive R-R intervals RMSSD (ms). • Frequency-Domain (Spectral Measures) Analysis. We analysed the low frequency (LF) and high-frequency (HF) power components in normalized units (n.u). The frequency ranges where, HF: 0.15–0.40 Hz and LF: 0.04–0.15 Hz. • Nonlinear domain analysis. SD1 and SD2 were measured to reflect the fluctuations of the HRV throw a Poincaré chart, physiologically, on the transverse axis. SD1 reflects parasympathetic activity while SD2 reflect the long-term changes of RR intervals and is considered as an inverse indicator of sympathetic activity Among the HRV analysis, no artifact correction was used, since the sample did not present any noise. - -Mental fatigue perception. By a scale ranged from 0–100, as in previous research (Redondo-Flórez et al.,2020) - -Reaction Time. Was measured throw a mobile app. Screen of the phone would be entirely white, randomly it would turn to a color and subject had to immediately react to the change and tap the screen. Participants were previously familiarize with the app, and the evaluations days 3 measures were taken before and after the class. The mean of this three moments would be the final value taken. 2.3 Statistical analysis The SPSS statistical package (version 21.0; SPSS, Inc., Chicago, Ill.) was used to analyze the data. Normality and homoscedasticity assumptions were checked with a Kolmogorov-Smirnov test. Differences between pre and post samples of the two situations evaluated were analyzed using a MANOVA with samples as a fixed factor and with a Bonferroni post hoc analysis. The Effect Size was tested by the η2. Finally, a bivariate correlation analysis between all the study variables was performed using a Pearson correlation analysis. The level of significance for all the comparisons was set at p ≤ 0.05.
Participants We analyzed a total of 50 volunteers university students (age 20.2 ± 2.9). From those, 38 were male students (age 21.2 ± 1.6) and 12 female students (age 21.1 ± 1.1). The exclusion criteria were: presence of any medical condition, intake of any dietary supplement, stimulants or other ergogenic aids. Prior to participation, the experimental procedures were explained to all the participants, who gave their voluntary written informed consent in accordance with the Declaration of Helsinki.
Procedure To reach the study aim we analyzed the students in two different moments. i. personal face-to-face class in where the use of the mask is mandatory during the entire lecture time. Surgical masks used by students were distributed by the University, therefore all students used the same model with the same face-fit; ii. online class with student at home did not wearing the mask. Both lectures were given at 8:30 A.M and have a duration of 150 min. Both classes were regular magistral classes of biomedical students attending one theorical class. The following variables were measured before and immediately after both lectures. Blood oxygen saturation by an oximeter OXYM4000 (Quirumed, Madrid), placed in the index finger of the right arm. Heart Rate (HR) and Heart Rate Variability (HRV) were recorded before and after the lectures by a Polar V800 HR monitor (Kempele, Finland) in a prone position following the procedures of previous research in educational context (Ramírez-Adrados et al.,2020a;2020b). The V800 has a sampling frequency of 1000 Hz being able to register the RR intervals (time interval between R waves of the electrocardiogram) for the analysis of the HRV and the number of beats per minute for the HR analysis. Subsequently, the following parameters of the HRV domains were analysed using the Kubios HRV software program with no factor of correction, since the measures obtained were clean and free of noise (University of Kuopio, Kuopio, Finland): • Time-Domain (Nonspectral) Analysis. We recorded the Mean RR (ms) and the square root of the mean value of the sum of squared differences of all successive R-R intervals RMSSD (ms). • Frequency-Domain (Spectral Measures) Analysis. We analysed the low frequency (LF) and high-frequency (HF) power components in normalized units (n.u). The frequency ranges where, HF: 0.15–0.40 Hz and LF: 0.04–0.15 Hz. • Nonlinear domain analysis. SD1 and SD2 were measured to reflect the fluctuations of the HRV throw a Poincaré chart, physiologically, on the transverse axis. SD1 reflects parasympathetic activity while SD2 reflect the long-term changes of RR intervals and is considered as an inverse indicator of sympathetic activity Among the HRV analysis, no artifact correction was used, since the sample did not present any noise. - -Mental fatigue perception. By a scale ranged from 0–100, as in previous research (Redondo-Flórez et al.,2020) - -Reaction Time. Was measured throw a mobile app. Screen of the phone would be entirely white, randomly it would turn to a color and subject had to immediately react to the change and tap the screen. Participants were previously familiarize with the app, and the evaluations days 3 measures were taken before and after the class. The mean of this three moments would be the final value taken.
Statistical analysis The SPSS statistical package (version 21.0; SPSS, Inc., Chicago, Ill.) was used to analyze the data. Normality and homoscedasticity assumptions were checked with a Kolmogorov-Smirnov test. Differences between pre and post samples of the two situations evaluated were analyzed using a MANOVA with samples as a fixed factor and with a Bonferroni post hoc analysis. The Effect Size was tested by the η2. Finally, a bivariate correlation analysis between all the study variables was performed using a Pearson correlation analysis. The level of significance for all the comparisons was set at p ≤ 0.05.
Results Data are presented as mean±sd. The MANOVA results indicate significant differences between the situations analyzed (Wilks lambda=0.256; F = 5.219; hypothesis degrees of freedom: 30; error degrees of freedom: 264.844; p =.000; η2=0.365). The mental fatigue perception and reaction time significantly increased after both class situation (with and without surgical mask use). By contrary blood oxygen saturation was higher when surgical mask was not used. Regarding HRV parameters there was a decrease in Mean RR, RMSSD and HF after the class, being higher with the surgical mask use . Regarding the correlation analysis we found positive significant correlations between mental fatigue perception and reaction time, LF and SD2, by contrary mental fatigue perception presented a negative significant correlations with the blood oxygen saturation, Mean RR, RMSSD, HF and SD1. The reaction time presented a positive significant correlation with LF and a negative significant correlation with the blood oxygen saturation, RMSSD, HF and SD1 .
Discussion The aim of the present study was to analyze the impact of surgical mask use in cognitive and psychophysiological response of university students during a lesson. The initial hypothesis was partially accomplished since the use of surgical mask produced an increased hear rate, and a decrease in blood oxygen saturation, but did not significantly decrease more than non-surgical mask condition the cognitive performance and HRV variables. We found a significant decrease in the blood oxygen saturation after the class with mask use. It seems how the prolonged use of surgical mask (150 min) negatively affect blood oxygen saturation. This data was in line with previous research conducted in surgeons during 1–4 h surgeons, where the blood oxygen saturation decreased from 98% to 96% . In this studio researcher also reported a significant increase in HR (from 85 to 90 bpm), tendency also measured in the present research where a significant 13 bpm was measured with the use of surgical mask . The inhalation of the exhaled CO2 that mechanically stops the mask would produce physiological modifications to compensate the lower O2 inhalation. In this line, blood pressure and aortic and left ventricular pressures increase, leading to an upsurge of cardiac and coronary workload finally increasing the HR . The decrease of blood oxygen saturation after the use of surgical mask, even significant, would not be clinical relevant, since the blood oxygen saturation remained in normal range (90–98%) , fact also applicated to the HR that was maintained in normal resting values (60–100 bpm) . Only when the use of mask is maintained in time (over 8 h in healthcare professionals) symptoms of hypoxemia such as chest discomfort and tachypnoea are presented . These response could be explained sine CO2 is a respiratory stimulant, and when is accumulated by the mask use increase lung ventilation and respiratory activity, fact that would explain the symptoms of confusion, impaired cognition, and disorientation, experienced by nurses . It would be interesting to analyze present student after the entire university classes day (8 h approx..) to check if the same response of healthcare professionals is presented also by them, but future research may seek this item. Regarding cognitive performance, we found how the class produced a significant increase in mental fatigue perception of student independently of the use or not of the surgical mask, sowing the mask situation a tendency to be higher than in the non-mask situation. Probably the duration of the lesson was to long, inducing this increased fatigue perception. According to the mental fatigue perception results, the reaction time also increased after the lesson, fact related with a decrease in information processing and cortical arousal, situation related with symptoms of Central Nervous System by previous authors . Also, this parameter showed a tendency to be higher than in the non-mask situation. The impact in these cognitive variables could be related with the decrease in the blood oxygen saturation found with the use of surgical mask. In this line, the correlation analysis showed a negative correlation between blood oxygen saturation and mental fatigue perception and reaction time. This result is in line with previous research that found how cognitive performance is associated with cerebral oxygenation and peripheral oxygen saturation . Then could be important to maintain cognitive resources during the entire class make some brakes to try decrease cortical demands and maintain blood oxygen saturation, since the option of live the mask is already not recommended in the actual situation. Regarding the autonomic modulation of students, we found how the 150 min lecture produced a decrease in Mean RR, RMSSD and HF, modifications related with an increased sympathetic modulation. This increase in the autonomic stress response was also measured in other university context as clinical stays, clinical simulations, clinical practice, final degree dissertations and objective structured clinical examination , , , , but in these cases the autonomic stress response was higher highlighting how the level of context elicitation have a direct impact in the autonomic response, since in the case of present study students they have a passive interaction in the lessons but in the others research students have an active interaction, in most of the cases interacting with patients and/or with the stress of being evaluated by teachers. Regarding the effect on the autonomic response of the surgical mask use, we only found a tendency to a general decrease in heart rate variability, fact related with a higher sympathetic modulation. Recent studies suggested that the chronic use of face mask result in an increased sympathetic modulation due to the increased hypoxia state, that consequently carries an increased stress, headaches, impaired motor function and cognition (Rosner., 2020). In the present research the low time exposition to the surgical mask use precluded these symptomatology, but it might expect that after the full school day they might arise. In these cases in where the surgical mask must be used for prolonged time, previous authors suggested take off the mask whereas possible and take deep breath for three minutes to quickly release the stress. If the condition does not allow people to take off the mask, wear a mask and take a deep breath for three to five minutes to relieve stress and hypoxia . Finally, the correlation analysis shown the importance of blood oxygen saturation for a correct cognitive function since presented a significant negative correlation with mental fatigue perception and reaction time. In this line the blood oxygen saturation presented a significant negative correlation with sympathetic modulation parameters, and this sympathetic modulation parameters a significant positive correlation with mental fatigue perception and reaction time. It is shown how cognitive functions would be beneficiate by a domain of parasympathetic modulation, as well as a higher blood oxygen saturation. The importance of blood oxygen saturation in cortical functions was highlighted when an increase in respired oxygen in a group of participants produced an increase in their cognitive performance Then, in educational context, especially when the mask must be used for prolonged time, would be recommend making some break to lead students to decrease their sympathetic modulation as well as to increase their blood oxygen levels. 4.1 Limitation and future practical applications The first limitation was the low sample size, but the limitations, restrictions, and COVID-19 health protocols precluded to recruit a larger sample. It would be optimal to analyze the cerebral tissue oxygen saturation for better comprehension of the impact of surgical mask in cognitive physiology. Also the control of certain stress hormones such as cortisol or alpha amylase would help into a better understanding on the stress response and HRV results. However, technological, and financial lack precluded its applications. Future research might seek to address these issues. In addition, the study of surgical mask use in professor, as well as the long time use of surgical mask in students and professors are proposed as future research lines.
Limitation and future practical applications The first limitation was the low sample size, but the limitations, restrictions, and COVID-19 health protocols precluded to recruit a larger sample. It would be optimal to analyze the cerebral tissue oxygen saturation for better comprehension of the impact of surgical mask in cognitive physiology. Also the control of certain stress hormones such as cortisol or alpha amylase would help into a better understanding on the stress response and HRV results. However, technological, and financial lack precluded its applications. Future research might seek to address these issues. In addition, the study of surgical mask use in professor, as well as the long time use of surgical mask in students and professors are proposed as future research lines.
Conclusion The use of surgical mask during a 150 min university lesson produced an increased heart rate and a decrease in blood oxygen saturation, not significantly affecting the mental fatigue perception, reaction time and time, frequency and non linear hear rate variability domains of students.
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Development, optimization and characterization of nanoemulsion loaded with clove oil-naftifine antifungal for the management of tinea | 755740a5-de45-419b-a6e2-09bd7aa70c83 | 8725874 | Pharmacology[mh] | Introduction Superficial fungal infections, such as tinea, are one of the most prevailing infections worldwide primarily caused by dermatophytes of the genera Epidermophyton , Microsporum , and Trichophyton (Branscomb, ). Such aerobic pathogenic fungi can grow and colonize on keratinized tissues like skin, hair and nails, owing to their ability to produce numerous proteolytic enzymes that can digest keratin (Branscomb, ). These infected keratinized tissues provide the desired temperature, pH, and nitrogen conditions to meet the nutritional needs of dermatophytes; therefore, such infections are restricted to superficial cutaneous tissues and rarely extend to deeper subcutaneous ones (Bottone, ). Although several antifungals have been reported to have essential activity against dermatophytes, such infections often relapsed after the medication was stopped since these organisms established a tolerance to prolonged treatment (Mukherjee et al., ). Dermatophytosis is usually treated through oral or topical pathways or a combination of both, considering the site, infection extent, severity, and causative organism (Rotta et al., ). Principally, the topical route is thought to be the first-line treatment for superficial and uncomplicated infections due to its high efficacy, good ability to localize drugs at the infection site, and low chance for systemic absorption, hence offering much fewer side effects (van Zuuren et al., ). Naftifine, a primary topical antimycotic drug with allylamine structure, is active against a broad spectrum of dermatophytes belonging to Trichophyton and Microsporum spp. and has shown good activity against Candida and Aspergillus spp. (Cuenca-Estrella et al., ). It is believed to exert a fungicidal effect through squalene epoxidase inhibition in fungi, thus diminishing ergosterol biosynthesis (Monk & Brogden, ). In contrast to other antifungal drugs like azoles, naftifine is highly selective to ergosterol biosynthesis and does not affect drug metabolism in the liver even if a significant portion reaches the systemic circulation (Lee et al., ). Although naftifine is well tolerated, it was reported to cause some mild inflammations and stinging sensation, which might affect patient compliance (Altmeyer et al., ). Naftifine is a topical, synthetic allylamine derivate similar to terbinafine, its molecular weight is 287.4, its logP equals 5, it has very poor aqueous solubility (0.000229 mg/mL) and pKa equal 9.08 (Chen et al., ) Eugenol is a phenolic compound that accounts for 45–90% of clove essential oil (Zhang et al., ) and has exhibited several pleiotropic activities, such as anti-inflammatory (Kim et al., ), anticancer, bactericidal (Hamed et al., ), antifungal (Darvishi et al., ), anesthetic (Tsuchiya, ), and analgesic effects (Baldisserotto et al., ). Its anti-inflammatory effect might be ascribed to its ability to block the nuclear factor-kappa B (NF-κB) signaling pathway, which is responsible for producing the inflammatory cytokines, namely interleukin-6 (IL-6), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) (Zhang et al., ). More importantly, eugenol offers good activity against dermatophytes due to its interaction with the fungal envelope, leading to the leakage of cells’ essential elements and eventually cell death (Lee et al., ). Furthermore, several investigations have suggested that eugenol also offers a transdermal penetration-enhancing effect (Mutalik & Udupa, ). Based on the above-mentioned findings, clove oil appears to be a promising support therapy in treating topical skin infections like tinea. An exemplary drug delivery system should offer maximum therapeutic effect with minimum toxicity (Montenegro et al., ). Nano-sized drug delivery systems have been considered a good substitute for conventional ones (Abou-Taleb et al., ; Alkhalidi et al., ), such as nanoemulsions (NE) systems that consist of 20–500 nm-sized nano-droplets stabilized by surfactants. Frequently, NE can be formulated as water-in-oil (W/O), oil-in-water (O/W) and also multiple emulsions (W/O/W) (Esmaeili et al., ; Hosny et al., ) systems, which exhibit several strength points compared to conventional emulsions. These advantages include: (1) the ability to effectively transport drugs to target sites owing to their very large surface area offered by the very small size of their droplets; (2) the capacity to guard against hydrolysis and enzymatic degradation of drugs; (3) enhanced drug loading, drug solubility and bioavailability; (4) decreased intra-patient variations, and (5) ability to attain controlled drug release (Sigward et al., ). Due to such advantages, NE provides an ideal platform for drug delivery systems. Nanoemulsions are usually stabilized by employing various surfactants and co-surfactants that form a protective fil around oil globules, preventing their coalescence and NE separation (Jaiswal et al., ). Quaternary ammonium compounds like cetylpyridinium chloride (CPC) were reportedly used as surfactants in nanoemulsions due to their stabilizing effect (Barney et al., ) and antimicrobial action against a broad spectrum of bacteria and fungi (Rawlison et al., ). Moreover, it is considered more effective against aerobic and anaerobic microorganisms with only minimal concentrations compared to other antiseptics like chlorhexidine (Uerra et al., ). The production of an effective drug delivery system requires a rational mixture of drugs and excipients; therefore, optimizing the formula composition is essential to achieve optimal quality. To obtain this goal, Design of Experiments (DoE) methodologies have been recently applied, in which the “best solution” can be achieved through fewer experiments to attain an optimal formulation (Singh et al., ). Moreover, DoE offers a better understanding of the formula composition and tracking of problems that might emerge during experimentation. Furthermore, DoE can help in assigning the more important input variables through certain screening techniques (Dhawan et al., ) and can uniquely anticipate a formulation’s performance prior to its preparation, hence saving effort, time, supplies, and cost (Huang et al., ). Considering these objectives, the current study was conducted to develop a clove oil-based nanoemulsion loaded with naftifine HCl as a topical treatment for superficial tinea infections.
Materials and methods 2.1. Materials Naftifine was acquired as a generous gift from Pharco Pharmaceutical Company, Egypt. (Alexandria, Egypt). Cetylpyridinium chloride was acquired as a generous gift from Saudi Drugs and Medical Instruments Company (SPIMACO), in (Qassim, Saudi Arabia). Clove oil was purchased from Avanti Polar Lipids (Alabaster, AL, USA). Diethylene glycol monoethyl ether (Transcutol ® ) was kindly provided by Gattefossé (Lyon, France) High-performance liquid chromatography grade methanol and acetonitrile were obtained from Merck (Darmstadt, Germany). Chloroform, absolute ethanol, and phosphate buffer pH 7.4 were purchased from Fisher Scientific UK (Loughborough, Leicestershire, UK). All other reagents and chemicals were of analytical grade. 2.2. Methods 2.2.1. Experimental design and optimization of self-nanoemulsion formulations Two response surface Box–Behnken designs were adopted during the current investigation using Design-Expert ® software v. 12.0.6.0 (Stat-Ease, Inc., Minneapolis, MN, USA). The first design was developed to investigate the effects of independent variables (i.e. (A) clove oil %, (B) the Smix ratio of surfactant to co-surfactant, and (C) amount of water added on the globule size of plain self-nanoemulsion formulations (SNEDDS). The second design was created to explore the effect of the independent variables, including (A) clove oil %, (B) the amount of NF in milligrams, and (C) the Smix ratio of surfactant to co-surfactant in the prepared medicated nanoemulsions. The investigated dependent responses were the globule size of the prepared SNEDDS (Y1), ex vivo % of naftifine permeated through rat skin (Y2), the zone of inhibition against Trichophyton rubrum (Y3), and interleukin-31 level (Y4). The independent factors and determined responses are shown in . 2.2.2. Self-nanoemulsion preparation The development of NF-loaded nanoemulsions was performed in two steps. The first step included the formation of the plain SNEDDS, in which 10–20% clove oil concentrations were mixed with 40–60% surfactant and cosurfactant mixture (Smix) and 20–50% water. The surfactant and co-surfactant were mixed in three different ratios (1:1, 2:1, and 3:1), according to the first design. In the second step, clove oil concentrations of 10, 13.5, or 17% were mixed with 90, 86.5, or 83% Smix, respectively. The active ingredient, NF, was mixed with the plain SNEDDS with the aid of sonication in concentrations of 10, 20, or 30 mg/g according to the second design, as is shown in . 2.2.3. Globule size measurements The droplet size of either plain CO-SNEDDS or NF-CO SNEDDS was measured by diluting 200 μL SNEDDS with 800 μL purified water in a volumetric flask. The diluted samples were vigorously agitated, and then 200 μL was withdrawn and used to measure the droplet size on a Microtrac ® zeta track particle size analyzer (Microtrac, Inc., Montgomeryville, PA, USA) (Hosny et al., ). 2.2.4. Ex vivo permeation study The ex vivo permeation study was performed following a previously published method (Salem et al., ). The NF permeation across rat skin from nanoemulsions was assessed using Franz cells with a diffusion area of 5 cm 2 , according to a previously reported method. 8-weeks-old Wistar albino rats, weighing 150–200 g, were used in this study. Following animal sacrifice, shaved abdominal skin was excised, separated from underlying connective tissues using a scalpel, and finally used as a model permeation membrane. The obtained membranes were mounted between the donor and receptor compartments of Franz diffusion cells so that the stratum corneum was facing the donor, while the dermal skin side was facing the receptor compartment. Nanoemulsions (equivalent to 20 mg NF) were placed in the donor compartment of the Franz cells, and the receptor compartment was filled with 12 mL phosphate buffer saline (PBS, pH 7.4). The medium was stirred at 100 rpm, and the temperature was kept at 37 ± 0.5 °C during the experiment. 1-mL samples were withdrawn at fixed time intervals of 0.5, 1, 2, 4, 8, 12, and 24 h, then the receptor media was replenished with equal volumes of fresh media to maintain sink conditions. Collected samples were then analyzed for their NF content using high-performance liquid chromatography (HPLC) in which a mixture of acetonitrile, tetrahydrofuran, and tetramethyl-ammonium hydroxide with a ratio of 62:10:28, respectively (pH 7.8), was used as the mobile phase that was pumped at a fixed flow rate of 1.2 mL/min. The measurements were performed at a maximum wavelength of 240 nm using an Agilent 1260 Infinity Diode array detector VL (G131SD) and injection volume of 100 μL. Limit of detection of and linear range naftifine were 0.0201 μg/mL and 0.080 μg/mL respectively. The peak areas of Naftifine HCl were plotted against Naftifine HCl concentrations. The least square line regression analysis was used to determine the slope, Y-intercept, and the correlation coefficient of the standard plots. 2.2.5. Antifungal activity evaluation The antifungal activity of NF-CO-SENDDs against Trichophyton rubrum was assessed using a slightly modified disk diffusion susceptibility method (Mahtab et al., ). According to the method recommended by the Clinical and Laboratory Standards Institute, a suspension of Trichophyton rubrum was made to 0.5 McFarland turbidity standard (106 CFU/mL) by employing a hemocytometer. An inoculum of 1 mL, from a suspension of 104 CFU/mL, was spread on the surface of Mueller–Hinton agar plates using sterile loops. Disks of 10-mm diameters containing NF-CO-SENDDs were then placed onto the inoculated agar plates using sterile forceps. The prepared plates were incubated at 37 °C for 24 h, and growth inhibition zone diameters (where fungal growth markedly decreased) were measured for each NF-CO-SENDDs formulation. 2.2.6. Interleukin-31 measurements Male Wistar albino rats averagely weighing 250 ± 10 gm were used in the study. 150 mg of each formulation containing 3.5 mg of NF were applied topically to the saved animals’ skin. Animals received treatment once daily for 14 days. At the end of the experiment, blood samples of 1 mL were withdrawn from animals’ tail vein and placed in edita tubes, then the samples were centrifuged at 4000 rpm for 10 min, supernatant (i.e. serum) was removed and kept at −20 °C for further investigations. Concentrations of IL‐31 serum levels were determined using an enzyme‐linked immunosorbent assay (ELISA) technique. Rat IL‐31 Quantikine M‐assay (R&D, Minneapolis, MN, USA, Catalog no. M1300C) was carried out according to the manufacturer’s instructions. A monoclonal antibody specific for rat’s IL-31 was pre-coated onto a microplate, and goat‐anti‐rat IgG (Jackson Immuno, Catalog no. 115‐035‐166) was employed as the detection antibody. A microtiter plate reader was used for optical density determination at 450 nm, and concentrations of IL-31serum levels were expressed in pg/mL (Grimstad et al., ). 2.2.7. Optimization and evaluation of the selected formulation 2.2.7.1. Experimental model evaluation Degrees of freedom, F -ratio, and p -value for all factors and their interactions were determined to analyze the variance of calculated models for the measured responses and select the model that best fit the obtained data. Specifically, p -values less than .05 indicate the significance of the model. Moreover, the determination coefficients, predicted ( R 2 ), adjusted ( R 2 ), and CV% values were used to determine the model fitness. In the current investigation, the criteria used for identifying the optimized medicated NF-CO SENDDs included minimum globule size and IL-31 levels and maximum ex vivo % naftifine and zone of inhibition against Trichophyton rubrum . 2.2.7.2. Characterization of the optimized NF-loaded nanoemulsion formulation The optimum formulation was fabricated and characterized by determining its globule size, IL-31 levels, ex vivo % naftifine permeated across skin, and zone of inhibition against Trichophyton rubrum and compared against that of commercial cream. For further evaluation, NE was subjected to skin sensitivity and stability studies. The ex vivo diffusion study for optimum formulation was performed as previously mentioned, with additional calculation of the diffusion coefficient (D), permeability coefficient (P), steady-state transdermal flux (Jss), and enhancement ratio (ER). 2.2.7.2.1. Zeta potential (ZP) measurements An electrophoretic mobility study was employed to assign the surface charges of the optimum formulation using a Malvern Zeta sizer (Malvern instruments, Malvern, UK) at a temperature of 25 °C and a fixed angle of 90° (Abdelbary et al., ). 2.2.7.2.2. Skin sensitivity test The test rats were held in laboratory cages and allowed free access to water and food. Animals were acclimatized for a period of 14 days prior to experimentation under standard conditions of 55 ± 5% relative humidity, 25 ± 1 °C temperature, and a 12-h dark and 12-h light cycle. Rats were handled and tended to according to the Animal Ethics Committee guidelines, Beni-Suef Clinical Laboratory Center, Beni-Suef, Egypt. Researchers followed the guidelines set forth in the Declaration of Helsinki and its “Guiding Principles in the Care and Use of Animals” (NIH Publication No. 85-23, 1985 revision), complying to ethical approval of the protocol before starting the experiment (Approval No. M12-11-2020). The dorsal skin of rats (4 × 4 cm 2 ) was carefully shaved with an electric clipper so as not to cause any damage. Three animal groups, each composed of 6 rats, were employed in the study. The first group was treated with normal saline and served as the control, the second group received the optimized formulation, and the third group received the commercial product. The tested formulations were applied twice a day for a period of 3 days. Quantification of 5 inflammation signs which were itching, erythema, papule, flakiness, and dryness were used in this study to determine the degree of skin sensitivity. Each parameter was assigned a score from 0 to 3, where 0 represents no sign of inflammation, while 4, represents the severe signs of inflammation (Mahtab et al., ). 2.2.7.2.3. Stability studies The physical stability of the optimum nanoemulsion formulation was tested following a previously reported method with a slight modification (Shafiq-un-Nabi et al., ). The optimized formulation was subjected to three freeze-thaw cycles between −20 °C and +25 °C, stored at each temperature for 48 h, and finally examined for their emulsification ability, precipitation, pH, and globule size.
Materials Naftifine was acquired as a generous gift from Pharco Pharmaceutical Company, Egypt. (Alexandria, Egypt). Cetylpyridinium chloride was acquired as a generous gift from Saudi Drugs and Medical Instruments Company (SPIMACO), in (Qassim, Saudi Arabia). Clove oil was purchased from Avanti Polar Lipids (Alabaster, AL, USA). Diethylene glycol monoethyl ether (Transcutol ® ) was kindly provided by Gattefossé (Lyon, France) High-performance liquid chromatography grade methanol and acetonitrile were obtained from Merck (Darmstadt, Germany). Chloroform, absolute ethanol, and phosphate buffer pH 7.4 were purchased from Fisher Scientific UK (Loughborough, Leicestershire, UK). All other reagents and chemicals were of analytical grade.
Methods 2.2.1. Experimental design and optimization of self-nanoemulsion formulations Two response surface Box–Behnken designs were adopted during the current investigation using Design-Expert ® software v. 12.0.6.0 (Stat-Ease, Inc., Minneapolis, MN, USA). The first design was developed to investigate the effects of independent variables (i.e. (A) clove oil %, (B) the Smix ratio of surfactant to co-surfactant, and (C) amount of water added on the globule size of plain self-nanoemulsion formulations (SNEDDS). The second design was created to explore the effect of the independent variables, including (A) clove oil %, (B) the amount of NF in milligrams, and (C) the Smix ratio of surfactant to co-surfactant in the prepared medicated nanoemulsions. The investigated dependent responses were the globule size of the prepared SNEDDS (Y1), ex vivo % of naftifine permeated through rat skin (Y2), the zone of inhibition against Trichophyton rubrum (Y3), and interleukin-31 level (Y4). The independent factors and determined responses are shown in . 2.2.2. Self-nanoemulsion preparation The development of NF-loaded nanoemulsions was performed in two steps. The first step included the formation of the plain SNEDDS, in which 10–20% clove oil concentrations were mixed with 40–60% surfactant and cosurfactant mixture (Smix) and 20–50% water. The surfactant and co-surfactant were mixed in three different ratios (1:1, 2:1, and 3:1), according to the first design. In the second step, clove oil concentrations of 10, 13.5, or 17% were mixed with 90, 86.5, or 83% Smix, respectively. The active ingredient, NF, was mixed with the plain SNEDDS with the aid of sonication in concentrations of 10, 20, or 30 mg/g according to the second design, as is shown in . 2.2.3. Globule size measurements The droplet size of either plain CO-SNEDDS or NF-CO SNEDDS was measured by diluting 200 μL SNEDDS with 800 μL purified water in a volumetric flask. The diluted samples were vigorously agitated, and then 200 μL was withdrawn and used to measure the droplet size on a Microtrac ® zeta track particle size analyzer (Microtrac, Inc., Montgomeryville, PA, USA) (Hosny et al., ). 2.2.4. Ex vivo permeation study The ex vivo permeation study was performed following a previously published method (Salem et al., ). The NF permeation across rat skin from nanoemulsions was assessed using Franz cells with a diffusion area of 5 cm 2 , according to a previously reported method. 8-weeks-old Wistar albino rats, weighing 150–200 g, were used in this study. Following animal sacrifice, shaved abdominal skin was excised, separated from underlying connective tissues using a scalpel, and finally used as a model permeation membrane. The obtained membranes were mounted between the donor and receptor compartments of Franz diffusion cells so that the stratum corneum was facing the donor, while the dermal skin side was facing the receptor compartment. Nanoemulsions (equivalent to 20 mg NF) were placed in the donor compartment of the Franz cells, and the receptor compartment was filled with 12 mL phosphate buffer saline (PBS, pH 7.4). The medium was stirred at 100 rpm, and the temperature was kept at 37 ± 0.5 °C during the experiment. 1-mL samples were withdrawn at fixed time intervals of 0.5, 1, 2, 4, 8, 12, and 24 h, then the receptor media was replenished with equal volumes of fresh media to maintain sink conditions. Collected samples were then analyzed for their NF content using high-performance liquid chromatography (HPLC) in which a mixture of acetonitrile, tetrahydrofuran, and tetramethyl-ammonium hydroxide with a ratio of 62:10:28, respectively (pH 7.8), was used as the mobile phase that was pumped at a fixed flow rate of 1.2 mL/min. The measurements were performed at a maximum wavelength of 240 nm using an Agilent 1260 Infinity Diode array detector VL (G131SD) and injection volume of 100 μL. Limit of detection of and linear range naftifine were 0.0201 μg/mL and 0.080 μg/mL respectively. The peak areas of Naftifine HCl were plotted against Naftifine HCl concentrations. The least square line regression analysis was used to determine the slope, Y-intercept, and the correlation coefficient of the standard plots. 2.2.5. Antifungal activity evaluation The antifungal activity of NF-CO-SENDDs against Trichophyton rubrum was assessed using a slightly modified disk diffusion susceptibility method (Mahtab et al., ). According to the method recommended by the Clinical and Laboratory Standards Institute, a suspension of Trichophyton rubrum was made to 0.5 McFarland turbidity standard (106 CFU/mL) by employing a hemocytometer. An inoculum of 1 mL, from a suspension of 104 CFU/mL, was spread on the surface of Mueller–Hinton agar plates using sterile loops. Disks of 10-mm diameters containing NF-CO-SENDDs were then placed onto the inoculated agar plates using sterile forceps. The prepared plates were incubated at 37 °C for 24 h, and growth inhibition zone diameters (where fungal growth markedly decreased) were measured for each NF-CO-SENDDs formulation. 2.2.6. Interleukin-31 measurements Male Wistar albino rats averagely weighing 250 ± 10 gm were used in the study. 150 mg of each formulation containing 3.5 mg of NF were applied topically to the saved animals’ skin. Animals received treatment once daily for 14 days. At the end of the experiment, blood samples of 1 mL were withdrawn from animals’ tail vein and placed in edita tubes, then the samples were centrifuged at 4000 rpm for 10 min, supernatant (i.e. serum) was removed and kept at −20 °C for further investigations. Concentrations of IL‐31 serum levels were determined using an enzyme‐linked immunosorbent assay (ELISA) technique. Rat IL‐31 Quantikine M‐assay (R&D, Minneapolis, MN, USA, Catalog no. M1300C) was carried out according to the manufacturer’s instructions. A monoclonal antibody specific for rat’s IL-31 was pre-coated onto a microplate, and goat‐anti‐rat IgG (Jackson Immuno, Catalog no. 115‐035‐166) was employed as the detection antibody. A microtiter plate reader was used for optical density determination at 450 nm, and concentrations of IL-31serum levels were expressed in pg/mL (Grimstad et al., ). 2.2.7. Optimization and evaluation of the selected formulation 2.2.7.1. Experimental model evaluation Degrees of freedom, F -ratio, and p -value for all factors and their interactions were determined to analyze the variance of calculated models for the measured responses and select the model that best fit the obtained data. Specifically, p -values less than .05 indicate the significance of the model. Moreover, the determination coefficients, predicted ( R 2 ), adjusted ( R 2 ), and CV% values were used to determine the model fitness. In the current investigation, the criteria used for identifying the optimized medicated NF-CO SENDDs included minimum globule size and IL-31 levels and maximum ex vivo % naftifine and zone of inhibition against Trichophyton rubrum . 2.2.7.2. Characterization of the optimized NF-loaded nanoemulsion formulation The optimum formulation was fabricated and characterized by determining its globule size, IL-31 levels, ex vivo % naftifine permeated across skin, and zone of inhibition against Trichophyton rubrum and compared against that of commercial cream. For further evaluation, NE was subjected to skin sensitivity and stability studies. The ex vivo diffusion study for optimum formulation was performed as previously mentioned, with additional calculation of the diffusion coefficient (D), permeability coefficient (P), steady-state transdermal flux (Jss), and enhancement ratio (ER). 2.2.7.2.1. Zeta potential (ZP) measurements An electrophoretic mobility study was employed to assign the surface charges of the optimum formulation using a Malvern Zeta sizer (Malvern instruments, Malvern, UK) at a temperature of 25 °C and a fixed angle of 90° (Abdelbary et al., ). 2.2.7.2.2. Skin sensitivity test The test rats were held in laboratory cages and allowed free access to water and food. Animals were acclimatized for a period of 14 days prior to experimentation under standard conditions of 55 ± 5% relative humidity, 25 ± 1 °C temperature, and a 12-h dark and 12-h light cycle. Rats were handled and tended to according to the Animal Ethics Committee guidelines, Beni-Suef Clinical Laboratory Center, Beni-Suef, Egypt. Researchers followed the guidelines set forth in the Declaration of Helsinki and its “Guiding Principles in the Care and Use of Animals” (NIH Publication No. 85-23, 1985 revision), complying to ethical approval of the protocol before starting the experiment (Approval No. M12-11-2020). The dorsal skin of rats (4 × 4 cm 2 ) was carefully shaved with an electric clipper so as not to cause any damage. Three animal groups, each composed of 6 rats, were employed in the study. The first group was treated with normal saline and served as the control, the second group received the optimized formulation, and the third group received the commercial product. The tested formulations were applied twice a day for a period of 3 days. Quantification of 5 inflammation signs which were itching, erythema, papule, flakiness, and dryness were used in this study to determine the degree of skin sensitivity. Each parameter was assigned a score from 0 to 3, where 0 represents no sign of inflammation, while 4, represents the severe signs of inflammation (Mahtab et al., ). 2.2.7.2.3. Stability studies The physical stability of the optimum nanoemulsion formulation was tested following a previously reported method with a slight modification (Shafiq-un-Nabi et al., ). The optimized formulation was subjected to three freeze-thaw cycles between −20 °C and +25 °C, stored at each temperature for 48 h, and finally examined for their emulsification ability, precipitation, pH, and globule size.
Experimental design and optimization of self-nanoemulsion formulations Two response surface Box–Behnken designs were adopted during the current investigation using Design-Expert ® software v. 12.0.6.0 (Stat-Ease, Inc., Minneapolis, MN, USA). The first design was developed to investigate the effects of independent variables (i.e. (A) clove oil %, (B) the Smix ratio of surfactant to co-surfactant, and (C) amount of water added on the globule size of plain self-nanoemulsion formulations (SNEDDS). The second design was created to explore the effect of the independent variables, including (A) clove oil %, (B) the amount of NF in milligrams, and (C) the Smix ratio of surfactant to co-surfactant in the prepared medicated nanoemulsions. The investigated dependent responses were the globule size of the prepared SNEDDS (Y1), ex vivo % of naftifine permeated through rat skin (Y2), the zone of inhibition against Trichophyton rubrum (Y3), and interleukin-31 level (Y4). The independent factors and determined responses are shown in .
Self-nanoemulsion preparation The development of NF-loaded nanoemulsions was performed in two steps. The first step included the formation of the plain SNEDDS, in which 10–20% clove oil concentrations were mixed with 40–60% surfactant and cosurfactant mixture (Smix) and 20–50% water. The surfactant and co-surfactant were mixed in three different ratios (1:1, 2:1, and 3:1), according to the first design. In the second step, clove oil concentrations of 10, 13.5, or 17% were mixed with 90, 86.5, or 83% Smix, respectively. The active ingredient, NF, was mixed with the plain SNEDDS with the aid of sonication in concentrations of 10, 20, or 30 mg/g according to the second design, as is shown in .
Globule size measurements The droplet size of either plain CO-SNEDDS or NF-CO SNEDDS was measured by diluting 200 μL SNEDDS with 800 μL purified water in a volumetric flask. The diluted samples were vigorously agitated, and then 200 μL was withdrawn and used to measure the droplet size on a Microtrac ® zeta track particle size analyzer (Microtrac, Inc., Montgomeryville, PA, USA) (Hosny et al., ).
Ex vivo permeation study The ex vivo permeation study was performed following a previously published method (Salem et al., ). The NF permeation across rat skin from nanoemulsions was assessed using Franz cells with a diffusion area of 5 cm 2 , according to a previously reported method. 8-weeks-old Wistar albino rats, weighing 150–200 g, were used in this study. Following animal sacrifice, shaved abdominal skin was excised, separated from underlying connective tissues using a scalpel, and finally used as a model permeation membrane. The obtained membranes were mounted between the donor and receptor compartments of Franz diffusion cells so that the stratum corneum was facing the donor, while the dermal skin side was facing the receptor compartment. Nanoemulsions (equivalent to 20 mg NF) were placed in the donor compartment of the Franz cells, and the receptor compartment was filled with 12 mL phosphate buffer saline (PBS, pH 7.4). The medium was stirred at 100 rpm, and the temperature was kept at 37 ± 0.5 °C during the experiment. 1-mL samples were withdrawn at fixed time intervals of 0.5, 1, 2, 4, 8, 12, and 24 h, then the receptor media was replenished with equal volumes of fresh media to maintain sink conditions. Collected samples were then analyzed for their NF content using high-performance liquid chromatography (HPLC) in which a mixture of acetonitrile, tetrahydrofuran, and tetramethyl-ammonium hydroxide with a ratio of 62:10:28, respectively (pH 7.8), was used as the mobile phase that was pumped at a fixed flow rate of 1.2 mL/min. The measurements were performed at a maximum wavelength of 240 nm using an Agilent 1260 Infinity Diode array detector VL (G131SD) and injection volume of 100 μL. Limit of detection of and linear range naftifine were 0.0201 μg/mL and 0.080 μg/mL respectively. The peak areas of Naftifine HCl were plotted against Naftifine HCl concentrations. The least square line regression analysis was used to determine the slope, Y-intercept, and the correlation coefficient of the standard plots.
Antifungal activity evaluation The antifungal activity of NF-CO-SENDDs against Trichophyton rubrum was assessed using a slightly modified disk diffusion susceptibility method (Mahtab et al., ). According to the method recommended by the Clinical and Laboratory Standards Institute, a suspension of Trichophyton rubrum was made to 0.5 McFarland turbidity standard (106 CFU/mL) by employing a hemocytometer. An inoculum of 1 mL, from a suspension of 104 CFU/mL, was spread on the surface of Mueller–Hinton agar plates using sterile loops. Disks of 10-mm diameters containing NF-CO-SENDDs were then placed onto the inoculated agar plates using sterile forceps. The prepared plates were incubated at 37 °C for 24 h, and growth inhibition zone diameters (where fungal growth markedly decreased) were measured for each NF-CO-SENDDs formulation.
Interleukin-31 measurements Male Wistar albino rats averagely weighing 250 ± 10 gm were used in the study. 150 mg of each formulation containing 3.5 mg of NF were applied topically to the saved animals’ skin. Animals received treatment once daily for 14 days. At the end of the experiment, blood samples of 1 mL were withdrawn from animals’ tail vein and placed in edita tubes, then the samples were centrifuged at 4000 rpm for 10 min, supernatant (i.e. serum) was removed and kept at −20 °C for further investigations. Concentrations of IL‐31 serum levels were determined using an enzyme‐linked immunosorbent assay (ELISA) technique. Rat IL‐31 Quantikine M‐assay (R&D, Minneapolis, MN, USA, Catalog no. M1300C) was carried out according to the manufacturer’s instructions. A monoclonal antibody specific for rat’s IL-31 was pre-coated onto a microplate, and goat‐anti‐rat IgG (Jackson Immuno, Catalog no. 115‐035‐166) was employed as the detection antibody. A microtiter plate reader was used for optical density determination at 450 nm, and concentrations of IL-31serum levels were expressed in pg/mL (Grimstad et al., ).
Optimization and evaluation of the selected formulation 2.2.7.1. Experimental model evaluation Degrees of freedom, F -ratio, and p -value for all factors and their interactions were determined to analyze the variance of calculated models for the measured responses and select the model that best fit the obtained data. Specifically, p -values less than .05 indicate the significance of the model. Moreover, the determination coefficients, predicted ( R 2 ), adjusted ( R 2 ), and CV% values were used to determine the model fitness. In the current investigation, the criteria used for identifying the optimized medicated NF-CO SENDDs included minimum globule size and IL-31 levels and maximum ex vivo % naftifine and zone of inhibition against Trichophyton rubrum . 2.2.7.2. Characterization of the optimized NF-loaded nanoemulsion formulation The optimum formulation was fabricated and characterized by determining its globule size, IL-31 levels, ex vivo % naftifine permeated across skin, and zone of inhibition against Trichophyton rubrum and compared against that of commercial cream. For further evaluation, NE was subjected to skin sensitivity and stability studies. The ex vivo diffusion study for optimum formulation was performed as previously mentioned, with additional calculation of the diffusion coefficient (D), permeability coefficient (P), steady-state transdermal flux (Jss), and enhancement ratio (ER). 2.2.7.2.1. Zeta potential (ZP) measurements An electrophoretic mobility study was employed to assign the surface charges of the optimum formulation using a Malvern Zeta sizer (Malvern instruments, Malvern, UK) at a temperature of 25 °C and a fixed angle of 90° (Abdelbary et al., ). 2.2.7.2.2. Skin sensitivity test The test rats were held in laboratory cages and allowed free access to water and food. Animals were acclimatized for a period of 14 days prior to experimentation under standard conditions of 55 ± 5% relative humidity, 25 ± 1 °C temperature, and a 12-h dark and 12-h light cycle. Rats were handled and tended to according to the Animal Ethics Committee guidelines, Beni-Suef Clinical Laboratory Center, Beni-Suef, Egypt. Researchers followed the guidelines set forth in the Declaration of Helsinki and its “Guiding Principles in the Care and Use of Animals” (NIH Publication No. 85-23, 1985 revision), complying to ethical approval of the protocol before starting the experiment (Approval No. M12-11-2020). The dorsal skin of rats (4 × 4 cm 2 ) was carefully shaved with an electric clipper so as not to cause any damage. Three animal groups, each composed of 6 rats, were employed in the study. The first group was treated with normal saline and served as the control, the second group received the optimized formulation, and the third group received the commercial product. The tested formulations were applied twice a day for a period of 3 days. Quantification of 5 inflammation signs which were itching, erythema, papule, flakiness, and dryness were used in this study to determine the degree of skin sensitivity. Each parameter was assigned a score from 0 to 3, where 0 represents no sign of inflammation, while 4, represents the severe signs of inflammation (Mahtab et al., ). 2.2.7.2.3. Stability studies The physical stability of the optimum nanoemulsion formulation was tested following a previously reported method with a slight modification (Shafiq-un-Nabi et al., ). The optimized formulation was subjected to three freeze-thaw cycles between −20 °C and +25 °C, stored at each temperature for 48 h, and finally examined for their emulsification ability, precipitation, pH, and globule size.
Experimental model evaluation Degrees of freedom, F -ratio, and p -value for all factors and their interactions were determined to analyze the variance of calculated models for the measured responses and select the model that best fit the obtained data. Specifically, p -values less than .05 indicate the significance of the model. Moreover, the determination coefficients, predicted ( R 2 ), adjusted ( R 2 ), and CV% values were used to determine the model fitness. In the current investigation, the criteria used for identifying the optimized medicated NF-CO SENDDs included minimum globule size and IL-31 levels and maximum ex vivo % naftifine and zone of inhibition against Trichophyton rubrum .
Characterization of the optimized NF-loaded nanoemulsion formulation The optimum formulation was fabricated and characterized by determining its globule size, IL-31 levels, ex vivo % naftifine permeated across skin, and zone of inhibition against Trichophyton rubrum and compared against that of commercial cream. For further evaluation, NE was subjected to skin sensitivity and stability studies. The ex vivo diffusion study for optimum formulation was performed as previously mentioned, with additional calculation of the diffusion coefficient (D), permeability coefficient (P), steady-state transdermal flux (Jss), and enhancement ratio (ER). 2.2.7.2.1. Zeta potential (ZP) measurements An electrophoretic mobility study was employed to assign the surface charges of the optimum formulation using a Malvern Zeta sizer (Malvern instruments, Malvern, UK) at a temperature of 25 °C and a fixed angle of 90° (Abdelbary et al., ). 2.2.7.2.2. Skin sensitivity test The test rats were held in laboratory cages and allowed free access to water and food. Animals were acclimatized for a period of 14 days prior to experimentation under standard conditions of 55 ± 5% relative humidity, 25 ± 1 °C temperature, and a 12-h dark and 12-h light cycle. Rats were handled and tended to according to the Animal Ethics Committee guidelines, Beni-Suef Clinical Laboratory Center, Beni-Suef, Egypt. Researchers followed the guidelines set forth in the Declaration of Helsinki and its “Guiding Principles in the Care and Use of Animals” (NIH Publication No. 85-23, 1985 revision), complying to ethical approval of the protocol before starting the experiment (Approval No. M12-11-2020). The dorsal skin of rats (4 × 4 cm 2 ) was carefully shaved with an electric clipper so as not to cause any damage. Three animal groups, each composed of 6 rats, were employed in the study. The first group was treated with normal saline and served as the control, the second group received the optimized formulation, and the third group received the commercial product. The tested formulations were applied twice a day for a period of 3 days. Quantification of 5 inflammation signs which were itching, erythema, papule, flakiness, and dryness were used in this study to determine the degree of skin sensitivity. Each parameter was assigned a score from 0 to 3, where 0 represents no sign of inflammation, while 4, represents the severe signs of inflammation (Mahtab et al., ). 2.2.7.2.3. Stability studies The physical stability of the optimum nanoemulsion formulation was tested following a previously reported method with a slight modification (Shafiq-un-Nabi et al., ). The optimized formulation was subjected to three freeze-thaw cycles between −20 °C and +25 °C, stored at each temperature for 48 h, and finally examined for their emulsification ability, precipitation, pH, and globule size.
Zeta potential (ZP) measurements An electrophoretic mobility study was employed to assign the surface charges of the optimum formulation using a Malvern Zeta sizer (Malvern instruments, Malvern, UK) at a temperature of 25 °C and a fixed angle of 90° (Abdelbary et al., ).
Skin sensitivity test The test rats were held in laboratory cages and allowed free access to water and food. Animals were acclimatized for a period of 14 days prior to experimentation under standard conditions of 55 ± 5% relative humidity, 25 ± 1 °C temperature, and a 12-h dark and 12-h light cycle. Rats were handled and tended to according to the Animal Ethics Committee guidelines, Beni-Suef Clinical Laboratory Center, Beni-Suef, Egypt. Researchers followed the guidelines set forth in the Declaration of Helsinki and its “Guiding Principles in the Care and Use of Animals” (NIH Publication No. 85-23, 1985 revision), complying to ethical approval of the protocol before starting the experiment (Approval No. M12-11-2020). The dorsal skin of rats (4 × 4 cm 2 ) was carefully shaved with an electric clipper so as not to cause any damage. Three animal groups, each composed of 6 rats, were employed in the study. The first group was treated with normal saline and served as the control, the second group received the optimized formulation, and the third group received the commercial product. The tested formulations were applied twice a day for a period of 3 days. Quantification of 5 inflammation signs which were itching, erythema, papule, flakiness, and dryness were used in this study to determine the degree of skin sensitivity. Each parameter was assigned a score from 0 to 3, where 0 represents no sign of inflammation, while 4, represents the severe signs of inflammation (Mahtab et al., ).
Stability studies The physical stability of the optimum nanoemulsion formulation was tested following a previously reported method with a slight modification (Shafiq-un-Nabi et al., ). The optimized formulation was subjected to three freeze-thaw cycles between −20 °C and +25 °C, stored at each temperature for 48 h, and finally examined for their emulsification ability, precipitation, pH, and globule size.
Results and discussion Dermatological and topical dosage forms are usually designed to easily deliver active agents across certain skin areas. Concerning the topical route, poor drug permeability contributes to prolonged treatment, hence leading to low patient adherence and high cost of treatment. Nano-sized drug delivery systems are usually used to overcome such limitations. These delivery systems permit high drug concentrations to penetrate the skin through an intercellular pathway (Singh & Ahuja, ) and depot drugs in the epidermis and stratum corneum. Nanoemulsions are one of the most extensively-used topically applied drug delivery systems to treat skin conditions, such as fungal infections. 3.1. Box–Behnken design analysis The two experimental designs were created using Design-Expert software (12.0.6.0, Stat-Ease, Inc., Minneapolis, MN, USA). The first design was used to determine the effect of each independent variable and its interactions on the globular size of plain NE and allocate the optimum oil amount to be used in drug-loaded NE. The second design was performed to study the effect of each independent variable and its influence on the globular size of medicated NE, ex vivo % of naftifine permeated, zone of inhibition against Trichophyton rubrum , and interleukin-31 level. Analysis of variance (ANOVA) and F -values at a 95% confidence interval ( p < .05) were employed to statistically test the validation of the selected model. Checkpoint analysis was used to check the accuracy and validity of the obtained mathematical models in terms of the predictions of dependent responses. The main effect diagrams, 3D-surface response, contour, and overlay plots of the desired responses relative to the optimal region in which the optimal nanoemulsions can be obtained were developed . Finally, desirability values were determined, and the predicted and actual parameters were compared to evaluate the formulation. 3.2. Formulation and characterization of plain nanoemulsion 3.2.1. Nanoemulsion droplet size and polydispersity index (PDI) Concerning topical delivery, NE physicochemical properties predominantly indicate the effectiveness of a developed formulation (Singh et al., ). Globule size is the most important NE character as it could differentiate the developed emulsions into micro-emulsions or nanoemulsions, whereby the formation of NE with the lowest globule size is highly desired. As shown in , the droplet size of the currently developed plain NE was in the range of 85–195 nm with an acceptable PDI between 0.1 and 0.35, which indicates fair homogeneity, adequate size distribution, and acceptable NE stability. The quadratic model of polynomial analysis was obtained to analyze the droplet size values and further explore the significant effect of (A) clove oil %, (B) Smix ratio, and (C) water % on the NE globule size. The suggested quadratic model acquired an adjusted R 2 of 0.9984, which was very close to the predicted R 2 of 0.9829. ANOVA analysis of the obtained data yielded the following equation: Globule size = + 1141.45 A + 152.47 B + 144.91 C − 1379.88 AB − 1338.49 AC − 261.02 BC − 2787.09 A ² BC + 4130.83 A B ² C + 2540.86 ABC ² As could be seen from the equation, all investigated variables had a significantly positive effect on NE droplet size with a p -value <.0001. However, the amount of oil was determined as the most pertinent parameter as it exhibited the largest coefficient (1141.5) compared to the Smix ratio (152.47) and water amount (144.91). In addition, the interaction between parameters involving (A) clove oil %, such as that with (AB) Smix ratio and (AC) water %, exhibited larger coefficient values (1379.88 and 1338.49, respectively) compared to the interaction of (BC), which exhibited a coefficient value of 261.02. The increase in globule size corresponding to increased clove oil amount could be explained by considering that an increase in oil amount would decrease the Smix ratio. Subsequently, this would decrease the capacity of the surfactant and co-surfactant to downsize the oil droplets; thus, larger oil globules would be obtained, which is similar to previously reported results (Cevc & Vierl, ; Okur Apaydin et al., ). Moreover, increasing the water amount would increase the volume of the aqueous phase and yield larger droplets. displays the contour, 3D-surface, and overlay plots that demonstrate the effect of the independent variables on plain NE droplet size. Contour and 3D-surface plots indicate that the globule size of plain NE mainly depends on the oil level in nanoemulsions, and the overlay plot reveals that the globule size was around 100 nm with a 10% oil concentration and was elevated to 143 nm when oil increased to 17%. Based on these results, the optimum range of clove oil that would yield a formulation with acceptable size was found between 10 and 17%; consequently, these oil levels were used to further prepare medicated NE in the second step of this research. 3.3. Formulation and characterization of medicated nanoemulsions 3.3.1. Nanoemulsion droplet size and polydispersity index (PDI) As shown in , globule size of the medicated NE ranged 119–310 nm with PDI values between 0.1 and 0.4, providing supportive evidence of good formulation stability, homogeneity, and size distribution. The obtained globule size data were then subjected to a quadratic model of polynomial analysis. The experimental design showed the investigated model’s efficiency to determine the significant effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio on medicated NE globule size. The chosen model achieved an adjusted R 2 of 0.9973 and predicted R 2 of 0.9913, as shown in . Data analysis by ANOVA resulted in the following equation: Globule size = + 171.99 + 36.44 A + 46.85 B + 4.14 C + 13.00 A B + 0.5000 A C − 7.50 BC + 6.94 A ² + 19.84 B ² − 0.8416 C ² From the above equation, it could be deduced that the (A) amount of oil and (B) amount of drug had a higher positive effect on NE globule size than (C) the Smix ratio, as (A) and (B) exhibited higher coefficient values (36.44 and 46.85, respectively) compared to (C) with a coefficient value of 4.14. The superior effect of oil and drug amounts on droplet size was further confirmed by the main effect diagram in , which revealed the high impact of changing the oil and drug amounts on droplet size. Furthermore, the previous equation showed that the interaction of clove oil and NF amount (AB) had the most significant effect on NE globule size compared to other interactions (i.e. AC and BC). Increasing the clove oil amount could have allowed a greater incorporation of the drug and, hence, result in droplets with larger diameter. Moreover, there was a corresponding decrease in the Smix ratio when the oil amount was increased, which led to the decreased ability of Smix to downsize the oil droplets and increased globule size. Comparatively, a higher NF amount might have caused swelling of the droplets and, thus, larger emulsion droplets. Similar results have been reported in the literature (Sakeena et al., ; Okur et al., ). illustrate the main effect diagrams, 3D surface response, and contour plots, which reveal the effect of the studied factors on medicated NE droplet size. 3.3.2. Ex vivo permeation study of naftifine loaded NE Ex vivo permeation studies usually effectively indicate the performance of a drug and its ability to overcome natural skin barriers like the stratum corneum (SC). The ex vivo % of naftifine permeated from drug loaded-NE formulations across rat skin fluctuated between 18–69%, as seen in . The collected data were used to prepare a quadratic model for polynomial analysis. The Box–Behnken design analysis demonstrates the effectiveness of the model to explore the effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio (C) on the % naftifine that permeated across the skin of rats. The suggested statistical model exhibited an adjusted and predicted R 2 of 0.9893 and 0.9714, respectively, which were obviously in close agreement, as shown in . The following equation was obtained after data analysis using ANOVA: E x vivo % naftifine permeated = + 63.41 + 5.68 A − 5.93 B − 3.35 C + 3.12 A B + 0.6250 A C − 0.6250 B C − 13.27 A ² − 4.79 B As indicated in the above equation, (A) clove oil amount had a significantly positive effect on % naftifine permeated, while (B) NF amount and (C) Smix ratio acquired a significantly negative effect on the same parameter. The increase in % NF permeated observed with increased clove oil amount might be attributed to the penetration enhancement characteristics of eugenol, the primary component of clove oil (Chaieb et al., ). It was previously reported that eugenol, like many other essential oil components, could interact and disrupt the barrier of SC without damaging the underlying tissues and, hence, promote drug penetration across the skin (Ahad et al., ). The inverse relationship between Y 2 and NF amount and Smix ratio could be ascribed to their effect on NE globule size, since it was observed that the increase in these two factors will result in larger droplets. Consequently, a smaller surface area will be available for drug permeation, leading to decreased % NF permeated across skin, which is similar to findings reported in literature (Hosny et al., ). Although clove oil amount displayed a positive effect on droplets size, its skin penetration enhancement ability overcome limitation of NF permeability. presents the main effect diagrams, 3D surface response, and contour plots, demonstrating the effect of the studied factors on % NF permeated across the skin. 3.3.3. Assessment of antifungal activity of NF-loaded nanoemulsions The antifungal activity of drug-loaded nanoemulsions was assessed against the dermatophytic fungus Trichophyton rubrum by measuring the inhibition zone of fungal growth in plates treated with NE formulations. As shown in , the diameter of the inhibition zone of Trichophyton rubrum equivocated between 5 and 24 mm. Then, based on the inhibition zones against Trichophyton rubrum , a linear model of polynomial equations was prepared to test the effect of the independent variables on the measured diameters of inhibition zones. The model’s predicted R 2 of 0.8777 was in a reasonable agreement with the adjusted R 2 of 0.9118, as presented in . Data analysis using ANOVA yielded the following equation: Zone of inhibition against Trichophyton rubrum = + 14.53 + 1.30 A + 4.46 B + 4.43 C This equation implies that all the used independent variables exerted a significantly positive effect on the inhibition zone against Trichophyton rubrum . In other words, increasing the amount of any of the three tested factors will increase the inhibition zone diameter; however, (B) NF amount and (C) Smix ratio showed a significant effect on the response ( p -value < .0001) compared to (A) clove oil % with a p -value <.02. The antifungal activity of clove oil against the tested fungus could be attributed to its eugenol content, which agrees with numerous other studies. As mentioned in literature, eugenol could induce leakage of potassium from fungal cells, thus inhibiting the uptake and use of energy by these cells, leading to envelop disruption, and finally inducing cell death (Chee & Lee, ). Moreover, the fungicidal effect of NF is thought to be conducted through the inhibition of fungal squalene epoxidase, inhibiting ergosterol biosynthesis (Monk & Brogden, ). The significant anti-fungal activity of NF against the tested fungus could be attributed to its high selectivity to ergosterol biosynthesis, unlike other anti-fungal drugs, such as azoles (Lee et al., ). The observed significant anti-fungal activity of the Smix could be ascribed to its cetylpyridinium chloride (CPC) content. Quaternary ammonium salts like CPC possess antimicrobial effects through various mechanisms (Sreenivasan et al., ), for instance, by disrupting cell membrane lipid bilayers and ultimately causing cellular content leakage., and finally cause cellular content leakage (Garcia-godoy, ). Moreover, exposure to CPC for longer periods could lead to additional destruction of intracellular materials, indicating autolysis (Evandro et al., ). displays the main effect diagrams, 3D surface response, and contour plots, which revealed the effect of the studied factors on the zone of inhibition against Trichophyton rubrum . 3.3.4. Interleukin-31 level measurements IL-31, a T-cell derived cytokine, may be involved in provoking some epithelial responses in atopic skin inflammation, such as redness, pain, and itching, that characterize some allergic reactions (Dillon et al., ). The obtained data of IL-31 serum levels were used to prepare a quadratic model for polynomial analysis following the Box–Behnken design in order to determine the impact of the studied factors on IL-31 serum levels. The model revealed a predicted R 2 of 0.9460, which was in reasonable accordance with the adjusted R 2 of 0.9840, as seen in . Data analysis by ANOVA produced the equation below: Interlukin − 31 Level = + 300.84 − 108.00 A + 187.85 B + 27.72 C − 91.25 A B + 5.00 A C + 3.75 B C + 41.29 A ² + 28.91 B ² + 4.17 C ² The measured IL-31 serum levels fluctuated between 100 and 800 pg/mL in the test rats, as presented in . From the above equation, it was noticed that (A) clove oil % presented a significantly negative effect on IL-31 serum levels ( p -value < .0001), while (B) NF amount and (C) Smix ratio exhibited a significantly positive effect, p -values of <.0001 and <.0073, respectively. The ability of clove oil to reduce IL-31 levels and, hence, improve the inflammatory side effects associated with NF could also be attributed to its eugenol content. Further, eugenol is known to inhibit the nuclear factor-kappa B (NF-κB) signaling pathway, which is a crucial step in preventing the transcription of cytokines and diminishing inflammation signs (Zhang et al., ). Moreover, compounds like eugenol that display antioxidant activity are able to modify oxidative stress and might indirectly participate in decreasing the production of inflammatory mediators. Therefore, eugenol is considered to be more effective in decreasing inflammation through its combined anti-inflammatory and antioxidant actions (Barboza et al., ). The positive effect of NF and CPC on IL-31 levels might be associated with mild inflammatory side effects in patients, which might affect their adherence to such drugs to some extent. displays the main effect diagrams, 3D surface response and contour plots, revealing the effects of the studied factors on IL-31 serum levels. 3.4. Optimization of NF-loaded nanoemulsion formulations From the previous data, an optimum NE formulation was developed using the most suitable properties. Design Expert ® indicated several solutions that could be used as various combinations of the independent variables’ levels. The optimum formulation was found to be composed of 14% clove oil and 12.5 mg NF with a Smix ratio of 3:1. The formula resulted in a globule size of 161 nm, ex vivo % naftifine permeated of 64%, IL-31 value of 180 pg/mL, and zone of inhibition against Trichophyton rubrum of 16 mm with 0.8030 desirability. It was noteworthy that optimum formulation had a much smaller zone of inhibition against Trichophyton rubrum (16 mm) compared to that of commercial cream (26 mm). presents the desirability plot, and indicates that the observed and predicted values of the optimum formulation parameters were in close agreement with no major differences ( p > .05), proving the model’s good predictability and validity. 3.5. Check point analysis Expected and adjusted R 2 values of the measured responses were in close agreement, validating the significant prediction capability of the design. In addition, experimental/predicted ratios with a percentage error below 10% and acceptable residuals were observed between the experimental and predicated responses, showing the lack of curvature in the responses and validity of the model. The results are presented in , and illustrates the overlay plot for the optimal region. 3.6. Zeta potential measurements of optimum formulation The optimized NF loaded nanoemulsion formulation acquired a ZP value of 28.31 ± 1.37 mV, further verifying the good stability of the developed formulation due to considerable repulsion between globules as predicted from such a large value. Furthermore, such a positive value will help in enhancing retention of NF in the skin and its effect through binding with the negatively charged phospholipid moieties of the skin. Notably, the observed large + ve ZP value might be ascribed to the use of cetylpyridinium chloride as a surfactant, which has a high positive charge. 3.7. Ex vivo permeation study of optimum formulation The optimized nanoemulsion formulation exhibited better skin permeation parameters compared to a commercial product. As seen in , the cumulative amount of permeated NF, steady state flux, permeability, and diffusion coefficients were improved by 2-, 3-, 5.75-, and 2.74-fold, respectively, in the optimum formulation compared to the commercial cream. Such enhancement in NF permeation in the case of nanoemulsion formulation could be due the NE components. As previously discussed, the main component of clove oil, eugenol, plays a pivotal role in improving skin penetration due to its ability to cause some disruption in the SC layer and deactivate its barrier properties. 3.8. Skin sensitivity test As seen in , the developed optimum NF-CO-SENDDs formulation was tolerated much better by rat skin than the commercial product. The reason behind such compatibility of NE formulation with the skin might be attributed to its clove oil content, which provides a good anti-inflammatory effect, as previously reported. These results are in good accordance with previously discussed results concerning IL-31 levels. 3.9. Stability study After storing the optimized formulation for 48 h subjected to three freeze-thaw cycles between −20 °C and +25 °C, no major differences were observed from the freshly prepared formula, as observed in . Such results confirm the adequate stability of the developed optimum NF-CO-SENDD, which can thus be properly used and stored.
Box–Behnken design analysis The two experimental designs were created using Design-Expert software (12.0.6.0, Stat-Ease, Inc., Minneapolis, MN, USA). The first design was used to determine the effect of each independent variable and its interactions on the globular size of plain NE and allocate the optimum oil amount to be used in drug-loaded NE. The second design was performed to study the effect of each independent variable and its influence on the globular size of medicated NE, ex vivo % of naftifine permeated, zone of inhibition against Trichophyton rubrum , and interleukin-31 level. Analysis of variance (ANOVA) and F -values at a 95% confidence interval ( p < .05) were employed to statistically test the validation of the selected model. Checkpoint analysis was used to check the accuracy and validity of the obtained mathematical models in terms of the predictions of dependent responses. The main effect diagrams, 3D-surface response, contour, and overlay plots of the desired responses relative to the optimal region in which the optimal nanoemulsions can be obtained were developed . Finally, desirability values were determined, and the predicted and actual parameters were compared to evaluate the formulation.
Formulation and characterization of plain nanoemulsion 3.2.1. Nanoemulsion droplet size and polydispersity index (PDI) Concerning topical delivery, NE physicochemical properties predominantly indicate the effectiveness of a developed formulation (Singh et al., ). Globule size is the most important NE character as it could differentiate the developed emulsions into micro-emulsions or nanoemulsions, whereby the formation of NE with the lowest globule size is highly desired. As shown in , the droplet size of the currently developed plain NE was in the range of 85–195 nm with an acceptable PDI between 0.1 and 0.35, which indicates fair homogeneity, adequate size distribution, and acceptable NE stability. The quadratic model of polynomial analysis was obtained to analyze the droplet size values and further explore the significant effect of (A) clove oil %, (B) Smix ratio, and (C) water % on the NE globule size. The suggested quadratic model acquired an adjusted R 2 of 0.9984, which was very close to the predicted R 2 of 0.9829. ANOVA analysis of the obtained data yielded the following equation: Globule size = + 1141.45 A + 152.47 B + 144.91 C − 1379.88 AB − 1338.49 AC − 261.02 BC − 2787.09 A ² BC + 4130.83 A B ² C + 2540.86 ABC ² As could be seen from the equation, all investigated variables had a significantly positive effect on NE droplet size with a p -value <.0001. However, the amount of oil was determined as the most pertinent parameter as it exhibited the largest coefficient (1141.5) compared to the Smix ratio (152.47) and water amount (144.91). In addition, the interaction between parameters involving (A) clove oil %, such as that with (AB) Smix ratio and (AC) water %, exhibited larger coefficient values (1379.88 and 1338.49, respectively) compared to the interaction of (BC), which exhibited a coefficient value of 261.02. The increase in globule size corresponding to increased clove oil amount could be explained by considering that an increase in oil amount would decrease the Smix ratio. Subsequently, this would decrease the capacity of the surfactant and co-surfactant to downsize the oil droplets; thus, larger oil globules would be obtained, which is similar to previously reported results (Cevc & Vierl, ; Okur Apaydin et al., ). Moreover, increasing the water amount would increase the volume of the aqueous phase and yield larger droplets. displays the contour, 3D-surface, and overlay plots that demonstrate the effect of the independent variables on plain NE droplet size. Contour and 3D-surface plots indicate that the globule size of plain NE mainly depends on the oil level in nanoemulsions, and the overlay plot reveals that the globule size was around 100 nm with a 10% oil concentration and was elevated to 143 nm when oil increased to 17%. Based on these results, the optimum range of clove oil that would yield a formulation with acceptable size was found between 10 and 17%; consequently, these oil levels were used to further prepare medicated NE in the second step of this research.
Nanoemulsion droplet size and polydispersity index (PDI) Concerning topical delivery, NE physicochemical properties predominantly indicate the effectiveness of a developed formulation (Singh et al., ). Globule size is the most important NE character as it could differentiate the developed emulsions into micro-emulsions or nanoemulsions, whereby the formation of NE with the lowest globule size is highly desired. As shown in , the droplet size of the currently developed plain NE was in the range of 85–195 nm with an acceptable PDI between 0.1 and 0.35, which indicates fair homogeneity, adequate size distribution, and acceptable NE stability. The quadratic model of polynomial analysis was obtained to analyze the droplet size values and further explore the significant effect of (A) clove oil %, (B) Smix ratio, and (C) water % on the NE globule size. The suggested quadratic model acquired an adjusted R 2 of 0.9984, which was very close to the predicted R 2 of 0.9829. ANOVA analysis of the obtained data yielded the following equation: Globule size = + 1141.45 A + 152.47 B + 144.91 C − 1379.88 AB − 1338.49 AC − 261.02 BC − 2787.09 A ² BC + 4130.83 A B ² C + 2540.86 ABC ² As could be seen from the equation, all investigated variables had a significantly positive effect on NE droplet size with a p -value <.0001. However, the amount of oil was determined as the most pertinent parameter as it exhibited the largest coefficient (1141.5) compared to the Smix ratio (152.47) and water amount (144.91). In addition, the interaction between parameters involving (A) clove oil %, such as that with (AB) Smix ratio and (AC) water %, exhibited larger coefficient values (1379.88 and 1338.49, respectively) compared to the interaction of (BC), which exhibited a coefficient value of 261.02. The increase in globule size corresponding to increased clove oil amount could be explained by considering that an increase in oil amount would decrease the Smix ratio. Subsequently, this would decrease the capacity of the surfactant and co-surfactant to downsize the oil droplets; thus, larger oil globules would be obtained, which is similar to previously reported results (Cevc & Vierl, ; Okur Apaydin et al., ). Moreover, increasing the water amount would increase the volume of the aqueous phase and yield larger droplets. displays the contour, 3D-surface, and overlay plots that demonstrate the effect of the independent variables on plain NE droplet size. Contour and 3D-surface plots indicate that the globule size of plain NE mainly depends on the oil level in nanoemulsions, and the overlay plot reveals that the globule size was around 100 nm with a 10% oil concentration and was elevated to 143 nm when oil increased to 17%. Based on these results, the optimum range of clove oil that would yield a formulation with acceptable size was found between 10 and 17%; consequently, these oil levels were used to further prepare medicated NE in the second step of this research.
Formulation and characterization of medicated nanoemulsions 3.3.1. Nanoemulsion droplet size and polydispersity index (PDI) As shown in , globule size of the medicated NE ranged 119–310 nm with PDI values between 0.1 and 0.4, providing supportive evidence of good formulation stability, homogeneity, and size distribution. The obtained globule size data were then subjected to a quadratic model of polynomial analysis. The experimental design showed the investigated model’s efficiency to determine the significant effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio on medicated NE globule size. The chosen model achieved an adjusted R 2 of 0.9973 and predicted R 2 of 0.9913, as shown in . Data analysis by ANOVA resulted in the following equation: Globule size = + 171.99 + 36.44 A + 46.85 B + 4.14 C + 13.00 A B + 0.5000 A C − 7.50 BC + 6.94 A ² + 19.84 B ² − 0.8416 C ² From the above equation, it could be deduced that the (A) amount of oil and (B) amount of drug had a higher positive effect on NE globule size than (C) the Smix ratio, as (A) and (B) exhibited higher coefficient values (36.44 and 46.85, respectively) compared to (C) with a coefficient value of 4.14. The superior effect of oil and drug amounts on droplet size was further confirmed by the main effect diagram in , which revealed the high impact of changing the oil and drug amounts on droplet size. Furthermore, the previous equation showed that the interaction of clove oil and NF amount (AB) had the most significant effect on NE globule size compared to other interactions (i.e. AC and BC). Increasing the clove oil amount could have allowed a greater incorporation of the drug and, hence, result in droplets with larger diameter. Moreover, there was a corresponding decrease in the Smix ratio when the oil amount was increased, which led to the decreased ability of Smix to downsize the oil droplets and increased globule size. Comparatively, a higher NF amount might have caused swelling of the droplets and, thus, larger emulsion droplets. Similar results have been reported in the literature (Sakeena et al., ; Okur et al., ). illustrate the main effect diagrams, 3D surface response, and contour plots, which reveal the effect of the studied factors on medicated NE droplet size. 3.3.2. Ex vivo permeation study of naftifine loaded NE Ex vivo permeation studies usually effectively indicate the performance of a drug and its ability to overcome natural skin barriers like the stratum corneum (SC). The ex vivo % of naftifine permeated from drug loaded-NE formulations across rat skin fluctuated between 18–69%, as seen in . The collected data were used to prepare a quadratic model for polynomial analysis. The Box–Behnken design analysis demonstrates the effectiveness of the model to explore the effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio (C) on the % naftifine that permeated across the skin of rats. The suggested statistical model exhibited an adjusted and predicted R 2 of 0.9893 and 0.9714, respectively, which were obviously in close agreement, as shown in . The following equation was obtained after data analysis using ANOVA: E x vivo % naftifine permeated = + 63.41 + 5.68 A − 5.93 B − 3.35 C + 3.12 A B + 0.6250 A C − 0.6250 B C − 13.27 A ² − 4.79 B As indicated in the above equation, (A) clove oil amount had a significantly positive effect on % naftifine permeated, while (B) NF amount and (C) Smix ratio acquired a significantly negative effect on the same parameter. The increase in % NF permeated observed with increased clove oil amount might be attributed to the penetration enhancement characteristics of eugenol, the primary component of clove oil (Chaieb et al., ). It was previously reported that eugenol, like many other essential oil components, could interact and disrupt the barrier of SC without damaging the underlying tissues and, hence, promote drug penetration across the skin (Ahad et al., ). The inverse relationship between Y 2 and NF amount and Smix ratio could be ascribed to their effect on NE globule size, since it was observed that the increase in these two factors will result in larger droplets. Consequently, a smaller surface area will be available for drug permeation, leading to decreased % NF permeated across skin, which is similar to findings reported in literature (Hosny et al., ). Although clove oil amount displayed a positive effect on droplets size, its skin penetration enhancement ability overcome limitation of NF permeability. presents the main effect diagrams, 3D surface response, and contour plots, demonstrating the effect of the studied factors on % NF permeated across the skin. 3.3.3. Assessment of antifungal activity of NF-loaded nanoemulsions The antifungal activity of drug-loaded nanoemulsions was assessed against the dermatophytic fungus Trichophyton rubrum by measuring the inhibition zone of fungal growth in plates treated with NE formulations. As shown in , the diameter of the inhibition zone of Trichophyton rubrum equivocated between 5 and 24 mm. Then, based on the inhibition zones against Trichophyton rubrum , a linear model of polynomial equations was prepared to test the effect of the independent variables on the measured diameters of inhibition zones. The model’s predicted R 2 of 0.8777 was in a reasonable agreement with the adjusted R 2 of 0.9118, as presented in . Data analysis using ANOVA yielded the following equation: Zone of inhibition against Trichophyton rubrum = + 14.53 + 1.30 A + 4.46 B + 4.43 C This equation implies that all the used independent variables exerted a significantly positive effect on the inhibition zone against Trichophyton rubrum . In other words, increasing the amount of any of the three tested factors will increase the inhibition zone diameter; however, (B) NF amount and (C) Smix ratio showed a significant effect on the response ( p -value < .0001) compared to (A) clove oil % with a p -value <.02. The antifungal activity of clove oil against the tested fungus could be attributed to its eugenol content, which agrees with numerous other studies. As mentioned in literature, eugenol could induce leakage of potassium from fungal cells, thus inhibiting the uptake and use of energy by these cells, leading to envelop disruption, and finally inducing cell death (Chee & Lee, ). Moreover, the fungicidal effect of NF is thought to be conducted through the inhibition of fungal squalene epoxidase, inhibiting ergosterol biosynthesis (Monk & Brogden, ). The significant anti-fungal activity of NF against the tested fungus could be attributed to its high selectivity to ergosterol biosynthesis, unlike other anti-fungal drugs, such as azoles (Lee et al., ). The observed significant anti-fungal activity of the Smix could be ascribed to its cetylpyridinium chloride (CPC) content. Quaternary ammonium salts like CPC possess antimicrobial effects through various mechanisms (Sreenivasan et al., ), for instance, by disrupting cell membrane lipid bilayers and ultimately causing cellular content leakage., and finally cause cellular content leakage (Garcia-godoy, ). Moreover, exposure to CPC for longer periods could lead to additional destruction of intracellular materials, indicating autolysis (Evandro et al., ). displays the main effect diagrams, 3D surface response, and contour plots, which revealed the effect of the studied factors on the zone of inhibition against Trichophyton rubrum . 3.3.4. Interleukin-31 level measurements IL-31, a T-cell derived cytokine, may be involved in provoking some epithelial responses in atopic skin inflammation, such as redness, pain, and itching, that characterize some allergic reactions (Dillon et al., ). The obtained data of IL-31 serum levels were used to prepare a quadratic model for polynomial analysis following the Box–Behnken design in order to determine the impact of the studied factors on IL-31 serum levels. The model revealed a predicted R 2 of 0.9460, which was in reasonable accordance with the adjusted R 2 of 0.9840, as seen in . Data analysis by ANOVA produced the equation below: Interlukin − 31 Level = + 300.84 − 108.00 A + 187.85 B + 27.72 C − 91.25 A B + 5.00 A C + 3.75 B C + 41.29 A ² + 28.91 B ² + 4.17 C ² The measured IL-31 serum levels fluctuated between 100 and 800 pg/mL in the test rats, as presented in . From the above equation, it was noticed that (A) clove oil % presented a significantly negative effect on IL-31 serum levels ( p -value < .0001), while (B) NF amount and (C) Smix ratio exhibited a significantly positive effect, p -values of <.0001 and <.0073, respectively. The ability of clove oil to reduce IL-31 levels and, hence, improve the inflammatory side effects associated with NF could also be attributed to its eugenol content. Further, eugenol is known to inhibit the nuclear factor-kappa B (NF-κB) signaling pathway, which is a crucial step in preventing the transcription of cytokines and diminishing inflammation signs (Zhang et al., ). Moreover, compounds like eugenol that display antioxidant activity are able to modify oxidative stress and might indirectly participate in decreasing the production of inflammatory mediators. Therefore, eugenol is considered to be more effective in decreasing inflammation through its combined anti-inflammatory and antioxidant actions (Barboza et al., ). The positive effect of NF and CPC on IL-31 levels might be associated with mild inflammatory side effects in patients, which might affect their adherence to such drugs to some extent. displays the main effect diagrams, 3D surface response and contour plots, revealing the effects of the studied factors on IL-31 serum levels.
Nanoemulsion droplet size and polydispersity index (PDI) As shown in , globule size of the medicated NE ranged 119–310 nm with PDI values between 0.1 and 0.4, providing supportive evidence of good formulation stability, homogeneity, and size distribution. The obtained globule size data were then subjected to a quadratic model of polynomial analysis. The experimental design showed the investigated model’s efficiency to determine the significant effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio on medicated NE globule size. The chosen model achieved an adjusted R 2 of 0.9973 and predicted R 2 of 0.9913, as shown in . Data analysis by ANOVA resulted in the following equation: Globule size = + 171.99 + 36.44 A + 46.85 B + 4.14 C + 13.00 A B + 0.5000 A C − 7.50 BC + 6.94 A ² + 19.84 B ² − 0.8416 C ² From the above equation, it could be deduced that the (A) amount of oil and (B) amount of drug had a higher positive effect on NE globule size than (C) the Smix ratio, as (A) and (B) exhibited higher coefficient values (36.44 and 46.85, respectively) compared to (C) with a coefficient value of 4.14. The superior effect of oil and drug amounts on droplet size was further confirmed by the main effect diagram in , which revealed the high impact of changing the oil and drug amounts on droplet size. Furthermore, the previous equation showed that the interaction of clove oil and NF amount (AB) had the most significant effect on NE globule size compared to other interactions (i.e. AC and BC). Increasing the clove oil amount could have allowed a greater incorporation of the drug and, hence, result in droplets with larger diameter. Moreover, there was a corresponding decrease in the Smix ratio when the oil amount was increased, which led to the decreased ability of Smix to downsize the oil droplets and increased globule size. Comparatively, a higher NF amount might have caused swelling of the droplets and, thus, larger emulsion droplets. Similar results have been reported in the literature (Sakeena et al., ; Okur et al., ). illustrate the main effect diagrams, 3D surface response, and contour plots, which reveal the effect of the studied factors on medicated NE droplet size.
Ex vivo permeation study of naftifine loaded NE Ex vivo permeation studies usually effectively indicate the performance of a drug and its ability to overcome natural skin barriers like the stratum corneum (SC). The ex vivo % of naftifine permeated from drug loaded-NE formulations across rat skin fluctuated between 18–69%, as seen in . The collected data were used to prepare a quadratic model for polynomial analysis. The Box–Behnken design analysis demonstrates the effectiveness of the model to explore the effect of (A) clove oil amount, (B) NF amount, and (C) Smix ratio (C) on the % naftifine that permeated across the skin of rats. The suggested statistical model exhibited an adjusted and predicted R 2 of 0.9893 and 0.9714, respectively, which were obviously in close agreement, as shown in . The following equation was obtained after data analysis using ANOVA: E x vivo % naftifine permeated = + 63.41 + 5.68 A − 5.93 B − 3.35 C + 3.12 A B + 0.6250 A C − 0.6250 B C − 13.27 A ² − 4.79 B As indicated in the above equation, (A) clove oil amount had a significantly positive effect on % naftifine permeated, while (B) NF amount and (C) Smix ratio acquired a significantly negative effect on the same parameter. The increase in % NF permeated observed with increased clove oil amount might be attributed to the penetration enhancement characteristics of eugenol, the primary component of clove oil (Chaieb et al., ). It was previously reported that eugenol, like many other essential oil components, could interact and disrupt the barrier of SC without damaging the underlying tissues and, hence, promote drug penetration across the skin (Ahad et al., ). The inverse relationship between Y 2 and NF amount and Smix ratio could be ascribed to their effect on NE globule size, since it was observed that the increase in these two factors will result in larger droplets. Consequently, a smaller surface area will be available for drug permeation, leading to decreased % NF permeated across skin, which is similar to findings reported in literature (Hosny et al., ). Although clove oil amount displayed a positive effect on droplets size, its skin penetration enhancement ability overcome limitation of NF permeability. presents the main effect diagrams, 3D surface response, and contour plots, demonstrating the effect of the studied factors on % NF permeated across the skin.
Assessment of antifungal activity of NF-loaded nanoemulsions The antifungal activity of drug-loaded nanoemulsions was assessed against the dermatophytic fungus Trichophyton rubrum by measuring the inhibition zone of fungal growth in plates treated with NE formulations. As shown in , the diameter of the inhibition zone of Trichophyton rubrum equivocated between 5 and 24 mm. Then, based on the inhibition zones against Trichophyton rubrum , a linear model of polynomial equations was prepared to test the effect of the independent variables on the measured diameters of inhibition zones. The model’s predicted R 2 of 0.8777 was in a reasonable agreement with the adjusted R 2 of 0.9118, as presented in . Data analysis using ANOVA yielded the following equation: Zone of inhibition against Trichophyton rubrum = + 14.53 + 1.30 A + 4.46 B + 4.43 C This equation implies that all the used independent variables exerted a significantly positive effect on the inhibition zone against Trichophyton rubrum . In other words, increasing the amount of any of the three tested factors will increase the inhibition zone diameter; however, (B) NF amount and (C) Smix ratio showed a significant effect on the response ( p -value < .0001) compared to (A) clove oil % with a p -value <.02. The antifungal activity of clove oil against the tested fungus could be attributed to its eugenol content, which agrees with numerous other studies. As mentioned in literature, eugenol could induce leakage of potassium from fungal cells, thus inhibiting the uptake and use of energy by these cells, leading to envelop disruption, and finally inducing cell death (Chee & Lee, ). Moreover, the fungicidal effect of NF is thought to be conducted through the inhibition of fungal squalene epoxidase, inhibiting ergosterol biosynthesis (Monk & Brogden, ). The significant anti-fungal activity of NF against the tested fungus could be attributed to its high selectivity to ergosterol biosynthesis, unlike other anti-fungal drugs, such as azoles (Lee et al., ). The observed significant anti-fungal activity of the Smix could be ascribed to its cetylpyridinium chloride (CPC) content. Quaternary ammonium salts like CPC possess antimicrobial effects through various mechanisms (Sreenivasan et al., ), for instance, by disrupting cell membrane lipid bilayers and ultimately causing cellular content leakage., and finally cause cellular content leakage (Garcia-godoy, ). Moreover, exposure to CPC for longer periods could lead to additional destruction of intracellular materials, indicating autolysis (Evandro et al., ). displays the main effect diagrams, 3D surface response, and contour plots, which revealed the effect of the studied factors on the zone of inhibition against Trichophyton rubrum .
Interleukin-31 level measurements IL-31, a T-cell derived cytokine, may be involved in provoking some epithelial responses in atopic skin inflammation, such as redness, pain, and itching, that characterize some allergic reactions (Dillon et al., ). The obtained data of IL-31 serum levels were used to prepare a quadratic model for polynomial analysis following the Box–Behnken design in order to determine the impact of the studied factors on IL-31 serum levels. The model revealed a predicted R 2 of 0.9460, which was in reasonable accordance with the adjusted R 2 of 0.9840, as seen in . Data analysis by ANOVA produced the equation below: Interlukin − 31 Level = + 300.84 − 108.00 A + 187.85 B + 27.72 C − 91.25 A B + 5.00 A C + 3.75 B C + 41.29 A ² + 28.91 B ² + 4.17 C ² The measured IL-31 serum levels fluctuated between 100 and 800 pg/mL in the test rats, as presented in . From the above equation, it was noticed that (A) clove oil % presented a significantly negative effect on IL-31 serum levels ( p -value < .0001), while (B) NF amount and (C) Smix ratio exhibited a significantly positive effect, p -values of <.0001 and <.0073, respectively. The ability of clove oil to reduce IL-31 levels and, hence, improve the inflammatory side effects associated with NF could also be attributed to its eugenol content. Further, eugenol is known to inhibit the nuclear factor-kappa B (NF-κB) signaling pathway, which is a crucial step in preventing the transcription of cytokines and diminishing inflammation signs (Zhang et al., ). Moreover, compounds like eugenol that display antioxidant activity are able to modify oxidative stress and might indirectly participate in decreasing the production of inflammatory mediators. Therefore, eugenol is considered to be more effective in decreasing inflammation through its combined anti-inflammatory and antioxidant actions (Barboza et al., ). The positive effect of NF and CPC on IL-31 levels might be associated with mild inflammatory side effects in patients, which might affect their adherence to such drugs to some extent. displays the main effect diagrams, 3D surface response and contour plots, revealing the effects of the studied factors on IL-31 serum levels.
Optimization of NF-loaded nanoemulsion formulations From the previous data, an optimum NE formulation was developed using the most suitable properties. Design Expert ® indicated several solutions that could be used as various combinations of the independent variables’ levels. The optimum formulation was found to be composed of 14% clove oil and 12.5 mg NF with a Smix ratio of 3:1. The formula resulted in a globule size of 161 nm, ex vivo % naftifine permeated of 64%, IL-31 value of 180 pg/mL, and zone of inhibition against Trichophyton rubrum of 16 mm with 0.8030 desirability. It was noteworthy that optimum formulation had a much smaller zone of inhibition against Trichophyton rubrum (16 mm) compared to that of commercial cream (26 mm). presents the desirability plot, and indicates that the observed and predicted values of the optimum formulation parameters were in close agreement with no major differences ( p > .05), proving the model’s good predictability and validity.
Check point analysis Expected and adjusted R 2 values of the measured responses were in close agreement, validating the significant prediction capability of the design. In addition, experimental/predicted ratios with a percentage error below 10% and acceptable residuals were observed between the experimental and predicated responses, showing the lack of curvature in the responses and validity of the model. The results are presented in , and illustrates the overlay plot for the optimal region.
Zeta potential measurements of optimum formulation The optimized NF loaded nanoemulsion formulation acquired a ZP value of 28.31 ± 1.37 mV, further verifying the good stability of the developed formulation due to considerable repulsion between globules as predicted from such a large value. Furthermore, such a positive value will help in enhancing retention of NF in the skin and its effect through binding with the negatively charged phospholipid moieties of the skin. Notably, the observed large + ve ZP value might be ascribed to the use of cetylpyridinium chloride as a surfactant, which has a high positive charge.
Ex vivo permeation study of optimum formulation The optimized nanoemulsion formulation exhibited better skin permeation parameters compared to a commercial product. As seen in , the cumulative amount of permeated NF, steady state flux, permeability, and diffusion coefficients were improved by 2-, 3-, 5.75-, and 2.74-fold, respectively, in the optimum formulation compared to the commercial cream. Such enhancement in NF permeation in the case of nanoemulsion formulation could be due the NE components. As previously discussed, the main component of clove oil, eugenol, plays a pivotal role in improving skin penetration due to its ability to cause some disruption in the SC layer and deactivate its barrier properties.
Skin sensitivity test As seen in , the developed optimum NF-CO-SENDDs formulation was tolerated much better by rat skin than the commercial product. The reason behind such compatibility of NE formulation with the skin might be attributed to its clove oil content, which provides a good anti-inflammatory effect, as previously reported. These results are in good accordance with previously discussed results concerning IL-31 levels.
Stability study After storing the optimized formulation for 48 h subjected to three freeze-thaw cycles between −20 °C and +25 °C, no major differences were observed from the freshly prepared formula, as observed in . Such results confirm the adequate stability of the developed optimum NF-CO-SENDD, which can thus be properly used and stored.
Conclusions In the current investigation, a Box–Behnken design was adopted to develop and optimize a clove oil-based nanoemulsions loaded with NF for the topical treatment of tinea. The optimal clove oil % that was used in NE formulation ranged between 10 and 17%, and the produced NF-CO-SENNDs gained an adequate droplet size between 119 and 310 nm, indicating optimal NE formation. The statistical design confirmed the synergistic effect of clove oil and NF in the treatment of fungal infections and proved the clove oil’s anti-inflammatory effect that can reverse the side effects of NF. The optimized formulation composed of 14% clove oil, 12.5 mg Naftifine, and prepared with an Smix ratio equaling 3:1, exhibited good antifungal and anti-inflammatory activity, achieving up to 2-, 3-, 5.75-, and 2.74-fold increases in the amount of permeated NF, steady state flux, permeability, and diffusion coefficients, respectively, compared with a commercial product. Furthermore, the optimized formulation gained an adequate zeta potential value of 28.31 ± 1.37 mV and showed reasonable thermodynamic stability together with no or mild signs of skin sensitivity. Collectively, the designed nanoemulsion containing clove oil and naftifine presents a promising topical delivery systems for the management of tinea.
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Teaching pediatric otoscopy skills to the medical student in the clinical setting: preceptor perspectives and practice | afd95a75-1a1a-45d8-9e58-c42949acc178 | 7667741 | Pediatrics[mh] | Acute otitis media (AOM) is the most frequent indication for antibiotic treatment of children in the United States. Approximately 40–50% of children will have more than one episode of AOM before the age of 2 years . It is estimated that over 5 million cases of AOM occur annually in United States children, resulting in more than 10 million prescriptions for antibiotics . The threat of rising healthcare costs, growing antibiotic resistance, and increased surgical referrals for recurrent AOM combine to make the accurate diagnosis of AOM important . Competency in the pediatric ear exam is critical to the accurate diagnosis and appropriate management of pediatric ear disease . The American Academy of Pediatrics (AAP) 2013 Clinical Practice Guideline stresses that diagnosis of AOM relies on adequate visualization of the tympanic membrane , a clinical skill acquired through a deliberate, stepwise approach . The AAP recommends that instruction in the evaluation of the middle ear begin “in medical school and continue throughout postgraduate training.” Especially given that physicians other than pediatricians will diagnose children with AOM, delivering standardized otoscopy curricula to trainees in medical school is “an absolute necessity” for “the most widespread effect” on clinical practice . Despite expert recommendations, peer-reviewed curricula in pediatric otoscopy have emerged only recently . Such curricula have demonstrated gains in knowledge and skills that translate to the clinical setting . However, their actual use in clinical teaching is unknown and relies on the individual faculty responsible for teaching pediatric otoscopy. In addition to peer-reviewed curricula, advances in technology, such as digital video otoscopes to improve visualization of the tympanic membrane, have emerged . Mannequins have also been developed to effectively teach and assess pneumatic otoscopy skills . However, standardized use and evaluation of these tools in the clinical teaching setting are still lacking. Medical students receive their main clinical exposure to pediatric otoscopy during the required third-year pediatric clerkship, traditionally relying on an immersion, apprentice-type learning model in primary care ambulatory settings. The Council on Medical Student Education in Pediatrics (COMSEP) clerkship curriculum recommends that medical students should be able to “observe the tympanic membrane using an otoscope and an insufflator” . A clear standard teaching practice for otoscopy is not evident in the literature; anecdotally, current practice is a mixture of variable didactics and apprentice-type teaching. One needs assessment revealed that student expectations of developing expertise in pediatric otoscopy were not met by the end of their pediatric clerkship. In addition, students reported anxiety with the pediatric ear exam even after completing the pediatric clerkship. Critical learning opportunities were missed, with students reporting inadequate observation of their exam technique and few supervising physicians providing feedback on students’ skills . Given the critical teaching role of pediatric preceptors, it is important to understand preceptor practice and teaching patterns and their use of existing curricula and AAP Guidelines in teaching otoscopy. Learners’ perceptions of their preceptors’ teaching practice have been reported . Yet, little is known about preceptors’ own otoscopy skills, their teaching needs, or their perceptions and attitudes toward teaching pediatric otoscopy to medical students. Van Uum explored general practitioners’ views and expectations regarding pain management of AOM. But we are not aware of any studies regarding preceptors’ and other clinicians’ teaching and clinical behaviors and attitudes in this area . A greater understanding of preceptor clinical and teaching reported practices and attitudes regarding pediatric otoscopy education could lead to improved skill acquisition and impact patient outcomes. Thus, we sought to inquire about preceptors’ perceptions and attitudes about both their clinical and teaching practices. “The best use of survey methodology is to investigate human phenomena … that are neither directly observable, nor available in documents.” Thus, we chose survey methodology to acquire this information with the use of a novel survey instrument that focused on our key domains of inquiry. We aimed to investigate how pediatric preceptors (PP) and members of the Council on Medical Student Education in Pediatrics (CM) perceive their own clinical skills and the teaching of otoscopy to medical students during the pediatric clerkship, including barriers to teaching in the outpatient clinical setting.
In 2017, pediatric educators from six different academic institutions developed a survey to send to pediatric ambulatory clinical preceptors affiliated with their home institutions. All participating institutions were academic teaching hospitals affiliated with a medical school whose pediatric clerkships contained outpatient primary care rotations. The pediatric preceptors were considered for inclusion because they supervised medical students in the ambulatory setting. Settings included ambulatory academic pediatric teaching clinics, private practices, and federally funded clinics. Recruitment criteria and identification of eligible preceptors were determined by group consensus by the research team. Each site obtained ethics approval to conduct the Preceptor Survey, and the lead author obtained ethics approval for questions included in the COMSEP Survey. In 2018, questions were submitted for inclusion in the 2018 COMSEP Annual Survey. This survey is sent to every member of COMSEP and is a venue for members to undertake survey research. To keep the survey manageable, the COMSEP Survey Committee reviews submissions and determines which studies will be included in the annual survey. The survey was one of four chosen to be included in the 2018 COMSEP Annual Survey. With the branching logic embedded in the survey, the survey asked participants to self-select if they teach and/or oversee the teaching of otoscopy skills to medical students on the required pediatrics clerkship. The COMSEP Survey respondents who met this criteria were asked to complete the otoscopy-related questions. The design of the Preceptor Survey and COMSEP Survey followed survey design practices outlined by Artino and colleagues . Peer-reviewed standards informed the content of both surveys . The final surveys were created through an iterative process. First, expert group consensus generated general themes of inquiry for a focus group. A focus group, consisting of 10 ambulatory general pediatricians at one site, further explored the content domains of the surveys. Findings from the focus group confirmed the domains of inquiry (i.e. choices for barriers to teaching, use of technology) for the surveys and further refined the question items. A survey design expert reviewed the surveys with subsequent revisions. Finally, the surveys were further refined through a pilot evaluation on three general practicing pediatricians at the lead author’s institution, with input from two additional pediatric educators. The results of the pilot survey were not included in the overall data analysis. The pilot evaluation did not alter the content of the questions. However, wording of some questions was edited for greater clarity to obtain more accurate responses. The Preceptor Survey focused on the following domains: attitudes about pediatric otoscopy, medical student teaching, teaching barriers, and preceptors’ clinical practices. The COMSEP Survey included similar domains, and in addition, explored COMSEP members’ views about their faculty who taught pediatric otoscopy. The COMSEP Survey excluded questions contained in the Preceptor Survey that queried the demographics of preceptors and personal clinical practice patterns. The majority of questions for the COMSEP Survey were derived from the Preceptor Survey. Additional questions were added in order to examine the perceptions of education leaders about their faculty who taught pediatric otoscopy and AOM to medical students. In addition to the above mentioned developmental process, the COMSEP Survey underwent an additional pilot evaluation at two investigators’ sites with subsequent revision. Both surveys were administered by directly emailing the targeted subjects, with a link to the survey included in the email message. The preceptor survey was built in the Qualtrics online survey platform (Qualtrics XM, Provo, Utah) at the lead author’s institution. Each site was provided a link for the survey to send to their preceptors. For the COMSEP Survey, the organization’s survey committee administered the survey to all of its members. Study investigators received de-identified, anonymous data for both the Preceptor and COMSEP Surveys, as well as demographic data for respondents of the COMSEP Survey (Fig. ). The Preceptor Survey was implemented at the different sites from September 15, 2017 to October 31, 2017. The COMSEP Survey was implemented from March 28, 2018 to May 15, 2018. As described previously, content validity for the surveys was achieved through literature reviews, expert opinion, and focus groups with other experts. Test-retest reliability comparing preceptors with COMSEP members resulted in a Cronbach’s alpha of 0.85. G*Power (Universität Kiel, Germany) was used to calculate a minimum sample size. For comparisons across institutions with a Wilcoxon signed-rank test, an effect size of .5, Alpha of .05, and power of .95 indicated the minimum sample size needed was 57 participants. Descriptive and inferential statistics performed with SPSS software version 25 (IBM, Chicago, Illinois) were used to analyze the results of the Preceptor and COMSEP Surveys. Mann-Whitney U Test were used to compare PP and CM responses to specific questions on the surveys. Statistical significance was defined as a p < 0.05.
The response rate for the Preceptor Survey was 58% (181/310). The overall response rate for the 2018 COMSEP Annual Survey was 44% (152/348). Forty-one percent (62/152) of the respondents of the survey self-identified themselves as teaching and/or overseeing the teaching of otoscopy skills to medical students and answered the otoscopy-related questions. Medical student education Ninety-five percent of PP and 79% of CM reported that all graduating medical students should be able to perform pediatric otoscopy, defined as visualization of the tympanic membrane using an otoscope. Additionally, 78% of PP and 97% of CM reported that a standardized curriculum for teaching pediatric otoscopy skills to medical students would enable preceptors to be more effective in their teaching. Preceptor clinical skills Ninety-five percent of PP and 100% of CM reported that the AAP 2013 Clinical Practice Guideline was useful for the diagnosis of AOM. However, when asked what specific diagnostic criteria they use to make the diagnosis of AOM in clinical practice, only 42% of PP correctly selected the recommended criteria of the AAP Guidelines, which is moderate to severe bulging of the tympanic membrane. Fifty-eight percent of PP and 47% of CM reported that skill in pneumatic otoscopy was important to the diagnosis of AOM. Yet, only 15% of PP and 35% of CM reported utilizing pneumatic otoscopy to diagnose AOM. Forty-four percent of PP and 23% of CM reported receiving no formal training in cerumen removal. Eighty-three percent of PP and 40% of CM reported demonstrating cerumen removal to students. Thirty-seven percent of PP and 29% of CM reported difficulty in removing cerumen. Barriers to teaching The most commonly reported barriers to teaching otoscopy skills were a lack of technological devices such as video otoscopes, tympanograms, and dual head otoscopes for teaching (PP 77%, CM 56%). Participants noted additional barriers to teaching including the presence of cerumen (PP 58%, CM 60%), time to teach in direct patient care (PP 46%, CM 48%), and parent anxiety (PP 62%, CM 54%). Some respondents in both groups also reported their personal teaching skills (23% PP, 21% CM) and pneumatic otoscopy skills (40% PP, 24% CM) as barriers to teaching. There were differences between the PP and CM responses regarding barriers to teaching otoscopy skills. PP reported more than CM that time to teach during direct patient care (mean rank PP = 64.73 vs. CM = 49.86, p = .005) and personal teaching skills (mean rank PP = 72.28 vs. CM = 43.77, p = .001) were barriers. PP also reported more than CM that their personal skill in pneumatic otoscopy (mean rank PP = 67.54 vs. CM = 47.60, p = .001) and cerumen removal (mean rank PP = 69.04 vs. 46.39, p = .001) were barriers. PP also reported more than CM that a lack of formal curriculum (mean rank PP = 67.30 vs. CM 47.79, p = .001) was a barrier (Fig. ).
Ninety-five percent of PP and 79% of CM reported that all graduating medical students should be able to perform pediatric otoscopy, defined as visualization of the tympanic membrane using an otoscope. Additionally, 78% of PP and 97% of CM reported that a standardized curriculum for teaching pediatric otoscopy skills to medical students would enable preceptors to be more effective in their teaching.
Ninety-five percent of PP and 100% of CM reported that the AAP 2013 Clinical Practice Guideline was useful for the diagnosis of AOM. However, when asked what specific diagnostic criteria they use to make the diagnosis of AOM in clinical practice, only 42% of PP correctly selected the recommended criteria of the AAP Guidelines, which is moderate to severe bulging of the tympanic membrane. Fifty-eight percent of PP and 47% of CM reported that skill in pneumatic otoscopy was important to the diagnosis of AOM. Yet, only 15% of PP and 35% of CM reported utilizing pneumatic otoscopy to diagnose AOM. Forty-four percent of PP and 23% of CM reported receiving no formal training in cerumen removal. Eighty-three percent of PP and 40% of CM reported demonstrating cerumen removal to students. Thirty-seven percent of PP and 29% of CM reported difficulty in removing cerumen.
The most commonly reported barriers to teaching otoscopy skills were a lack of technological devices such as video otoscopes, tympanograms, and dual head otoscopes for teaching (PP 77%, CM 56%). Participants noted additional barriers to teaching including the presence of cerumen (PP 58%, CM 60%), time to teach in direct patient care (PP 46%, CM 48%), and parent anxiety (PP 62%, CM 54%). Some respondents in both groups also reported their personal teaching skills (23% PP, 21% CM) and pneumatic otoscopy skills (40% PP, 24% CM) as barriers to teaching. There were differences between the PP and CM responses regarding barriers to teaching otoscopy skills. PP reported more than CM that time to teach during direct patient care (mean rank PP = 64.73 vs. CM = 49.86, p = .005) and personal teaching skills (mean rank PP = 72.28 vs. CM = 43.77, p = .001) were barriers. PP also reported more than CM that their personal skill in pneumatic otoscopy (mean rank PP = 67.54 vs. CM = 47.60, p = .001) and cerumen removal (mean rank PP = 69.04 vs. 46.39, p = .001) were barriers. PP also reported more than CM that a lack of formal curriculum (mean rank PP = 67.30 vs. CM 47.79, p = .001) was a barrier (Fig. ).
Most medical students receive the majority of their training in the pediatric ear exam during the ambulatory component of the required pediatrics clerkship, where preceptors serve as their “front line” teachers. Proper pediatric otoscopy is essential to the accurate diagnosis of AOM. Despite this emphasis in the most recent AAP 2013 Clinical Practice Guidelines on AOM, literature on the use of the AAP Guidelines, implementation of standardized curricula, and teaching in real-time clinical settings are lacking . Little is known about the informal training that preceptors deliver to their learners on pediatric otoscopy, although it is clear that preceptor practices and attitudes can affect student performance of these skills . Gaining an understanding of preceptors’ clinical and teaching practices is a crucial first step toward improving student learning and skill acquisition, which can ultimately impact patient outcomes . Preceptors (PP) and education leaders (CM) in our study strongly agreed that all graduating medical students should learn basic pediatric otoscopy skills and that there is a need for the implementation of standardized curricula for effective teaching. But, preceptors need practical strategies, support, and infrastructure in their clinics to implement these curricula. Future work should focus on incorporating curricula to the teaching of pediatric otoscopy skills in the clinical setting, with direct evaluation and feedback on the learned skills. For instance, the otolaryngology education literature demonstrates many efforts aimed to help otolaryngology specialists teach their learners with varying modalities . Similarly, faculty development for the primary care preceptor should be offered, to help such educators teach standardized content in real patient care settings. Preceptors and education leaders cited similar multi-faceted barriers to teaching pediatric otoscopy. Some reported barriers were expected, such as the time required to teach effectively in direct patient care settings and lack of clinic supplies. Barriers related to psychosocial concerns such as student and/or parent anxiety were also anticipated results. However, difficulty with procedural skills such as pneumatic otoscopy and cerumen removal may be the most surprising reported barrier. If preceptors feel that they lack these skills, it makes sense that they would be hesitant to teach the same skill to students. Indeed, such reported difficulties may influence basic otoscopy teaching as the presence of cerumen can influence the diagnostic accuracy of AOM . Of note, the presence of cerumen as a barrier has been described in other specialties as well . Furthermore, emerging device technology may play a future role in faculty development in teaching otoscopy skills and lead to improved diagnostic accuracy, appropriate management, and better patient care. Whether to aid with tympanic membrane visualization using image capture of the tympanic membrane or for skills-training with simulation, advances should be explored in the context of improving diagnostic accuracy in the clinical settings . However, it should be noted that under resourced clinics may find it challenging to implement such emerging technology. Such technology should be developed also in the context of primary care clinical practices which provide teaching in direct patient care settings. Our study aimed mainly to investigate preceptors’ teaching practices. Yet, the results also revealed interesting self-reports about preceptors’ own knowledge and skills. An advantage of our chosen study methodology is that a survey can reveal undocumented non-observed human phenoma . These findings are important with a clinical skill such as pediatric otoscopy, where preceptor modelling remains the key learning strategy in direct patient care settings. The educational experiences of our learners may reflect the preceptors’ strengths, deficiencies, and variability. Our findings suggest some discrepancy between preceptors’ acknowledgement of the importance of the AAP Guideline and their reported clinical practice. For instance, the majority of preceptors did not choose correctly, the main diagnostic criteria of the AAP Guidelines as the criteria they use in their own practice. These self-reported skill deficiencies and discrepancies between AAP Guideline and actual clinical practice influence the learning of students and residents in the clinical setting and reveal the need for continued faculty development, even for the experienced and academically-oriented preceptor. Opportunities for such knowledge and skill development for pediatric preceptors and other faculty could be offered at national and regional AAP educational meetings and also be considered at other specialty meetings such as Family Medicine . Some pediatric preceptors reported teaching and demonstrating skills such as pneumatic otoscopy and cerumen removal that were not taught to them and that they themselves still find difficult to perform. Many of the preceptors and educators were not performing pneumatic otoscopy, even though they selected pneumatic otoscopy as the ideal method for diagnosis. Furthermore, a large proportion of preceptors and educators who identified cerumen as a key barrier still themselves reported deficiencies with cerumen removal. Our study reveals preceptors’ barriers and deficiencies in their own practices that might not have otherwise been identified. Our results suggest that faculty competency in specific clinical skills that they are responsible for teaching cannot always be assumed. This also can be seen as an opportunity for improvement, with targeted teaching interventions for the preceptors themselves. As with other clinical skills, skill demonstration with real patients is an important teaching strategy. The reported variance of our participants from standard guidelines is not unique. Despite clear expert recommendations, clinicians’ otoscopy practice patterns continue to vary widely, often deviating from the AAP Guideline. Other studies have also found that many providers do not routinely perform pneumatic otoscopy, an AAP recommended component in the pediatric ear exam. In addition, it is unclear if the AAP guidelines have impacted the practice of pediatric otoscopy with regards to cerumen removal. Cerumen, which is present in most pediatric patients, can complicate tympanic membrane visualization. Marchisio suggests some pediatrician reluctance to remove cerumen when the final diagnosis is AOM. Our findings echo the findings from Marchiso and Shah-Becker . Despite the AAP Guidelines stating cerumen as a barrier in diagnostic accuracy, 37% of preceptors and 23% of education leaders in our study who identified cerumen as a key barrier still themselves reported deficiencies with cerumen removal. While this study focused on a core pediatric skill, the survey methodology can be used to identify how other core clinical skills are currently being taught . Formal and deliberate efforts are needed to ensure that graduating students are truly equipped with the skill sets presumed to have been learned in the clinical setting. We anticipate our findings to help inform curriculum development, learning strategies, and faculty development for those preceptors responsible for teaching these skill sets in clinical settings. Our study has limitations. Although our study surveyed a range of preceptors and educational leaders in pediatrics, it did not include family medicine and emergency medicine physicians who may also teach pediatric otoscopy to medical students. In addition, although the surveys focused on faculty self-reported skills and knowledge, it did not examine actual faculty competency in both skills and teaching. Some of our preceptors acknowledged a lack of specific skills training during their residency and reported current difficulty with the same skills that they are responsible for teaching. Our study also made some inferences based on comparison of faculty’s responses to recognized standard of care versus their reported actual practice.
Pediatric otoscopy has been an assumed competency with vague and variable benchmarks for different levels of learners including the graduating medical student. Differences in competency may also exist among current faculty by their own report . Better dissemination and implementation of the AAP Guidelines on AOM for all learner groups, including faculty, may lead to better diagnosis of AOM and improved outcomes for patients. Our findings suggest that more global attention to skills and knowledge of preceptors who teach on the “front lines” would be of value. Our study suggests that faculty competency and skills in performing and teaching otoscopy in the direct patient care settings is a crucial first step.
Additional file 1. 2018 COMSEP Annual Survey. Additional file 2. Preceptor Survey.
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Diagnostik von Erkrankungen des Sehnervenkopfes in Zeiten von künstlicher Intelligenz und Big Data | 657d7614-3a28-4f8a-ba4c-0648f66508c3 | 8062109 | Ophthalmology[mh] | „Big Data“ beschreibt die Analyse von großen Datenmengen. Diese ermöglicht die kostengünstige und ressourcensparende Beantwortung verschiedener klinischer Fragestellungen, um so auch übergeordnete Zusammenhänge aufzeigen zu können . So konnten beispielsweise eine Assoziation zwischen minimierter Sonnenstrahlenexposition und erhöhter Inzidenz eines primären Offenwinkelglaukoms, sowie ein erhöhtes Risiko einer Glaukomerkrankung bei Patienten mit Diabetes mellitus oder vorbestehender arterieller Hypertonie identifiziert werden . Basis für diese Auswertungen sind große, strukturierte und digitale Datensammlungen. Dies hat im Bereich der Augenheilkunde dazu geführt, dass verschiedene Register gegründet wurden. Besonders nennenswert sind in diesem Zusammenhang das „Save-Sight“-Register in Australien, das „IRIS“-Register in den USA und das „OREGIS“-Register unter Schirmherrschaft der Deutschen Ophthalmologischen Gesellschaft (DOG) in Deutschland . „Big Data“ beschreibt die Analyse von großen Datenmengen Unterstützt wird diese Entwicklung durch eine zunehmende elektronische Dokumentation der Patientenvisiten . Gerade in Zeiten einer Pandemie kann sich dies als hilfreich erweisen. Bommakanti et al. entwickelten und implementierten beispielsweise ein Tool, welches das individuelle Risiko eines Fortschreitens einer Augenerkrankung – wie einem Glaukom – durch eine verzögerte Inanspruchnahme der Versorgung und das Morbiditätsrisiko durch eine COVID-19-Exposition berücksichtigt und die Triage anstehender Augenarzttermine erleichtert . Weitere Möglichkeiten von strukturierten großen Datensätzen sind die Anwendung von KI für eine Segmentierung und Klassifikation oder Prädiktion des Krankheitsverlaufs.
KI ist ein Teilbereich der Informatik und beschreibt Algorithmen, die in der Lage sind, „intelligente“ Entscheidungen zu treffen. Maschinelles Lernen (ML) und Deep Learning (DL) sind Unterbegriffe der KI und beschreiben Algorithmen, welche die Fähigkeiten besitzen, bestimmte Lösungsansätze selbstständig zu „erlernen“ (Abb. ). ML kann als eine Erweiterung der klassischen Statistik bezeichnet werden. Statistische Modelle sind darauf ausgelegt, Varianzen zu erklären und herauszuarbeiten, mit welcher Wahrscheinlichkeit es sich dabei um Zufall handelt. ML-Modelle haben genauso wie die klassischen statistischen Modelle das Ziel, durch „Training“ anhand von Musterdaten exakte Vorhersagen zu treffen. Im Vergleich zu den klassischen statistischen Modellen ist hier das Ergebnis in der Regel allerdings weniger gut nachvollziehbar. Machine Learning ist eine Unterform der künstlichen Intelligenz, welche Deep Learning beinhaltet Beim DL werden sog. tiefe neuronale Netzwerke verwendet, bei dem Algorithmen orientiert an der Struktur des menschlichen Gehirns aufgebaut sind. In der einfachsten Form hat ein neuronales Netzwerk 3 Elemente: den Input Layer, in dem die Daten dem System zugeführt werden, die Hidden Layers, in denen die Daten weiterverarbeitet werden, und den Output Layer, in dem eine Information (statistische Entscheidung) ausgegeben wird. Diese Algorithmen sind insbesondere für die automatische Bildanalyse geeignet, jedoch sind für den Anwender die Entscheidungsprozesse nicht immer nachvollziehbar und führen somit häufig zu einer sog. „Black Box“ (; Abb. ). Bildsegmentierung Die Bildsegmentierung ist der Vorgang des Überprüfens eines jeden einzelnen Bildpunktes, ob dieser einem uns interessierenden Objekt, wie z. B. einer anatomischen Struktur, angehört. Die Untersuchung des Sehnervenkopfes kann neben der stereoskopischen Fundoskopie mithilfe unterschiedlicher Bildgebungsmodalitäten wie der Farbfundusfotografie oder der optischen Kohärenztomographie (OCT) erfolgen. Für eine korrekte Zuordnung von strukturellen Veränderungen zu verschiedenen Sehnervenerkrankungen ist eine genaue Segmentierung der anatomischen Strukturen erforderlich. Eine große Exkavation im Verhältnis zu der Sehnervenscheibe (Cup-Disc-Ratio) kann beispielsweise ein Hinweis für eine glaukomatöse Optikusschädigung sein. Zwar ist eine große Exkavation nicht direkt pathognomonisch für ein Glaukom, jedoch minimiert eine automatisierte robuste Berechnung der Cup-Disc-Ratio (CDR) die hohe Inter- und Intraobservervariabilität der Beurteilung von Papillen auf Fundusfotos . Mehrere Arbeitsgruppen entwickelten deshalb Modelle, mit denen eine automatische Segmentierung des Sehnervenkopfes in Cup und Disc und somit eine leichte Berechnung der CDR auf Fundusfotos möglich ist (; Abb. ) Trotzdem ist diese aufgrund des Mangels an scharfen Konturen und fehlender Tiefeninformationen innerhalb eines 2‑dimensionalen Bildes fehleranfällig. Zhao et al. konnten dieses Problem mit einem 2‑stufigen halb-überwachten Ansatz lösen. Mithilfe eines tiefen neuronalen Netzes wurden in einem ersten Schritt auf Fundusfotos vorher nicht definierte Merkmale des Sehnervenkopfes extrahiert (Output). Somit wird eine aufwendige und fehleranfällige manuelle Markierung umgangen, da das System selbstständig nach Merkmalen (engl. „features“) suchte. In einem zweiten Schritt wurden diese Merkmale wiederum als Input für ein weiteres Regressionsmodell zur Vorhersage der vertikalen CDR verwendet. Das Modell konnte die CDR mit einem mittleren absoluten Fehler von 0,0563 sehr genau vorhersagen und übertraf klassische Modelle, die auf einer manuellen Segmentierung basierten . Im Gegensatz zu Fundusfotos ermöglich ein OCT-Scan eine 3‑dimensionale Darstellung des Sehnervenkopfes und des peripapillären Gewebes. Diese hat zu einem tieferen Verständnis von strukturellen Veränderungen im Bereich des Sehnerven bei verschiedenen Optikuserkrankungen geführt. Im Rahmen einer glaukomatösen Optikusneuropathie kommt es beispielsweise zu typischen Veränderungen im Bereich der Papille und der peripapillären retinalen Nervenfaserschicht (RNFL). Bislang segmentieren kommerziell erhältliche Geräte v. a. die RNFL und die auf der Bruch-Membran basierende minimale Randsaumweite (BMO-MRW). Diese Parameter haben sich v. a. bei der Detektion und Verlaufsbeurteilung von Glaukompatienten als sinnvoll erwiesen. Jedoch können bei bis zu 40 % der RNFL-Scans Segmentierungsfehler aufgrund einer schlechten Aufnahmequalität auftreten . Eine manuelle Korrektur dieser Fehler ist zeitaufwendig und behindert den Arbeitsfluss im klinischen Alltag. Mit dem DL-Modell, das von Mariottoni et al. vorgeschlagen wurde, ließ sich die RNFL in OCT-Bildern mit schlechter Aufnahmequalität besser messen, als mit der Software des Herstellers . Neben der RNFL und BMO-MRW zeigen sich bei Fortschreiten eines Glaukoms jedoch auch Änderungen anderer anatomischer Strukturen, die auf dem OCT-Scan der Papille sichtbar sind. Zwar konnten Thompson et al. auf OCT-Scans mithilfe eines DL-Modells ohne Segmentierung der RNFL besser ein Glaukom diagnostizieren als mit der Nervenfaserschichtdickenmessung , welche eine segmentierungsunabhängige Klassifikation von gesunden Patienten und Patienten mit einem Glaukom ermöglicht. Dies limitiert im Umkehrschluss jedoch auch die klinische Anwendung des Algorithmus allein auf die genannten Patientengruppen. Im Gegensatz dazu sind Bildsegmentierungsalgorithmen wie der von Devalla et al. universell bei allen Erkrankungen des Sehnervenkopfes anwendbar, da sie nicht speziell auf die automatische Identifikation einer bestimmten Erkrankung, sondern allein auf eine optimierte Segmentierung einer Bildgebungsmodalität trainiert sind. Die genannte Arbeitsgruppe konnte mithilfe eines mehrschichtigen neuronalen Netzwerkes die RNFL, das prälaminare Gewebe, das retinale Pigmentepithel, die Aderhaut, die Lamina cribrosa und die peripapilläre Sklera automatisiert zuordnen und markieren . Die automatische Segmentierung konnte robust sowohl in gesunden als auch in für Segmentierungsfehler anfälligen glaukomatös veränderten Sehnervenköpfen durchgeführt werden . In einem weiteren Ansatz konnte die gleiche Arbeitsgruppe einen DL-Algorithmus entwickeln, der die Qualität von OCT-B-Scans unterschiedlicher Geräte so harmonisierte, dass in einem weiteren Schritt eine geräteunspezifische Segmentierung der Strukturen möglich war . Dies macht eine einfache Implementierung der Segmentierung von OCT-Scans im klinischen Alltag auf unterschiedlichen Geräten möglich und erleichtert die Diagnostik und Verlaufsbeurteilung von Erkrankungen des Sehnervenkopfes wie dem Glaukom. Glaukomatöse Optikusneuropathie Da eine glaukomatöse Optikusneuropathie im Frühstadium asymptomatisch verläuft, ist das Glaukom für ein Screening von großen Patientenkohorten geeignet. Jedoch liefert aktuell noch kein einzelnes Untersuchungsverfahren allein ausreichend valide Daten, um ein Glaukom sicher zu diagnostizieren. Für ein kosteneffektives Glaukomscreening wäre ein einzelner Test mit gleichzeitig hoher Sensitivität und Spezifität wünschenswert . Da die digitale Farbfundusfotografie weit verbreitet und kostengünstig ist, scheint eine automatisierte, KI-gestützte Bilddatenanalyse zur Detektion von glaukomatösen Optikusschädigungen auf dieser Bildgebungsmodalität sehr attraktiv . Für ein kosteneffektives Glaukomscreening wäre ein einzelner Test wünschenswert Die Klassifikation von glaukomatösen Optikusneuropathien auf Farbfundusfotos ist schon mit einer hohen Genauigkeit möglich. Li et al. konnten mithilfe von 48.116 Fundusfotos einen DL-Algorithmus mit einer Fläche unter der Kurve (AUC) von 0,986 zur Detektion von glaukomatösen Optikusneuropathien generieren . Phene et al. konnten mit ihrem DL-Algorithmus, trainiert auf 86.618 Fundusfotos, sogar 2 Glaukomspezialisten bei der Klassifikation einer glaukomatösen Optikusatrophie übertreffen . Für den Augenarzt ist die Logik hinter der Entscheidung des Algorithmus aufgrund der „Black Box“ von Algorithmen v. a. bei tiefen neuronalen Netzwerken jedoch nicht nachvollziehbar. Dies konnte die Arbeitsgruppe um Phene et al. mithilfe einer logistischen Regression jedoch umgehen und zeigen, dass sowohl für den Glaukomspezialisten als auch für den Algorithmus die gleichen Merkmale (CDR > 0,7, Papillenrandkerbe, Nervenfaserdefekt, Gefäßverlauf) am ausschlaggebendsten für die Klassifikation waren . Obwohl die Fundusfotografie der optimale Kandidat für ein Glaukomscreening zu sein scheint, können mit OCT-Scans zusätzliche Informationen wie die peripapilläre RNFL oder BMO-MRW über den Sehnervenkopf gewonnen werden. Medeiros et al. konnten zeigen, dass es möglich ist, einen Algorithmus darauf zu trainieren, automatisiert die Dicke der RNFL allein auf Fundusfotos zu quantifizieren . Sie trainierten ein tiefes neuronales Netzwerk mit Fundusfotos und den korrespondierenden SD(„spectral domain“)-OCT-Scans von 2312 Sehnerven. Das DL-System konnte auf einem Testdatensatz, bestehend aus 6292 Papillenfotos, die mittlere Dicke der RNFL mit einer absoluten Abweichung von 82,5 ± 16,8 µm vorhersagen. Dieses Modell übertraf sogar Augenärzte in der Klassifikation von Bildern von Sehnervenköpfen mit und ohne einen Gesichtsfelddefekt . Die gleiche Arbeitsgruppe konnte ähnlich vielversprechende Ergebnisse mit der Vorhersage der mittleren BMO-MRW allein auf Fundusfotos erzielen . Neben der Quantifizierung von RNFL und BMO-MRW auf Farbfundusfotos könnten andere KI-Ansätze zu einem tieferen Verständnis der Auswirkung von strukturellen Veränderungen des Sehnerven auf seine Funktion führen. Christopher et al. konnten mithilfe eines DL-Modells Gesichtsfelddefekte nur anhand von OCT-Scans des Sehnervenkopfes vorhersagen . Dieser Ansatz könnte im klinischen Alltag helfen, die Häufigkeit der zeitaufwendigen Gesichtsfelduntersuchung bei Glaukompatienten effektiver zu gestalten und gezielter anzuwenden. Mariottoni et al. konnten eine KI-basierte Zuordnung von strukturellen OCT-RNFL-Schäden zu Gesichtsfelddefekten bei einem Glaukom entwickeln. Dies ermöglicht ein tieferes Verständnis des Zusammenhanges von Struktur und Funktion und kann im klinischen Alltag bei der Beurteilung von RNFL-Defekten helfen . Stauungspapille Eine der größten Herausforderungen bei der Anwendung von KI ist es, robuste Ansätze auch für Erkrankungen mit geringer Inzidenz zu entwickeln. Teilweise ist bei diesen eine ausreichend große Anzahl an Patienten nur mit Datenbanken oder großen multizentrischen Studien zu erzielen. Trotzdem kann gerade die Abgrenzung einer Erkrankung mit hoher Inzidenz wie dem Glaukom zu anderen selteneren Sehnervenerkrankungen schwierig und zugleich klinisch hochrelevant sein. Dieser Fragestellung widmeten sich Yang et al. und konnten mit einem DL-Modell zwischen glaukomatöser und nichtglaukomatöser Optikusneuropathie auf 3815 Farbfundusfotos mit einer Sensitivität von 93 % und einer Spezifität von 81 % unterscheiden . Große Datensätze bei Erkrankungen mit niedriger Inzidenz zu generieren ist eine Herausforderung Vergleichsweise einfach ist für einen erfahrenen Augenarzt die Detektion einer Stauungspapille. Die direkte Ophthalmoskopie wird aber nur noch vereinzelt von Internisten oder Neurologen beherrscht. Jedoch zeigt sich bei 2,6 % aller Patienten mit neurologischen Symptomen eine Stauungspapille (STP), die Hinweis auf einen erhöhten Hirndruck sein kann . Wird diese übersehen und bleibt eine intrakranielle Hypertension unbehandelt, kann dies zu einem irreversiblen Nervenfaserdefekt mit konsekutiver Funktionsminderung führen. Aus diesem Grund wird in verschiedenen Kliniken und Notaufnahmen mithilfe der digitalen Fundusfotografie ein Bild des Sehnervenkopfes erstellt . Dieses Bild wiederum muss durch einen Augenarzt vor Ort oder per Telemedizin in einem anderen Zentrum beurteilt werden . Hier wäre ein robuster KI-Ansatz zur automatischen Detektion von Papillenödemen sehr hilfreich, jedoch sind große Datensätze bei Erkrankungen mit niedriger Inzidenz ein limitierender Faktor. Echegaray et al. konnten mithilfe eines ML-Algorithmus automatisiert auf Farbfundusfotos den Grad des Papillenödems nach Frisén mit einer gleichen Genauigkeit wie ein erfahrener Neuroophthalmologe klassifizieren . Akbar et al. konnten automatisiert mit einer Genauigkeit von 92,9 % eine Stauungspapille von gesunden Sehnervenköpfen auf Farbfundusfotos abgrenzen , ähnliche Ergebnisse wurde von Fatima et al. erzielt . Die verwendeten Datensätze waren mit einer Anzahl von jeweils unter 300 Fundusfotos in beiden Fällen nur gering. Auch ist die Unterscheidung zwischen gesund und krank zwar vielversprechend, entspricht jedoch nicht der Realität, in der mehr als 2 Alternativen vorhanden sind. So ist es klinisch teilweise schwierig, zwischen Papillenödemen und Pseudopapillenödemen – beispielsweise bei hyperopen Augen – zu unterscheiden. Mit einem ML-Modell konnten Ahn et al. zwischen geschwollenen Sehnervenköpfen aufgrund unterschiedlicher Optikusneuropathien, Pseudopapillenödemen und gesunden Sehnervenköpfen unterscheiden . Zusätzlich umgingen die genannten Autoren das Problem eines kleinen Datensatzes. Zum einen konnte mithilfe von Augmentierung der vorhandenen Daten die Diversität des Datensatzes erhöht werden, ohne tatsächlich neue Daten zu generieren. Dies minimiert das Risiko einer Überanpassung (engl. „overfitting“), was bedeutet, dass der Algorithmus nicht auf externe Daten anwendbar ist, da er zwischen gesund und krank anhand von Merkmalen unterscheidet, die nur in dem vorhandenen Datensatz, aber nicht auf einem weiteren externen Datensatz vorhanden sind. Zum anderen wurde ein vortrainiertes tiefes neuronales Netzwerk verwendet. Dadurch wurden trotz der geringeren Datenmengen gute Ergebnisse erzielt. Einen deutlich größeren Datensatz konnten Milea et al. in einer multizentrischen Studie generieren. Die Arbeitsgruppe trainierte einen DL-Algorithmus auf 14.341 Fundusfotos, von denen 2148 Papillen ein Papillenödem aufgrund einer intrakraniellen Hypertension hatten. Der Algorithmus konnte auf einem externen Datensatz von 1505 Farbfundusfotos mit einer AUC von jeweils 0,99 zwischen gesunden Sehnervenköpfen und Stauungspapillen sowie zwischen Stauungspapillen und anderen Pathologien des Sehnervenkopfes unterscheiden. Die Studie aus dem New England Journal of Medicine zeigt, dass auch bei Erkrankungen mit geringer Inzidenz mithilfe von multizentrischen Datensätzen robuste Algorithmen generiert werden können. Der Algorithmus der BONSAI-Arbeitsgruppe könnte bei Implementierung einen großen Einfluss auf die tägliche Routine in Notaufnahmen haben und maßgeblich die Versorgung von Patienten mit intrakranieller Hypertension durch eine schnellere Diagnostik und Therapie verbessern.
Die Bildsegmentierung ist der Vorgang des Überprüfens eines jeden einzelnen Bildpunktes, ob dieser einem uns interessierenden Objekt, wie z. B. einer anatomischen Struktur, angehört. Die Untersuchung des Sehnervenkopfes kann neben der stereoskopischen Fundoskopie mithilfe unterschiedlicher Bildgebungsmodalitäten wie der Farbfundusfotografie oder der optischen Kohärenztomographie (OCT) erfolgen. Für eine korrekte Zuordnung von strukturellen Veränderungen zu verschiedenen Sehnervenerkrankungen ist eine genaue Segmentierung der anatomischen Strukturen erforderlich. Eine große Exkavation im Verhältnis zu der Sehnervenscheibe (Cup-Disc-Ratio) kann beispielsweise ein Hinweis für eine glaukomatöse Optikusschädigung sein. Zwar ist eine große Exkavation nicht direkt pathognomonisch für ein Glaukom, jedoch minimiert eine automatisierte robuste Berechnung der Cup-Disc-Ratio (CDR) die hohe Inter- und Intraobservervariabilität der Beurteilung von Papillen auf Fundusfotos . Mehrere Arbeitsgruppen entwickelten deshalb Modelle, mit denen eine automatische Segmentierung des Sehnervenkopfes in Cup und Disc und somit eine leichte Berechnung der CDR auf Fundusfotos möglich ist (; Abb. ) Trotzdem ist diese aufgrund des Mangels an scharfen Konturen und fehlender Tiefeninformationen innerhalb eines 2‑dimensionalen Bildes fehleranfällig. Zhao et al. konnten dieses Problem mit einem 2‑stufigen halb-überwachten Ansatz lösen. Mithilfe eines tiefen neuronalen Netzes wurden in einem ersten Schritt auf Fundusfotos vorher nicht definierte Merkmale des Sehnervenkopfes extrahiert (Output). Somit wird eine aufwendige und fehleranfällige manuelle Markierung umgangen, da das System selbstständig nach Merkmalen (engl. „features“) suchte. In einem zweiten Schritt wurden diese Merkmale wiederum als Input für ein weiteres Regressionsmodell zur Vorhersage der vertikalen CDR verwendet. Das Modell konnte die CDR mit einem mittleren absoluten Fehler von 0,0563 sehr genau vorhersagen und übertraf klassische Modelle, die auf einer manuellen Segmentierung basierten . Im Gegensatz zu Fundusfotos ermöglich ein OCT-Scan eine 3‑dimensionale Darstellung des Sehnervenkopfes und des peripapillären Gewebes. Diese hat zu einem tieferen Verständnis von strukturellen Veränderungen im Bereich des Sehnerven bei verschiedenen Optikuserkrankungen geführt. Im Rahmen einer glaukomatösen Optikusneuropathie kommt es beispielsweise zu typischen Veränderungen im Bereich der Papille und der peripapillären retinalen Nervenfaserschicht (RNFL). Bislang segmentieren kommerziell erhältliche Geräte v. a. die RNFL und die auf der Bruch-Membran basierende minimale Randsaumweite (BMO-MRW). Diese Parameter haben sich v. a. bei der Detektion und Verlaufsbeurteilung von Glaukompatienten als sinnvoll erwiesen. Jedoch können bei bis zu 40 % der RNFL-Scans Segmentierungsfehler aufgrund einer schlechten Aufnahmequalität auftreten . Eine manuelle Korrektur dieser Fehler ist zeitaufwendig und behindert den Arbeitsfluss im klinischen Alltag. Mit dem DL-Modell, das von Mariottoni et al. vorgeschlagen wurde, ließ sich die RNFL in OCT-Bildern mit schlechter Aufnahmequalität besser messen, als mit der Software des Herstellers . Neben der RNFL und BMO-MRW zeigen sich bei Fortschreiten eines Glaukoms jedoch auch Änderungen anderer anatomischer Strukturen, die auf dem OCT-Scan der Papille sichtbar sind. Zwar konnten Thompson et al. auf OCT-Scans mithilfe eines DL-Modells ohne Segmentierung der RNFL besser ein Glaukom diagnostizieren als mit der Nervenfaserschichtdickenmessung , welche eine segmentierungsunabhängige Klassifikation von gesunden Patienten und Patienten mit einem Glaukom ermöglicht. Dies limitiert im Umkehrschluss jedoch auch die klinische Anwendung des Algorithmus allein auf die genannten Patientengruppen. Im Gegensatz dazu sind Bildsegmentierungsalgorithmen wie der von Devalla et al. universell bei allen Erkrankungen des Sehnervenkopfes anwendbar, da sie nicht speziell auf die automatische Identifikation einer bestimmten Erkrankung, sondern allein auf eine optimierte Segmentierung einer Bildgebungsmodalität trainiert sind. Die genannte Arbeitsgruppe konnte mithilfe eines mehrschichtigen neuronalen Netzwerkes die RNFL, das prälaminare Gewebe, das retinale Pigmentepithel, die Aderhaut, die Lamina cribrosa und die peripapilläre Sklera automatisiert zuordnen und markieren . Die automatische Segmentierung konnte robust sowohl in gesunden als auch in für Segmentierungsfehler anfälligen glaukomatös veränderten Sehnervenköpfen durchgeführt werden . In einem weiteren Ansatz konnte die gleiche Arbeitsgruppe einen DL-Algorithmus entwickeln, der die Qualität von OCT-B-Scans unterschiedlicher Geräte so harmonisierte, dass in einem weiteren Schritt eine geräteunspezifische Segmentierung der Strukturen möglich war . Dies macht eine einfache Implementierung der Segmentierung von OCT-Scans im klinischen Alltag auf unterschiedlichen Geräten möglich und erleichtert die Diagnostik und Verlaufsbeurteilung von Erkrankungen des Sehnervenkopfes wie dem Glaukom.
Da eine glaukomatöse Optikusneuropathie im Frühstadium asymptomatisch verläuft, ist das Glaukom für ein Screening von großen Patientenkohorten geeignet. Jedoch liefert aktuell noch kein einzelnes Untersuchungsverfahren allein ausreichend valide Daten, um ein Glaukom sicher zu diagnostizieren. Für ein kosteneffektives Glaukomscreening wäre ein einzelner Test mit gleichzeitig hoher Sensitivität und Spezifität wünschenswert . Da die digitale Farbfundusfotografie weit verbreitet und kostengünstig ist, scheint eine automatisierte, KI-gestützte Bilddatenanalyse zur Detektion von glaukomatösen Optikusschädigungen auf dieser Bildgebungsmodalität sehr attraktiv . Für ein kosteneffektives Glaukomscreening wäre ein einzelner Test wünschenswert Die Klassifikation von glaukomatösen Optikusneuropathien auf Farbfundusfotos ist schon mit einer hohen Genauigkeit möglich. Li et al. konnten mithilfe von 48.116 Fundusfotos einen DL-Algorithmus mit einer Fläche unter der Kurve (AUC) von 0,986 zur Detektion von glaukomatösen Optikusneuropathien generieren . Phene et al. konnten mit ihrem DL-Algorithmus, trainiert auf 86.618 Fundusfotos, sogar 2 Glaukomspezialisten bei der Klassifikation einer glaukomatösen Optikusatrophie übertreffen . Für den Augenarzt ist die Logik hinter der Entscheidung des Algorithmus aufgrund der „Black Box“ von Algorithmen v. a. bei tiefen neuronalen Netzwerken jedoch nicht nachvollziehbar. Dies konnte die Arbeitsgruppe um Phene et al. mithilfe einer logistischen Regression jedoch umgehen und zeigen, dass sowohl für den Glaukomspezialisten als auch für den Algorithmus die gleichen Merkmale (CDR > 0,7, Papillenrandkerbe, Nervenfaserdefekt, Gefäßverlauf) am ausschlaggebendsten für die Klassifikation waren . Obwohl die Fundusfotografie der optimale Kandidat für ein Glaukomscreening zu sein scheint, können mit OCT-Scans zusätzliche Informationen wie die peripapilläre RNFL oder BMO-MRW über den Sehnervenkopf gewonnen werden. Medeiros et al. konnten zeigen, dass es möglich ist, einen Algorithmus darauf zu trainieren, automatisiert die Dicke der RNFL allein auf Fundusfotos zu quantifizieren . Sie trainierten ein tiefes neuronales Netzwerk mit Fundusfotos und den korrespondierenden SD(„spectral domain“)-OCT-Scans von 2312 Sehnerven. Das DL-System konnte auf einem Testdatensatz, bestehend aus 6292 Papillenfotos, die mittlere Dicke der RNFL mit einer absoluten Abweichung von 82,5 ± 16,8 µm vorhersagen. Dieses Modell übertraf sogar Augenärzte in der Klassifikation von Bildern von Sehnervenköpfen mit und ohne einen Gesichtsfelddefekt . Die gleiche Arbeitsgruppe konnte ähnlich vielversprechende Ergebnisse mit der Vorhersage der mittleren BMO-MRW allein auf Fundusfotos erzielen . Neben der Quantifizierung von RNFL und BMO-MRW auf Farbfundusfotos könnten andere KI-Ansätze zu einem tieferen Verständnis der Auswirkung von strukturellen Veränderungen des Sehnerven auf seine Funktion führen. Christopher et al. konnten mithilfe eines DL-Modells Gesichtsfelddefekte nur anhand von OCT-Scans des Sehnervenkopfes vorhersagen . Dieser Ansatz könnte im klinischen Alltag helfen, die Häufigkeit der zeitaufwendigen Gesichtsfelduntersuchung bei Glaukompatienten effektiver zu gestalten und gezielter anzuwenden. Mariottoni et al. konnten eine KI-basierte Zuordnung von strukturellen OCT-RNFL-Schäden zu Gesichtsfelddefekten bei einem Glaukom entwickeln. Dies ermöglicht ein tieferes Verständnis des Zusammenhanges von Struktur und Funktion und kann im klinischen Alltag bei der Beurteilung von RNFL-Defekten helfen .
Eine der größten Herausforderungen bei der Anwendung von KI ist es, robuste Ansätze auch für Erkrankungen mit geringer Inzidenz zu entwickeln. Teilweise ist bei diesen eine ausreichend große Anzahl an Patienten nur mit Datenbanken oder großen multizentrischen Studien zu erzielen. Trotzdem kann gerade die Abgrenzung einer Erkrankung mit hoher Inzidenz wie dem Glaukom zu anderen selteneren Sehnervenerkrankungen schwierig und zugleich klinisch hochrelevant sein. Dieser Fragestellung widmeten sich Yang et al. und konnten mit einem DL-Modell zwischen glaukomatöser und nichtglaukomatöser Optikusneuropathie auf 3815 Farbfundusfotos mit einer Sensitivität von 93 % und einer Spezifität von 81 % unterscheiden . Große Datensätze bei Erkrankungen mit niedriger Inzidenz zu generieren ist eine Herausforderung Vergleichsweise einfach ist für einen erfahrenen Augenarzt die Detektion einer Stauungspapille. Die direkte Ophthalmoskopie wird aber nur noch vereinzelt von Internisten oder Neurologen beherrscht. Jedoch zeigt sich bei 2,6 % aller Patienten mit neurologischen Symptomen eine Stauungspapille (STP), die Hinweis auf einen erhöhten Hirndruck sein kann . Wird diese übersehen und bleibt eine intrakranielle Hypertension unbehandelt, kann dies zu einem irreversiblen Nervenfaserdefekt mit konsekutiver Funktionsminderung führen. Aus diesem Grund wird in verschiedenen Kliniken und Notaufnahmen mithilfe der digitalen Fundusfotografie ein Bild des Sehnervenkopfes erstellt . Dieses Bild wiederum muss durch einen Augenarzt vor Ort oder per Telemedizin in einem anderen Zentrum beurteilt werden . Hier wäre ein robuster KI-Ansatz zur automatischen Detektion von Papillenödemen sehr hilfreich, jedoch sind große Datensätze bei Erkrankungen mit niedriger Inzidenz ein limitierender Faktor. Echegaray et al. konnten mithilfe eines ML-Algorithmus automatisiert auf Farbfundusfotos den Grad des Papillenödems nach Frisén mit einer gleichen Genauigkeit wie ein erfahrener Neuroophthalmologe klassifizieren . Akbar et al. konnten automatisiert mit einer Genauigkeit von 92,9 % eine Stauungspapille von gesunden Sehnervenköpfen auf Farbfundusfotos abgrenzen , ähnliche Ergebnisse wurde von Fatima et al. erzielt . Die verwendeten Datensätze waren mit einer Anzahl von jeweils unter 300 Fundusfotos in beiden Fällen nur gering. Auch ist die Unterscheidung zwischen gesund und krank zwar vielversprechend, entspricht jedoch nicht der Realität, in der mehr als 2 Alternativen vorhanden sind. So ist es klinisch teilweise schwierig, zwischen Papillenödemen und Pseudopapillenödemen – beispielsweise bei hyperopen Augen – zu unterscheiden. Mit einem ML-Modell konnten Ahn et al. zwischen geschwollenen Sehnervenköpfen aufgrund unterschiedlicher Optikusneuropathien, Pseudopapillenödemen und gesunden Sehnervenköpfen unterscheiden . Zusätzlich umgingen die genannten Autoren das Problem eines kleinen Datensatzes. Zum einen konnte mithilfe von Augmentierung der vorhandenen Daten die Diversität des Datensatzes erhöht werden, ohne tatsächlich neue Daten zu generieren. Dies minimiert das Risiko einer Überanpassung (engl. „overfitting“), was bedeutet, dass der Algorithmus nicht auf externe Daten anwendbar ist, da er zwischen gesund und krank anhand von Merkmalen unterscheidet, die nur in dem vorhandenen Datensatz, aber nicht auf einem weiteren externen Datensatz vorhanden sind. Zum anderen wurde ein vortrainiertes tiefes neuronales Netzwerk verwendet. Dadurch wurden trotz der geringeren Datenmengen gute Ergebnisse erzielt. Einen deutlich größeren Datensatz konnten Milea et al. in einer multizentrischen Studie generieren. Die Arbeitsgruppe trainierte einen DL-Algorithmus auf 14.341 Fundusfotos, von denen 2148 Papillen ein Papillenödem aufgrund einer intrakraniellen Hypertension hatten. Der Algorithmus konnte auf einem externen Datensatz von 1505 Farbfundusfotos mit einer AUC von jeweils 0,99 zwischen gesunden Sehnervenköpfen und Stauungspapillen sowie zwischen Stauungspapillen und anderen Pathologien des Sehnervenkopfes unterscheiden. Die Studie aus dem New England Journal of Medicine zeigt, dass auch bei Erkrankungen mit geringer Inzidenz mithilfe von multizentrischen Datensätzen robuste Algorithmen generiert werden können. Der Algorithmus der BONSAI-Arbeitsgruppe könnte bei Implementierung einen großen Einfluss auf die tägliche Routine in Notaufnahmen haben und maßgeblich die Versorgung von Patienten mit intrakranieller Hypertension durch eine schnellere Diagnostik und Therapie verbessern.
Die strukturierte Sammlung und Auswertung von Daten mithilfe von Big-Data-Analysen sowie die Verwendung maschinellen Lernens auf digitalisierten Daten hat zu einer Vielzahl an interessanten Anwendungen geführt. Mit diesen können Zusammenhänge besser erkannt und die Diagnostik und Verlaufsbeurteilung von Erkrankungen des Sehnervenkopfes erleichtert oder automatisiert werden. Eine Voraussetzung für die klinische Anwendung ist in Europa die CE-Kennzeichnung als ein Medizinprodukt und in den USA die Zulassung durch die Food and Drug Administration (FDA). In den nächsten Jahren wird sich zeigen, ob eine Implementierung dieser Algorithmen in den Alltag umgesetzt werden kann. Die Anwendung von künstlicher Intelligenz in der Augenheilkunde ist jedoch längst keine Zukunftsmusik mehr. Zuletzt konnte ein auf KI basierender Algorithmus zur Früherkennung einer diabetischen Retinopathie auf Fundusfotos eine Zulassung in Europa (2019) und in den USA (2018) erhalten .
Um eine automatisierte Klassifikation von Erkrankungen mit hoher und mit geringer Inzidenz zu ermöglichen, ist die strukturelle Erfassung von Bilddaten in Registern oder in multizentrischen Studien notwendig. KI(künstliche Intelligenz)-basierte Algorithmen können durch eine verbesserte Segmentierung von Fundusfotos und OCT(optische Kohärenztomographie)-Scans des Sehnervenkopfes die Diagnostik und Verlaufsbeurteilung von Sehnervenerkrankungen optimieren. KI-basierte Algorithmen können auf Farbfundusfotos besser ein Glaukom erkennen als ein Augenarzt und bieten deshalb einen interessanten Ansatz für ein Glaukomscreening von großen Datenmengen. KI-basierte Algorithmen könnten den Ablauf in Notaufnahmen durch eine automatisierte Diagnostik von Papillenödemen auf Farbfundusfotos optimieren.
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