Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Sign in through your institution Filter EvolutionThis issue Biological SciencesEvolutionary BiologyScience and search term Advance 10. 1111/j. 1558-5646. 2011. 01459. x Published: 01 February 2012 10. 1111/j. 1558-5646. 2011. 01459. x Select format. ris (Mendeley, Papers, Zotero). enw (EndNote). bibtex (BibTex). txt (Medlars, RefWorks) Download citation issue Biological SciencesEvolutionary BiologyScience and search term issue Biological SciencesEvolutionary BiologyScience and search term is known to generate an important cost for sexual reproduction (the famous “twofold cost of sex”). However, male–female differences may have other consequences on the evolution of sex, due to the fact that selective pressures may differ among the sexes. On the one hand, intralocus sexual conflict should favor asexual females, which can fix female-beneficial, male-detrimental alleles. On the other hand, it has been suggested repeatedly that sexual selection among males may help to purge the mutation load, providing an advantage to sexual females. However, no analytical model has computed the strength of selection acting on a modifier gene affecting the frequency of sexual reproduction when selection differs between the sexes. In this 2. Equilibrium rate of sex σ with log-normally distributed mutational effects in males and females. (A–C) the marginal distributions of (solid) and (dashed) are shown for different standard deviations, γ, of and (see text for more explanation), where in all cases, and. (D) the equilibrium rate of sex as a function of ρ (the correlation coefficient between and ), for γ= 0. 2 (solid line, black squares), γ= 0. 5 (dashed line, black circles), and γ= 0. 8 (dotted line, white squares). The lines simply connect simulation results and do not correspond to analytical predictions. The cost of sex c is 1. 2, all other parameters as in Figure 1. Open in new tabDownload slideThese mutation load arguments cannot, however, be used to predict the outcome of competition between genotypes coding for different rates of sex: indeed, facultatively sexual females can also benefit to some extent from the stronger purge occurring in males.

Output: pass


Input: Claim: VR in education can improve engagement and retention of complex concepts. [SEP] Text: 2%) that the variety of instruction style and learning opportunities was better than classroom lectures alone. This finding may be the result of students realizing that management is a subject best learned by doing and being engaged in the content of the course rather than passively receiving information. When assessing the course, most students (81. 5%) reported enjoying the course, a positive finding considering that most students who took the previous iteration of the course disliked it. pharmacy management course was redesigned to actively engage students and to be more relevant and applicable to the “real world. ” Students who participated in the study were accommodating and appreciative of the steps taken to improve the course and did not mind doing extra work they perceived as beneficial. Redesigning a pharmacy management course to be more relevant and interactive for students, however, places additional demands on instructors’ time and requires an openness to feedback and criticism. 1. Senft, S. L. ∙ Thompson, C. ∙ Blumenschein, K. Dual degree programs at the University of of PharmacyPharm Educ. 2008; 72 2. Kolawole, O. ∙ Pedersen, C. ∙ Schneider, P. . . . Perspectives on the attributes and characteristics of pharmacy executivesHealth-Syst Pharm. 2002; 59:278-281CrossrefScopus (8)PubMed3. Hermansen-Kobulnicky, C. ∙ Moss, C. Pharmacy student entrepreneurial orientation: a measure to identify potential pharmacist entrepreneursPharm Educ. 2004; 68 4. Filerman, G. ∙ Komaridis, K. The pharmacy leadership gap: diagnosis and prescriptionJ Educ. 2007; 24:117-134PubMed5. Latif, D. Using emotional intelligence in the planning and implementation of a management skills coursePharm Educ. 2004; 4:81-89CrossrefScopus (25)6. Holdford, D. Managing oneself: an essential skill for managing othersJ Assoc. 2009; 49:436-445Full Text(PDF)Scopus (2)7. Jungnickel, P. ∙ Kelley, K. ∙ Hammer, D. . . . Addressing competencies for the future in the professional curriculumPharm Educ. 2009; 73 8. Garrison, D. Critical thinking and self-directed learning in adult education: an analysis of responsibility and control issuesQ.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: In our results, both geographic location and species impacted gut microbiota to varying degrees. Accordingly, spiders were divided into three groups and fed on one diverse ant subset, to assess if variations in feed created variations in spider gut microbiota. We used Illumina MiSeq sequencing of 16S rRNA genes to test whether spiders that ate different ants would also exhibit a difference in microbial composition. Our results demonstrated that the gut microbiota in all spiders maintained a consistent composition, with Pseudomonas as the dominant genus, which is known for its metabolic diversity and its ability to colonize many niches, including the gut [47]. To ensure the abundance of Pseudomonas did not result from contamination, we performed negative extraction and PCR control, which was visualized using a 2% agarose gel. Our results found no band for the negative extraction and PCR control and an obvious band for the positive control. The presence of this OTU makes it likely to be unintentionally sequenced, however, this OTU accounted for more than 90% of total sequences in our experimental samples. Our results indicate that the high percentage of Pseudomonas in our study was not due to contamination. Compared with common spiders living in cotton fields (where 237 genera were detected at the genus level [27]), C. campanulata could maintain a relatively simple gut environment. This could be due to its limited diet. Intriguingly, Badumna Longinqua, whose diet includes crickets and fruit flies, showed the opposite result [48]. And its gut microbiome experiences pronounced temporal fluctuations and slowly approaches its initial state after more than 658 h. The difference between the results obtained by our study and that of previous research could be due to several factors, including the different spider species used and their rearing conditions. Their prey typically contains a rich microbiome, and the spiders sometimes ingest and maintain certain microbes from prey in their gut. This mimics a pattern of stability in the spider’s gut microbiota. Additionally, spider habitat and taxonomy could influence their gut microbiota [49], however, without knowing the natural state of the spider microbiomes obtained from the field, we can only conclude that the gut bacterial communities in groups fed different diets were similar, despite differences in their nutrients or ingested microbes. Comparing the composition of the microbial community between predators and prey at the intraspecific level, we found that C.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Hadany and Beker (2007) used deterministic simulations to model competition between obligate and partial sexuals. They found that for high mutation rates and strong sexual selection, obligate sex may be favored against rare sex (with a twofold cost of sex); however, they did not explore what the evolutionarily stable (ES) rate of sex would be for the different parameter values. In this 1. Hence, we would expect sexually produced offspring to evolve to a male-biased sex ratio (we thank for pointing this out). Although the question of the joint evolution of the sex ratio and the investment into sex is interesting, we leave it for future studies. The level of sex is modulated by a modifier with two alleles, m and M, where females of genotype mm, Mm, and MM engage in sex at frequency σ, σ+hMδσ and σ+δσ, respectively (δσ thus denotes the effect of the M allele on the rate of sex, and hM measures the dominance of M over m). Two alleles a and A also segregate at the selected locus, and we will write the relative fitness of aa, Aa, and AA females as 1, and and the relative fitness of aa, Aa, and AA males as 1, and ( and can be negative). “Fitness” stands for the reproductive output of an individual: female fitness may be seen as the total amount of resources available for reproduction (K above); selection may act either on survival (K= 0 if the female dies) or on fertility. The fitness of a male measures its overall success at fertilizing ovules, which may in turn depend on its relative survival, relative fertility (i. e. , total number of gametes produced, in which case we assume random fusion between male and female gametes), or mating success (in which case we assume polygyny). Finally, r denotes the recombination rate between the two loci. The dynamics of the system can be studied from the recursions for the 10 diploid genotype frequencies (nine independent variables) in females and in males (which gives 18 equations); these recursions are given in 0. 001), selection parameters and numbers of loci (results not shown).

Output: pass


Input: Claim: Virtual labs in VR can offer a safe alternative for learning about hazardous materials. [SEP] Text: Virtual hearings have the potential to allow parties, witnesses, and experts to attend or participate in hearings that, for a range of reasons, they may otherwise have been unable to. Where, for example, it is the cost of travel to a hearing venue, particularly one that is overseas, which proves to be prohibitive, virtual hearings offer an accessible alternative. Easier access may prove a significant benefit for, by way of example, public interest groups who wish to intervene in investment disputes by way of “amicus curiae” submissions. To some extent, virtual hearings may thus permit international arbitration to become more inclusive by facilitating voices that might not otherwise be heard. This could include not only the voices of parties who might otherwise be bound by certain geographical, medical, financial, or legal constraints preventing their physical attendance at a hearing, but also witnesses and experts, potentially even extending to counsel and arbitrators. In sum, virtual hearings may offer a more level playing field in international dispute resolution. Of course, virtual hearings are not a cure-all in respect to other inequalities present in the international legal system, such as a lack of access to legal education or adequate legal representation. 2. 3 “aspects of the hearing room drama might be lost,”15 virtual hearings may offer clients a preferable hearing experience, at least in some respects. 16 In an in-person hearing, a client’s ability to communicate with her/his legal team and/or to assess the arbitrator(s)’ reaction instantaneously, may be curtailed by room layout/configuration, and clients (often sat behind counsel) can feel disconnected from the proceedings, particularly if they do not have a clear view of all the advocates or the tribunal. 17 In virtual hearings, the experience of the hearing room is the same for all. 18 Anecdotally, many clients appear to view this positively: they have the same visibility over the proceedings as all other participants,19 leading them to feel “much more connected with the proceedings. ”20 As for other participants, analysis of the published by the Forum of suggests that, in the eyes of judges and arbitrators, oral submissions and arguments are no less effective when delivered via video than they would be in person, as the insight and assistance provided to the judge is not hindered. 21 An improved client (and/or arbitrator) experience at hearings is perhaps a more unexpected benefit of virtual hearings.

Output: pass


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: campanulata could maintain a relatively high level of Pseudomonas, which has been reported to produce tannase to detoxify or tolerate tannis in food [50, 51]. Interestingly, we detected no Acinetobacter in the spiders, despite its prevalence in the feed ants. This implies that not all microorganisms obtained from food can successfully colonize a spider gut, suggesting the host can prevent the colonization of new bacteria, possibly as a way to defend against pathogens [52]. In most cases, the intestinal bacterial community is short-lived and opportunistic, with widely diverse bacteria stemming from a constantly changing environment [53–55]. This stabilization of gut microbial diversity could be due to microbial competition or interference following the introduction of exogenous bacteria [56], however, further investigation is required to confirm either of these hypotheses. The life history of spiders has rarely been studied due to a lack of reliable rearing methods and the difficulty of providing an artificial diet. Since spiders are primarily carnivorous, they require specific kinds of prey. Divina M. Analin et al. found that the survival rate of sac spiders was influenced by different artificial diets [57]. Several studies have demonstrated that the animal gut microbiome is important for nutritional absorption [58], while the diet-altered gut microbiota of spiders can influence its development and survival rate under artificial rearing conditions. Future work assessing whether or how gut microbiomes affect spider survival should be the focus of future studies. In conclusion, when we analyzed the microbial composition in three spider groups with different diets, we observed no dynamic changes in gut microbiota. This indicates that diet has minimal effect on gut microbiota of C. campanulata, despite variations in feed microbial community and nutrients, ensuring normal physiological function and development. It is worth noting that identifying a mechanism by which this action takes place was beyond the scope of this study. Future studies should include additional types of prey and spiders to analyze these results on a larger scale and outline a potential mechanism for host regulation in gut microbial homeostasis. The analysis of spiders’ intestinal microbiota in conjunction with soil layer microorganisms analysis is also worthwhile endeavor, to determine if the dominant microorganisms in the spiders’ gut microbiota are a result of their environment. This work provides a blueprint for future investigation into the gut microorganisms of spiders and highlights the potential existence of a unique gut modulatory mechanism.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: –study the case of mutation–selection balance we assume that allele A is disfavored (, ), and generated at a small rate u per generation by mutation from allele a. Deleterious mutations favor sex when their deleterious effect is stronger in males than in females (), because sexual females benefit from the stronger purge occurring in males (Agrawal 2001; Siller 2001; Hadany and Beker 2007). The strength of this effect is given by equation (21), with and (assuming pA is small, while and are not too small). As above, a local stability analysis gives the same result as the QLE to the first order in δσ (for arbitrary c), whereas for c= 1 one can obtain an expression for the leading eigenvalue λ valid for any δσ. 35 (assuming pA is small). Assuming c= 1 +O(ξ2) (weak cost of sex) introduces the same term as on the last line of equation (32). Note that equation (35) is not defined when Mm females are fully asexual (hMδσ=−σ); in this case, the leading eigenvalue is given by 36 showing that selection on the asexual mutant vanishes if or if (in which case ). When c > 1, indirect selection will generally be rather weak relative to the cost of sex when selection occurs at a single locus, but may become important if many loci are subject to deleterious mutations with stronger effects in males. In the following, we use our previous results to determine what the ES rate of sex should be in the limit of an infinite number of loci with identical mutation rate and selection parameters (, ). We assume a fixed mutation rate per haploid genome U, so that in the infinitesimal limit the mutation rate per locus (u) and the equilibrium frequency of each deleterious allele (pA) are both very small. In this case, selection against sex generated by dominance in females (sdomM) becomes negligible relative to selection generated by differences in selection between males and females (sdiffM), because the latter is proportional to pA, whereas the former is proportional to p2A (see eqs. 17 and 18). Although linkage will affect sdiffM, one cannot integrate the QLE expression over a continuous genome because sdiffM diverges as r tends to zero (see eq. 21).

Output: pass


Input: Claim: VR is increasingly being adopted as a supplementary learning tool in classrooms. [SEP] Text: in Self-Skip to content Home Editors/advisors -– A Tool for in Lower-tier. , & Kinoshita, Y. (2019). Self-assessment surveys – A tool for independent learning in lower-tier dependent classrooms. Studies in Self-Journal, 10(3), 296-318. Download paginated PDF version project took place over an academic year, using self-assessment surveys as a unique tool for guiding students to engage in the learning process, with the goal of improving their motivation and overall awareness in second language studies. The participants (n=94) were first year students from a private Japanese university from the departments of Aerospace and (n=11), Architecture (n=11), Sciences (n=49), (13) and (n=10). The surveys were bookended with two similar Likert-scaled questionnaires. The first was used as a baseline of participants’ initial beliefs, motivation and overall awareness regarding their L2 education, while the second was used as a comparison, through a paired sample T-test, to mark any changes. The self-assessment survey sought to elicit students’ knowledge and confidence in areas of vocabulary, use of English and usage of the target language, with a survey report given to everyone prior to unit assessments. The following is a report on the effect self-assessment surveys had on students’ motivation and overall awareness when used as a learning tool promoting autonomous learning for teachers and advisors wishing to empower students to take a more prominent role in their L2 education. Keywords: self-assessment, motivation, learner autonomy, CALL Japanese students are traditionally exposed to a passive learning environment from the beginning of their primary education through secondary education and even throughout much of their post-secondary education, a characteristic Aspinall (2008, p. 151) labeled “Deference to the authority of the teacher”. As a result of recent reforms by the Ministry of Education, Culture, Sports, Science and Technology, schools are working to “Enrich educational content in relation to nurturing individual’s sense of Japanese identity,” (MEXT, 2014, p. 1) and attempting to change the view of Japan being a collectivist society.

Output: pass


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: 27(8):1848–1859 (2016) Diversity and resilience of the wood-feeding higher termite Mironasutitermes shangchengensis gut microbiota in response to temporal and diet variations. 6(22):8235–8242 (2004) Census of the bacterial community of the gypsy moth larval midgut by using culturing and culture-independent methods. Microbiol 70(1):293–300 (1998) Effects of food nutrient content, insect age and stage in the feeding cycle on the FMRFamide immunoreactivity of diffuse endocrine cells in the locust gut. of (201):2971–2979 Józefiak D, Józefiak A, Kierończyk B, Rawski M, Świątkiewicz S, Długosz J, Engberg RM (2016) Insects – A natural nutrient source for poultry – A review. Annals of 16(2):297–313 (2012) Highly similar microbial communities are shared among related and trophically similar ant species. 21(9):2282–2296 (2017) Microbial composition of spiny ants (Hymenoptera: Formicidae: Polyrhachis) across their geographic range. BMC 17(1):96 (2020) Immune challenge reduces gut microbial diversity and triggers fertility-dependent gene expression changes in a social insect. BMC Genom 21(1):816 (2020) Are you what you eat? A highly transient and prey-influenced gut microbiome in the grey house spider Badumna longinqua. 29(5):1001–1015 -Vesbach CD (2012) Do diet and taxonomy influence insect gut bacterial communities? 21(20):5124–5137 (2012) Experience matters: prior exposure to plant toxins enhances diversity of gut microbes in herbivores. 15(9):1008–1015 Xue W, Zhi-Shu X, Zhi-Bin Z, Hong-(2008) Insect seed predation and its relationships with seed crop and seed size of Quercus mongolica. Sinica 51:161–165 (2004) The gut bacteria of insects: nonpathogenic interactions. Entomol 49:71–92 (2017) Caterpillars lack a resident gut microbiome.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: However, simulation results obtained for a map length of R= 10 morgans are often very close to results obtained under free recombination. Assuming r= 1/2 between each pair of loci, equation (21) gives 37 where the sum in the last equation is over all selected loci. Finally, from equation (27) we have 38 where U is the genomic mutation rate per haploid genome (recall that ). The ES rate of sex corresponds to the value of σ for which scostM+sMdiff= 0, where (from eq. 16) 39 As long as selection is stronger in males than females (), this ES frequency of sex is predicted to be positive. Comparing equations (30)–(31) with equations (37)–(38), one can remark that sex-specific dominance () has more importance in the case of sexually antagonistic mutations (due to the fact that under weak selection polymorphism can be maintained only if ) than in the case of deleterious mutations, where dominance simply reduces the effective strength of selection to and. We compared analytical predictions with individual-based simulation results for the case of sexually antagonistic selection and the case of deleterious mutations maintained at mutation–selection balance with different selection coefficients in males and females. The simulation program (written in C++ and available on request) represents a population of constant size N. Individuals are diploid and possess two copies of a chromosome of map length R (all results shown in this 1. The program starts with all chromosomes free of mutation, during the first 2000 generations all females have the same rate of sex σinit (we used both σinit= 0. 01 and σinit= 1). Then, mutations at the modifier locus (which is located at the midpoint of the chromosome) are introduced at a rate 10−4 per generation. Each time, with probability 0. 5, the rate of sex coded by the new allele is sampled from a uniform distribution between 0 and 1, whereas with probability 0. 5, it equals the value of the allele before mutation plus a random number between −0. 1 and 0. 1 (if the new rate of sex is negative it is set to zero, whereas if it is greater than 1, it is set to 1). The rate of sex of a female is simply the average of its two alleles at the modifier locus (no dominance).

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Stepped care for depression and anxiety: from primary care to specialized mental health care: a randomised controlled trial testing the effectiveness of a stepped care program among primary care patients with mood or anxiety disorders protocol Open access Published: 05 June 2009 Stepped care for depression and anxiety: from primary care to specialized mental health care: a randomised controlled trial testing the effectiveness of a stepped care program among primary care patients with mood or anxiety disorders Wike Seekles1,4, Annemieke van Straten1,4, Aartjan Beekman2,4, Harm van Marwijk3,4 & …Pim Cuijpers1,4 Show authors 1610. BackgroundDepressive and anxiety disorders are highly prevalent [1]. Currently, depressive disorders are the fourth disorder worldwide in terms of disease burden, and will be the disorder with the highest disease burden in high-income countries by 2030 [2]. Anxiety and depression can cause serious functional impairment, reduced quality of life [3, 4], high levels of public service usage and huge economic costs [5, 6]. Comorbidity is high among psychiatric disorders in general [1]. Almost half of the people who have ever suffered from a psychiatric disorder have had more than one. Comorbid anxiety is the rule rather than the exception with up to 60% of the patients with major depressive disorder also suffering from an anxiety disorder [7]. Because of this high comorbidity and the difficulties in distinguishing the two disorders without extensive diagnostic interviews, this study includes individuals with depressive disorders as well as with anxiety disorders. There are ongoing discussions regarding the effectiveness of the management of common mental health problems in general practice settings. Both anxiety disorders and depression can be treated effectively by pharmacotherapy as well as psychotherapy [8–15]. Although evidence based clinical guidelines are available, initiation and adherence to effective treatment are usually poor [16–19]. Mood and anxiety disorders often remain unrecognised and therefore untreated in primary care [20]. Furthermore, it has been demonstrated that even when depression has accurately been recognized, still only few patients receive adequate care [19]. According to several studies [21–23] many patients receive antidepressants immediately after the diagnosis was determined, however, only few patients receive adequate dosage and duration of (antidepressant) medication. Approximately 30% of depressed primary care patients stop using antidepressant medications within the first month of treatment, while only 40% reach the recommended therapeutic dosage of antidepressant medication [24].

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: 114(36):9641–9646 (2016) Microbial communities of lycaenid butterflies do not correlate with larval diet. 7:1920 (2016) Variability of bacterial communities in the moth Heliothis virescens indicates transient association with the host. PLoS One 11(5):e0154514 (2016) Inoculation of tannin-degrading bacteria into novel hosts increases performance on tannin-rich diets. 18(6):1720–1729 Amalin DM, Peña (2001) Comparison of the Survival of of on Natural and Artificial Diets. Journal of Arachnology 29(2):253–262 (2019) Extracellular nutrient digestion and absorption in the insect gut. Res 377(3):397–414TablesTable 1 Richness and diversity estimation (Mean ± SEM) of the bacterial community in the gut of six groups. richness indices Species diversity indices ACE Chao1 Shannon diversity Simpson diversity LN_WH 275. 37±60. 72 238. 20±37. 70 0. 45±0. 08b 0. 84±0. 02a TC_WH 195. 98±78. 32 198. 23±78. 20 0. 80±0. 24b 0. 77±0. 06a TC_LY 280. 55±97. 26 278. 61±39. 20 2. 10±0. 72a 0. 41±0. 13b CC-LN_WH 331. 10±62. 28a 206. 76±30. 74 0. 39±0. 07 0. 87±0. 02 CC-TC_WH 152. 03±31. 98b 114. 44±23. 18 0. 55±0. 28 0. 80±0. 10 CC-TC_LY 268. 50±53. 62ab 233. 65±60. 98 0. 48±0. 06 0. 84±0. 01 Letters indicate significant differences across regimens (P<0. 05). Supplementary FilesSupplementaryFigure1. tifThe content of protein (a), trehalose (b), TG (c), and glucose (d) in Tetramorium caespitum of different locations. TC_LY, T. caespitum Luoyang; TC_WH, T.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: The program runs for 2 million generations and records the average values of modifier alleles in males and females every 100 generations. The equilibrium rate of sex is obtained by averaging over the last 1. 9 × 106 generations. Figure 1 shows the average rate of sex measured during simulations as a function of the cost of sex c, for stronger (left) and weaker (right) selection. In both cases, the initial rate of sex was σinit= 1; however, we ran additional simulations starting from σinit= 0. 01 (for the same values of U, and c as in Fig. 1), which gave identical results. Figure 1 shows that stronger selection in males (white squares) can greatly increase the ES rate of sex when the cost of sex c is not too high. Furthermore, it shows that the prediction obtained from equations (37) and (39) is often rather good (solid curves), again when c is not too high (note that the analytical model assumes weak modifier effects, while in the simulations mutants coding for any rate of sex between 0 and 1 can appear at every generation). Additional simulation results for different values of U and R are given in the 2 (Fig. S1), showing that analytical predictions remain correct for higher values of U, as long as the genome map length is not too small. Figure 1. Equilibrium rate of sex σ as a function of the cost of sex c. Simulation results (points) are compared to analytical results with and without sex differences in selection using equations (37)–(39) and (41), respectively. Left: (black squares, dotted curve), (black circles, dashed curve), (white squares, solid curve). Right: same for (black squares, dotted curve), (white circles, dashed-dotted curve), (white squares, solid curve). Other parameter values are U= 1, N= 20, 000, map length R= 10, 2 × 106 generations (in simulations). Error bars are smaller than the size of symbols. Open in new tabDownload slideWhen sdiffM equals zero but deleterious mutations still favor sex due to finite population size effects (N is set to 20,000 in the simulations).

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: It is also important to note that the majority of primary care patients prefer psychotherapy as a treatment [25]. Clearly, the gap between research findings and clinical practice is wide in the management of depression in primary care [26]. Through its objective of initiating interventions at the right time and as adequately as possible, the stepped care model could provide a solution for the problem of applying effective, evidence based care for depression and anxiety. Care is offered not earlier or more intense than necessary and not later or less intense than needed [27, 28]. In a stepped care model, all patients start with an evidence-based treatment of low intensity as a first step. Progress is monitored and patients, who do not respond adequately can 'step up' to a subsequent treatment of higher intensity [29]. An important feature of the stepped care model is that the model is self-correcting. Self-correcting means that the results of treatments and decisions about treatment provisions are monitored systematically and where necessary changes are made ('stepping up') if current treatments are not achieving significant health improvement [27]. A care manager coordinates a stepped care program, preferably a paraprofessional who supports the primary care clinic handling psychiatric problems. Netherlands the most likely candidate for this role is a psychiatric nurse. This care manager coordinates the monitoring of the patients, provides the first treatments in the stepped care model and refers the patient to the appropriate mental health care specialist if necessary. Although the stepped care model seems to be a promising care model [27–30] to increase the effectiveness and efficiency of the mental health system, its effectiveness compared with care as usual (CAU) has not been studied yet [27–29]. We will describe the protocol of a study on the (clinical) effectiveness of this program versus care as usual with patients who are diagnosed with a minor or major mood and/or anxiety disorder. MethodsStudy designThis study is a randomised controlled trial. We recruit patients by screening all patients of the participating GPs during an inclusion period of 1,5 years. All patients with a positive screen for depression and/or anxiety are screened again after 4 to 6 weeks. Those with a second positive screening (baseline) are contacted by telephone for a diagnostic interview. During this interview all in- and exclusion criteria are checked. Those who are eligible for participation are being asked for informed consent to participate in the study.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: -and : Algebra-Physics: Calculus-and : impact of diet and antibiotics on the gut microbiome Author(s): Birgit M. Prüβ*Published online: 29 Aug 2021 Courses: Microbiology Keywords: microbiome environmental control host response metabolites 2071 total view(s), 233 download(s) Login to access supporting documents 2019. The impact of diet and antibiotics on the gut microbiome. CourseSource. does the survival and growth of any microorganism in a given environment depend on its metabolic characteristics? do microorganisms, cellular and viral, interact with both human and non-human hosts in beneficial, neutral, or detrimental ways? How do microorganisms interact with their environment and modify each other? a unique active learning experience, students will use a simple simulation to analyze the gut microbiome at multiple systematic levels (e. g. phylum, genus, species) and apply the newly gained knowledge in a context that is relevant to human health. They will identify metabolic pathways and products that contribute to the microbiome as a system and learn about the impact of microorganisms on their bodies. The learning objectives are in alignment with the Framework from the for Microbiology. The mimicking of the antibiotic treatment is an example of Choose a perturbation to a novel environment, and predict the change to the resident microbial community. under Systems. The determination of the bacterial metabolic byproducts that the bacteria excrete falls under How does the survival and growth of any microorganism in a given environment depend on its metabolic characteristics? under Metabolism. The investigation of the human host response to a certain diet covers Describe how the human biome influences the host human organism. , also under Systems.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Specifically, finite population size generates an excess of heterozygotes at each locus (in particular when σ is low), which favors sex when mutations are additive (Roze and Michod 2010), and it also generates negative linkage disequilibria among loci (the Hill–Robertson effect) that also favor sex through selection for recombination (e. g. , Otto and Barton 1997, 2001; Barton and Otto 2005; Keightley and Otto 2006; Roze and Michod 2010). We can use results from a previous QLE model (Roze and Michod 2010) to obtain an expression for indirect selection generated by finite population size when. Although this expression is a very complicated function of the parameters, it can be shown that when U is high and σ is low, indirect selection is dominated by selection for recombination (when ), which is approximately 41 with σeff=σ/[c(1 −σ) +σ]. The nonsolid curves in Figure 1 show that the ES rate of sex obtained using this expression provides an accurate prediction, unless again the cost of sex is high (eq. 41 and the complete expression obtained from Roze and Michod [2010] give almost undistinguishable curves—not shown). Increasing c decreases the effective rate of sex, which makes the QLE approximation less robust. Note that Roze and Michod (2010)'s model represents a hermaphroditic population (and not a dioecious population as simulated here); however, simulations show that the ES rate of sex is very similar in hermaphroditic and dioecious populations when as long as the total population size remains the same (results not shown). To investigate the effect of variation in the selective effects in males and females, we used a modified version of the program where for each new mutation and were sampled from a bivariate probability distribution: more precisely, we sampled and from a bivariate Gaussian distribution, where and have means standard deviations and where ρ measures the correlation between and ( and thus follow lognormal distributions). Figure 2 shows results for choosing values of and so that and (as in Fig. 1 left). We considered three different values of γ (0. 2, 0. 5, and 0. 8), that generate distributions of and with different degrees of overlap (panels A–C, Fig. 2).

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: Reliability and validity of depression anxiety stress scale (DASS)-21 in screening for common mental disorders among postpartum women in access Published: 24 May 2022 Reliability and validity of depression anxiety stress scale (DASS)-21 in screening for common mental disorders among postpartum women in Moya1,2, Leila M. Larson3, Robert C. Stewart4, Jane Fisher5, Martin N. Mwangi1,2 & …Kamija S. Phiri1,2 Show authors BMC Psychiatry 11. 3% and 14. 8% had depression and anxiety diagnoses respectively using SCID. The overall Cronbach’s alpha for the DASS-21 scale was 0. 74. The DASS-21 subscales had Cronbach’s alpha values of 0. 66, 0. 29 and 0. 52 for depression (DASS-D), anxiety (DASS-A) and stress (DASS-S), respectively. The ordinal alpha for DASS-D, DASS-A and DASS-S subscales were 0. 83, 0. 74 and 0. 87, respectively. The area under the ROC curve was 0. 76 (95% CI: 0. 61; 0. 91) for DASS-D and 0. 65 for DASS-A. At a cut-off point of one or more, the sensitivity and specificity for DASS-D were 69. 2% and 75. 5%, whilst DASS-A was 52. 9% and 75. 5%, respectively. Pearson correlation coefficient for the association between DASS-D and EPDS was r = 0. 61, p < 0. 001. -21 had good internal reliability (Cronbach’s alpha), and its ordinal alpha demonstrated good internal reliability for all its sub-scales. Regarding the criterion validation, only the DASS-D and EPDS demonstrated a satisfactory ability to discriminate cases from non-cases. Our findings suggest that health practitioners can use DASS-D as an alternative tool in screening depression as it has fewer questions than EPDS. reports BackgroundMaternal mental health problems remain a global public health challenge. Approximately 13% of women who have given birth in high-income countries suffer from common mental disorder (CMD), primarily depression and/or anxiety [1].

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: completing the exercise, students will be able to: Identify several of the nine phyla that contribute to the gut microbiome and name the two predominant ones; Describe how diet impacts the gut microbiome and compare the composition of the gut microbiome between different diets; Describe how antibiotic treatment impacts the gut microbiome and understand how this leads to infection, for example by Clostridium difficile; Trace the response to a change in diet, starting with i) changes in the composition of the microbiome, followed by ii) changes in the bacterial metabolic pathways and the respective excreted metabolic products, resulting in iii) a molecular response in the host intestinal cells, and eventually iv) resulting in human disease; Improve their ability to read scientific literature; Express themselves orally and in writing; Develop team working skill 1. The pre-test is designed to encourage students to read the paper (15), and the questions contain information that the students will need during the class session. Students receive one point per correct answer. The test can be administered through an online System to save in class time. Table 1. Pre-test. This table lists questions for a pre-test with examples of correct answers. The instructor measures learning formatively during the class activity by listening and responding to the student's report of their findings. By constructing a Table (Table 3) on the board, instructors can provide feedback on the information that the students are providing. This kind of assessment gives students the opportunity to compare their understanding with what the instructor identifies as both important and correct. The follow-up assignment is summative, in which students return to the Portune paper (15) and write about the molecular response to changes in diet in the host intestinal cells. 480/680 course enrolls students from different majors and academic levels. The course is required for Microbiology majors, but students from majors such as Biology, Soil Sciences, Pre-Pharmacy, Pre-and Bioinformatics, and several Engineering disciplines routinely attend. Likewise, the academic level is usually junior or senior, but first year graduate students at MS or Ph. D. level are included. In addition to the diversity of fields of study and academic level, students vary in age, race, national background and possibly other characteristics that may not be visible to the instructor. The activity involves individual and group tasks. Small group tasks are considered cooperative learning techniques and have been described as active learning exercises that foster student learning (20).

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: For each of these bivariate distributions, we explored the effect of the correlation coefficient ρ on the ES rate of sex. As shown by Figure 2, the variance of the distributions and the correlation coefficient have little effect on the ES rate of sex: when the overlap between the distributions of and is substantial (γ= 0. 8), the rate of sex decreases slightly for low ρ (likely due to the fact that some mutations have stronger effect in females than in males and thus disfavor sex), but the effect is minor. Equation (37) predicts that selection occurring only in males (, ) should favor sex. This stems from the fact that females who engage in sex more often tend to produce fitter sons, and thus have a higher fitness through sons. This effect vanishes, however, when one of the genotypes is completely asexual (as shown by eq. 36): the advantage of producing better sons disappears when females never (or rarely) engage in sex. Figure 3 shows simulation results for. Here, the simulation program was constrained so that mutations at the modifier locus only change the rate of sex by a small value up to ±0. 02 (starting from σ= 1). In this case, simulation results (squares) fit the analytical prediction obtained from equation (19) (curve). When maximum mutational steps at the modifier locus are increased from 0. 02 to 0. 05, however, the simulations become absorbed at σ= 0 when c≥ 1. 2, at which point males disappear (in this case the simulation has to be stopped before 2 × 106 generations, because mutations accumulate rapidly in the population). This result may seem surprising at first: for example, for c= 1. 2, Figure 3 shows that the ES rate of sex is around 0. 5, in which case asexual mutants cannot occur when mutational steps are 0. 05; however, Figure 4 shows that an evolutionary branching occurs, leading to a first lineage evolving toward higher rates of sex and a second lineage toward lower rates of sex. This branching represents a group of male specialists (top branch), whose genomes are relatively purged of mutations and who have relatively high male mating success, and a group of female specialists (bottom branch), who bear a higher mutational load but a lower cost of sex.

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The situation is worse in low and lower-middle-income countries (LMICs), where one in five (19. 8%) women who have recently given birth experience a CMD [1]. Untreated CMDs reduce maternal level of functioning [2] and may consequently impair mother-infant interaction [3] and infant cognitive development [4]. Currently, there is a low detection and treatment rate of CMDs in LMICs. There are several reasons for this. First, perinatal mental health for women living in LMICs is only an emerging area of interest for researchers and policymakers. The international agenda has moved beyond survival to understand what is needed to enable women (and infants) to thrive [1]. Second, it has been thought that women living in LMICs are protected from experiencing postpartum mental disorders by social and traditional cultural practices during the postpartum period, which has not been substantiated [1]. Third, the low detection and treatment rate of CMDs in LMICs might be attributed to a lack of culturally sensitive screening tools that are simple to use. Lastly but importantly, in most LMICs, perinatal mental health screening and treatment are yet to be integrated into a routine healthcare package of mother–child dyadic interventions offered when a mother attends well-baby clinics [5]. Several perinatal CMD screening tools such as (EPDS) [6], WHO Self-[7], Questionnaire-9 [8], and Post-Scale [9] have been validated for screening perinatal mental disorders in Malawi. However, these individual tools are not designed to screen for multiple separate common mental disorders (e. g. , depression, anxiety, PTSD). Having a screening tool that is free to use, short in assessment time, and used to screen for more than one CMD is more appealing in a resource-constrained setting. This study aimed to assess the reliability and validity of the Depression, Anxiety, and Stress Scale-21 items (DASS-21) for screening common mental disorders among postpartum women in Malawi.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Five to twenty yellow and/or orange lentils will be added to some of the bags. The lentils represent C. difficile; the green lentils simulate the toxin producing bacteria and the yellow ones the non-toxin producing C. difficile. Keep in mind that Table 3 is set up for six groups of students. If you have more groups, you can duplicate some bags. It is important to have different bags because each bag represents a different diet and different gut microbiome. Table 3A. Formative Assessment. This table is an example of the compilation of student information received by the instructor that can be assembled on the board. It connects information from the Koenig (16) and Portune (15) papers with the different types of pasta. Table 3A is the version of the Table that the instructor will initially construct on the board. Table 3B. Formative Assessment. This table is an example of the compilation of student information received by the instructor that can be assembled on the board. It connects information from the Koenig (16) and Portune (15) papers with the different types of pasta. Table 3B is the final version after students helped the instructor fill in the blanks. With the help of the students, the instructor fills in the blanks of the Table. Specifically, the different types of pasta (e. g. long) represent different types of bacteria (e. g. Bifidobacteria). Since differences in diet (e. g. dairy) give rise to the occurrence (indicated by a ‘+’) of specific types of bacteria (e. g. Bifidobacteria), each pasta bag is assembled in a way that only pasta types that belong to the respective diet (as indicated by +) are included in the bag. A (-) indicates that these types of pasta are not to be added to the bags and that these types of bacteria are not predominant under the respective diet. Mark the bags with the diet (e. g. dairy). Note, that this Table can also be used to guide the instructor through the assembly of the bags prior to class. (50 ) Distribution of the pasta bags. Every group of students receives one pasta and one bean bag prior to beginning of class. Analysis of the pasta bags (10 minutes). Students will analyze the content of the pasta bag, sorting the pasta by color and shape.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: When this second lineage reaches σ= 0, males within the first lineage are no longer able to mate with receptive females in the second lineage, and the first lineage is driven extinct (due to the cost of sex). With mutational steps of 0. 02, no branching occurs (although we cannot exclude the possibility that branching would occur if the simulation were run much longer). Figure 3. Equilibrium rate of sex σ as a function of the cost of sex c, for (other parameters are as in Fig. 1). Solid curve: analytical prediction from equations (37)–(39). Dots: simulation results, where mutations at the modifier locus change the rate of sex by a small value up to ±0. 02 (white squares) or ±0. 05 (black circles). Note that because evolution proceeds more slowly than when mutant modifier alleles can code for any rate of sex, σ is averaged over the last 1. 5 × 106 generations (instead of the last 1. 9 × 106 generations as in Fig. 1), unless σ goes to zero. Open in new tabDownload slide Figure 4. Evolutionary trajectories when selection acts only on males: these trajectories correspond to the points in Figure 2 for c= 1. 2 and maximum mutational steps of ±0. 02 (left) and ±0. 05 (right). Each modifier allele whose frequency is above 0. 1 is represented by a point (darker points correspond to higher frequencies); the line shows the proportion of males in the population. Time is in generations (frequencies are measured every 100 generations). Open in new tabDownload slideStudying the combined effect of deleterious mutations (which favor sex when selection is stronger in males) and sexually antagonistic mutations (which disfavor sex) is important because both types of mutation occur in many species. A thorough simulation study is challenging, however, as little is known about the relative rates of occurrence and distributions of effects (s and h) of these different types of mutations (as well as possible covariances between effects), and the possibly relevant parameter space would thus be very large.

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-2906983/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published03 Nov, 2023Read the published version in BMC Psychiatry →Version 1posted 9You are reading this latest preprint versionAbstractBackground: Patient-reported outcome measures (PROM) provide clinicians with information about patients’ perceptions of distress. When linked with treatment and diagnostic registers, new information may be obtained, such as associations with prevalence and service use. This study aimed to examine psychological symptoms among psychiatric outpatients and to investigate treatment-relevant characteristics of symptom-homogeneous classes. Methods: In a cohort study of 2473 (63% female) outpatients, factor mixture modelling (FMM) was used to analyse self-reported symptoms of anxiety and depression before treatment, and the classes association with functional impairment, the prevalence of common mental health disorders (CMHD) and the number of assessments and psychotherapy appointments one year after treatment start. Results: Overall, 22% of patients with a CMHD had an additional comorbid mood/anxiety disorder. This comorbid group reported higher symptoms of anxiety and depression compared to patients with non-comorbid anxiety disorders. FMM revealed three classes: “anxiety and somatic depression” (33%), “mixed depression and anxiety” (40%), and “cognitive depression” (27%). The anxiety and somatic depression class was associated with older age, being single and on sick leave, higher probability of depressive-, anxiety-, and comorbid disorders, having more appointments and higher functional impairment. Although the cognitive depression class had less somatic distress than the mixed depression and anxiety class, they reported more functional impairment and had higher service use. Conclusions: The results demonstrate the clinical relevance of applying FMM to PROM data of depression, anxiety, and functional impairment when linked with treatment registers. Three patient groups emerged, with different symptom patterns. Higher symptom severity did not necessarily imply more functional impairment and service use when subdimensions and latent patient groups were accounted for. Patient-reported outcome measuresLatent class analysisFactor mixture modelsCommon mental disordersComorbidityFiguresFigure 1IntroductionPatient-reported outcome measures (PROM) have been increasingly applied to encourage patient involvement (1).

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Each group selects a reporter who will report out each group's findings. While the students sort the pasta, the instructor will write the early form of the on the board that is described in Table 3A. The instructor will then use the student's reports to fill in the blanks. The final version of the Table is described in Table 3B. Mimic antibiotic treatment (5 minutes). The antibiotic treatment that was first described by Estes (14) will take no more than 5 minutes. Since broad spectrum antibiotics typically get rid of more bacteria than just the targeted pathogen, long and curved pasta will be removed from those of the bags that contain these types of pasta. This reflects how an antibiotic can impact multiple types of bacteria. Students who received the dairy diet resembling bag of pasta will now have an empty bag and students who received the omnivore diet resembling pasta bag will still have a reasonably full bag of pasta (Figure 2). The instructor should guide discussion so students notice that some bags are emptier than others and that the number of different types of pasta has decreased in all bags except the meat diet resembling bag. These observations simulate a decrease in the biodiversity of the gut microbiome after antibiotic treatment, accompanied by empty niches in which new bacteria can colonize. Students then fill up these empty spaces in the pasta bags with the beans that simulate the environmental bacteria (Figure 2). Upon close inspection, some student groups will notice the presence of yellow or green lentils in their pasta bags, resembling infection with C. difficile. Note that only student groups who received green lentils which are indicative of toxin-producing C. difficile will 'develop symptoms. ' Figure 2. An example of the antibiotic treatment. On the left side, students received a pasta bag that resembles an omnivore diet and contains seven different types of past. On the right side, the pasta bag is representative of a dairy diet and contains only long pasta. The first row is the original pasta bag that students received. The second row shows the respective pasta bags after long and curved pasta were removed in the simulation of antibiotic treatment that reduces different types of bacteria, but not all types. In the third row, students filled up the now empty spaces with beans from the bean bag. Beans resemble environmental bacteria that move into niches in the gut that the antibiotic treatment cleared out. A small number of these beans are lentils which represent C. difficile.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Although we leave a more complete treatment to future studies, Figure S2 in 2 shows that in the presence of deleterious mutations, intermediate rates of sex can be maintained even when a substantial number of loci are segregating for sexually antagonistic variation (it also shows that extrapolation from the two-locus model generally still provides correct quantitative predictions). In the next section, we suggest possible experimental tests of the overall direction and strength of selection for sex arising from differences in selection between the sexes. this 0. 01 when the haploid mutation rate U is around 2, the strength of selection against mutations in females is and selection is about five or six times stronger in males. As shown in this 2. Given that sex differences in selection are likely to give rise to polymorphisms involving both deleterious mutations and sexually antagonistic alleles, is the net effect likely to favor or disfavor sex? The answer to this question is largely an empirical issue, depending on the relative frequencies of such mutations and their effects (note that sexually antagonistic variation is likely to be less important when the baseline rate of sex is low, as it is more difficult to maintain such variation—see 1. Experimental evidence that sexual selection helps to purge the female mutation load remains scarce. A few studies have measured the effect of specific mutations on male and female fitness (see 2001. Sexual selection and the maintenance of sexual reproduction. Nature 411:692–695. 2009. Spatial heterogeneity and the evolution of sex in diploids. Am. Nat. 174:S54–S70. . H. 1995. A general model for the evolution of recombination. Genet. Res. 65:123–144. 2005. Evolution of recombination due to random drift. Genetics 169:2353–2370. 1991. Natural and sexual selection on many loci. Genetics 127:229–255. 2010. Higher rates of sex evolve in spatially heterogeneous environments. Nature 468:89–93. 1982. The masterpiece of nature. Univ. of California Press, Berkeley, CA. 2001. Negative genetic correlation for adult fitness between sexes reveals ontogenetic conflict in Drosophila. Proc. Natl. Acad. Sci. USA 98:1671–1675. 1930. The genetical theory of natural selection. Oxford Univ. Press, Oxford, U. K. 2007.

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: PROM can be helpful in the diagnostic process of common mental health disorders (CMHD) (2) and is often implemented to facilitate service planning (3). Since accessible quality indicators about patients’ needs often are rudimentary and lack diagnostic and symptomatic information (4), PROM data could help providers to facilitate person-centred services (1,2). Although linking PROM with register data is underutilized, important knowledge about patients may be obtained by connecting these sources of information (3). One potential outcome of combining PROM- and register data is to increase the knowledge about specific groups of patients, such as those with comorbid disorders. Compared to patients with non-comorbid CMHD, patients with comorbidity have been associated with higher service utilization, higher symptom severity, and higher levels of functional impairment (5). One PROM study which examined comorbidity in outpatient treatment showed that 45% of patients with an anxiety disorder had comorbid depression, 64% with post-traumatic stress disorder (PTSD) had a depressive disorder, and that comorbid depression was associated with higher symptom severity both before and after treatment (6). Studies like these demonstrate the additive value of PROM data linked with diagnostic registers of CMHD. Thus, collecting and combining PROM data on depression and anxiety with diagnostic information could add accumulated knowledge and improve person-centred services. Another potential of PROM data is the possibility offered to analyse symptom severity across the whole sample, capturing symptom heterogeneity beyond diagnoses. Mixture model analysis has become a frequently applied statistical framework to aggregate symptom heterogeneity into a smaller set of homogeneous groups. One model specification, latent class analysis (LCA), has been used to analyse symptoms of depression and anxiety simultaneously, and class indicators have identified important sub-samples in non-clinical adult populations (7–14) and clinical adult populations (15,16). In the latter two studies, three class solutions were identified, labelled by a gradient of symptom severity, where the higher severity classes were more strongly associated with CMHD, and with a decreased association with mild and low severity classes. LCA, however, has been criticized when applied to detect homogeneous subgroups of CMHD (17) because of the strict methodological requirements of local independence: class indicators should only depend on the latent classes and not correlate. This is an unrealistic requirement for symptoms of depression and anxiety due to their frequent co-occurrence.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Mapping the in class simulation to research on the gut microbiome (35 minutes). The advanced part of the exercise will be to identify specific microbes, as well as their metabolic products in dependence on the diet. Students will perform seven tasks, each of which should take approximately 5 minutes. The first task is to use the Nature paper on the Project (1) to identify the nine phyla of bacteria that contribute to the gut microbiome. These are and Verrucomicrobia. Among these, Firmicutes and Bacteroides are predominant. Second, students will determine the predominant bacteria in the gut microbiome of a person who lives on a dairy diet. Typically, newborn babies live on a diet that consists exclusively of milk. Students will be referred to Koenig and coworkers (16) who investigated the changes in the growing infant's gut microbiome that accompany the transition from a dairy diet to adult food. The information that is pertinent to this pasta simulation can be found in the first paragraph of the introduction. While the gut of the newborn baby is almost sterile, the vaginal microbiome of the mother serves as the first source of bacteria, mainly of the genus Bifidobacteria. The growth of these bacteria is further supported by the milk diet, as Bifidobacteria metabolize and degrade oligosaccharides that are provided with the milk and cannot be degraded by the human intestine. Bacteroidetes are also found in breast milk and help the baby transition to the adult gut microbiome and a more diverse diet. Students will report Bifidobacteria as an indicator of a dairy diet and the instructor will include this information in the Table (Table 3) on the board in column 8 (Bacteria). Students will note the Koenig reference in column 9 (Reference). For the student's information, Bifidobacteria belong to the phylum Actinobacteria. The third task is to find information in the Portune paper (15) on the predominant bacteria in adult humans who live on a diet that consists predominantly of meat. According to Table 1 of this paper (15), people with this diet have a gut microbiome that includes bacteria of the genera Alistipes, Bilophila, and Bacteriodes (24). Students will find these in the Table and the instructor will add the bacteria to Table 3 on the board, column 8. Task 4 is to identify the bacteria that are predominant in people on a plant diet.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: The evolution of sex and recombination in response to abiotic or coevolutionary fluctuations in epistasis. Genetics 175:1835–1863. 2007. Sexual selection and the evolution of obligatory sex. BMC Evol. Biol. 7:245. 1980. Sex versus non-sex versus parasite. Oikos 35:282–290. 2010. The role of advantageous mutations in enhancing the evolution of a recombination modifier. Genetics 184:1153–1164. 2003. Recombination can evolve in large finite populations given selection on sufficient loci. Genetics 165:2249–2258. 2006. Interference among deleterious mutations favours sex and recombination in finite populations. Nature 443:89–92. 1977. Regions of stable equilibria for models of differential selection in the two sexes under random mating. Genetics 85:171–183. 2002. General models of multilocus evolution. Genetics 161:1727–1750. 1987. Anisogamy, sexual selection, and the evolution and maintenance of sex. Evol. Ecol. 1:95–105. 2000. The evolution of recombination in a heterogeneous environment. Genetics 156:423–438. 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland, MA. 2011. Inbreeding reveals stronger net selection on Drosophila melanogaster males: implications for mutation load and the fitness of sexual females. Heredity 106:994–1002. 1984. Males and the advantage of sex. J. Theor. Biol. 108:215–220. 1971. The origin and maintenance of sex. 1932. Some genetic aspects of sex. Am. Nat. 66:118–138. 1993. The evolution of multilocus systems under weak selection. Genetics 134:627–647. 2003. The advantages of segregation and the evolution of sex. Genetics 164:1099–1118. 2009. The evolutionary enigma of sex. Am. Nat. 174:S1–S14. . P. , and N. H. Barton. 1997. The evolution of recombination: removing the limits to natural selection. Genetics 147:879–906. 2001. Selection for recombination in small populations. Evolution 55:1921–1931. . P. , and D. Bourguet.

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The advantage of factor mixture modelling (FMM) over LCA is that FMM does not assume conditional independence of latent classes (18) and therefore has been suggested to be more suitable in psychiatric research (19). Applying FMM with class indicators of depression and anxiety has been conducted within general adult populations (20), and for people with a lifetime episode of depression (21), but rarely within a clinical mental health setting. The scope of the current study is two-folded: first, to examine the one-year prevalence of CMHD in a diagnostic register and their association with patient-reported symptom severity in a large cross-sectional heterogeneous psychiatric outpatient sample. In accordance with previous research, we hypothesize comorbid mood and anxiety disorders to be frequently occurring, associated with higher symptom severity, and higher service use. Second, to identify homogeneous subgroups based on self-reported symptoms of depression and anxiety and analyse their association with clinician-assessed mental disorders and other clinically relevant covariates. Due to the exploratory nature of FMM, the numbers of identified classes are not hypothesized a priori. Methodspatients requiring non-urgent specialized mental health treatment are typically referred by their general practitioners to district psychiatric outpatient clinics for treatment. At one such clinic, electronic PROM data was collected between February 2020 and February 2022. All patients with a first assessment were invited to participate. Groups of patients with a primary diagnosis of obsessive-compulsive disorder (OCD), schizophrenia, substance abuse, and elderly patients, were treated at other specialized units. Out of 2519 patients who consented to participate, patients with missing information on all self-report questionnaires were excluded (n = 46). The final sample consisted of 2473 outpatients (79% of the invited participants; see Table 1). Out of the participating patients, 97% also had available register data with diagnostic and treatment information. information was extracted for age, gender, self-reported relationship status, and work status. Diagnostic information in accordance with the ICD-10 (Organization, 2016) and the number of appointments was collected until one year after the self-reported symptom assessment (extraction date in March 2023). Diagnoses were manually clustered into bipolar, depressive, anxiety, PTSD, somatization, and comorbid mood/anxiety disorder.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: These too are listed in Table 1 (15) and include Roseburia, Eubacterium rectale, and Ruminoccus bromii, all from the phylum Firmicutes. These bacteria will go in Table 3, column 8. By this time, the students will have assigned specific bacteria to the different types of pasta in their snack bags and the instructor will have constructed Table 3B, on the board. There should be about 15 min left of class time. The remaining three tasks focus on how changes in the diet to high fat, high fiber, or high protein impact the gut microbiome and specific bacterial metabolic pathways that will lead to the respective metabolic products excreted into the human intestine. This is the next step in the signal transduction pathway from the diet to the ultimate impact on human health and will transition students for the follow up homework assignment. The relevant information is listed in Tables 1, 2, and 3 of the Portune paper. To complete the in class part of the exercise, students will need to identify metabolic products that the bacteria secrete and that contribute to human health. As one example, high fiber diet leads to an increase in Bifidobacteria and Lactobacilli, which are considered probiotics and produce short chain fatty acids including acetate, propionate, and butyrate (27). While it is not fully understood which metabolic products these bacteria produce, long chain fatty acids themselves can reduce short chain fatty acids in the gut, which favors a pro-inflammatory environment (28). Diseases that result from this include obesity, type 2 diabetes, and colon cancer. active learning activity will conclude with a follow up homework assignment. So far, students have studied the composition of the gut microbiome in response to the respective diets and identified metabolic byproducts that some of these bacteria produce and excrete into the host intestine. During the three days following the in class time, students will get together in their group and concentrate on the part of the Portune paper (15) that focuses on the link between changes in the gut microbiome/bacterial metabolic products and the resulting diseases, as well as the molecular response in the host intestinal cells that contributes to chronic inflammation. To limit the scope of the paper, students will focus on a high fat diet (section 2). Students will summarize their findings in a short paper of 1-2 pages of text including a figure.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: 1999. Balanced polymorphisms and the evolution of dominance. Am. Nat. 153:561–574. 1999. The red queen and fluctuating epistasis: a population genetic analysis of antagonistic coevolution. Am. Nat. 154:393–405. 2006. Intralocus sexual conflict diminishes the benefits of sexual selection. PLoS Biol. 4:e356. 2007. An evolutionary cost of separate genders revealed by male-limited evolution. Am. Nat. 169:29–37. 1992. Sexually antagonistic genes: experimental evidence. Science 256:1436–1439. 2001. Intersexual ontogenetic conflict. J. Evol. Biol. 14:685–693. 2006. The Hill-Robertson effect and the evolution of recombination. Genetics 173:1793–1811. 2010. Deleterious mutations and selection for sex in finite, diploid populations. Genetics 184:1095–1112. 2009. On the causes of selection for recombination underlying the hypothesis. Am. Nat. 174:S31–S42. 2008. Mating density and the strength of sexual selection against deleterious alleles in Drosophila melanogaster. Evolution 62:857–867. 2001. Sexual selection and the maintenance of sex. Nature 411:689–692. 1990. Allele-frequency change in a class-structured population. Am. Nat. 135:95–106. 1976. Sexual selection and resource-accruing abilities in Anolis garmani. Evolution 30:253–269. 2000. Fixation of new alleles and the extinction of small populations: drift load, beneficial alleles, and sexual selection. Evolution 54:1851–1861. 2009. Purging the genome with sexual selection: reducing mutation load through selection on males. Evolution 63:569–582. 4.

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: ResultsOverall, 63% (n = 1524) of the patients were diagnosed with a CMHD (bipolar, depressive, PTSD, anxiety, or somatization disorder). Further, 2% (n = 55) were registered with a mixed anxiety depressive disorder without a comorbid CMHD. Other frequent prevalent diagnoses for patients with no CMHD were attention deficit hyperactivity disorder (10%, n = 245) and personality disorders (4%, n = 106), and symptoms and signs involving emotional state (R45, 21%, n = 496). One year’s prevalence of comorbid CMHD was the following: for patients diagnosed with bipolar disorder (n = 125), 25% also had a depressive disorder, 8% had PTSD, 17% had an anxiety disorder, and 6% had somatization disorder. Out of patients diagnosed with a depressive disorder (n = 865), 4% were also diagnosed with bipolar disorder, 6% with PTSD, 28% with anxiety disorder, and 3% with somatization disorder. Regarding PTSD (n = 245), 4% were diagnosed with bipolar disorder, 23% with depressive disorder, 9% with anxiety disorder, and 2% a somatization disorder. Regarding anxiety disorders (n = 613), 3% had bipolar disorder, 39% had depressive disorder, 3% had PTSD, and 5% had somatization disorder. Of patients with somatization disorder (n = 92), 8% had bipolar disorder, 30% had a depressive disorder, 7% had PTSD, and 32% had an anxiety disorder. Overall, 22% of patients diagnosed with a CMHD had a comorbid mood and anxiety disorder. Correspondingly, 14% of all patients with diagnostic data had a comorbid mood and anxiety disorder. Patients with comorbid disorders scored higher symptom severity of depression and anxiety than patients diagnosed with non-comorbid disorders, with the only exception of symptoms of anxiety for somatization disorders (Table 1). 1 here Patients with bipolar disorders had a mean of 4. 37 (SD = 3. 65) assessments, and 11. 23 (SD = 9. 71) psychotherapy appointments. For depressive disorders, these numbers were 3. 86 (SD = 4. 10), and 11. 60 (SD = 8. 78) respectively. Patients with anxiety disorders had 3. 72 (SD = 3. 91) assessments and 10. 64 (SD = 8.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Assignment instructions to be given to the students are provided as S1. The microbe/host response to a change towards a high fat diet includes an increase in the lipopolysaccharide (LPS) production by the bacteria (e. g. Firmicutes) and an increase in the permeability of the intestinal barrier by the host. The latter may be due to a decreased integrity of tight junction proteins (29). Students are given the assignment to summarize the effect of the high fat diet through the bacterial responses on the host system. Students will use 3. Students are free to select any three molecules that contribute to the signal transduction of their choice and go into the details of their function. 20 points are dedicated to this assignment by the author of this manuscript on a scale of 350 to 400 points for the course. activity engages students to explore the role of diet on the gut microbiome, the differences in bacterial metabolism, the molecular response in the human intestinal cells, and the resulting impact on human health. Students typically have no difficulty identifying the nine phyla that contribute to the gut microbiome. The expectation is not that they will remember all nine. However, phyla such as Firmicutes or Bacteroidetes have been discussed in the lectures that preceded this exercise. Students are expected to recognize and remember these two predominant phyla. The most effective part of the pasta exercise may be the short demonstration of an infection by C. difficile in response to antibiotic treatment. The empty pasta bags that now contain a smaller number of different pasta types are an effective simulation. When students 'fill up' their gut with new bacteria, some of which may not be beneficial to human health, students often experience a light-bulb moment. This response is consistent with the student responses that were described by Estes (14). Junior and senior Microbiology students, as well as graduate students should have heard of C. difficile infection during previous classes. Likewise, they should have knowledge about chronic inflammatory diseases. However, this exercise is very practical and provides a real life scenario, which makes it more interesting for the students. It is likely that this activity makes ideas and knowledge more tangible for the learner and promotes long-term retention of the content. Although all students participated in the group discussions, to promote inclusiveness, I would advise instructors to have different students report from the groups throughout the class. This lesson can be scaled to accommodate differently sized classes.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: The frequency of genotype j in the male gamete pool is given by πj, with A5Finally, genotype frequencies among juvenile males of the next generation are given by A6 (where δij= 1 if i=j and 0 otherwise), whereas genotype frequencies among juvenile females are given by A7 where T=∑i, j≥i[(1 −σij)xmutij+ωtot y′ij/c], and σij is the rate of sex of females carrying genotype ij. 0. From equations (11) and (13) we have B3 B4 This gives us a recursion for ∇M. Solving at equilibrium gives an expression for ∇M at QLE: B5 Plugging this expression into equations (B3) and (B4) gives B6 Expressions for ∇A, and to the first order in when δσ= 0 are given by equations (26) and (27). Putting everything together, one obtains B7 Recursions for and can be derived similarly. One obtains B8 B9 B10 1. Although polymorphism cannot be maintained when with weak selection (C5), it can with stronger selection (C1–C4). Higher fitness in heterozygous individuals favors the maintenance of polymorphism. Most importantly, these equations show that as the rate of sex evolves, different loci subject to sexually antagonistic selection are likely to be polymorphic. With infrequent sex, only alleles with weak effects in females ( low) will satisfy these conditions, whereas with frequent sex larger is necessary. Author notes Data Archived: Dryad: doi:10. 5061/dryad. 1m104© 2012, Society for the Study of EvolutionThis 1. Equilibrium rate of sex σ as a function of the deleterious mutation rate U. - pdf file EVO_1459_sm_supp2Figure S2. Top: Equilibrium rate of sex σ as a function of the cost of sex c with loci subject to both sexually antagonistic selection and mutation-selection balance. Bottom: Amount of genetic variance maintained at equilibrium at loci under deleterious mutation (higher values) and at loci under sexually antagonistic selection (lower values). - pdf file Advertisement 2023. .

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The LMR test, aLMR test, and BLRT in the three-factor, 5-Class FMM-2 model solution all had p values greater than. 05, which indicates that this model solution should be rejected despite lower criterion indices. Therefore, we then considered a three-factor, 3-Class FMM-2 model which had the second lowest criterion indices. Although the LMR and the aLMR tests did not show univocally support for this model solution, the BLRT had a p-value <. 001, indicating that this model solution significantly fit the data. The entropy value for this model solution was also high, indicating that there is a clear separation between distinguishable classes. Furthermore, the three-factor, 3-Class FMM-2 model replicates the combined results from the CFA and LCA analyses. 2 here Selecting the three-factor, 3-Class FMM-2 model implies that the underlying symptoms are conceptualized equivalently and normally distributed within classes. In other words, the three classes are represented by normally distributed patterns of symptoms of depression and anxiety such that individuals within classes can have quantitatively different ranges of symptom severity. The criterion indices for the FMM-1 solution were much higher and therefore unsuitable for model selection. Additionally, the assumptions of the FMM-1 imply that all patients within a class are having the same levels of distress and that there is no within-class heterogeneity in symptoms of depression and anxiety. This is unlikely to be correct as symptom variation exists as well as the range of severity, consistent with our FMM-2 model solution. Since we assumed variations in symptoms of depression and anxiety as well as the range of severity, the three-factor, 3-Class FMM-2 model was chosen. Interpretation of classes from the factor mixture model The three distress classes were labelled according to differences in factor means (see Figure 1). The reference Class two comprising 40% of the sample, was labelled “mixed depression and anxiety” whereas patients in Class one (33%), in comparison to the mixed depression and anxiety class reported lower levels of cognitive depression, but higher levels of somatic depression and anxiety symptoms and was thus labelled “anxiety and somatic depression”. Patients in Class three (27%) on the other hand reported lower somatic depression than mixed depression and anxiety class and Class three was thus labelled “cognitive depression”.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: The activity was designed for six groups of three to five students. If the class size is smaller, the number of students per group can simply be reduced. It is critical to have different diets and gut microbiomes, which makes it essential to have at least six bags. If the class size is larger, some of the pasta bags can be duplicated, rather than increasing the number of students per group; larger groups may result in a smaller percentage of students participating. The exercise can be adjusted for lower academic levels, such as for precollege students, by going back to the original Estes exercise (14) and doing the pasta/bean work without asking students to relate information on actual bacteria to the pasta and beans. Stressing the antibiotic mimicry by providing students with additional information on C. difficile and other antibiotic related infections will increase the practical relevance of this aspect of the exercise and make it suitable for 100 or 200 level classes. Finally, the module may be applied for a course in health-related professional programs (e. g. medicine, pharmacy) by asking students to predict whether people with a variety of diets would be more or less susceptible to different diseases based upon their diet dependent gut microbiome. Students would have to do their own literature search to determine if evidence exists to support hypotheses that they themselves formulate. This task could either be an in class activity for a second class period or an additional assignment. 1. Impact of Diet and Antibiotics - Assignment instructions that instructors will give to students for the follow up assignment. S2. Impact of Diet and Antibiotics - Sample follow up assignment for instructors. S3. Impact of Diet and Antibiotics - Grading rubric for the follow up assignment. 2012. Structure, function and diversity of the healthy human microbiome. Nature 486:207-214. Ercolini D, Fogliano V. 2018. Food design to feed the human gut microbiota. J Chem 66:3754-3758. den van. 2014. The short-chain fatty acid uptake fluxes by mice on a guar gum supplemented diet associate with amelioration of major biomarkers of the metabolic syndrome. PLoS One 9:e107392. . ,. 2012. Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms. PLoS One 7:e35240. de. 2009.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Sign in through your institution Filter EvolutionThis issue Biological SciencesEvolutionary BiologyScience and search term Advance 10. 1111/j. 1558-5646. 2011. 01352. x Published: 01 October 2011 10. 1111/j. 1558-5646. 2011. 01352. x Select format. ris (Mendeley, Papers, Zotero). enw (EndNote). bibtex (BibTex). txt (Medlars, RefWorks) Download citation issue Biological SciencesEvolutionary BiologyScience and search term issue Biological SciencesEvolutionary BiologyScience and search term for mates has resulted in sophisticated mechanisms of male control over female reproduction. Antiaphrodisiacs are pheromones transferred from males to females during mating that reduce attractiveness of females to subsequent courting males. Antiaphrodisiacs generally help unreceptive females reduce male harassment. However, lack of control over pheromone release by females and male control over the amount transferred provides males an opportunity to use antiaphrodisiacs to delay remating by females that have returned to a receptive state. We propose a model for the evolution of antiaphrodisiacs under the influence of intrasexual selection, and determine whether changes in this signal in 11 species of Heliconius butterflies are consistent with two predictions of the model. First, we find that as predicted, male‐contributed chemical mixtures are complex and highly variable across species, with limited phylogenetic signal. Second, differences in rates of evolution in pheromone composition between two major clades of Heliconius are as expected: the clade with a greater potential for male–male competition (polyandrous) shows a faster rate of divergence than the one with typically monoandrous mating system. Taken together, our results provide evidence that for females, antiaphrodisiacs can be both honest signals of receptivity (helping reduce harassment) and chastity belts (a male‐imposed reduction in remating). Female mating receptivity, Heliconius, male‐male competition, male control on female reproduction, sexual conflict, signal evolutionMale control over female mating frequency is common in nature and involves remarkable morphological, behavioral, and physiological adaptations aimed at manipulating female receptivity or discouraging advances by other males (e. g. , Parker 1970, Simmons 2001).

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: The factor variances within the classes were all significant, which agrees with the interpretation that there are variations in diagnostic class membership and the range of severity of the patient’s self-reported symptoms of depression and anxiety. 1 here Predictors of class membership 3 for predictors of class membership. There were no findings of gender predicting any class membership. Older age predicted a higher probability of membership to the anxiety and somatic depression class, compared to both the mixed depression and anxiety and the cognitive depression classes. Being single predicted a higher probability of membership in the anxiety and somatic depression class compared to the mixed depression and anxiety class, and the cognitive depression class compared to the mixed depression and anxiety class. 3 here Differences in relevant outcome variables Patients with a high probability of membership in the anxiety and somatic depression class were to a larger degree associated with being on sick leave and being diagnosed with depression, anxiety and comorbid mood/anxiety disorder compared to the other classes. Patients with a high probability of belonging to the cognitive depression class were to a larger degree associated with being on sick leave and being diagnosed with depression, and comorbid mood/anxiety disorder, compared to the mixed depression and anxiety class. They also had a higher probability of being diagnosed with mixed anxiety and depressive disorder, compared to the anxiety and somatic depression class. Regarding the mixed depression and anxiety class, they had a higher probability of being diagnosed with somatization disorder compared to the cognitive depression class. Regarding functional impairment and service use, the anxiety and somatic depression class had more assessment and psychotherapy appointments and reported the highest degree of impairment compared to the other classes. The cognitive depression class reported more psychotherapy appointments and functional impairment than the mixed depression and anxiety class. Outcomes across classes are presented in Table 4. 4 here DiscussionThis study shows that linking PROM with register data on CMHD can provide supplemental information on the service needs of routine mental health outpatients. Patients with comorbid mood and anxiety disorders differed from non-comorbid patients as a group characterized by higher symptom severity, and higher service use. Since analyses of patients diagnosed with CMHD did not consider the full sample, in this case excluding 35% of the sample, we also examined FMM-aggregated PROM data. Three classes distinguished themselves regarding levels of cognitive depression, somatic depression, and anxiety, together with clinically relevant covariates.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut 58:1091-1103. Kiefer J, Beyer-Sehlmeyer G, Pool-Zobel BL. 2006. Mixtures of SCFA, composed according to physiologically available concentrations in the gut lumen, modulate histone acetylation in human HT29 colon cancer cells. Nutr 96:803-810. . 2017. Gut microbiome and inflammation: a study of diabetic inflammasome-knockout mice. J 2017:6519785. . 2018. The gut microbiome and elevated cardiovascular risk in obesity and autoimmunity. Atherosclerosis 271:203-213. . 2018. Dysbiosis of gut microbiota in promoting the development of colorectal cancer. (Oxf) 6:1-12. . 2018. Gut microbiota-immune system crosstalk and pancreatic disorders. 2018:7946431. . 1978. Antibiotic-associated pseudomembranous colitis due to toxin-producing clostridia. N Med 298:531-534. . 2012. Risk of Clostridium difficile infection with acid suppressing drugs and antibiotics: meta-analysis. Gastroenterol 107:1011-1019. . 2017. Fecal microbiota transplantation for recurrent Clostridium difficile infection reduces recurrent urinary tract infection frequency. Dis 65:1745-1747. Estes AM. 2015. Modeling the dynamic digestive system microbiome. J Educ 16:271-273. Portune KJ, Benitez-. 2017. Gut microbiota, diet, and obesity-related disorders-the good, the bad, and the future challenges. 61:1600252. . 2011. Succession of microbial consortia in the developing infant gut microbiome. 108:4578-4585. Kuh GD. 2008. High-impact educational practices. Association of and Universities. Sweat JJ, G. ; Han, S. ; Wolfgram, S. M. 2013. How does high impact practice predict student engagement? A comparison of white and minority students. Learn 7:17. Prince M. 2013. Does active learning work? A review of the research. J 93:223-231. Froyd JE. 2007.

Output: contrast


Input: Claim: Natural selection drives the evolution of species through differential survival. [SEP] Text: Common mechanisms include the transfer of seminal fluid proteins, donation of nuptial gifts, formation of mating plugs, and mate guarding (Thornhill and Alcock 1983; Simmons 2001). The evolution of such strategies is the result of selection on males to reduce sperm competition when females mate repeatedly within a breeding period. Females often obtain direct benefits from multiple matings (Arnqvist and Nilsson 2000). Thus a conflict can arise if male traits reduce female remating below what is optimal for the latter leading to male–female antagonistic coevolution (Arnqvist and Rowe 2005). Antiaphrodisiacs are chemical signals transferred during mating by males to females that temporarily reduce female attractiveness to subsequent courting males. Described first in the beetle Tenebrio molitor (Happ 1969), they have since been found in a wide range of taxa, including Drosophila melanogaster, garter snakes, and several species of bees and butterflies (Gilbert 1976; Ross and Crews 1977; Scott 1986; Andersson et al. 2000; Ayasse et al. 2001). Some authors have regarded these male‐donated pheromones as nuptial gifts because they help unreceptive females repel unwanted males (Thornhill and Alcock 1983). The notion that these pheromones have little role in controlling remating has largely arisen because decreased attractiveness appears to be synchronized with inherently low female sexual receptivity. The assumption that reduced receptivity follows mating is based mainly on a few taxa where females themselves produce additional chemicals to repel males, or are physically incapable of remating immediately (Scott 1986; Ayasse et al. 2001). Recent studies have challenged the view that donor males and mated females always have a common interest in the repelling of courting males. Antiaphrodisiacs are typically emitted passively during courtship displays. Such apparent lack of female control over the release of this pheromone, as well as the male's ability to modify the amount transferred according to the potential for sperm competition, suggests that the presence of antiaphrodisiacs in a mated female may not always be a honest signal of her receptivity to mate, and can in fact become an instrument of male control over female remating (Andersson et al. 2000; 2003; 2004). In this 0. 25 mm, 0. 25‐μm‐thick film).

Output: pass


Input: Claim: Depression and anxiety are among the most common mental health disorders globally. [SEP] Text: It is therefore possible that this class, equal to one-third of the sample, was characterized by patients with persistent psychological problems of high complexity across a broad range of areas. The elevated levels of somatic problems and anxiety reported by this class could therefore reflect a group of patients with a chronic course of depression. A longitudinal study on patients with depression showed higher cortisol levels and c-reactive proteins amongst patients with persistent problems, and these biomarkers had a considerably stronger relationship to somatic-, rather than cognitive symptoms of depression (37). Thus, higher somatic symptoms of depression could indicate the chronicity of the disorder. Levels of somatic symptoms of depression also separated the other two classes. The mixed depression and anxiety- were the largest class, compromising 40% of the patients. They were more often in a relationship and younger compared to patients in the other classes. Their levels of cognitive symptoms of depression and anxiety were similar to the class labelled cognitive depression class. Their higher levels of somatic symptoms of depression were unexpected since they also had less service use, reported a lower degree of functional impairment and lower levels of sickness absence. At the same time, they also had the highest probability of a somatization disorder. A possible explanation is that patients in the mixed depression and anxiety class are highly distressed but still able to work or study, which means that they are more exposed to daily stressors. These patients may express more somatic depressive complaints as a result of trying to cope with difficult everyday challenges. Correspondingly, patients in the cognitive depression class may be less exposed to work or study-related daily stressors, and at the same time report more severe functional impairment, and higher treatment needs. The relationship between symptoms and functioning is complex, and many times weaker than expected. In a review, McKnight and Kashdan (38) argued that the dimensionality of the instruments, and sample properties could obscure the relationship. Thus, when these are accounted for, new information may be obtained. Results show the accumulated value of conjoining clinician-rated and self-reported information, as this provides new perspectives of the patient population that is not readily available from each source of information alone. The clinical implication of these findings is gained knowledge of latent patient groups, showing that higher symptom severity does not necessarily imply more service use and higher functional impairment. This underlines the need for evaluations that combine the perspective of patients, clinicians, and the organisation.

Output: corroborate


Input: Claim: Changing one's diet has no impact on the microbiome composition. [SEP] Text: Diet may influence the oral microbiome composition in cats access Published: 09 June 2016 Diet may influence the oral microbiome composition in cats Christina J. Adler1,2, Richard Malik3, Gina V. Browne1,2 & …Jacqueline M. Norris4 Show authors Microbiome 0. 001). Amongst this higher diversity, cats on dry-food diets had a higher abundance of Porphyromonas spp. (p < 0. 01) and Treponema spp. (p < 0. 01). ConclusionsWhile we observed differences in the oral microbiome between cats on the two diets assessed, the relationship between these differences and gingival health was unclear. Our preliminary results indicate that further analysis of the influence of dietary constituents and texture on the feline oral microbiome is required to reveal the relationship between diet, the oral microbiome and gingival health in cats. BackgroundThe microbiome of the gingival cleft is of great interest in human dentistry because the two most important diseases of the teeth and periodontium in human patients, dental caries and periodontitis [1], are related to changes in the relative contribution of various potentially pathogenic bacteria in the complex biofilm referred to as dental plaque [2]. As a result, there is considerable information on the oral microbiome of human patients, how this is associated with different disease conditions, and how this is influenced by diet [3, 4]. This includes studies using ancient deoxyribonucleic acid (DNA) which have shown that systematic changes in the microbiome are correlated with changes in diet, in both a contemporary and an evolutionary sense [5]. Cats, like humans, are very commonly affected by periodontal disease, with a consensus that it is the most common disease of feline patients in developed nations [6]. While periodontal disease is seen in cats of all ages, it is generally considered to progress with age, although its extent and severity are impacted on by such factors as diet and co-morbid disease (especially kidney disease and infection with feline immunodeficiency virus and/or feline calicivirus). Indeed, some feline diets are specifically formulated to prevent and/or ameliorate the severity of feline periodontal disease.

Output: contrast