Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: There is very good agreement between the reference datasets as to the global-mean and the Arctic-mean temperatures after the beginning of the satellite era in 1979. However, we see some discrepancy between the gridded observations and the ERA5 reanalysis before this time with the reanalysis being consistently cooler in the Arctic. This is likely due to the limited number of regular observations in the Arctic prior to the use of satellite remote sensing, which means that Arctic temperatures in the ERA5 dataset are poorly constrained by observations. We also see this difference between ERA5 and the observational datasets in the timeseries of Arctic amplification calculated using a 29 year window (figure 1(b)). For this reason we choose to focus our analysis on the period after 1980 as others have recommended [6]. Since the reference datasets are so similar for this post-1980 period we use a multi-observational mean (MOM) for the remainder of our analysis. This is a mean of the ERA5, and HadCRUT5 timeseries. We can see that Arctic amplification in the observation datasets starts with values close to 1 in the late 1970s, steadily increases to a peak value of around 4 at the turn of the century, before decreasing in the 2000s. In the last year of each timeseries the expectation value of the Arctic amplification is below the 5th percentile of the peak value in the timeseries, giving high confidence that Arctic amplification has peaked. Reset image size Figure 1. Arctic (thin lines) and global (thick lines) annual-mean temperatures from 1950–2021 in five different observation or reanalysis datasets shown as anomalies relative to the 1981–2010 climatology (upper figure). The time series of Arctic amplification for each dataset calculated using a 29 year window (lower figure). Download figure:Standard image High-resolution image By using the definition of Arctic amplification as the ratio of the trend in the Arctic to the trend in the global-mean temperatures one must choose a window over which to calculate the temperature trends. Figure 2 shows the Arctic amplification as a function of time for window lengths ranging from 9 to 41 years, together with the corresponding trend in sea ice area. There is a clear peak in both the Arctic amplification and the rate of loss of sea ice in the early 2000s, centred around 2005. For example, Arctic amplification calculated using a 17 year window reaches a peak of 8 in 2004 before dropping to 2. 5 in 2011.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. 2011; 43: 246-52. 19. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012; 491: 119-24. 20. Diversity of the human intestinal microbial flora. Science 2005; 308: 1635–8. 21. Burnham WR, Lennard-. Mycobacteria as a possible cause of inflammatory bowel disease. Lancet 1978;2(8092 Pt 1):693-6. 22. Chiodini RJ. Crohn's disease and the mycobacterioses: a review and comparison of two disease entities. Rev 1989; 2: 90-117. 23. Prevalence of enteropathogenic bacteria in surgically treated chronic inflammatory bowel disease. Hepatogastroenterol 1998; 45: 1552-8. 24. coli adherence and invasion in Crohn's disease and colon cancer. Gastroenterol 2004; 127: 80-93. 25. -Howard J, Bjarnason I. Mucosal antibodies in inflammatory bowel disease are directed against intestinal bacteria. Gut 1996; 38: 365-75. 26. Do high serum levels of anti-Saccharomyces cerevisiae antibodies result from a leakiness of the gut barrier in Crohn's disease? 2003; 15: 1281-5. 27. t al. Genetics of the innate immune response in inflammatory bowel disease. Dis 2007; 13: 338-55. 28. . Pathogen recognition and innate immunity. Cell 2006; 124: 783-801. 29. -Volhard C. Establishment of dorsal-ventral polarity in the Drosophila embryo: the induction of polarity by the Toll gene product. Cell 1985; 42: 791-8. 30. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene. Science 1998; 282: 2085-8. 31. . TOLLing away in Brazil. 2006; 7: 675-9. 32. The repertoire for pattern recognition of pathogens by the innate immune system is defined by cooperation between toll-like receptors. 2000; 97: 13766-71. 33. .

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: KeywordsBiopesticideEntomopathogensIntegrated pest managementTuta absoluta1 IntroductionTomato (Solanum lycopersicum L. ) is one of the horticultural plants affected by insect pests, microbial diseases, and nematode infections [1, 2]. According to Santana et al. [3], tomato leaf miner, Tuta absoluta Meyrick is one of the emerging insect pests that severely affect tomato production. The larval stages attack the aerial parts (leaves, stems and fruits) of tomato and destroy 80–100% of production [4]. The mouthpart and antenna of the insect have gustatory and olfactory sense organs (different types of sensilla) to select host plants [5]. Most domesticated and cultivated tomato varieties are vulnerable to the insect infestations. However, wild species of tomato, such as, S. habrochaites and S. cheesmaninae that are capable of synthesizing biomolecules, methyl-ketones (2-tridecanone), sesquiterpenes (zingiberene) and acyl sugar (acylglucose and acylsucrose) showed high resistance against T. absoluta [6, 7, 8]. This gives insight to develop pest resistant cultivars against the insect pests [6]. Although there are various methods to control insects, currently, chemical insecticides are principally used in the management of leaf miner. Several studies, however, showed that continuous use of the chemicals are implicated with destruction of natural enemies, buildup of insecticide residues on tomato fruits, and the environment, rapid development of insecticide resistance, and reduced profits from high insecticide costs [9, 10, 11]. This necessitates a shift from conventional pest control practices to integrated pest management (IPM), in order to reduce application of pesticides and produce healthy food [12]. Microbial entomopathogens are a natural component of IPM to control insect pests and naturally regulated by ecological factors with negligible effects on biodiversity [13]. Beauveria bassiana, Metarhizium anisopliae, and Bacillus thuringiensis are the most important microorganisms that are widely used to protect plants from insect pests for horticultural production [14, 15, 16, 17].

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: There is no indication of any other peak in Arctic amplification in the period since 1970, and the values of Arctic amplification found in the early 2000s of around 8 for the shorter time windows of 13 and 17 years are unprecedented. This peak in Arctic amplification is concurrent with an unprecedented rate of loss of sea ice area, as may be expected given the dominant role of the sea ice feedback in Arctic amplification at this time. Reset image size Figure 2. Heatmap of the change in Arctic amplification and rate of sea ice area loss in time (y-axis) for different window lengths (x-axis). Data are from the MOM for Arctic amplification and from ERA5 for the sea ice area. Non-significant values are shown using 1/3 thickness of the colour bands with significance defined at the p < 0. 1 threshold. For example, none of the Arctic amplification values in 1970 are statistically significant, whereas all of the sea ice area trends in 1970 are signifcant. Download figure:Standard image High-resolution image That this peak in Arctic amplification is coupled to the rate of loss of sea ice area is clear when we adjust the latitude threshold we use to define the Arctic (see supplementary figure 2). We find that across all latitude thresholds considered and a wide range of time windows, from 13 to 29 years, we see a clear peak in Arctic amplification. The magnitude of Arctic amplification increases as we move the threshold to higher latitudes, confirming the expectation that Arctic amplification is most pronounced over the Arctic Ocean. It is the values close to the peak Arctic amplification which increases the most as we move towards higher latitudes, meaning that the peak becomes even more pronounced the further north we set the definition of the Arctic. If this peak in Arctic amplification was purely due to the forced response from increasing atmospheric CO2 then we would expect to find a peak in the CMIP6 MMM. The MMM of 32 global climate models shows that Arctic amplification tends to decrease from the 1980s through to the end of the 21st century where it remains stable with values of 2. 4 ± 0. 2 under emissions scenarios where global temperatures continue to rise throughout the 21st century (figure 3). In the SSP126 scenario global temperatures stabilize sometime in the second half of the 21st century, but the Arctic continues to warm [31], and so Arctic amplification once again increases in the mid-to-late 21st century.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Recognition of double-stranded RNA and activation of NF-kappaB by Toll-like receptor 3. Nature 2001; 413: 732-8. 34. The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5. Nature 2001; 410: 1099-103. 35. TLR9 signals after translocating from the ER to CpG DNA in the lysosome. 2004; 5: 190-8. 36. . Class II transactivator: mastering the art of major histocompatibility complex expression. Biol 2000; 20: 6185-94. 37. Inohara N, Nunez G. The NOD: a signaling module that regulates apoptosis and host defense against pathogens. Oncogene 2001; 20: 6473-81. 38. . Signalling pathways and molecular interactions of NOD1 and NOD2. Immunol 2006; 6: 9-20. 39. . pyrin and hereditary immunological disorders. Immunol 2006; 6: 183-95. 40. Inohara N, Nunez G. NODs: intracellular proteins involved in inflammation and apoptosis. Immunol 2003; 3: 371-82. 41. Crohn's disease and the NOD2 gene: a role for paneth cells. Gastroenterol 2003; 125: 47-57. 42. Nod1 detects a unique muropeptide from gram-negative bacterial peptidoglycan. Science 2003; 300: 1584-7. 43. Nod2 is a general sensor of peptidoglycan through muramyl dipeptide (MDP) detection. J 2003; 278: 8869-72. 39. Kaser A, Blumberg RS. Autophagy, microbial sensing, endoplasmic reticulum stress, and epithelial function in inflammatory bowel disease. Gastroenterol 2011; 140: 1738-47. 40. . Paneth cells directly sense gut commensals and maintain homeostasis at the intestinal host-microbial interface. 2008; 105: 20858–63. 41. XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell 2008; 134: 743–56. 42. .

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: These microorganisms establish themselves endophytically in the plant tissue and augment synergistic pest control [18], promote plant growth, and crop productivity [19]. The hitherto studies showed successful endophytic colonization of tomato plants with entomopathogens [20]. The authors reiterated that B. bassiana showed significant growth improvement in tomato plants with direct (87. 5%) and indirect (72. 5%) protection activity against T. absoluta. Other studies showed that B. bassiana produce large amount of bioactive compounds of flavonoids, phenols and alkaloids that have antagonistic effect against several types of insects and microbial pathogens [21, 22, 23]. Similarly, Metarhizium spp. produce plant growth promoting hormones, cell division stimulators, and nutrient bioavailability modifiers to improve host plant growth besides management of insect pests [24]. It is established that success in pest control and plant promotion by entomopathogens depends on strain selection, appropriate formulation, proper application, suitable environmental condition for application, and application timing [25, 26]. To this end, entomopathogens are screened for effective control of insect pests and plant growth promotion function. In Ethiopia, one study showed that some strains of B. bassiana and M. anisopliae reduced 84 and 76% of T. absoluta infestation under field conditions [27]. However, there is still a dearth of information on the synergistic role of entomopathogenic fungi (EPF) and bacteria (B. thuringiensis) against T. absoluta under greenhouse and field conditions. Therefore, in this study, effective strains of B. bassiana, M. anisopliae, and B. thuringiensis, those previously screened under laboratory condition [28, 29, 30] were evaluated under greenhouse and field conditions. 2 Materials and methods2. 1 Tomato varietiesThree tomato varieties were selected for this experiment. The newly released “Awash” variety with large fruit size and good aroma for consumption and better marketing [31], and the heat tolerant and disease resistant “Venes” tomato variety were collected from Merkamba PLc. , Addis Ababa, Ethiopia. These two varieties were used for greenhouse experiment which was conducted at University (AAU), Collage of Natural and Computational Sciences.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: However, there is no strong evidence of a peak in Arctic amplification occurring in the MMM. Individual models show a wide range of behaviours, but they all have the highest values of Arctic amplification occurring at some time in the 20th century in all scenarios except for the SSP126 (supplementary figure 1). This suggests that internal variability is key to creating a peak in Arctic amplification, but the MMM plot suggests that the magnitude of that peak is controlled by the mean state, and so peaks in Arctic amplification that occur in a climate with less sea ice will have lower values. This is confirmed by analysis of the CESM2 large ensemble. We calculated how large a peak in the Arctic amplification would be if it occurred in each year from 1850 to 2100 (figure 4). We found that peaks in Arctic amplification never occurred in the CESM2-LE before the 1980s and that the magnitude of the peaks decreased in time from the 1980s until the end of the 21st century. Reset image size Figure 3. Timeseries of the MMM Arctic amplification for the period 1975–2080 calculated using a window of 29 years for each of the scenarios SSP126, SSP245, SSP370, and SSP585 (lower). The uncertainty, given by the 25th and 75th percentiles, is shown for the SSP585 scenario. Download figure:Standard image High-resolution image Reset image size Figure 4. The peak value of Arctic amplification that occurs within members of the CESM2 large ensemble. We define a peak as having occurred if the value of Arctic amplification in a given year is the highest in the decade centered on that year with the requirement that all years within the decade have a statistically-significant value. The black line indicates the ensemble mean value with the dashed line indicating the 25th and 75th percentiles of the distribution for each year. Download figure:Standard image High-resolution image This pattern in the observations of a peak in Arctic amplification occurring around the turn of the century is even clearer when we look at the seasonal cycle (figure 5). There is a large seasonal variation in Arctic amplification with the highest values found in the winter months (October–April). For the MOM we see a clear peak in Arctic amplification occurs around 1998–2002 and that within the seasonal cycle the peak is centred on January.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: An essential role for XBP-1 in host protection against immune activation in C. elegans. Nature 2010; 463: 1092–5. 43. Virus-plus-susceptibility gene interaction determines Crohn’s disease gene Atg16L1 phenotypes in intestine. Cell 2010; 141: 1135–45. 44. TLR activation of the transcription factor XBP1 regulates innate immune responses in macrophages. 2010; 11: 411–8. 45. Coombes JL, Powrie F. Dendritic cells in intestinal immune regulation. Immunol 2008; 8: 435-46. 46. Johansson- Functional specialization of gut CD103+ dendritic cells in the regulation of tissue-selective T cell homing. J 2005; 202: 1063-73. 47. Interleukin 23 production by intestinal CD103(+)CD11b(+) dendritic cells in response to bacterial flagellin enhances mucosal innate immune defense. Immunity 2012; 36: 276-87. 48. . Signaling through the JAK/STAT pathway, recent advances and future challenges. Gene 2002; 285: 1-24. 49. . Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins. Science 1994; 264: 1415-21. 50. O'. Cytokine signaling in 2002: new surprises in the Jak/Stat pathway. Cell 2002; 109(Supp l): S121-31. 51. Disruption of the Jak1 gene demonstrates obligatory and nonredundant roles of the Jaks in cytokine-induced biologic responses. Cell 1998; 93: 373-83. 52. . Jak2 deficiency defines an essential developmental checkpoint in definitive hematopoiesis. Cell 1998; 93: 397-409. 53. . Tyrosine kinase 2 (TYK2) in cytokine signalling and host immunity. 2011; 17: 3214-32. 54. Firmbach--Favera R, Krolewski JJ. Tyk2, prototype of a novel class of non-receptor tyrosine kinase genes. Oncogene 1990; 5: 1329-36. 55. van Boxel-. Complex modulation of cell type-specific signaling in response to type I interferons.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: For the field trial, the high yielding commercial hybrid “Gellila” variety were bought from Florensis PLc. , Addis Ababa, Ethiopia. The experiment was conducted between January 12 to May 26, 20/2021 under irrigation cropping system at Kebele, (Meki) district, State, Ethiopia (Figure 1). Figure 1 Map of field experiment sites in the. 2. 2 Microbial bioinsecticidesFour entomopathogenic fungi; B. bassiana-AAUB03 (MT588402), B. bassiana-AAUB28 (MT588414), M. anisopliae-AAUM39 (MT463525), M. anisopliae-AAUM78 (MT463530), and two entomopathogenic bacteria; B. thuringiensis-AAUF6 (MW250834), and B. thuringiensis-AAUMF9 (MW250856) were selected on the basis of their effective larvicidal activity against T. absoluta under laboratory conditions [28, 29, 30] for greenhouse tests. From which, B. bassiana-AAUB03, M. anisopliae-AAUM78, and B. thuringiensis-AAUF6 were selected for the trial under field conditions. 2. 3 Preparation of entomopathogenic fungi (EPF)The fungal strains were produced in diphasic (liquid and solid state) fermentations following standard methods [32]. They were grown on potato dextrose agar (PDA) medium at 25 °C until conidiation for 20 days. The conidia were scraped into sterile test tube containing 20 mL of water and 0. 01% Tween 80 to produce 1 × 106 conidial suspensions per milliliter. Of which, 15 mL of suspension from each strain was inoculated into 150 mL of potato dextrose broth (PDB) in 250 mL Erlenmeyer flasks and incubated at 28 °C for 7 days with manual agitation every two days to improve aeration. Then, 120 mL of blastoconidia was transferred into 1 kg of autoclaved wheat bran substrate and moistened with sterile water in 1. 5 kg capacity of polyethylene bags having pores to allow free flow of air for solid-state fermentation.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: Whereas during the summer (June–July) Arctic amplification is relatively weak (1–3) and does not change much over time. Reset image size Figure 5. The seasonal variation in Arctic amplification as a function of time for the MOM, and for the multi model mean of the SSP126 and SSP585 scenarios calculated using a 29 year window. Download figure:Standard image High-resolution image The MMM does capture the essential element of the seasonal cycle in Arctic amplification: that the highest Arctic amplification occurs in the winter months. However, there is not such a clear peak in Arctic amplification during the 20th century as seen in the observations. However, there is a clear shift in the seasonality of Arctic amplification in the high emissions scenario ssp585 during the 21st century. As there is a shift towards seasonal ice cover in the Arctic in SSP585 around the 2040s we see a corresponding reduction in Arctic amplification in the autumn months of September, October, and November. 4. DiscussionRecent work has demonstrated that on average the Arctic has been warming at almost four times the global-mean rate since satellite records began in 1979 [6]. This rapid Arctic warming has already had profound consequences for the region, particularly in the thinning and retreat of sea ice. Since the emergence of recent Arctic amplification in the late 1990s and early 2000s it has been proposed that the retreat of sea ice is critical to the establishment of strong Arctic amplification [9]. This is supported by the identification of a strong positive feedback between summer sea ice area and Arctic warming. The observation that Arctic amplification already peaked around 2000 is consistent with a peak in the rate of loss of sea ice area, volume, and thickness around that time. While a lot of focus has been on the retreating sea ice edge, the loss of sea ice volume is more dramatic with around two-thirds of sea ice volume observed during the 1980s already having melted [10]. In addition to the slowed reduction of sea ice, and so reduced albedo-feedback effect, another cause for the recent peak in Arctic amplification may be that as sea ice thins and becomes more broken there is less frequent occurrence of shallow, stably-stratified atmospheric boundary layers over ice. It is the presence of these shallow boundary layers which can strongly influence surface air temperature responses to changes in radiative forcing [15] and these surface inversions have been demonstrated to be an important component of Arctic amplification [25].

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Inflammatory bowel diseases, genetics, JAK-STAT pathway Kaynakça 1. Fiocchi C. Inflammatory bowel disease: etiology and pathogenesis. Gastroenterol 1998; 115: 182-205. 2. Editorial: (1560–1624): the other fabricius. JAMA 1964; 190: 933. 3. . Landmark 9. 4. Wilks S. Morbid appearances in the intestine of Miss Bankes. Times & Gazette 1859; 2: 264. 5. . Current concept on the pathogenesis of inflammatory bowel disease-crosstalk between genetic and microbial factors: pathogenic bacteria and altered bacterial sensing or changes in mucosal integrity take "toll" Gastroenterol 2006; 12: 1829-41. 6. Halme L, Paavola-. Family and twin studies in inflammatory bowel disease. Gastroenterol 2006; 12: 3668-72. 7. . Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447: 661–78. 8. Hugot JP, Laurent-Puig P, Gower-Rousseau C, et al. Mapping of a susceptibility locus for Crohn's disease on chromosome 16. Nature 1996; 379: 821-3. 9. . Genetics and pathogenesis of inflammatory bowel disease. Nature 2011; 474: 307-17. 10. . Clinical patterns of familial inflammatory bowel disease. Gut 1996: 38; 738-41. 11. . Epidemiology of inflammatory bowel disease in a German twin cohort: results of a nationwide study. Dis 2008; 14: 968–76. 12. Clustering in time of familial IBD separates ulcerative colitis from Crohn’s disease. Dis 2009; 15: 1867–74. 13. . Concordance of inflammatory bowel disease among Danish twins: results of a nationwide study. Gastroenterol 2000; 35: 1075-81. 14. Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease. Nature 2001; 411: 599-603. 15. A frameshift mutation in NOD2 associated with susceptibility to Crohn’s disease. Nature 2001; 411: 603-6. 16.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 5 g kg−1 of substrate) from optimized rice [38], and lower conidial density (8. 7 × 107 conidia g−1) of B. bassiana strain grown on brewer's spent grain [39], their germination rate was as good as those obtained from both substrates. This deviation may come from substrate difference since the latter differ in their nitrogen, carbon and amino acids contents that significantly enhance growth and conidial production of entomopathogens [32, 40]. Although M. anisopliae-AAUM39 induced the lowest conidial density (1. 3 × 108 conidia g−1) on wheat bran, its production was much higher than the conidial density of 4 × 106 conidia g−1 produced in the earlier study [41]. This variation in conidial production is due to many factors include; types of substrates, moisture content, incubation temperature, age of initial inoculums, initial concentration of conidia, inoculums size, incubation period, the presence of substrate degrading enzymes and aeration of culture during fermentation process [38, 42]. 3. 2 Greenhouse study3. 2. 1 Leaf protectionThe entomopathogens significantly (P < 0. 05) reduced the leaf damage inflicted by the insect pest, T. absoluta ranged from 76% with B. thuringiensis-AAUFM9 to 93% with B. bassiana-AAUB03 on Awash tomato variety and 65–83% on Venes variety compared to the untreated control (Table 2). This is best performance compared to previous report of reduction in the insect infestation of 46–75% on tomato plants [43]. The entomopathogen treatments showed significant variation in suppressing the insect infestation to reduce the percent leaf damage of Awash variety that was not different from 96% of protection by chemical treatment (Table 2). They also showed the same pattern, but with less percentage reduction of leaf lesion (65–83%) on Venes variety compared to the insecticide that scored 87% of protection. Qayyum et al [44] indicated that variation in effectiveness is attributed to the difference in the inherent ability of entomopathogens to successfully colonize plant species and attack insect pests. TreatmentsAwash varietyVenes varietyMean LI (%)Protection (%)Mean LI (%)Protection (%)B. bassiana-AAUB036.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: Preprints AbstractDiscussion © Author(s) 2023. This work is distributed under the Attribution 4. 0 License. © Author(s) 2023. This work is distributed under the Attribution 4. 0 License. Preprints AbstractDiscussionMetrics 20 Jun 2023 | 20 Jun 2023 Status: a revised version of this preprint is currently under review for the journal TC. Toward a marginal Arctic sea ice cover: changes to freezing, melting and dynamics and Bateson Abstract. As summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening and making up an increasing percentage of the summer sea ice. The MIZ is defined as the region of the ice cover that is influenced by waves, and for convenience here is defined as the region of the ice cover between ice concentrations (area fractions) A of 15 to 80 %. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice free summers. We compare individual processes of ice volume gain and loss in the ice pack (A>80 %) to those in the MIZ to establish and contrast their relative importance and examine how these processes change as the summer MIZ fraction and amplitude of the seasonal sea ice growth/melt cycle increases over decadal timescales. We use an atmosphere-forced, physics-rich sea ice-mixed layer model that includes a prognostic floe size distribution (FSD) model including brittle fracture and form drag. The model has been compared to FSD observations, satellite observation of sea ice extent and. The MIZ fraction of the July sea ice cover, when the MIZ is at its maximum extent, increases by a factor of 2 to 3, from 14 % (20 %) in the 1980s to 46 % (50 %) in the 2010s in NCEP (HadGEM2-ES) atmosphere-forced simulations. In a HadGEM2-ES forced projection the July sea ice cover is almost entirely MIZ (93 %) in the 2040s. Basal melting accounted for the largest proportion of melt in regions of pack ice and MIZ for all time periods. During the historical period, top melt was the next largest melt term in pack ice, but in the MIZ top melt and lateral melt were comparable.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: al. A genom wide analysis provides evidence for novel linkages in inflammatory bowel disease in a large European cohort. 1999; 64: 808-16. 17. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn's disease susceptibility loci. 2010; 42: 1118-25. 18. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. 2011; 43: 246-52. 19. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012; 491: 119-24. 20. Diversity of the human intestinal microbial flora. Science 2005; 308: 1635–8. 21. Burnham WR, Lennard-. Mycobacteria as a possible cause of inflammatory bowel disease. Lancet 1978;2(8092 Pt 1):693-6. 22. Chiodini RJ. Crohn's disease and the mycobacterioses: a review and comparison of two disease entities. Rev 1989; 2: 90-117. 23. Prevalence of enteropathogenic bacteria in surgically treated chronic inflammatory bowel disease. Hepatogastroenterol 1998; 45: 1552-8. 24. coli adherence and invasion in Crohn's disease and colon cancer. Gastroenterol 2004; 127: 80-93. 25. -Howard J, Bjarnason I. Mucosal antibodies in inflammatory bowel disease are directed against intestinal bacteria. Gut 1996; 38: 365-75. 26. Do high serum levels of anti-Saccharomyces cerevisiae antibodies result from a leakiness of the gut barrier in Crohn's disease? 2003; 15: 1281-5. 27. t al. Genetics of the innate immune response in inflammatory bowel disease. Dis 2007; 13: 338-55. 28. . Pathogen recognition and innate immunity. Cell 2006; 124: 783-801. 29. -Volhard C. Establishment of dorsal-ventral polarity in the Drosophila embryo: the induction of polarity by the Toll gene product. Cell 1985; 42: 791-8. 30. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene. Science 1998; 282: 2085-8. 31. .

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 6 ± 3. 2g93. 4ab16. 5 ± 1. 5e83. 5bB. bassiana-AAUB2813. 9 ± 2. 0de86. 1b19. 3 ± 2. 0ef80. 2bcM. anisopliae-AAUM3920. 8 ± 3. 2c79. 2c27. 6 ± 1. 7cd72. 4dM. anisopliae-AAUM7810. 3 ± 3. 7ef89. 7b19. 8 ± 2. 1ef80. 7bcB. thuringeinsis-AAUF69. 9 ± 2. 4f90. 1ab22 ± 2. 0de78cB. thuringeinsis-AAUMF923. 1 ± 1. 7bc76. 9c34. 6 ± 2. 2bc65. 4eTutan36% SC (insecticide)4. 0 ± 2. 12hj96. 0a13 ± 1. 2gh87aUntreated controlMean69. 7 ± 4. 1a-8673. 5 ± 10. 2a-77Table 2Effectiveness of the entomopathogens in reducing leaf damage of tomato by T. absoluta under greenhouse conditions. LI, Leaf infestation; same letters within the column indicate no significant differences p <0. 05). Open table in a new tabAmong the entomopathogens, B. bassiana-AAUB03 showed slightly higher percentage leaf damage reduction (88%) on both tomato varieties, followed by percentage leaf damage decrease of plants treated with M. anisopliae-AAUM78 (83%) and B. thuringensis-AAUF6 (84%). This was similar to the previous report of 73 and 84% leaf damage reduction of T. absoluta on Coshoro variety treated with B. bassiana and M. anisopliae, respectively [45]. However, B. thuringensis-AAUF6 induced 78% of leaf damage reduction on the Venes variety which was slightly higher reduction in leaf damage of 67% reported by Hosseinzadeh et al. [46]. These isolates were also significantly more effective in reducing leaf damage than the commercially recommended dose of B. thuringiensis that only reduced 31% of leaf damage on tomato variety [47].

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: This is due to a relative increase of lateral melting and a relative reduction of top melting by a factor of 2 in the MIZ compared to the pack ice. The volume fluxes due to dynamic processes decreases due to the reduction in ice volume in both the MIZ and pack ice. As the ice cover becomes marginal (MIZ), it melts earlier: in the region that was pack ice in the 1980s and became marginal in the 2010s, peak melting starts 20/12 days earlier (NCEP/HadGEM2-ES). This continues in the projection where melting in the region that becomes MIZ in the 2040s shifts 14 days earlier. How to cite. Frew, R. C. , Feltham, D. , Schroeder, D. , and Bateson, A. W. : Toward a marginal Arctic sea ice cover: changes to freezing, melting and dynamics, Discuss. [preprint], in review, 2023. Received: 14 Jun 2023 – Discussion started: 20 Jun 2023 Publisher's note: remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors. Download & links Preprint (PDF, 1958 KB) Download & links Preprint (1958 KB) and Bateson Status: final response (author comments only) Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse Login for authors/editors Subscribe to comment alert RC1: 'Comment on tc-2023-91', #1, 21 Jul 2023 General comments –The paper provides an assessment of the mass budgets in the MIZ/non-MIZ regions in Arctic sea ice simulations. It uses a comprehensive sea ice model which has been well utilized. It acknowledges that the lack of active atmosphere and dynamic ocean components affects feedbacks in the system, although some deeper discussion of how this might affect the results could be helpful. Overall, I believe that the experiment design is reasonable and can provide some valuable insights on changing Arctic sea ice mass budgets and their projection into the future. However, as noted below, I believe that there is a need for a somewhat deeper analysis and more interpretation of the results. For example, the study explores differences between simulations with different atmospheric forcing.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: TOLLing away in Brazil. 2006; 7: 675-9. 32. The repertoire for pattern recognition of pathogens by the innate immune system is defined by cooperation between toll-like receptors. 2000; 97: 13766-71. 33. . Recognition of double-stranded RNA and activation of NF-kappaB by Toll-like receptor 3. Nature 2001; 413: 732-8. 34. The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5. Nature 2001; 410: 1099-103. 35. TLR9 signals after translocating from the ER to CpG DNA in the lysosome. 2004; 5: 190-8. 36. . Class II transactivator: mastering the art of major histocompatibility complex expression. Biol 2000; 20: 6185-94. 37. Inohara N, Nunez G. The NOD: a signaling module that regulates apoptosis and host defense against pathogens. Oncogene 2001; 20: 6473-81. 38. . Signalling pathways and molecular interactions of NOD1 and NOD2. Immunol 2006; 6: 9-20. 39. . pyrin and hereditary immunological disorders. Immunol 2006; 6: 183-95. 40. Inohara N, Nunez G. NODs: intracellular proteins involved in inflammation and apoptosis. Immunol 2003; 3: 371-82. 41. Crohn's disease and the NOD2 gene: a role for paneth cells. Gastroenterol 2003; 125: 47-57. 42. Nod1 detects a unique muropeptide from gram-negative bacterial peptidoglycan. Science 2003; 300: 1584-7. 43. Nod2 is a general sensor of peptidoglycan through muramyl dipeptide (MDP) detection. J 2003; 278: 8869-72. 39. Kaser A, Blumberg RS. Autophagy, microbial sensing, endoplasmic reticulum stress, and epithelial function in inflammatory bowel disease. Gastroenterol 2011; 140: 1738-47. 40. . Paneth cells directly sense gut commensals and maintain homeostasis at the intestinal host-microbial interface.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: All the treatments showed significant (F 19, 32 = 10. 23, p <0. 001) variation (4–34%) of leaf infestation (LI) by T. absoluta on both varieties of tomato compared to high damage (>70%) observed from untreated control plants (Table 2). In the other study infestation rate of T. absoluta was vary from cultivar to cultivar in tomato production [48]. Based on the mean evaluation of all the treatments, entomopathogens induced more protection (86%) on Awash variety than they did (77%) on Venes variety (Table 2). In general, B. thuringeinsis-AAUF6 performed as good as the other entomopathogenic fungi (B. bassiana-AAUB28 and M. anisopliae-AAUM78) in protecting the two tomato varieties from leaf miner pest under greenhouse conditions. B. thuringeinsis-AAUF6 was better induced leaf protection than the commercial B. thuringeinsis showed that less performance on leaf protection compared to chemical insecticides [53]. 3. 2. 2 Fruit protectionIn this study, the findings showed significant (F 8, 57 = 12. 23, p <0. 002) variation among treatments to protect the fruits of both Awash and Venes varieties from insect damage (Table 3). Thus, B. bassiana-AAUB03 treated plants produced the largest (93%) number of marketable fruits (36 fruits/plant) on Awash variety with 13–40% increase in the number of marketable fruits over other entomopathogens and the standard insecticide treatments. In another study, B. bassiana was less effective (29%) on fruit protection from the T. absoluta as reported by Shahini et al. [47]. TreatmentsAwash varietyVenes variety(%)(%)B. bassiana-AAUB0339. 3 ± 2. 4a36. 7 ± 1. 2a93. 5b28. 5 ± 1. 4a23. 9 ± 1. 0a83. 7aB. bassiana-AAUB2835. 7 ± 2. 7b25. 2 ± 0. 8d70. 6ef22. 4 ± 1. 7c15. 1 ± 0. 8d67. 4cM. anisopliae-AAUM3929. 7 ± 1.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: “” – please provide a reference and brief information on the product. In particular, it should be noted that is a model product and not direct observations. Line 165. “By the 2010s the MIZ” – please provide a comparison to the observations here. Line 175. “basal growth makes up the largest proportion of melting” - Do you mean “basal melt” here? Line 177: “significantly more” – what is the significance level used to determine this? Line 186. “This means that it is likely that MIZ closer to the pack ice has a different balance of processes to the outer MIZ that has lower ice concentrations. ” Given this, what is the value in separating things into a MIZ/non-MIZ framework? Is it useful? What are the limitations? Would it be beneficial to look at the mass budgets as a function of ice concentration instead? Line 192-194. “A possible explanation for the increase in top melting in the future MIZ…” Is this inconsistent with the results from Keen et al. that did include active ocean models? Are there other factors that could explain increased top melt? Do factors like the change in seasonality, regionality play a role? Could you provide more analysis (for example of heat budgets) to gain a better understanding of the factors at play? Line 194-197. “This means that the results here could be seen as a lower estimate on the ice loss…” I would encourage you to also assess the HadGEM2-ES runs to determine if those exhibit different ice loss characteristics. I appreciate that the ice models are different in these runs which will affect the results but it would nonetheless provide a useful point of comparison on the sea ice response with coupled ocean feedbacks. Line 198. “convection and ridging”. Isn’t it just advection of the ice that can cause a mass flux? Won’t ridging affect the distribution of ice but conserve ice volume/mass? Line 229-230. “Peak total melting rates …” Why are there these differences between the NCEP and HadGEM2-ES runs? Line 234-236.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: 2008; 105: 20858–63. 41. XBP1 links ER stress to intestinal inflammation and confers genetic risk for human inflammatory bowel disease. Cell 2008; 134: 743–56. 42. . An essential role for XBP-1 in host protection against immune activation in C. elegans. Nature 2010; 463: 1092–5. 43. Virus-plus-susceptibility gene interaction determines Crohn’s disease gene Atg16L1 phenotypes in intestine. Cell 2010; 141: 1135–45. 44. TLR activation of the transcription factor XBP1 regulates innate immune responses in macrophages. 2010; 11: 411–8. 45. Coombes JL, Powrie F. Dendritic cells in intestinal immune regulation. Immunol 2008; 8: 435-46. 46. Johansson- Functional specialization of gut CD103+ dendritic cells in the regulation of tissue-selective T cell homing. J 2005; 202: 1063-73. 47. Interleukin 23 production by intestinal CD103(+)CD11b(+) dendritic cells in response to bacterial flagellin enhances mucosal innate immune defense. Immunity 2012; 36: 276-87. 48. . Signaling through the JAK/STAT pathway, recent advances and future challenges. Gene 2002; 285: 1-24. 49. . Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins. Science 1994; 264: 1415-21. 50. O'. Cytokine signaling in 2002: new surprises in the Jak/Stat pathway. Cell 2002; 109(Supp l): S121-31. 51. Disruption of the Jak1 gene demonstrates obligatory and nonredundant roles of the Jaks in cytokine-induced biologic responses. Cell 1998; 93: 373-83. 52. . Jak2 deficiency defines an essential developmental checkpoint in definitive hematopoiesis. Cell 1998; 93: 397-409. 53. . Tyrosine kinase 2 (TYK2) in cytokine signalling and host immunity. 2011; 17: 3214-32. 54. Firmbach--Favera R, Krolewski JJ.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: thuringeinsis-AAUMF9 that produced 22 and 20 marketable, respectively showing 38% increase compared to the least effective treatments, B. bassiana-AAUB28 and M. anisopliae-AAUM39. In general, the various treatments produced 60–84% of marketable fruits from the total count and displayed 5-9-fold higher number of fruits than the untreated control plants that were almost totally infected with the insect pest. 3. 2. 3 Fruit yieldThe marketable fruit yield obtained from different treatments was significantly (P < 0. 05) higher than the yield of untreated Awash tomato variety (Table 4). The data showed that B. bassiana-AAUB03 treatment induced the highest fruit yield (3. 6 kg/plant) which was twice more than the ones treated with B. thuringeinsis-AAUMF9. However, the marketable fruit yield (3–3. 2 kg/plant) from insecticide, Tutan 36%SC treated plant was not significantly different from plants treated with M. anisopliae-AAUM78, B. thuringeinsis-AAUF6. TreatmentsAwash varietyVenes varietyTFW/P (Kg)MFW/P (Kg)MF (%)TFW/P (Kg)MFW/P (Kg)MF (%)B. bassiana-AAUB033. 8 ± 1. 2a3. 6 ± 0. 9a94. 7a3. 4 ± 0. 6a3. 1 ± 0. 9a91. 2aB. bassiana-AAUB283. 3 ± 0. 9a2. 7 ± 1. 2ab81. 8b3 ± 0. 3a2. 4 ± 1. 2ab80bM. anisopliae-AAUM392. 8 ± 1. 0ab2. 1 ± 0. 1b75. 0c2. 9 ± 0. 2ab2. 1 ± 1. 2b72. 4cM. anisopliae-AAUM783. 6 ± 0. 8a3. 2 ± 2. 3a88. 9b3. 7 ± 1. 3a3. 7 ± 1. 2a89. 2abB. thuringeinsis-AAUF63. 5 ± 2. 1a3. 2 ± 0.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: “In the NCEP simulation there is a 17% increase, whilst in the HadGEM2-ES simulation there is a 6% decrease, likely due to the larger melt rates in the NCEP simulation. ” Why “due to the larger melt rates”? How do the differences in melt rates drive the different ice growth response? Line 268-270. “Top melt was twice as important …” Please provide information on why these differences are present. Conclusions section. Please provide information on what new insights were gained in this study relative to previous work and the broader implications of this study. Citation: AC2: 'Reply on RC1', Rebecca Frew, 30 Nov 2023 See attached PDF, uploaded as PDF to retain original formatting Citation: RC2: 'Comment on tc-2023-91', #2, 27 Jul 2023 The paper makes use of a sophisticated sea-ice model (CICE-Icepack) to investigate the processes affecting ice mass gain/loss in the marginal ice zone (MIZ) compared to the pack ice. Two simulations with different atmospheric forcing are performed: one using the NCEP reanalysis, available from 1979 to 2020 and the other using the HadGEM2-ES model, available from 1980 to 2050. Such a framework allows for validations of the model with observations in the 1980s, where the ice cover is dominated by the presence of thick multiyear ice (low-MIZ) and in the 2010s when the ice cover is much thinner and younger (high-MIZ). Then, the model is used to assess the processes affecting the ice mass balance in the 2040s, where the sea-ice cover is projected to be seasonally ice-free (all-MIZ). While the research topic is important, the methods are sound and the results are interesting, the text and the structure have significant flaws. Therefore, I suggest that major revisions should be conducted by the author and co-authors to improve the flow and the clarity of the text. 1- There are several structural issues within the text that require attention. First, the introduction is mostly composed of method statements with some discussion statements. It should focus more on presenting the existing literature, which would help emphasize the paper's significance and delineating its original contributions. Second, the method section appears to duplicate information already mentioned in the introduction.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Tyk2, prototype of a novel class of non-receptor tyrosine kinase genes. Oncogene 1990; 5: 1329-36. 55. van Boxel-. Complex modulation of cell type-specific signaling in response to type I interferons. Immunity 2006; 25: 361-72. 56. . The tyrosine kinase Tyk2 controls IFNAR1 cell surface expression. EMBO J 2003; 22: 537-47. 57. Partial impairment of cytokine responses in Tyk2-deficient mice. Immunity 2000; 13: 549-60. 58. Tyk2 plays a restricted role in IFN alpha signaling, although it is required for IL-12-mediated T cell function. Immunity 2000; 13: 561-71. 59. Roy B, Cathcart MK. Induction of 15-lipoxygenase expression by IL-13 requires tyrosine phosphorylation of horylation of Jak2 and Tyk2 in human monocytes. J 1998; 273: 32023-9. Tüm Kaynakçayı Göster Kaynakça Göster Toplam 62 adet kaynakça vardır. Ayrıntılar Türkçe Konular Sağlık Kurumları Yönetimi Bölüm Güray İÜNİVERSİTESİ 0000-0002-6054-9244 Türkiye Hüseyin Trakya Üniversitesi, Tıp Fakültesi, Dalı, Edirne, 0000-0002-3054-475X Türkiye Yayımlanma Tarihi 28 Haziran 2020 Yayımlandığı Sayı Yıl 2020 Cilt: 2 Sayı: 3 Kaynak Göster APA Can, G. , & Tezel, H. A. (2020). İnflamatuvar barsak hastalıkları ve genetik. Anadolu Güncel Tıp Dergisi, 2(3), 80-86. . İnflamatuvar barsak hastalıkları ve genetik. Med J. Haziran 2020;2(3):80-86.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 9a91. 4a3. 8 ± 1. 6a3. 5 ± 1. 0a92. 1aB. thuringeinsis AAUMF92. 6 ± 0. 7b1. 9 ± 1. 5c73. 1c2. 2 ± 0. 8bc1. 6 ± 1. 3c72. 7cTutan36%SC (insecticide)3. 2 ± 0. 8a3 ± 1. 3a93. 8a3 ± 1. 2a2. 8 ± 1. 2a93. 3aUntreated control1. 1 ± 2. 7c0. 28 ± 1. 3e25. 5efg1. 3 ± 1. 0d0. 5 ± 0. 8d-f38. 5d-gTable 4The fruit weight and marketability of tomato per plant treated with entomopathogens under greenhouse conditions. TFW, total fruit weight per plant; MFW, marketable fruit weight per plant; MF, marketable fruits per plant; same letters within the column indicate no significant differences between treatments (p <0. 05). Open table in a new tabThe fruit yield pattern was similar to the same treatments on Venes variety in that B. thuringeinsis-AAUF6 produced 3. 5 kg/plant of marketable fruits, followed by M. anisopliae-AAUM78 (3. 3 kg/plant), B. bassiana-AAUB03 (3. 1 kg/plant) and Tutan36%SC (2. 8 kg/plant) that were twice more protective than the least effective strain (B. thuringeinsis-AAUMF9). In all cases, marketable fruit yield obtained from the above mentioned isolates was more than 90% of the total yield. The rest of the isolates also exhibited 72–89% marketable fruit yield with both tomato varieties. This implies that most of the isolates performed as good as those treated with Coragen 200 SC (insecticides) that protected the tomato and produced up to 94% marketable fruit yield with local Coshoro variety in Ethiopia [49]. Buragohain et al. [50] in India also reported that commercially formulated B. bassiana (Green Beauveria® and BB Power®) and B.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: For a general reader, it is extremely confusing to read. I would try to avoid mentioning the exact values when you are making comparisons. For example, in this case instead of saying "The maximum sea ice extent [. . . ] shows a modest decline from 1. 22e7 km2 in the 1980s to 1. 15e7 km2" in the 2040s" I would just say something like "The difference between the maximum sea-ice extent in the 2040s compared to the 1980s is modest in the HadGEM simulation (Table 1). " Then the reader that is really interested in the exact values can investigate the table or the figure. This is a general comment that should be applied to all the result sections. The author should unearth the “story” in their simulations and present that instead. 28) Line 137: Why only North of 66. 5 N? There are large MIZ regions south of that (e. g. , Labrador Coast, Bering Sea, etc. ) 29) Figure 1: Put units in millions of km2 instead of having a 1e13 factor. This is valid for all plots. Why are there vertical bars in the NASA team and Bootstrap SIE data? Reduce the number of x ticks. Increase the size of x and y labels for all figures. 30) Figure 2: add a) and b) for each panel and refer to each of the specific panels in the text. This is noisy, plot a running average? 31) Table 2: Again, I do not really like the use of a table here. I would prefer an histogram. This would facilitate visual comparison for the reader. 32) Figure 4: I would add larger title on top of each column (e. g. , on the top of the first column put "NCEP" and the left of the first row put "Always pack". No need to keep a long subtitle for each panel. Remove the y ticks label in each of the subplot and keep only the one in the first column. Merge the third column with the second column (i. e. , add 2040s with comparison with both the 1980s and 2010s). These comments are valid for figures 5 and 6. 33) Lines 251-281: Same comments as in the results there is no need to say all the percentages. This will help to highlight what are the main results of this study.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: doi:10. 38053/acmj. 689278 Chicago Can, Güray, ve Hüseyin Ahmet Tezel. “İnflamatuvar Barsak hastalıkları Ve Genetik”. Anadolu Güncel Tıp Dergisi 2, sy. 3 (Haziran 2020): 80-86. (01 Haziran 2020) İnflamatuvar barsak hastalıkları ve genetik. Anadolu Güncel Tıp Dergisi 2 3 80–86. IEEE G. Can ve H. A. Tezel, “İnflamatuvar barsak hastalıkları ve genetik”, Med J, c. 2, sy. 3, ss. 80–86, 2020, doi: 10. 38053/acmj. 689278. üray - Tezel, Hüseyin Ahmet. “İnflamatuvar Barsak hastalıkları Ve Genetik”. Anadolu Güncel Tıp Dergisi 2/3 (Haziran 2020), 80-86. . İnflamatuvar barsak hastalıkları ve genetik. Med J. 2020;2:80–86. MLA Can, Güray ve Hüseyin Ahmet Tezel. “İnflamatuvar Barsak hastalıkları Ve Genetik”. Anadolu Güncel Tıp Dergisi, c. 2, sy. 3, 2020, ss. 80-86, doi:10. 38053/acmj. 689278. . İnflamatuvar barsak hastalıkları ve genetik. Med J. 2020;2(3):80-6. İndir Makale Dosyaları Sayfası Arşiv Cilt: 2 Sayı: 1 Cilt: 2 Sayı: 2 Cilt: 2 Sayı: 3 Cilt: 2 Sayı: 4 (UAK) Equivalency: 1b [Original research 2020.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: thuringeinsis (Green Larvicide® and Delfin® WG) showed more than 90% of marketable fruit yield of tomato by protecting them from T. absoluta. 3. 3 Field study3. 3. 1 Leaf protectionThe three effective strains (B. bassiana-AAUB03, M. anisopliae-AAUM78, and B. thuringiensis-AAUF6) significantly reduced leaf infestation (LI) of Gellila tomato variety when applied in single or in combination with each other and Tutan36% SC (insecticide) under field conditions (Table 5). All treatments except M. anisopliae-AAUM78 (T2) and B. thuringeinsis-AAUF6 (T3) showed 91–95% leaf protection with significant (F 18, 67) = 13. 12, p <0. 001) variation on leaf infestation (LI) (Table 5). In fact, at the early stage of tomato plantation, the insect infestation rate was between, 12. 1 and 39. 8% (data not shown), that was reduced to 4. 7–9. 7%, due to repeated application of entomopathogens and increase in age of the plants (Table 5). Klieber and Reineke [51] also reported the same pattern as a function of time and duration of biopesticide application. Similarly, commercial B. bassiana (Beaucitech® WP) and Metarhizium strain (Metatech® WP) showed 90–98% and 88–95% leaf protection on Roma tomato variety, respectively [52]. NoTreatmentMean LI (%)Protection (%)T1B. bassiana-AAUB038. 27 ± 0. 9c91. 73aT2M. anisopliae-AAUM7812. 71 ± 0. 8b87. 29bT3B. thuringeinsis-AAUF617. 84 ± 1. 0a82. 16bT4AAUF6 + AAUM788. 59 ± 1. 0c91. 41aT5AAUB03 + AAUM78 + AAUF64. 68 ± 1. 3e95. 32aT6AAUB03 + AAUM78 + 25% Tutan36%SC5. 62 ± 1. 5d94.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: For 80% SIC (the upper MIZ boundary), we can estimate (Hibler 1979) that ice strength is less than 2% of its maximum. In the MIZ internal stresses in the ice play only a small role and sea ice is essentially in free drift. The sea ice in the MIZ behaves distinctly to pack ice as it can be more easily advected. This has implications for those wanting to cross the Arctic: a larger Arctic MIZ would be easier to send ships across. The larger concentration of smaller floes and lower sea ice concentration in the MIZ has a number of consequences for the sea ice interactions with the ocean and atmosphere. Lateral melting will be enhanced due to the increased perimeter to surface area ratio, creating open water more efficiently than top or basal melt, and potentially fuelling the ice-albedo feedback. The lower the ice concentration, the more the surface ocean is warmed due to the lower albedo of open ocean, further enhancing ice melt and leading to the positive ice-albedo feedback. The increased open water fraction can also mean an increase in wind mixing in the mixed layer and will affect spin up (e. g. (Martin et al 2016)). There is a wave-floe size feedback that means the smaller the floes, the larger the impact of the waves, so a positive feedback loop exists that can act to increase the action of waves on the sea ice floes and further increase the concentration of smaller floes. The location and volume of sea ice melt has implications for stratification and so how deeply solar heat is mixed down. More sea ice melt means the mixed layer is shoaled and solar heat is concentrated in the upper water column. Meanwhile there are other important sea ice processes, such as top melting where it is less clear that we would expect there to be a contrast between the MIZ and the pack ice, for example in the formation of melt ponds. In the Arctic, the snow thickness is generally modest compared to that on Antarctic sea ice, and the location of top melting and the formation of surface melt ponds is primarily driven by atmospheric conditions. Projections suggest that the MIZ will increasingly dominate the Arctic sea ice cover, especially in summer. It seems likely, therefore, that MIZ-focused processes will play an increasing role in controlling the mass budget of Arctic sea ice. ”Second, the method section appears to duplicate information already mentioned in the introduction.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: To this aim, we analyzed the gene expression data contained in CMap, which were obtained from cultured human cells treated with bioactive small molecules [15, 16]. Moreover, we obtained the definition of genes as targets of specific drugs from analysis of the DrugBank database [33]. For every CAGC centered on a drug target associated to a molecule used in CMap (682 associations), we tested whether the genes in the CAGC are significantly upregulated or downregulated upon drug treatment (Mann-test). We performed 8435 tests, 3510 of which were significant with a Rate (FDR) < 0. 05. Importantly in 3428 cases the median ranks are consistent with an upregulation of the CAGC genes, while only in 82 cases it is consistent with a downregulation. The median rank distribution for all the CMap instances and the exemplar case of the genes composing the CAGC of ROCK1 (a target of Fasudil) in the CMap instance n. 436 (1e-05 M of Fasudil for 6 h in PC3 cells) are reported in Figure 3. Considering that the majority (76%) of the drugs used in CMap and associated to a cluster significantly up- or down-regulated are classified as inhibitors in DrugBank, these results strongly validate the general idea that the genes anticorrelated with a drug target are upregulated when the function of the target gene is inhibited. Figure 3Cmap rank in CAGC genes. shows the gene rank distribution for all genes and all cmap instances (green curve) and the distribution of the median gene rank of each CAGC whose center is a known drug target (red curve). Note that the gene rank is defined as the highest rank among the probesets associated to the gene, which explains the non-uniform distribution of all genes. As an exemplar case, in panel B we show a box-plot comparing, for the cmap instance n. 436 (1e-05 M of Fasudil for 6 h in PC3 cells), the genes in the CAGC of ROCK1 (a known target of Fasudil) with all the other genes. The rank of the CAGC genes is significantly higher (Pvalue < 3. 4e-05 Mann-test), implying that the inhibition of the CAGC center by the drug leads to a general overexpression of the genes that compose its CAGC.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 38aT7AAUF6 + 50% Tutan36%SC7. 77 ± 0. 7c92. 23aT8Tutan36%SC (positive control)6. 12 ± 0. 9d93. 88aT9Untreated control93. 88 ± 1. 0-Table 5The effect of entomopathogen treatments to reduce tomato (Gellila variety) leaf infestation from T. absoluta under field conditions. LI, mean leaf infestation; same letters within the column indicate no significant differences between treatments (p <0. 05). Open table in a new tabThe findings showed that the single treatment of B. bassiana-AAUB03 (T1) maintained its leaf protection (91%) as good as the combined treatments (T4, T5, T6 and T7) (Table 5). Allegrucci et al [20] corroborated that B. bassiana is efficient in its endophytic colonization to induced direct (86%) and indirect (73%) leaf damage protection from leaf miner. The IPM treatments with consortia of entomopathogens and reduced dose of the chemical insecticide was equally effective as full dose insecticide (positive control) treated plants (65%) in the control of T. absoluta (Table5). This may be associated with the ability of the entomopathogens to produce different kinds of secondary metabolites that synergistically induce systemic and repellant responses against pests [19, 53]. Furthermore, combined treatments of the entomopathogenic fungi and quarter reduced concentration of Tutan36% SC was the second most effective treatment in reducing leaf infestation. This suggests that reduction in pest infestation can be enhanced due to chemical interference on the physiology of the insect and increase their susceptibility to entomopathogens [47, 54]. 3. 3. 2 Fruit protectionThe total and marketable fruit production was significantly (F 23, 82 = 6. 15, p <0. 001) different among the treatments in the field conditions (Table 6). Tomato plants treated with B. bassiana-AAUB03 (T1) produced a large number of total (80. 3 fruits/plant) fruits per plant and 69. 3 fruits/plant with 86. 3% marketable fruits.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: 5 wave simulation shows no significant change in significant wave height or interannual variability in significant wave height (Bateson. 2021). Although the wave forcing fields do not have any trends, the propagation of the waves into the ice field does respond to the changes in the ice cover over time. The simulations were initialised with a 6 year spin up period, this is a similar length to previous studies using the same model setup (Rolph et al. , 2020; Bateson et al. , 2022). As we are using a standalone sea ice model, the amount of spin-up required is much shorter than a climate simulation, or a coupled sea ice-ocean model. ” Specific comments 1) Lines 2-3, 4-5 and 7-8: Theses sentences are repetitive : " [. . . ] the MIZ has been widening and making up an increasing percentage of the summer sea-ice", " The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice free summers" and " [. . . ] as the summer MIZ fraction and amplitude of the seasonal sea ice growth/melt cycle increases over decadal timescales ". This is not appropriate in an abstract. A has been changed to SIC throughout. Sentence changed to “and examine how these processes change as the summer MIZ fraction increases over time. ” 2) Line 4: Use SIC instead of A for sea-ice concentration. If you are to define an acronym, use it consistently through the manuscript. A has been changed to SIC. 3) Line 9: The name of the model used (CICE) should be mentioned in the abstract. The name CICE has been added, see line 8. 4) Line 12: The notation that you start using to compare NCEP and HadGEM2-ES atmosphere-forced simulation is NCEP (HadGEM2-ES) (e. g. , "from 14 % (20 %)"). Please use this notation consistently through the abstract. This has been amended, see line 18. 5) Line 18: Why redefine MIZ? We have removed this from text. 6) Line 18: Saying that "the ice cover becomes more marginal" is incorrect. Use thinner, younger, mobile or "MIZ-like".

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Full size imageAssociation of available drug targets to orphan genetic disorders through CAGCsOn the basis of the above results, we thought to use CAGCs to associate know drug targets to mendelian genetic disorders. To this aim, we selected CAGCs characterized by two features: the centre of the CAGC is a drug target and the other genes that compose the cluster are significantly enriched for genes associated to related morbid map phenotypes [32] (Figure 4). Indeed, we would expect that the pharmacological down-modulation of some of these centres may compensate for the loss of at least some of the specific disease genes that are among them. Under this assumption, the drugs that are capable of inhibiting the CAGC centre would become potential candidates for all the related mendelian disorders associated to the cluster. In other words, we propose a drug as possible treatment for a genetic disease when the responsible gene (DG) belongs to an anticorrelation cluster that has the drug target as the centre and that is significantly enriched for other genes implicated in disorders similar to the disorder resulting from DG mutation. Using this strategy, we obtained the list of drug targets/disease associations reported in the Additional file 1. The list could contain both completely novel associations or associations which are already supported by previous evidence. Although we would expect most of the associations to be novel, finding a significant number of associations supported by literature could represent an important validation of our method. In consideration of the difficulty of automatically assessing this point, we decided to systematically inspect the list by expert analysis. The most prominent results are reported below. Calmodulins and malformative genetic syndromes Calmodulins 1 and 3 (CALM1 and CALM3) are, potentially, the most prominent targets underscored by our approach. Indeed, they are represented in 426 of the associations reported in the Additional file 1, on a total of 2973. Since the two genes are strongly coexpressed (data not shown), the corresponding CAGCs were largely overlapping. Interestingly, these CACGs were strongly enriched for genes implicated in very complex and heterogeneous genetic syndromes.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: Whereas, combined treatments of entomopathogens with quarter-reduced concentration of Tutan 36%SC (insecticide) (T6) and full dose (T7) of insecticide was scored equal number of total fruits (79 fruits/plant) and 72 fruits/plant with 92. 1% of marketability. These treatments showed 15–18 fruits/plant marketable fruit production increment compared to the least effective entomopathogen (M. anisopliae-AAUM78) (T2) that scored 45 fruits/plant with 74% of marketability. NoTreatmentTotal fruits/plantMarketable fruit/plantProtection (%)T1B. bassiana-AAUB0380. 3 ± 0. 9a69. 3 ± 0. 9a86. 3bT2M. anisopliae-AAUM7864. 3 ± 1. 2d54. 0 ± 1. 2c74. 0cT3B. thuringeinsis-AAUF676. 3 ± 1. 0b65. 3 ± 1. 0b75. 6cT4AAUF6 + AAUM7871. 3 ± 1. 2b61. 7 ± 2. 1b86. 5bT5AAUB03 + AAUM78 + AAUF667. 0 ± 1. 1d61. 0 ± 1. 9bc91. 0aT6AAUB03 + AAUM78 + 25% Tutan36%SC78. 7 ± 0. 6a72. 5 ± 0. 2a92. 1aT7AAUF6 + 50% Tutan36%SC65. 0 ± 1. 4d56. 7 ± 1. 3c87. 2bT8Tutan36%SC (positive control)79. 3 ± 0. 9a72. 3 ± 1. 0a91. 2aT9Untreated control40. 0 ± 1. 5efg12. 0 ± 1. 4d-f30b-gTable 6Efficacy of entomopathogens in reducing fruit damage of tomato (Gellila variety) from T. absoluta under field conditions. Same letters within the column indicate no significant differences between treatments (p <0. 05). Open table in a new tabThe tomato plants treated with B. thuringeinsis-AAUF6 (T3) showed considerable (75.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: This has been amended, see lines 17-18 “As more of the summer ice cover becomes MIZ”. 7) Line 22: Remove "traditionally". This is its definition. You could cite an older paper. Removed, see line 22. 8) Line 24: Cite from the oldest to the newest. This comment is valid for the whole manuscript. Corrected see line 24. 9) Line 26: What kind of fragmentation are you referring to here? Wave-induced? "[. . . ] higher concentration of smaller floe" I would use "number" or "fraction", to avoid confusion with sea-ice concentration. We are referring to the summer break up of the sea ice cover including wave induced fragmentation and brittle fracture. “Concentration” has been changed to “fraction”, see line 26. 10) Lines 27-29: You say: "As the sea ice cover shrinks [. . . ] the MIZ contracts" followed by "As summer ice has retreated [. . . ] the MIZ fraction [. . . ] has been increasing". These two sentences appear to say the exact opposite. This needs to be clarified. We have changed this to: “As summer Arctic sea ice has retreated over the past 40 years the fraction of the summer sea ice cover that is MIZ has increased (Rolph et al. 2020). ” See lines 27-29 11) Lines 32-44: This is the closest from an introduction that we get. You need to expand this section. Explain clearly what has been done in previous studies. What method did they use? What were their results? Then finish the introduction by clearly stating which gap in the literature you are trying to fill. We have added some lines about processes in the MIZ, to introduce and motivate why we are studying the mass budget in the MIZ, see lines 32-49 (also see answer to the first of the general comments). 12) Lines 47-53: This is all method section, there is no need to describe in depth all the components of the model here. We have now created an “Analysis Method” section and moved it there, see Section 2. 6 in the revised manuscript. 13) Lines 53-60: What is this? Why use the future tense? Is this a general statement or are you discussing the results of your model?

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Similarly, we consider the association between prostaglandin-endoperoxide synthase 1 (PTGS1) and AUTSX2 partially validated by the finding that significantly elevated levels of prostaglandin E2 (PGE2) have been found in autistic patients [39]. Drug targets for heart failure syndromes and for neuromuscular disorders The Ser/Thr kinase ROCK1, a downstream effector of the cytoskeletal modulator RhoA small GTPase [40], was associated by our pipeline to 57 different genetic disorders, characterized by a high prevalence of muscular, cardiac and neurodegenerative phenotypes (Table 1). Interestingly enough, specific inhibitors of this protein, such as the FDA approved Fasudil, have displayed beneficial effects in experimental animal models of some diseases included in the list. Indeed, ROCK1 has been shown to play an important role in the transition from cardiac hypertrophy to failure in mice [41] and the administration of ROCK1 inhibitors has repeatedly been associated to beneficial effects in non genetic models of heart failure [42-45]. Even more strikingly, it has been recently shown that Fasudil improves survival and promotes skeletal muscle development in a mouse genetic model of spinal muscular atrophy [46], one of the prominent diseases included in our list. Moreover, it is interesting to notice that ROCK1 expression has been correlated to disease progression in an animal model of ALS [47], although in these case a beneficial use of ROCK inhibitors has not been so far reported. A beneficial activity of ROCK inhibitors has also been documented in experimental models of myopathies. In particular, in muscle of dystrophin/utrophin double-knockout, which represent an intensely studied model of Duchenne muscular dystrophy, the RhoA/ROCK1 pathway is hyperactive, leading to a reduction of the myogenic potential of muscle stem cells [48]. Accordingly, treatment with a ROCK1 inhibitor improves the myogenic potential of stem cells and increases muscle regeneration in vivo [48]. A second interesting target for muscular disorders is given by the IKBKB (IKK-β) protein, a Ser/Thr kinase that phosphorylates and inactivates inhibitors of the NF-kB pathway [49] and which we found as potential target for four different myopathies.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 3 fruits/plant) number of total fruits (65. 3 fruits/plant) with 75. 6% marketability followed by combined treatment of B. thuringeinsis-AAUF6 + M. anisopliae-AAUM78 (T4) that showed 71. 3 fruits/plant with 86. 5% marketable fruits (Table 7). However, the consortium of all entomopathogens (T5) was effective in fruit protection (91%) but relatively less effective on fruit number production. In general, marketable fruit production in all the treatments was highly significant (p <0. 05) compared to untreated (T9) control showing 5-folds of improvement by protecting plants from the insect pest. NoTreatmentsTotal and Marketable fruit weightsTFW/P (kg)MFW/P (kg)MF (%)T1B. bassiana-AAUB0311. 21 ± 1. 0a9. 67 ± 1. 1a86. 3bT2M. anisopliae-AAUM788. 73 ± 0. 9b7. 33 ± 1. 0c78. 9cT3B. thuringiensis-AAUF610. 75 ± 0. 7a8. 4 ± 0. 7b78. 1cT4AAUF6 + AAUM7810 ± 0. 8ab8. 75 ± 0. 9b87. 5bT5AAUB03 + AAUM78 + AAUF610. 42 ± 1. 0a9. 72 ± 1. 0a93. 3aT6AAUB03 + AAUM78 + 25% Tutan36%SC11. 64 ± 0. 9a10. 92 ± 1. 0a93. 8aT7AAUF6 + 50% Tutan36%SC10. 53 ± 0. 8ab9. 18 ± 0. 9a87. 2bT8Tutan36%SC (insecticide)11. 33 ± 0. 3a9. 81 ± 1. 0a86. 6bT9Untreated control5. 25 ± 0. 6c-e1. 58 ± 0. 7d-f30. 1c-fTable 7Marketable fruits from tomato (Gellila variety) plants treaded with entomopathogens under field conditions.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: ) This was a mistake in the text, we have removed this text – there had been a figure of the averaged reanalysis atmospheric fields in an earlier draft that was removed where this latitude had been used. 29) Figure 1: Put units in millions of km2 instead of having a 1e13 factor. This is valid for all plots. Why are there vertical bars in the NASA team and Bootstrap SIE data? Reduce the number of x ticks. Increase the size of x and y labels for all figures. Units and labels have been adjusted, see Figure 3 (figure has been renumbered). 30) Figure 2: add a) and b) for each panel and refer to each of the specific panels in the text. This is noisy, plot a running average? We have made the plots wider, and only included the 1979-2020 period to make it a bit clearer and added Figure 6. We have adjusted the labels on Figures 5-7. We’re not keen on combining the second and third columns as the regions are different for the two comparisons (1980s vs 2010s and 2010s vs 2040s), the two 2010s will be different as the areas used are different, so there would be four bars in the second column if we do this. 33) Lines 251-281: Same comments as in the results there is no need to say all the percentages. This will help to highlight what are the main results of this study. We need to clearly see how they are original compared to what was previously done. What could be done in future work? A number of percentages and exact values have been removed in the results and conclusion sections. We have added a paragraph to the end of the Conclusions that makes some comments on broader insights from this study: “Our analysis demonstrates a different balance of processes control the volume budget of the MIZ versus the pack ice. They are understandable in terms of the physical processes that dependent on the ice concentration, such as wave-ice interaction and lateral melt, which we are able to account for in our relatively physics rich sea ice model. We suggest that representation of such processes, in models such as climate models, requires more attention as a greater fraction of the sea ice cover becomes MIZ. ” mentioned earlier, I believe that this is truly interesting and useful work. However, it is not yet a finished product that is ready for submission to a scientific journal.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: SANs were generated by first calculating the Pearson correlation coefficients of every microarray probeset with all the other probesets. A directed edge was established from probeset p1 to probeset p2 if p1 fell within the top 1% probesets in terms of anti-correlation with p2. These directed networks were then converted into undirected SANs by requiring a reciprocal <1% ranking. We mapped each probeset to corresponding identifiers using the Affymetrix na26 annotation, then an undirected edge was established between two Entrez gene G1 and G2 if there was at least one edge from a probeset assigned to G1 to a probeset assigned to G2 and vice versa (reciprocal 1% ranking). We then constructed conserved anti-coexpression gene networks (CAGN) starting from SANs by mapping every identifier to the corresponding Homologene cluster (build 63). Two human genes G1h and G2h were connected in the CAGN if 1) they were connected in the human SAN, 2) booth of them were associated one-to-one to mouse genes by Homologene and 3) the corresponding genes G1m and G2m were connected in the murine SAN. We constructed 18 CAGNs: 15 are specific of a single tissue (Adipose tissue, ganglia, Gastrointestinal tract, Heart, Kidney, Liver, Lung, Lymphatic tissues, Ovary, Prostate, Skeletal muscle, Stratified Epithelium), meaning that both the human and the murine SAN contributing to the tissue specific CAGN are based on samples derived from the same tissue. The three remaining CAGNs are not tissue-specific, because one is based on all the samples contained in the database, the second is based on the samples deriving from all the normal human and mouse tissue while the third derives from tumor cells data. We have previously shown [30] that coexpression information deriving from various tissue-specific datasets and from heterogeneous non-tissue-specific datasets contains highly complementary information. We thus chose to merge all the 18 CAGNs into a single one that we used for subsequent analyses (the merged network contained 15954 genes).

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: TFW, total fruit weight per plants; MFW, marketable fruit weight per plant; MF, marketable fruits per plant; same letters within the column indicate no significant differences between treatments (p <0. 05). Open table in a new tab3. 3. 3 Fruit yieldsThe marketable fruit yield (kg/plant) of the single and combined entomopathogens treated Gellila variety showed considerable variations (Table 7). Thus, almost all of the strains applied in consortia and combined with insecticide showed the highest percentage of marketable fruit (87. 2–93. 8%) yields compared to positive control (86. 6%). All entomopathogens combined treatments (T5) and the two entomopathogenic fungi (B. bassiana-AAUB03 + M. anisopliae-AAUM78) combined with quarter-reduced concentration of insecticide (T6) showed marketable fruit yield of 10. 9 and 9. 7 kg/plant, respectively. Fruits obtained from the plants treated with consortia of entomopathogens showed a 25% significant (P < 0. 05) difference between the most and the least effective treatments with 40–55% yield increase compared to the untreated control. It is interesting to note that there was no significant (P < 0. 05) variation in marketable fruits yield between the plants treated with B. bassiana-AAUB03, combination of B. thuringeinsis-AAUF6 and half concentration of Tutan36% SC and the full dose of Tutan36%SC treated plants. The finding showed that 9. 7, 9. 2 and 9. 8 kg/plant with 86. 3, 87. 2 and 86. 6% of fruit marketability, respectively (Table 7). Similarly, the Coshoro variety tomato treated with B. bassiana was produced 98. 2% of marketable fruit yield in Ethiopia [49]. However, the second least effective entomopathogen, B. thuringeinsis-AAUF6 showed more than 2-folds of fruit yields (8. 4 kg/plant) compared to 3. 2 kg/plant of marketable fruit yields scored by tomato plants treated with commercial B. thuringeinsis (Costar®) under field conditions [55].

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-1216059/v1This work is licensed under a CC BY 4. 0 LicenseStatus:PostedVersion 1posted You are reading this latest preprint versionAbstractThis study investigates the mechanism of seasonal sea ice variation and recent warming amplification. Seasonal temperature changes in the vertical structure reveal that the autumn and winter seasons are warming more than summer. The thermodynamic processes of sea-ice-air interactions via the heat flux component have been studied. The summer ice has receded by half (∼52%), producing excessive heat. This sea ice loss plays a significant role in determining the heat exchange between the ocean and atmosphere in the following season. During a warm season, the ocean heats up due to incident solar radiation. As a result, delayed ice growth and atmospheric warming occur. Sea ice and heat flux feedbacks explain a large part of Arctic atmospheric warming. These abrupt changes are closely coupled to accelerated ice loss and atmospheric warming, which are still uncertain. Tropospheric warmingArctic amplificationturbulent heat fluxradiative heat fluxand net heat fluxFiguresFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6IntroductionArctic sea ice variability and dynamics are important indicators of climate change 1,2 strongly influenced by ocean-atmosphere forcing 3. The accelerated decline in Arctic sea ice extent (SIE) was recorded at a rate of -4. 7% per decade annually 4. In contrast, the highest SIE decline was observed in summer (-76. 5±6. 1 ×103km2yr-1), and the lowest was observed in spring (-39. 8±2. 9 ×103km2yr-1) 5. Hence, the primary concern of Arctic sea ice studies is seasonal sea ice variability, particularly during summer 6. Since the satellite era, multiyear ice has decreased dramatically, leading to thinning of Arctic sea ice 7–9. Changes in sea ice thickness are attributed to the interaction between dynamic and thermodynamic responses 10,11 of sea ice cover to the ocean and atmospheric forcing 12. In the past four decades, approximately 40% of summer Arctic sea ice has been lost 13, resulting in strong heat transfer from the ocean to the atmosphere through large open seas. Warming in the Arctic has been recorded twice as much as the global temperature average known as (AA) 14–17.

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Finally, for each gene G present in the merged CAGN, we define a conserved anti-coexpression gene cluster (CAGC), composed by the nearest-neighbours G' of the gene G in the merged CAGN. The gene G, the centre of the cluster, is not considered as a member of the cluster. CAGC are available as Additional file 2 on the journal web site and at the URL disease phenotypes described in OMIM were correlated on the basis of MimMiner [32]. MimMiner assigns a similarity score to all pairs of OMIM phenotype records, based on the text mining analysis of their phenotype descriptions. The pheno-cluster of the phenotype P is the set of genes directly associated by OMIM to P or to a phenotype P' whose similarity with P is at least 0. 4. The reason for choosing this cutoff is that biologically meaningful relationships were mostly detected in phenotype pairs with a similarity score equal to or greater than this value [32]. Drug-phenotype associationWe statistically associated drug targets to phenotypes by evaluating the overlap between the CAGC and Pheno-Clusters, through a Fisher exact test. We considered as significant the overlaps with P value < 1e-4, corresponding to 2. 5% Benjamini-Hochberg FDR. We used as reference for known drugs and targets DrugBank version 3 [33]. If a drug targeted a CAGC centre and there was a statistically significant association between the CAGC and one or more phenotypes, we putatively inferred an effect of the drug for these phenotypes. The idea under this inference criterion is that, if a drug D inhibits its targets, D should increase the expression of the CAGC centered in G with an effect on the associated phenotypes. If this inference criterion is valid, then we can predict that a drug will increase the expression of CAGCs centered in its targets. To validate this observation we used gene-expression profiles derived from the treatment of cultured human cells with a large number of perturbagens produced by the CMap project (build 2) [16]. For the purpose of the current validation CMap can be viewed as a matrix having genes on the rows and experiments on columns. Each experiment consists of a perturbation of a cell-line with a given concentration of a drug.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: All these effective treatments showed 20–33% marketable yield increment compared to plants treated with the least effective strain (M. anisopliae-AAUM78). Shibru and Getu [49] have reported 78. 5% of marketable fruit yield from the tomato treated with M. anisopliae, which is comparable with the result (78. 9%) obtained from our M. anisopliae-AAUM78. Thus, treatments with their own effectiveness in control of T. absoluta enhanced the production of marketable yield compared to untreated plants. This suggests that all of the treatment options are effective to control T. absoluta and produce tomato on sustainable basis. 3. 4 Effect of entomopathogens on the growth of tomato plantsInterestingly, none of the applied entomopathogens caused any negative effect on the growth of tomato, rather they showed better growth performance and productivity in both greenhouse and field conditions (Table 8). All the tomato varieties (Awash, Venes and Gellila) treated with entomopathogens showed 40–83 cm of shoot length and 12–45 number of shoot branches (Table 8). It is almost equal or better compared to tomato treated with Tutan36%SC. In fact, B. bassiana showed plant growth promotion and increased height, number of leaves, grain weight, crop yield, and germination on the corn crop besides reducing larvae of Rachiplusia un [56]. TreatmentsResults from greenhouse conditionAwash varietyVenes varietySL (cm)PB (n)SL (cm)PB (n)AAUB0348 ± 1. 24b15 ± 1. 44a43 ± 3. 07c16 ± 1. 58bAAUB2852 ± 1. 89a12 ± 1. 44c47 ± 1. 94b16 ± 1. 44bAAUM3953 ± 2. 36a16 ± 1. 00a40 ± 2. 42d15 ± 1. 23bAAUM7843 ± 1. 44c14 ± 1. 00b44 ± 2. 30c16 ± 1. 00bAAUF650 ± 2. 04ab14 ± 1. 23b48 ± 1. 44ab18 ± 1. 00aAAUMF951 ± 1. 62a15 ± 1. 23a51 ± 2. 24a12 ± 1.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: According to recent model-based research, the Arctic temperature will rise to 5°C by 2100 18. ice-albedo process is the primary cause of Arctic sea ice growth and retreat 14. This process is slowed in the summer because the sea ice begins to melt during the early warming phase, allowing more heat to be absorbed and the sea ice to shrink. In the winter, however, the process is reversed, with cold driving up sea ice growth. Due to variations in the amount of sunlight, ice-albedo feedback mechanisms are weaker in the summer and more robust in the autumn and winter 1,19. Furthermore, the cold and warm waters from the adjoining seas are driven by wind and accelerate the process of sea ice growth or retreat 20,21. If current trends continue, the Arctic will have an ice-free summer 22 and be open for trade and commerce soon by the end of this century. Previous studies have shown that air circulation is a crucial factor in seasonal sea ice variability 8,23. The atmospheric circulation pattern directly influences Arctic sea ice thermodynamics and oceanic heat flux. Air temperature (AT) has been found to rise across the vertical column of the atmosphere, from the surface to the high troposphere, resulting in exacerbated Arctic warming 24,25. There is no clear link between warming in the Arctic and changes in sea ice concentration, sea surface temperature (SST), and Eurasian snow cover 26. However, direct radiative forcing and poleward heat transfer 27,28 are important factors for upper-tropospheric warming in the Arctic 29. The decadal trends were computed in this work to determine the dominant spatial pattern of seasonal sea ice and temperature variability in the Arctic region. Furthermore, the thermodynamic processes responsible for seasonal sea ice variability, such as turbulent, radiative, and net heat fluxes, were investigated to comprehend the impact of ongoing seasonal sea ice loss induced by ice-ocean-atmosphere interactions. The primary forces for the rapid melting of sea ice and atmospheric warming aloft the surface have been identified. This study provides new insight into the relative role of thermodynamic forcing in the seasonal variability of Arctic sea ice and vertical variations in atmospheric temperature. Table 1 sea ice extent trends and standard errors from 1979–2020 were calculated. Based on a null hypothesis of zero trends with degrees of freedom 40 (n = 42−2), the R values are highlighted at a significance level of 99% (bold).

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: The matrix values are properly rank-transformed ratios between normalized expression values of the gene in the treated cell-line and a control; the greater the value the greater the fold-change in expression of the gene in the case versus the control. CMap reports the data in terms of Affymetrix probesets, which we mapped to using the standard Affymetrix annotation (version na32). Since many probesets can be associated to the same gene, in each CMap instance we define the gene rank as the rank associated to the probeset with the highest rank. This explains why the gene rank distribution tends to be growing (see Figure 3) while the distribution of probeset rank is uniform by construction. Moreover some ranks are lost since some probesets can't be associated to any gene. Since DrugBank and CMap use different drug identifiers, we were able to associate CMap data to only 682 DrugBank compound. We used Chembl (version 12) [55] as a third source of drug information to map drug identifiers. Given a CAGC associated to a drug D, we expect that its genes are over-expressed in cell lines treated with the drug targeting the CAGC centre. We tested this hypothesis independently for each CMap experiment that uses the D (there are possibly many experiment using the same drug with different concentration or different cell-lines) with a two sided Mann-test. For each drug we performed N x M tests, where N is the number of CAGCs whose centre G is targeted by D, and M is the number of experiments in CMap that involve D. Functional enrichment statistical validationTo verify that CAGC tend to contain genes sharing the same biological function we defined two functional indices, 1) for GO categories, 2) for pheno-clusters. Given a CAGC we used the Fisher exact test to compute the p-value of the enrichment of genes in each GO category (pheno-cluster). The GO (pheno-cluster) functional index of a CAGC is then the p-value of the most significant GO category (pheno-clusters).

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: 41dTutan36%SC (Positive control)49 ± 2. 47ab15 ± 1. 44a49 ± 1. 00ab14 ± 1. 23cWithout any (Negative control)43 ± 2. 12c8 ± 1. 23d48 ± 3. 56ab10 ± 1. 44eResults from field conditionGellila varietyAAUB0379. 45 ± 2. 08ab35. 8 ± 1. 45cAAUM7879. 07 ± 1. 54ab37 ± 2. 72cAAUF679. 82 ± 2. 45ab39. 7 ± 1. 34bAAUF6 + AAUM7881. 64 ± 1. 98a44. 93 ± 0. 94aAAUB03 + AAUM78 + AAUF683. 84 ± 3. 12a45. 11 ± 2. 54aAAUB03 + AAUM78 + 25% Tutan36%SC79. 25 ± 2. 09ab38. 73 ± 3. 21bAAUF6 + 50% Tutan36%SC77. 32 ± 2. 06b36. 52 ± 4. 67cTutan36%SC (Positive control)71. 05 ± 2. 45c33. 18 ± 4. 23cWithout any (Negative control)67. 3 ± 4. 12d26. 41 ± 1. 43eTable 8The effect of entomopathogens on the growth of tomato varieties under greenhouses and field conditions. SL, mean shoot length; PB, mean number of branches per plant; same letters within the column indicate no significant differences between treatments (p <0. 05). Open table in a new tabThe entomopathogens might be fully colonize plants and induce growth besides insect damage reduction or entomopathogens could also antagonize certain pathogens and favor the growth of plants [56, 57]. In addition, Metarhizium spp. produced plant growth hormones (auxin and cytokinins), the cellular division stimulator [24] and nutrient bioavailability modifier, siderophore [58, 59] that augment growth of plants. Furthermore, endophytic microbes induce adaptation of plants to environmental stresses and improve metabolic pathways through interlinking each other to exchange compounds that improve efficient functioning [60], produce antibiotics and plant growth enhancing substances [61]. 4 ConclusionIn conclusion, single and consortium application of B. bassiana, M.

Output: corroborate


Input: Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: 103km2yr−1 R %Decade−1 Annual -56. 9±2. 5 -23. 03 -4. 7±0. 2 Spring -43. 9±3. 0 -14. 76 -3. 2±0. 2 Summer -83. 2±5. 4 -15. 46 -10. 3±0. 6 Autumn -55. 0±4. 2 -13. 22 -5. 0±0. 3 Winter -46. 5±3. 1 -15. 19 -3. 0±0. 2 DiscussionSince 1979, the total Arctic SIE decadal trend has shown that summer has the highest negative trend (-10. 3±0. 6% decade-1) followed by autumn (-5. 0±0. 3% decade-1), spring (-3. 2±0. 2% decade-1) and winter (-3. 0±0. 2% decade-1) (Table 1). Arctic sea ice declines at a rate of -56. 9±2. 5 ×103km2yr-1 throughout the year, with the maximum loss in summer and autumn and the minimum loss in spring. The interannual variation in the Arctic recorded a dipping minimum SIE in 2020 (3. 74 million km2), which is 0. 35 million km2 more than the lowest record of 2012 (3. 39 million km2) 30. The decadal trend in seasonal ice and temperature is examined in the following sections to further understand the decadal variation. Seasonal variations in sea ice and temperature In the last four decades, the SIC trend in Baffin Bay, the Sea, Barents, and the has shown a significant negative trend in all seasons (Fig. 1a-d). Summer experiences, maximum SIE losses throughout the Arctic except for a small region of the central Arctic. The marginal seas have been identified as the area experiencing the most significant loss in decadal SIC from spring to autumn. The SIC and SST have a substantial negative correlation throughout the year, whereas a significant negative correlation (r = −0. 95, p <0. 01) was observed in summer compared to the other seasons (Table S1). Notably, the region is not permanently frozen, and it has a higher SST (Fig. 1e-h).

Output: contrast


Input: Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: We computed the functional indices for each CAGC in the real network and in 100 random networks obtained by permuting node (gene) labels, and finally we compared the cumulative distribution of functional indices derived from real versus randomized networks using a Kolmogorov-Smirnov test (see Figure 2). GO data [31] were obtained from the site. All the associations were considered, including those inferred from electronic annotation (IEA). 9. 10. 1016/j. healthpol. 2010. 05. 017. 56. 10. 1093/bib/bbr021. 20. 10. 1007/s00439-012-1206-y. 74. 10. 1161/. 111. 258541. 14. 10. 2133/dmpk. DMPK-10-RV-062. 74. PubMed 60. 10. 4103/0022-3859. 81870. 310. 10. 1016/j. drudis. 2011. 02. 016. 8. 10. 1093/nar/gkr299. 20. 10. 1038/nbt. 2151. 33. 10. 1002/ibd. 22958. 6. 10. 1073/pnas. 1000138107. 5. 10. 4161/auto. 6. 8. 13551. 60. 10. 1038/nrc2044. 35. 10. 1126/science. 1132939. 10. 1371/journal. pmed. 0040122. 91. 10. 1016/j. copbio. 2008. 07. 011. 11. 8. 10. 1073/pnas. 95. 25. 14863. 10. 1371/journal. pcbi. 1000043. 10. 1371/journal. pone. 0002439. 10. 1186/1471-2105-9-208. 10. 1186/1471-2105-5-179. 255. 10. 1126/science. 1087447. 28. CAS PubMed 505. 10. 1104/3650. 9. 10. 1093/bioinformatics/btg209. 6. 80. 10. 1038/ejhg. 2011. 96. 9. 10. 1038/75556. 42. 10. 1038/sj.

Output: pass


Input: Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: anisopliae and B. thuringeinsis against T. absoluta showed considerable leaf and fruit damage reductions. B. bassiana-AAUB03, M. anisopliae-AAUM78 and B. thuringiensis-AAUF6 are the most effective strains in T. absoluta management. Their consortia and combination with quarter or half dose of Tutan36% SC showed stronger activity in reduction of T. absoluta infestation. Besides to pest control activity, entomopathogens improved crop productivity without any effect on the growth of the plant in both greenhouse and field conditions. Therefore, application of entomopathogens in single, consortium and combining with reduced concentration of recommended rate of insecticide could be utilized in IPM strategy. DeclarationsAuthor contribution statementBirhan Aynalem: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper. Diriba Muleta; Mulissa Jida; Fekadu Shemekite; Fassil Aseffa: Contributed reagents, materials, analysis tools or data; Wrote the paper. Funding statementThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Data availability statementData included in 1. 13 MB)Supplementary material 1. Duressa, F. T. Newly emerging insect pests and diseases as a challenge for growth and development of Ethiopia: the case of Western OromiyaJ. Agri. Sci. Food Res. 2017; 9:1-62. Tonnang, H. E. Z. ∙ Mohamed, S. F. ∙ Khamis, F. . . . Identification and risk assessment for worldwide invasion and spread of Tuta absoluta with a focus on Sub-Saharan Africa: implications for phytosanitary measures and managementPLoS One. 2015; 10:1-193. Santana, P. A. ∙ Kumar, L. ∙ Da-Silva, R. S. . . . Global geographic distribution of Tuta absoluta as affected by climate changeJ. Pest. Sci. 2019; 92:1373-1385CrossrefScopus (83)4. Desneux, N. ∙ Luna, G. M. ∙ Guillemaud, T. . . .

Output: corroborate