Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is irrelevant (pass) to the claim as it discusses various aspects of innate immune receptors and pathogen recognition without any mention of bioinformatics or genetic diseases. It does not provide information that supports or contradicts the claim about eliminating genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that B. bassiana is used in treatments that protect tomato varieties from pests like T. absoluta, indicating its effectiveness as a biocontrol agent. It shows that treated plants with B. bassiana produced a larger number of marketable fruits compared to untreated controls, reinforcing its role in pest management.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by questioning the current understanding of melting processes and the conditions in the Arctic, indicated by phrases like 'this means that it is likely that MIZ closer to the pack ice has a different balance of processes' and 'this means that the results here could be seen as a lower estimate on the ice loss'. These statements suggest that there is still uncertainty regarding ice recovery and that previous melting may have lasting effects, going against the claim that the ice has recovered and that there are no long-term impacts.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text does not provide any information related to the claim about bioinformatics and genetic diseases. It consists of a collection of references to various studies focusing on immune response, inflammation, and signaling pathways, but does not mention bioinformatics or its potential implications for genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by providing details on how B. bassiana treatments were effective, indicating that it can significantly increase marketable fruit yields compared to untreated plants. The mention of the specific treatment, 'B. bassiana-AAUB03,' leading to higher yields supports its use as a biocontrol agent against insect pests.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by discussing ongoing issues with Arctic ice mass balance and projections for future ice conditions. It mentions validating model simulations for different periods, highlighting that the ice cover is projected to be seasonally ice-free by the 2040s. This indicates a significant loss rather than a recovery, contradicting the claim that the majority of ice has recovered and suggesting long-term effects from previous melting.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is irrelevant to the claim about bioinformatics eliminating genetic diseases. It primarily discusses tyrosine kinase genes and cytokine responses without addressing the potential role of bioinformatics in disease elimination.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by stating that B. bassiana-AAUB03 produced a substantial marketable fruit yield and performed comparably to other biocontrol agents in protecting tomatoes, indicating its effectiveness as a biocontrol agent against pests causing damage to the crop.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by discussing the maximum sea ice extent and its decline, stating that the extent in the 2040s shows a modest decline compared to the 1980s. This implies that there is not a full recovery of the ice and suggests ongoing effects from previous melting rather than a lack of long-term consequences.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text does not address the claim regarding bioinformatics and its potential to eliminate all genetic diseases. Instead, it focuses on inflammatory bowel diseases and genetics without providing any information or evidence related to the effectiveness of bioinformatics in disease elimination.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by detailing the effectiveness of the commercial B. bassiana (Beaucitech® WP) as a biocontrol agent, specifically mentioning its ability to provide 90–98% leaf protection against pest infestation in the Roma tomato variety. This illustrates its role as a biocontrol agent in agricultural pest management.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by discussing ongoing processes in the Arctic that contribute to sea ice melt, such as increased lateral melting and the positive feedback loops associated with lower sea ice concentrations. It addresses the implications of these processes and suggests that the marginal ice zone (MIZ) will increasingly dominate the Arctic sea ice cover, indicating that there are significant long-term effects from previous melting, contradicting the idea that the majority of ice has recovered.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the analysis of gene expression data and the effects of drug treatments on gene regulation. It does not mention bioinformatics eliminating genetic diseases or provide evidence supporting or opposing this idea.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by providing specific findings that demonstrate the effectiveness of Beauveria bassiana (B. bassiana) as a biocontrol agent against the pest Tuta absoluta. It states that the treatment of B. bassiana-AAUB03 maintained 91% leaf protection and produced successful outcomes in pest control, thereby supporting the role of B. bassiana in biocontrol.


Input: Task: contrast the claim using the given text. 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". [SEP] Justify:

Output: The text contrasts the claim by discussing how the marginal ice zone (MIZ) is projected to increase as the Arctic transitions to ice-free summers, suggesting that there are still significant changes occurring in the ice cover, which challenges the idea of recovery and absence of long-term effects from melting ice.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is largely irrelevant to the claim about bioinformatics eliminating all genetic diseases. Instead, it discusses the association of drug targets to mendelian genetic disorders and the potential for certain drugs to treat genetic conditions. While it mentions potential treatments and drug associations, it does not support the idea that bioinformatics will eliminate all genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by mentioning 'B. bassiana-AAUB03' as one of the treatments evaluated for its efficacy against pests. It compares its effectiveness in producing marketable fruit and reducing damage in a tomato variety, indicating its usage as a biocontrol agent in the context of pest management.


Input: Task: contrast the claim using the given text. 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? [SEP] Justify:

Output: The text contrasts the claim by discussing the ongoing changes in Arctic sea ice, particularly the mention that '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.' This indicates that rather than recovering, ice conditions continue to change, highlighting long-term effects from past melting rather than a complete recovery.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various genetic targets and therapeutic approaches for specific genetic diseases, such as ROCK1 inhibitors and their effects on certain disorders like cardiac hypertrophy and muscular dystrophy. However, it does not provide any evidence or assertion that bioinformatics can ultimately eliminate all genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by specifically mentioning 'B. bassiana-AAUB03', which indicates the use of Beauveria bassiana as a biocontrol agent, alongside detailed outcomes related to its effectiveness in fruit production and protection against insect pests. This demonstrates its application in pest management, supporting the claim.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by indicating a lack of a clear recovery in the Arctic ice and emphasizing that understanding of sea ice processes, such as wave-ice interaction and lateral melt, requires more focus in climate models. The discussion includes how current analyses reveal ongoing complexities in sea ice dynamics, suggesting there are significant processes at play that impact the volume budget of Arctic ice rather than indicating a recovery.


Input: Task: pass the claim using the given text. 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). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the generation of specific network models based on gene expression data with no mention of eliminating genetic diseases or the potential impact of bioinformatics in doing so.


Input: Task: corroborate the claim using the given text. 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]. [SEP] Justify:

Output: The text corroborates the claim by demonstrating the effectiveness of Beauveria bassiana (B. bassiana) as a biocontrol agent in improving marketable fruit yields. It specifically mentions that treatment with B. bassiana produced a significant percentage (98.2%) of marketable fruit yield in the Coshoro variety tomato in Ethiopia, indicating its role in pest control and plant productivity.


Input: Task: contrast the claim using the given text. 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. [SEP] Justify:

Output: The text contrasts the claim by presenting evidence of significant ice loss in the Arctic. It states that approximately 40% of summer Arctic sea ice has been lost in the past four decades and that there has been an accelerated decline in Arctic sea ice extent recorded at a rate of -4.7% per decade. This suggests that rather than recovering, the Arctic ice has diminished significantly, indicating potential long-term effects from melting.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text does not address the claim regarding the potential of bioinformatics to eliminate all genetic diseases. Instead, it discusses gene co-expression clusters and statistical associations between drug targets and phenotypes, which does not provide evidence for bioinformatics achieving the elimination of genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that Beauveria bassiana (B. bassiana) not only serves to control pests effectively but also promotes growth in crops such as corn, which supports its use as a biocontrol agent. It mentions that B. bassiana contributed to increased height, number of leaves, grain weight, and crop yield, further establishing its efficacy in pest control and plant growth promotion.


Input: Task: contrast the claim using the given text. 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). [SEP] Justify:

Output: The text contrasts the claim by highlighting that ongoing research shows that Arctic temperature is expected to rise significantly, and the dynamics of sea ice growth and retreat are influenced by various factors, including air circulation and thermodynamic processes. It mentions that the Arctic may have an ice-free summer if current trends continue, which implies that previous melting is still affecting sea ice extents and that recovery is not as pronounced as the claim suggests.


Input: Task: pass the claim using the given text. 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). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the methodology of analyzing gene expression data and statistical validation related to drug interactions and gene functions. It does not provide any information supporting or opposing the assertion that bioinformatics can eliminate all genetic diseases.


Input: Task: corroborate the claim using the given text. 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. [SEP] Justify:

Output: The text corroborates the claim by discussing the effects of Beauveria bassiana (B. bassiana) as an entomopathogen, which is known to reduce insect damage and enhance plant growth. The statement emphasizes that B. bassiana is among the entomopathogens applied singly or in consortium, indicating its role in biocontrol strategies. Furthermore, it mentions that fungal pathogens can interact beneficially with plants, thus supporting the notion of B. bassiana being utilized as a biocontrol agent.


Input: Task: contrast the claim using the given text. 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). [SEP] Justify:

Output: The text contrasts the claim by providing quantitative evidence of the continuing decline of Arctic sea ice extent (SIE) and highlights a significant negative trend in seasonal ice over the last four decades. It specifically notes that summer has the highest negative trend and states that the total Arctic SIE continues to decrease, indicating that rather than recovering, the ice has been consistently losing extent with significant losses observed in summer and autumn.


Input: Task: pass the claim using the given text. 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. [SEP] Justify:

Output: The text does not address the claim regarding bioinformatics' ability to eliminate all genetic diseases. Instead, it describes a method for computing functional indices in networks, which is unrelated to the claim.


Input: Task: corroborate the claim using the given text. 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. . . . [SEP] Justify:

Output: The text corroborates the claim by mentioning 'B. bassiana-AAUB03' as one of the most effective strains in managing 'T. absoluta,' which indicates its use as a biocontrol agent against this pest. This supports the assertion that Beauveria bassiana is indeed utilized in biocontrol strategies.


Input: Task: contrast the claim using the given text. 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 the inflow of warmer Atlantic waters, which keeps the area ice-free 11,31,32. Furthermore, the Arctic is warming rapidly, with temperatures rising by up to 0. 5°C at its marginal seas. There is accelerated heat and energy transfer from the ocean to the atmosphere aided by the lower trend in SIC, and it is primarily linked to the AA 14. Moreover, the increase in temperature during cold seasons (autumn and winter) is one of the possible reasons for the amplified warming in the Arctic 28. Similarly, the present study found differential atmospheric warming and cooling in different seasons in the Arctic by analyzing the seasonal and decadal trends of T2M (Fig. 1i-l). We observed a significant positive T2M trend throughout the year, with the highest trend during cold seasons compared to the warm season. During the summer, most of the heat observed from the atmosphere is used to melt the sea ice, resulting in a lower surface temperature (Fig. 1k). On the other hand, the T2M trends in autumn are higher due to the underlying mechanism through which absorbed latent oceanic heat is released back into the atmosphere during the summer. This contrasting behaviour of seasonal T2M is often attributed to the accelerated melting of sea ice, which keeps the surface air temperature near freezing in boreal summer 33,34. The enhanced heat flow from the exposed open sea surface, rather than ice-albedo feedback, is responsible for amplifying temperature during the cold season 35. However, the Arctic SIC shows a significant negative correlation with the T2M in all seasons, with the highest correlation in autumn (Table S1). Furthermore, in the following section, we have attempted to determine the mechanism responsible for temperature amplification in the Arctic. in the of the seasonal variations in air temperature (AT) at the vertical level in the (30ºN-90ºN) are shown in Fig. 2. Warm seasons have a lower AT trend than cold seasons, which corresponds to the observations in the previous section. The question is to determine what drives significant warming in the mid- and upper Arctic atmosphere during the cold seasons. The temperature variation of the Arctic atmosphere on the surface and in the air aloft is influenced by the quantity of sea ice cover. As a result, during sea ice melting, surface amplification occurs14, resulting in stable atmospheric stratification at lower altitudes in the summer. [SEP] Justify:

Output: The text contrasts the claim by detailing the ongoing warming and melting processes occurring in the Arctic. It states that factors such as the inflow of warmer Atlantic waters and rising temperatures are contributing to an ice-free Arctic, which implies that the majority of ice has not recovered. Additionally, the text discusses the significant correlations between sea ice cover and temperature variations, suggesting that previous melting does have long-term effects on atmospheric temperatures and ecosystem dynamics.


Input: Task: pass the claim using the given text. Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Skip to main content Explore journals Get published About BMC My account Search all BMC 1. Though the length L is usually fixed to be a small value (e. g. , 13) in previous studies [2, 3], it is still infeasible to perform exhaustive search to check all potential phosphorylation motifs. Besides, it is also unclear which metric is more suitable to measure the statistical significance of the motif. To efficiently find phosphorylation motifs, two heuristic methods have been proposed. The Motif-X method [2] is a greedy algorithm that reports motifs in an iterative manner. In each round, one most statistically significant motif is detected. The peptides matching the motif identified in the first round are removed prior to the second round of searching. This procedure repeats a number of rounds until no significant motifs can be found. The MoDL method [3] is an optimization-based algorithm, which formulates the motif-finding problem as the minimization of description length. In other words, MoDL tries to optimize the expressiveness of a set of motifs rather than quantifying the significance of a single motif. However, both Motif-X and MoDL can only find a small subset of phosphorylation motifs. They cannot guarantee to find all statistically significant motifs so that some important phosphorylation patterns remain unknown to biologists. Furthermore, Motif-X is limited to discover non-overlap motifs while MoDL unusually reports at most three motifs. In this paper, we present a new algorithm called Motif-All for the discovery of all statistically significant phosphorylation motifs. Motif-All uses the odds ratio to quantify the over-expressiveness of each motif in the set of phosphorylated peptides against the background set. To avoid exhaustive search, we impose a support constraint for each motif on the set of phosphorylated peptides. The use of support constraint enables us to borrow ideas from association rule mining [4] to generate and prune candidates in a level-wise manner before calculating the odds ratio. To demonstrate the superiority of Motif-All method, we conduct experimental studies using the PhosPhAt database 3. 0 of Arabidopsis phosphorylation sites [5, 6]. Motif-All performs better than Motif-X and MoDL in finding more significant phosphorylation motifs. [SEP] Justify:

Output: The text is irrelevant to the claim about bioinformatics eliminating all genetic diseases. It discusses algorithms for discovering statistically significant phosphorylation motifs without addressing the potential of bioinformatics to eliminate genetic diseases.


Input: Task: corroborate the claim using the given text. Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: The entomopathogen Beauveria bassiana has epiphytic and endophytic activity against the tomato leaf miner Tuta absolutaJ. Appl. Entomol. 2016; 140:580-589CrossrefScopus (0)18. Biswas, C. ∙ Dey, P. ∙ Satpathy, S. . . . Endophytic colonization of white jute (Corchorus capsularis) plants by different Beauveria bassiana strains for managing stem weevil (Apion corchori)Phytoparasitica. 2013; 41:17-21CrossrefScopus (50)19. Russo, M. L. ∙ Scorsetti, A. C. ∙ Vianna, M. F. . . . Endophytic effects of Beauveria bassiana on corn (Zea mays) and its herbivoreRachiplusia nu (Lepidoptera: Noctuidae) Insects. 2019; 10:110-119CrossrefScopus (0)20. Allegrucci, N. ∙ Velázquez, M. S. ∙ Russo, M. L. . . . Endophytic colonisation of tomato by the entomopathogenic fungus Beauveria bassiana: the use of different inoculation techniques and their effects on the tomato leaf miner Tuta absoluta (Lepidoptera: gelechiidae)J. Plant Protect. Res. 2017; 57:206-21321. Pourtaghi, E. ∙ Talaei-Hassanloui, R. ∙ Nasibi, F. . . . Endophytic colonization of tomato by Beauveria bassiana for control of the greenhouse whitefly, Trialeurodes vaporariorum (Hemiptera: aleyrodidae)Acta Biol. 2020; 14:149-160Crossref22. Gunatilaka, A. A. Natural products from plant-associated microorganisms: distribution, structural diversity, bioactivity, and implications of their occurrenceJ. Nat. Prod. 2006; 69:509-526CrossrefScopus (857)PubMed23. Ownley, H. B. ∙ Gwinn, D. K. ∙ Vega, E. F. [SEP] Justify:

Output: The text corroborates the claim by providing multiple examples of Beauveria bassiana being used against specific pests. It mentions its 'epiphytic and endophytic activity against the tomato leaf miner Tuta absoluta' and highlights its role in managing pests like the stem weevil and greenhouse whitefly. This supports the assertion that Beauveria bassiana is utilized as a biocontrol agent.


Input: Task: contrast the claim using the given text. Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: A previous study also found that AT in the Arctic has a highly stable and stratified vertical structure 3. During the spring season, the negative AT trend is confined to the upper atmosphere (∼250 hPa), which suggests that the influence of sea ice loss is constrained to the surface and lower levels of the atmosphere (Fig. 2a) due to limited vertical mixing 27. The summer AT trend recorded maximum warming in the mid-atmosphere relative to the lower and upper atmospheric AT (Fig. 2b). The positive ice-albedo feedback mechanism is more apparent during the summer. Increased atmospheric heat absorption by the ocean causes the open water to become warmer than the surrounding atmosphere. In all other seasons, mid-tropospheric warming is most likely due to an imbalance in horizontal energy transmission 28. The ocean's heat accumulated in the summer was released in the subsequent seasons, as observed in autumn (Fig. 2c). The AT trend in the mid-troposphere of the Arctic during autumn is approximately 0. 6°C per decade. The AT trend is positive during the cold seasons due to weak air stratification and greater vertical mixing. The upper troposphere (∼250 hPa) warms in the winter due to enhanced vertical mixing of heat and energy from the surface to the atmosphere aloft rather than ice-albedo feedback. Additionally, during the winter, the retreating sea ice and delayed freezing allow for the release of excess heat stored in the ocean 34,36,37. In the upper troposphere, a negative AT trend (60ºN-90ºN) is recorded in all seasons (Fig. 2a-c) except in winter, which shows a positive AT trend and winter warming (Fig. 2d). Arctic atmospheric warming above the surface might also be influenced by other possible factors such as cloud cover 38, increased downward LW radiation 35, heat and energy transfer from the lower latitudes, and differential radiative forcing 28. The following section investigated the role of heat fluxes associated with seasonal variations in Arctic sea ice cover. sea ice changes using and NHF This study examined the contribution of ocean-atmospheric heat fluxes to atmospheric warming and stability due to sea ice changes. Interannual and seasonal variations in sea ice cover were also investigated since they increase the interaction between the ocean, ice, and atmosphere. [SEP] Justify:

Output: The text contrasts the claim by discussing various aspects of Arctic atmospheric temperature trends and the implications of sea ice loss. It indicates that the influence of sea ice loss extends beyond seasonal fluctuations and that Arctic warming continues to be affected by heat fluxes and vertical mixing. Additionally, the text references how the retreating sea ice and delayed freezing contribute to further warming, which implies ongoing consequences from previous melting. Thus, it suggests that the ice has not recovered and may still be experiencing long-term effects from melting.


Input: Task: pass the claim using the given text. Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: Furthermore, it is very fast and is able to finish the mining of large data sets within a reasonable time period. The rest of the paper is organized as follows: Section 2 presents the Motif-All algorithm. Section 3 shows the experimental results. Section 4 gives some discussions and Section 5 concludes the paper. MethodsThere are two critical issues in phosphorylation motif finding. The first is how to measure the over-expressiveness of each motif. The second is how to perform the search in an efficient manner. In the proposed Motif-All method, we use odds ratio to evaluate if one candidate motif is over-expressed. To search efficiently, we use the following strategies to improve the running efficiency of Motif-All. We impose a support constraint on each candidate motif. Here the support for a motif is defined as the percentage of phosphorylated peptides that match this motif. The notation of support is widely used in association rule mining [4]. One motif is said to be frequent if its support is no less than a given threshold. The aim of introducing support constraint is two-fold: on the one hand, it can filter out non-frequent motifs that may correspond to random artifacts; on the other hand, it makes it possible to generate and prune motifs in a level-wise manner so as to avoid brute-force search. We divide the mining process into two stages. In the first stage, we perform frequent motif finding using only the data set P since the number of phosphorylated peptides is much smaller than that of unphosphorylated ones. In the second stage, we collect support information using the data set N to calculate the statistical significance of those candidate motifs from the first stage. We will report all phosphorylation motifs whose p-values are no larger than a user-specified significance threshold. Odds ratio and statistical significance scoreThe odds of an event is the probability that this event occurs divided by the probability that it does not occur. The odds ratio is defined as the ratio of the odds of an event in one group to the odds in the complementary group [7]. In the context of phosphorylation motif discovery, the first group corresponds to the set of phosphorylated peptides P and the second group is the set of unphosphorylated peptides N. For a given motif m, we can construct a contingency table as shown in Table 1. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the Motif-All algorithm and various technical aspects of phosphorylation motif finding in bioinformatics, without addressing or supporting the idea of eliminating genetic diseases.


Input: Task: corroborate the claim using the given text. Claim: Beauveria bassiana is used as a biocontrol agent against various pests. [SEP] Text: Endophytic fungal entomopathogens with activity against plant pathogens: ecology and evolutionBioControl. 2010; 55:113-128CrossrefScopus (305)24. Liao, X. ∙ Lovett, B. ∙ Fang, W. . . . Metarhizium robertsii produces indole-3-acetic acid, which promotes root growth in Arabidopsis and enhances virulence to insectsMicrobiology. 2017; 163:980-991CrossrefScopus (87)PubMed25. Batta, Y. A. Recent advances in formulation and application of entomopathogenic fungi for biocontrol of stored-grain insectsBiocontrol Sci. Technol. 2016; 26:1171-1183CrossrefScopus (27)26. Ibrahim, L. ∙ Dakache, C. ∙ Kreidy, M. E. . . . Environmentally sustainable production of Metrhizium anisopliae and Beauveria bassiana for control of Tuta absolutaInt. J. Agri. Biosyst. Eng. 2017; 2:1-1227. Shiberu, T. ∙ Getu, E. Entomopathogenic effect of Beauveria bassiana (Bals. ) and Metarrhizium anisopliae (Metschn. ) on Tuta absoluta (Meyrick) (Lepidoptera: gelechiidae) larvae under laboratory and glasshouse conditions in EthiopiaJ. Plant Pathol. Microbiol. 2017; 8:411-41428. Aynalem, B. ∙ Muleta, D. ∙ Venegas, J. . . . Morphological, molecular, and pathogenicity characteristics of the native isolates of Metarhizium anisopliae against the tomato leaf miner, Tuta absoluta (Meyrick 1917) (Lepidoptera: gelechiidae) in EthiopiaEgypt J. Biol. Pest Contr. 2020; 30:1-1129. Aynalem, B. ∙ Muleta, D. ∙ Venegas, J. . . . [SEP] Justify:

Output: The text corroborates the claim by discussing Beauveria bassiana's application as a biocontrol agent, particularly against Tuta absoluta, which is a pest affecting crops. The phrase 'Environmentally sustainable production of Metrhizium anisopliae and Beauveria bassiana for control of Tuta absoluta' explicitly connects Beauveria bassiana with pest control.


Input: Task: contrast the claim using the given text. Claim: The majority of ice in the Arctic has already recovered, and there are no long-term effects from previous melting. [SEP] Text: The seasonal sea ice growth or retreat is driven by the ocean-atmospheric heat exchange process influenced by the THF and RHF. sea ice variation is determined primarily by dynamic and thermodynamic mechanisms 39. The dynamic process involves the movement and accumulation of sea ice to the south, eventually melting. On the other hand, thermodynamics deals with the exchange of heat and energy between the ocean, ice, and atmosphere. Since several other mechanisms function simultaneously, these processes are independent. The earlier study revealed that one-third of the long-term variations in the oceanic heat content in the Arctic result from the fluctuation in ocean-atmosphere heat flux 40. In response to thermodynamic processes, our study focused on the seasonal change in sea ice. The surface RHF and THF signs illustrate the direction of ice-ocean-atmosphere interactions. The RHF is governed primarily by the wind speed and AT near the surface, whereas integrals across the entire atmospheric column mainly determine the THF. Reduced sea ice can provide positive surface THF (upward), heat up the atmosphere, and indicate that ice drives the atmosphere. The negative THF (downwards) implies that the atmosphere drives sea ice. The negative NHF is associated with heat from the ocean and vice versa 41. Accelerated sea ice loss in the Arctic will result in more heat transfer from the ocean to the atmosphere, resulting in atmospheric warming amplification. A composite analysis was carried out to explain the heat flow process that contributes to atmospheric warming and ice melting. ice loss occurs throughout the year, but we considered the heat flux changes only in the negative SIC phase in this study. During the negative SIC phase in spring, the peripheral Arctic seas have negative anomalies, with only the central Arctic experiencing positive anomalies (Fig. 3a). The increasing insolation causes the sea ice to melt with the onset of spring, resulting in a positive THF across the Arctic Ocean, whereas the RHF and NHF are observed to be negative (Fig. 3b-d). A positive LH anomaly has been found in the central Arctic, while a greater negative SH anomaly remains across the Arctic region (Fig. S1). The positive LH and SH fluxes imply that sea ice transfers heat to the atmosphere 42. Spring SIC had a significant (p <0. 01) positive correlation with THF (r = 0. 67), RHF (r = 0. [SEP] Justify:

Output: The text contrasts the claim by discussing the processes that drive sea ice variations in the Arctic. It indicates that accelerated sea ice loss leads to more heat transfer from the ocean to the atmosphere, which exacerbates atmospheric warming. The emphasis on the heat flux changes, atmospheric warming amplification, and the ongoing loss of sea ice throughout the year implies that rather than recovering, the sea ice is influenced by dynamic and thermodynamic mechanisms leading to significant changes and potential long-term impacts.


Input: Task: pass the claim using the given text. Claim: Bioinformatics can eliminate all genetic diseases in the future. [SEP] Text: In this table, c00, c01, c10 and c11 are non-negative “cell counts” and denotes that the motif m doesn’t exist. Then, the calculation of odds ratio reduces to: (1) Table 1 A contingency table for a phosphorylation motifFull size tableAn odds ratio of 1 means that the target motif is equally likely to exist in both P and N. An odds ratio greater than 1 indicates that this motif is more likely to appear in the set P. To conduct statistical inference, one approach is to use large sample approximations to the sampling distribution of the log odds ratio. More precisely, the sample log odds ratio is: (2) and the standard error for the log odds ratio is approximately: (3) Then, the z-valueZ(m) = LOR(m)/SE(m), (4)follows a standard normal distribution. Finally, we can calculate the p-value to assess the statistical significance of each motif. Frequent motif miningGiven a set of phosphorylated peptides P and a user-specified support threshold s, the objective of frequent motif finding is to discover all motifs whose supports are no less than s. The support for a motif is the percentage of phosphorylated peptides in P that match this motif. In other words, a motif m is frequent if and only if its cell count c00 in Table 1 satisfies c00 ≥ |P|s with | • | denoting the size of a set. Note that a similar occurrence constraint is utilized in the Motif-X algorithm [2], which represents the minimal number of phosphorylated peptides needed to match the residue/position pair in its greedy search procedure. There are two fundamental differences between our support constraint and their occurrence constraint: The support constraint is applied to the entire motif rather a single residue/postion pair. The support constraint can be used to prune the search space besides preventing the generation of random artifacts. One may argue that such a support constraint will result in the loss of some less frequent motifs that are statistically significant. We will explain its rationale from two perspectives: First, since the motif describes the phosphorylation pattern, it should be applicable to many substrates; otherwise, such pattern might be random artifact due to the limited number of known phosphorylation peptides. [SEP] Justify:

Output: The text is irrelevant to the claim regarding bioinformatics and genetic diseases. It focuses on statistical methods and motif finding in the context of phosphorylated peptides, without addressing the capability of bioinformatics in eliminating genetic diseases.