Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Most doctors, explains Miller, only look for a pre-specified, subset of potential mutations, hoping that whichever ones are found inside the tumour’s DNA have been linked to drugs that have demonstrated their effectiveness in fighting those mutations. The downside is that, even when mutations are identified, there is a limited array of treatment. “Metastatic cancer is largely unique among advanced medical conditions, because the therapies are so grossly inadequate that most treatments — even the good ones — fail,” says Miller. This cancer-drug-finding challenge has somehow turned the task of looking for the oddball mutation in specific types of cancer genes — alterations that would not normally be found in that tumour type — into a promising cancer-fighting strategy. When an assay uses an all-inclusive approach and ignores a mutation’s proclivity for certain types of cancer, a mutation — with a good-outcome drug associated with it — may turn up in the most unexpected tumours. As an example, Miller cites Herceptin (trastuzumab), a targeted therapy for an amplification of the human epidermal growth factor receptor 2 (HER2) gene often found in HER2-positive metastatic breast cancer and HER2-positive gastric cancer. “We have now seen — because we conduct the same broad test in every tumour type — either an amplification or mutation in this critical HER2 gene in nearly 30 different tumour types,” he says. Genomic alterationsCancer is caused by alterations to the genes that regulate cell growth and division. These alterations can affect the nucleotide sequence of the gene or the structure of the whole chromosome. variationSingle nucleotide polymorphisms (1), insertions (2) or deletions (3) may result in a change to the amino acid sequence of the encoded protein (missense mutation) or premature truncation (nonsense mutation), which can render the resulting protein non-functional. Structural variationLarge insertions (1), deletions (2) or duplications (3) of the entire gene can result in gene copy number changes leading to alterations in the levels of gene expression and overproduction or underproduction of the resulting protein. Inversions (4) or translocations (5) of a segment of the chromosome can create fusion genes, which may lead to a protein with a different function from the two fusion partners, or to up-regulation of the protein. [SEP] Justify:

Output: The text corroborates the claim by discussing how personalized medicine utilizes genetic data, such as identifying specific mutations in tumors, to tailor treatments like Herceptin to the unique genetic profiles of different cancer types. Miller emphasizes the importance of genetic understanding in treatment, illustrating how genomic alterations can lead to targeted therapies, thus supporting the essence of personalized medicine.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Все попытки «торговцев сомнением» [19] оспорить статус официальной экспертизы, подорвать общественное доверие к профессиональным компетенциям или моральным качествам конкретных ученых или теоретическому фундаменту целых дисциплинарных областей, а тем более продвижение альтернативного взгляда на проблему, оцениваются академией как антинаучные, деструктивные и социально опасные деяния. [SEP] Justify:

Output: The text contrasts the claim by stating that any attempts to challenge established scientific expertise or promote alternative views are considered anti-scientific and socially dangerous by the academic community. This implies that biohacking, viewed as an alternative approach, lacks academic legitimacy and hence cannot be recognized as a replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: The cotyledon cell wall and intracellular matrix are factors that limit iron bioavailability of the common bean (Phaseolus vulgaris). Food & Function, 7(7), 3193–3200. . (2019). The germ fraction inhibits iron bioavailability of maize: identification of an approach to enhance maize nutritional quality via processing and breeding. Nutrients, 11(4):833. doi:10. 3390/nu11040833. PMID: 31013776; PMCID: PMC6521246. . (2013). Seed coat removal improves iron bioavailability in cooked lentils: studies using an in vitro digestion/Caco-2 cell culture model. J Chem, 61(34):8084-9. doi:10. 1021/jf4022916. Epub 2013 Aug 14. PMID: 23915260. . (2014). Differences in relative iron bioavailability in traditional Bangladeshi meal plans. Bull, 35(4):431-9. doi:10. 1177/15648265140350040510. 1177/156482651403500405. PMID: 25639128. Lung’aho MG, Glahn RP. (2010). Use of white beans instead of red beans may improve iron bioavailability from a Tanzanian complementary food mixture. Res, 80(1):24-31. doi:10. 1024/0300-9831/a000003. PMID: 20533242. . (2020). Impact of ascorbic acid on the in vitro iron bioavailability of a casein-based iron fortificant. Nutrients, 12(9):2776. doi:10. 3390/nu1209277610. 3390/nu12092776. PMID: 32932834; PMCID: PMC7551990. Behind the is a with the Department of Agriculture, Service. He has over 32 years of experience in nutritional physiology and over 170 peer-reviewed publications. His major research focus is on factors that improve iron nutrition from staple foods, food products and food systems. for Agriculture and Health 538 Ithaca, NY 14853 USA E: [email protected] T: +1 607-255-2452 W: Department of Agriculture, Service (USDA-ARS). [SEP] Justify:

Output: The text discusses various studies related to iron bioavailability in different legumes and cereal grains, as well as the nutritional physiology associated with these food sources. It does not reference ancient civilizations or staple crops they relied on, thus being irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: In 2011, the technical cost, without the analysis, was around US$20,000. “Now it’s down to about US$4,000 per whole genome,” says Solit. “It’s still too expensive to do in every patient but it’s getting less expensive every year. One can envision that in 10 or 15 years, or sooner, it’s going to cost less than US$1,000 to sequence the entire genome of every patient’s tumour. ”Now, at MSKCC, patients with advanced metastatic cancer who have had their tumours genetically tested fall into one of three groups, says Solit. In the first group are patients whose cancer has a mutation for which there is an associated drug, which is prescribed for the patient. In the second group are patients whose cancer is found to have an activating driver mutation for which there is no associated drug. “Patients in this group may wind up in clinical trials that MSKCC may be offering,” he says. “Even though the patient is disappointed there’s no standard, approved drug to target the specific mutation, at least physicians can avoid treating them with a drug that has no chance of working, based on the assay. ” Finally, in the third group are patients whose tumours have no mutations of any of the 341 most commonly mutated cancer-associated genes. As more tumours are sequenced, Solit anticipates that the number of patients in the third group will shrink dramatically because the research will have advanced to find key mutations in all patients. And, with the development, regulation and approval of additional cancer drugs, the number of patients in the second group will also decrease. But if resourcing time and money is a challenge, so is the development of effective therapies. Solit points to the massive, international, and so far unsuccessful effort over the past 30 years to create a KRAS inhibitor. “Between 15% and 20% of patients have KRAS gene mutations, which are common in various cancers, and we still don’t have a good KRAS inhibitor,” he says. “There are a lot of cancer genes which are important, and we don’t have drugs to target them, either. ”Biological factorsFor some experts, wiping out cancer goes beyond sequencing and digs into the cunning core of cancer itself. [SEP] Justify:

Output: The text corroborates the claim by illustrating how genetic testing of tumors can influence treatment decisions. It mentions that patients with specific mutations may receive associated drugs while others may be directed to clinical trials, thereby tailoring patient treatment based on their genetic data. This aligns with the concept of personalized medicine that relies on genetic information to guide treatment choices.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Все попытки «торговцев сомнением» [19] оспорить статус официальной экспертизы, подорвать общественное доверие к профессиональным компетенциям или моральным качествам конкретных ученых или теоретическому фундаменту целых дисциплинарных областей, а тем более продвижение альтернативного взгляда на проблему, оцениваются академией как антинаучные, деструктивные и социально опасные деяния. [SEP] Justify:

Output: The text contrasts the claim by stating that attempts to undermine official expert status and promote alternative views, such as biohacking, are viewed by the academic community as anti-scientific and socially dangerous. This suggests that biohacking is not accepted as a valid replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: Jinfan Zhang3 733 Accesses AbstractThe discovery of Jian (the bamboo writing slips found in the tomb of Qin in Shuihudi) unearthed in Yunmeng county in Hubei province in 1975 revealed us the law of the state of Qin in Period. Although it did not include all the laws of the state of Qin, it was evident that the book was theoretically based on the theories of legalists and it had played the function of adjustment to the social life, state activities and the families and individuals in many aspects. This is a preview of subscription content, log in via an institution to check access. Access this 34. 9910 units per month Download 29. 95 Price excludes VAT (USA) Available as PDF Read on any device Instant download Own it forever Buy 139. 00 Price excludes VAT (USA) Available as EPUB and PDF Read on any device Instant download Own it forever Buy e179. 99 Price excludes VAT (USA) Durable hardcover edition Dispatched in 3 to 5 business days Free shipping worldwide - see info calculation will be finalised at checkout Purchases are for personal use only Institutional subscriptions Notes1. “Ji” (of Huang) in (of the Grand Historian). 2. “Ji” (of the State of Qin) in (of the Grand Historian). 3. “Ji” (of Huang) in (of the Grand Historian). 4. “Za Chao” (of Decrees of the State of Qin) in (in Qin Dynasty). 5. (Slips from the Tombs of Qin in Shuihudi), p. 128. 6. (Slips from the Tombs of Qin in Shuihudi), p. 285. 7. “Ding Fen” (Defining a Person’s Social Status) in Shu (of Lord Shang). 8. “Ji” (of the of Han Dynasty) in (of Han Dynasty) (Book 1). 9. “Ding Fen” (Defining a Person’s Social Status) in Shu (of Lord Shang). 10. “Shen Fa” (of Law) in Shu (of Lord Shang). 11. (of Han Dynasty). 12. “Xiu Quan” (On the Usage of Power) in Shu (of Lord Shang). 13. [SEP] Justify:

Output: The text does not address the claim regarding staple crops relied upon by ancient civilizations. It discusses the discovery of bamboo writing slips related to the state of Qin and elaborates on theories and laws without mentioning agricultural practices or staple crops. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: AbstractBipolar disorder involves diverse features and symptom targets that extend beyond mood alone. RCTs that establish drug efficacy for an overall diagnosis and illness state can help practitioners devise personalized combination therapy regimens that increase the probability of a desired outcome. AbstractThe quest for “personalized medicine” in psychiatry has focused mainly on pursuing potential biomarkers such as pharmacogenetic predictors of drug response. However, the collective randomized trial database across phases of bipolar disorder allows one to identify clinical characteristics that inform the likelihood of desired treatment outcomes. In turn, those characteristics, termed moderators and mediators of drug response, enable those who administer treatment to construct clinical profiles that can help them tailor pharmacotherapies to the features of a given patient rather than simply to an overall diagnosis. Bipolar disorder typically involves more heterogeneous than uniform clinical presentations, partly because of its highly prevalent psychiatric and medical comorbid conditions. Further clinical diversity arises from characteristics such as bipolar I versus II disorder subtype, rapid cycling, mixed versus pure affective episodes, psychosis, anxiety, chronicity, cognitive dysfunction, and suicidality, among other distinguishing features. By coupling such profiles with an awareness of the psychotropic breadth of spectrum held by particular medications, clinicians can devise strategic combination therapy regimens, capitalizing on synergies and using drugs that exert multiple relevant effects, addressing comorbid conditions, incorporating medications that could offset adverse effects of other agents, and avoiding or deprescribing medication options that lack known evidence to target symptoms within the clinical profile of a given patient. Bipolar disorder represents one of the most heterogeneous known forms of psychopathology. Although mood and affective disturbances are, by definition, core elements of the condition, more nuanced endophenotypic studies have placed increasing nosologic importance on related dimensions, such as changes in energy or motor activity (1), attentional and executive dysfunction (2), impulsivity and aggression (3, 4), anxiety (5), psychosis proneness (6), sleep-wake cycle dysregulation (7), susceptibility to formal thought disorder (8), and affective vulnerability to chronobiological and social rhythm disruptions (9). Moreover, given that two thirds of bipolar disorder patients have at least one distinctly comorbid psychiatric or substance use diagnosis (10), the clinical target profile for treatment of any given patient becomes far more complex than simply choosing a medication based solely on the overarching diagnosis. [SEP] Justify:

Output: The text corroborates the claim by discussing how personalized medicine, particularly in the context of bipolar disorder, involves constructing clinical profiles that tailor treatment regimens to the unique characteristics of individual patients. It describes the process of using clinical characteristics and potential biomarkers, such as pharmacogenetic predictors, to inform treatment decisions to fit the specific needs of each patient rather than relying solely on an overall diagnosis.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Все попытки «торговцев сомнением» [19] оспорить статус официальной экспертизы, подорвать общественное доверие к профессиональным компетенциям или моральным качествам конкретных ученых или теоретическому фундаменту целых дисциплинарных областей, а тем более продвижение альтернативного взгляда на проблему, оцениваются академией как антинаучные, деструктивные и социально опасные деяния. [SEP] Justify:

Output: The text contrasts the claim by stating that attempts to undermine official medical expertise and promote alternative views are deemed anti-scientific and socially dangerous by the academic community. This suggests that biohacking is not recognized as a valid replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: “Ding Fa” (Law Making) in Shu (of Lord Shang). 14. “Qu Qiang” (of the Disobedient) in Shu (of Lord Shang). 15. “Ding Fen” (Defining a Person’s Social Status) in Shu (of Lord Shang). 16. “Shang Xing” (Rewards and Punishments) in Shu (of Lord Shang). 17. “Kai Sai” (Reform) in Shu (of Lord Shang). 18. “Qu Qiang” (of the Disobedient) in Shu (of Lord Shang). 19. “Kai Sai” (Reform) in Shu (of Lord Shang). 20. “Suan Di” (Measuring Land) in Shu (of Lord Shang). 21. “Shang Xing” (Rewards and Punishments) in Shu (of Lord Shang). 22. “Shen Fa” (of Law) in Shu (of Lord Shang). 23. “Wai Nei” (and the Inner) in Shu (of Lord Shang). 24. “Kai Sai” (Reform) in Shu (of Lord Shang). 25. “Hua Ce” (Policies) in Shu (of Lord Shang). 26. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 27. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 28. (Qing Dynasty), “Zi Xu” (The Author’s Preface) to (Collections of Laws in Han Dynasty). 29. “Ji” (of Huang) in (of the Grand Historian). 30. “Da Wen” (and Answers) in (in Qin Dynasty). 31. “” (of the biographies of ) in (of the Grand Historian). 32. “Lv” (Statutes on the Regulation of Officials) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). 33. “Za” (Statutes on in the Capital) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses various laws and historical writings without addressing the agricultural practices or staple crops of ancient civilizations. There is no mention of staple crops or comparisons between different civilizations in terms of their agricultural reliance.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Consequently, asking what the best treatment is for mania or for bipolar depression becomes as nonspecific and oversimplified a question as if one were to ask how best to treat cancer or infections, or even heart disease. Bipolar disorder involves diverse and protean features with varied dimensions of psychopathology, expressed to greater or lesser degrees at different points in time. Optimal pharmacotherapy therefore requires devising individualized treatments suited to the unique characteristics of a given patient, following a model of personalized medicine. Hence, the main objective of this 1. Recognized moderators of bipolar disorder treatment outcomesModeratorRelevanceAge at onsetEarly onset (prepubertal, adolescent) is one of the more robust correlates of poor outcome, although it sometimes may be a proxy variable for more immediate causes of poor outcome (e. g. , social isolation or poorer premorbid functioning). Baseline severityHigh baseline severity tends to suppress placebo responsivity; it also provides the opportunity for greater variability in severity levels over time than that which occurs with the more restricted range of low baseline severity. ChronicityLong-standing illness states often respond less well than acute episodes to standard pharmacotherapies and incur higher risk for maladaptation to illness over time (e. g. , demoralization, diminished effort, loss of social and economic supports). Episode numberPatients who have endured multiple episodes may respond less well to lithium than to divalproex (15) and possibly other broader spectrum psychotropics. Predominant polarityEpisodes predominated by mania more than depression are associated with better responses to lithium, divalproex, and most second-generation antipsychotics; depression predominance more than mania is associated with better response to lamotrigine and quetiapine plus lithium or divalproex (16). SexDirect effects of sex on treatment outcome have not been described in bipolar pharmacotherapy trials, although indirect effects may bear on longitudinal outcome (e. g. , contraindication of divalproex and pregnancy, elevated postpartum risk for mood episodes, and an artifact of higher prevalence of rapid cycling among bipolar women than men [17]). Sex also may interact with mediating factors (e. g. , poorer adherence by men [18]). [SEP] Justify:

Output: The text corroborates the claim by stating that optimal pharmacotherapy for bipolar disorder requires devising individualized treatments tailored to the unique characteristics of a given patient, which aligns with the principles of personalized medicine. Although it does not explicitly mention genetic data, the emphasis on individualized treatments supports the notion that treatments are tailored to the specifics of each patient.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Биохакеры, переносят сами научные процедуры, а также анализ их результатов на интернет-платформы, «таким образом, данные исследований могут быть проверены, а их этическая обоснованность и безопасность могут быть оценены большей группой и более быстрыми темпами, чем традиционные эксперименты в закрытых лабораториях» [16, p. 215]. [SEP] Justify:

Output: The text contrasts the claim by discussing how biohackers conduct scientific procedures and analyze results in an open manner, suggesting that their methods and data can be evaluated more quickly and ethically than traditional laboratory experiments. This indicates that biohacking is not necessarily a recognized replacement for traditional medical treatments, rather it operates in a different framework.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: 34. “Lv” (of Executing the Commands) in (in Qin Dynasty). 35. “Zhao Ce” (of the State of Zhao) in Ce (Stratagems of the Warring States). 36. “Qiang Guo” (a Prosperous Country) in (Xun Zi). 37. (Works of Marx and Engels), Vol. 1, The People’s Publishing House, 1972, p. 697. 38. “Zhi” (of and Economy) in (of Han Dynasty). 39. “” (Thirteen 1985. 40. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 41. “Shi Jia” (of Chen She) in (of the Grand Historian). 42. “Ji” (of the of Han Dynasty) in (of Han Dynasty). 43. “Fu Lv” (Statutes on the Household Registration) in “Za Chao” (of Decrees of the State of Qin) in (in Qin Dynasty). 44. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 45. “Da Wen” (and Answers) in (in Qin Dynasty). 46. “Ji” (of Huang) in (of the Grand Historian). 47. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 48. “Ji” (of Huang) in (of the Grand Historian). 49. “Xing” (Punishment) (Part 1) in (Codes), Vol. 163. 50. “Ji” (of Huang) in (of the Grand Historian). 51. (History as a Mirror), Vol. 6, annotated by Hu Sansheng. 52. “Ji” (of Huang) in (of the Grand Historian). 53. “Qin Ce” (of the State of Qin) in Ce (Strategems of the Warring States). 54. “” (Biographies of ) in (of the Grand Historian). 55. “Wai Pian” (Supplementary Essays) in (Master Shen). 56. [SEP] Justify:

Output: The text lists various historical references and works related to ancient Chinese dynasties, but does not provide any information regarding staple crops or ancient civilizations' agricultural practices. Therefore, it is irrelevant to the claim, which addresses a specific assertion about agricultural reliance across civilizations.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: One could readily envision crafting a tailored pharmacotherapy regimen for a given patient with bipolar disorder that incorporates certain anticonvulsants meant to target specific illness characteristics or comorbid conditions such as those described in Table 3 (48–73)—without conflating such “ancillary” effects with the core targeting of affective symptoms. Illustrative examples are provided at the end of this 4. Breadth of psychotropic properties of second-generation antipsychoticsaAgentAcute maniaMania preventionAcute depressionDepression prevention√√2 (−) placebo-controlled trials (78)2 (−) placebo-controlled trials (79, 80)bSmall open trials1 (−) small placebo-controlled trial (81)Asenapine√√No data√No dataSmall open trialsBrexpiprazoleNo dataNo dataNo dataNo dataEfficacy in MDD trials with or without anxious distress (82)No dataCariprazine√No data√No dataNo dataNo dataLurasidoneNo datacNo data√No data√No dataOlanzapine√√2 (+) placebo-controlled trials (83)√√1 small (+) placebo-controlled trial (84)Quetiapine√√√√√1 (+) placebo-controlled trial (85)Risperidone√√dNo data1 (−) placebo-controlled trial (86)b,d1 (−) placebo-controlled trial for anxiety symptoms in bipolar patients with comorbid panic or GAD (87)1 (+) (88), 4 (−) placebo-controlled trials as adjuncts to SSRIs in (nonbipolar) military (89–91) or civilian (92) PTSDZiprasidone√√c2 (−) placebo-controlled trials (93)1 (−) placebo-controlled trial (94)b,e1 (−) placebo-controlled trial in bipolar disorder with comorbid panic disorder or GAD (95)2 (−) placebo- controlled trials (96, 97)aMDD, major depressive disorder; GAD, generalized anxiety disorder; SSRIs, selective serotonin reuptake inhibitors. bMaintenance trial following an index manic or mixed episode; sample enrichment likely contributed to a low observed rate of depression relapses in both treatment arms. [SEP] Justify:

Output: The text corroborates the claim by discussing the concept of a tailored pharmacotherapy regimen for patients with bipolar disorder, which implies the customization of treatment plans to meet individual patient characteristics and conditions. This aligns with the principles of personalized medicine, where genetic and clinical data are utilized to adapt treatments to specific patients.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Биохакеры, переносят сами научные процедуры, а также анализ их результатов на интернет-платформы, «таким образом, данные исследований могут быть проверены, а их этическая обоснованность и безопасность могут быть оценены большей группой и более быстрыми темпами, чем традиционные эксперименты в закрытых лабораториях» [16, p. 215]. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that biohackers conduct scientific procedures and analyze results in an online format, implying that these methods differ from traditional laboratory experiments and may not be universally accepted as a replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: “Lie Zhuan” (Biographies of Qing Bu) in (of the Grand Historian). 57. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 58. “Da Wen” (and Answers) in (in Qin Dynasty). 59. “Da Wen” (and Answers) in (in Qin Dynasty). 60. “Ji” (of Huang) in (of the Grand Historian). 61. “Cang Lv” (Statutes on Storage of Forage) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). 62. (Qing Dynasty) Shen Jiaben, “Si Kou” (of Justice) in “Fen Kao” (Research on Penal Law) in Kao (A of the in the Past Dynasties). 63. “Zhi” (of Criminal Law) in (of Jin Dynasty). 64. “Ji” (of Huang) in (of the Grand Historian). 65. “Ji” (of Huang) in (of the Grand Historian). 66. “Qi Yu” (Records of Qi State) in (Records of Various States). 67. “Lv” (Statutes on National Projects) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). 68. (Song Dynasty), “Shuo” (Comment on ) in (Works of Master Zhu), Vol. 67. 69. “Zhi Zhuan” (of Xiao Wangzi) in (of Han Dynasty). 70. “Da Wen” (and Answers) in (in Qin Dynasty). 71. “Lv” (Statutes on the Removal of Officials) in “Za Chao” (of Decrees of the State of Qin) in (in Qin Dynasty). 72. “Lv” (Statutes on the Removal of Officials) in “Za Chao” (of Decrees of the State of Qin) in (in Qin Dynasty). 73. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 74. [SEP] Justify:

Output: The text provided is a list of references and sources that do not discuss staple crops or address the claim in any way. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Therefore, an argument can be made for further optimizing the dosing of her current medications versus considering an adjunctive antidepressant (sertraline, fluoxetine, venlafaxine, and bupropion all have at least some randomized data, albeit not placebo controlled); versus replacing lurasidone with quetiapine, OFC, or cariprazine along with close metabolic monitoring; versus adding back low-dose lithium augmentation with its potential to synergize with lamotrigine (55) with close renal monitoring; versus contemplating a more aggressive treatment, such as electroconvulsive therapy (depending on her symptom severity and consequent disability); or versus experimental or novel approaches such as intravenous ketamine (127), midday 7,000-lux bright-light therapy (128), or putative dopamine agonists such as pramipexole, modafinil, or traditional psychostimulants (129). No singular intervention stands above others, and all options have their pros and cons. Whatever course of action is advised, providing a rationale that applies evidence-based findings to Elizabeth’s unique presentation is paramount. Future DirectionsWhile existing treatments for bipolar disorder can be effective across all phases of illness, many patients still have incomplete remissions or take regimens that are ill suited to the idiosyncrasies of their unique presentations. Future studies must address outcomes related not only to mood but also cognition, impulsivity, psychosis, circadian dysregulations, and anxiety and other comorbid conditions in the hope that both treatment adherence and overall illness burden might improve from targeting all relevant symptom domains. Alongside the search for new drug mechanisms and novel compounds, intervention studies (and practice guidelines) should routinely account for known moderators and mediators of treatment outcome, which, in turn, can help practitioners translate RCT findings in ways that best fit the distinct clinical profile of individual patients. ConclusionsBipolar disorder is a phenomenologically heterogeneous condition with multiple symptom targets that extend beyond mood alone. Randomized trials that establish drug efficacy for an overall diagnosis and illness state—such as bipolar mania or depression—can provide a wealth of further information to help practitioners recognize characteristics that may increase the probability of a desired outcome. [SEP] Justify:

Output: The text corroborates the claim by discussing the importance of tailoring treatment options to the individual patient's unique presentation. It emphasizes the need for a rationale that applies evidence-based findings to Elizabeth’s distinct clinical profile, aligning with the principles of personalized medicine, which aims to optimize treatment by considering the individual characteristics of patients. Additionally, it highlights that future studies must account for various moderators and mediators of treatment outcomes, reinforcing the idea that treatment should be personalized based on genetic data and other individual factors.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Биохакеры, переносят сами научные процедуры, а также анализ их результатов на интернет-платформы, «таким образом, данные исследований могут быть проверены, а их этическая обоснованность и безопасность могут быть оценены большей группой и более быстрыми темпами, чем традиционные эксперименты в закрытых лабораториях» [16, p. 215]. [SEP] Justify:

Output: The text contrasts the claim by indicating that biohackers conduct scientific procedures and analyze their results on internet platforms, suggesting that the evaluation of their ethical justification and safety is more rapid compared to traditional lab experiments. This implies that biohacking may not have the same recognition or validation as traditional medical treatments.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: “Ben Ji” (Sketches of Emperor Xiaowen) in (of the Grand Historian), annotated by Ying Shao. 75. “Da Wen” (and Answers) in (in Qin Dynasty). 76. “Da Wen” (and Answers) in (in Qin Dynasty). 77. “” (Thirteen 1985. 78. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 79. “Fu Lv” (Statutes on the Household Registration) in “Za Chao” (of Laws of Qin) in (in Qin Dynasty). 80. “Da Wen” (and Answers) in (in Qin Dynasty). 81. “Da Wen” (and Answers) in (in Qin Dynasty). 82. “Da Wen” (and Answers) in (in Qin Dynasty). 83. “Da Wen” (and Answers) in (in Qin Dynasty). 84. “Lv” (Statutes on National Projects) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). 85. (Slips from the Tombs of Qin in Shui Hudi), p. 166, Press, 1978. 86. “Lie Zhuan” (Biographies of Shang Yang) in (of the Grand Historian). 87. “Da Wen” (and Answers) in (in Qin Dynasty). 88. “Lie Zhuan” (of Jian Jun) in (of the Grand Historian). 89. “Zhuan” (of Jia Yi) in (of Han Dynasty). 90. “Nong Zhan” (and Warring) in Shu (of Lord Shang). 91. “Tian Lv” (Statutes on Farming and Forest Protection) in (in Qin Dynasty). 92. “Tian Lv” (Statutes on Farming and Forest Protection) in (in Qin Dynasty). 93. “Za Chao” (of Decrees of the State of Qin) in (Slips of the Qin Dynasty). 94. “Lie Zhuan” (Biographies of Businessmen) in (of the Grand Historian). 95. “Da Wen” (and Answers) in (Slips of the Qin Dynasty). 96. [SEP] Justify:

Output: The text does not provide any information related to the claim about ancient civilizations relying on the same staple crops. Instead, it consists of citations and annotations without contextual information about agricultural practices among these civilizations.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Clinicians might usefully think of an individual patient’s candidacy for a pharmacotherapy, which is based not solely on the randomized trial evidence for the overall disease entity but, more specifically, on matching recognized treatment moderators and the unique clinical profile of an individual patient beyond the diagnosis alone. FootnoteDr. Goldberg received no financial support for this study. 1. : Activation in bipolar disorders: a systematic review. JAMA Psychiatry 2017; 74:189–196Crossref2. Miskowiak KW, Kjærstad HL, Meluken I, et al: The search for neuroimaging and cognitive endophenotypes: a critical systematic review of studies involving unaffected first-degree relatives of individuals with bipolar disorder. Rev 2017; 73:1–22Crossref3. : Trait impulsivity as an endophenotype for bipolar I disorder. 2012; 14:565–570Crossref4. Dervic K, Garcia-Amador M, Sudol K, et al: and II versus unipolar depression: clinical differences and impulsivity/aggression traits. 2015; 30:106–113Crossref5. : Is subclinical anxiety an endophenotype for bipolar I patients? A study from a sample. J 2010; 122:267–272Crossref6. Mahon K, Perez-Rodriguez MM, Gunawardane N, et al: Dimensional endophenotypes in bipolar disorder: affective dysregulation and psychosis proneness. J 2013; 151:695–701Crossref7. : Sleep-wake cycle phenotypes in young people with familial and non-familial mood disorders. 2016; 18:642–649Crossref8. Osher Y, Bersudsky Y: Thought disorder in euthymic bipolar patients: a possible endophenotype of bipolar affective disorder? J Dis 2007; 195:857–860Crossref9. : Social rhythm disrupting events increase the risk of recurrence among individuals with bipolar disorder. 2015; 17:869–879Crossref10. : psychiatric comorbidity and its relationship to historical illness variables in 288 patients with bipolar disorder. Psychiatry 2001; 158:420–426Crossref11. : Exclusion criteria and generalizability in bipolar disorder treatment trials. 2018; 9:130–134Crossref12. : How often can meta-analyses of individual-level data individualize treatment? [SEP] Justify:

Output: The text corroborates the claim by discussing the concept of matching treatment based on the unique clinical profile of an individual patient, which aligns with the principles of personalized medicine that utilize genetic and other individual data for tailored treatments. The mention of 'matching recognized treatment moderators and the unique clinical profile' indicates a focus on personalization in medical treatment.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Кроме того, пользователи форума перенимают опыт взаимодействия на портале, а после транслируют его в русскоязычный сегмент интернета, создавая локальные группы пользователей ТКМП. 16 Интернациональный характер взаимодействий на форуме подчеркивает для биохакеров контраст с академическими исследованиями, зависящими от финансирования со стороны национальных государств, а потому далеких от идеалов свободной и демократической науки. [SEP] Justify:

Output: The text contrasts the claim by discussing the varied nature of biohacking interactions, which differ from traditional medical research that is influenced by national funding. This implies that biohacking does not have a universal recognition or acceptance as a replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: “Shi” (Judicial Principles, Methods and Cases) in (in Qin Dynasty). 97. “Lv” (Statutes on Currency and Property) in “Zhong” (of Laws of Qin Dynasty) in (in Qin Dynasty). 98. “Zhi” (of the Criminal Law) in (of Han Dynasty). 99. “Lie Zhuan” (of Li Si) in (of the Grand Historians). 100. (Tang Dynasty), (Biographies of Shu Duan). 101. “Da Wen” (and Answers of Law) in (Slips of the Qin Dynasty). 102. “Ji” (of Huang) in (of the Grand Historian). 103. “Ji” (of Huang) in (of the Grand Historian). 104. “Ji” (of Huang) in (of the Grand Historian). 105. “Shuo” (Categories of Saying) (Part 2) in Zi (Han Feizi). 106. “Ren Zhu” (The Monarch) in Zi (Han Feizi). 107. “Ren Zhu” (The Monarch) in Zi (Han Feizi). 108. “Ji” (of Huang) in (of the Grand Historian). 109. “Xing De” (Morality) in Lun (Debates on Salt and Iron). 110. “Xing De” (Morality) in Lun (Debates on Salt and Iron). 111. “Xing De” (Morality) in Lun (Debates on Salt and Iron). 112. “Lie Zhuan” (of Meng Tian) in (of the Grand Historian). 113. “Ji” (of Huang) in (of the Grand Historian). 114. “Ji” (of Huang) in (of the Grand Historian). 115. “” (of et al) in (of the Grand Historian). 116. “” (Biographies of ) in (of the Grand Historian). 117. “Ji” (of Huang) in (of the Grand Historian). 118. “Ji” (of Huang) in (of the Grand Historian). 119. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not provide any information related to staple crops or ancient civilizations. Instead, it primarily lists various texts and laws from different Chinese dynasties, which does not address the idea that all ancient civilizations relied on the same staple crops.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: of Personalized and edited by Ernst R. Berndt, Dana P. Goldman and University of Chicago Press, 2019Cloth: 978-0-226-61106-8 | Electronic: 978-0-226-61123-5DOI: 10. 7208/chicago/9780226611235. 001. 0001 of (cloth, ebook) Barnes & DeGruyter Multi-eBooks (formerly NetLibrary) and precision medicine (PPM)—the targeting of therapies according to an individual’s genetic, environmental, or lifestyle characteristics—is becoming an increasingly important approach in health care treatment and prevention. The advancement of PPM is a challenge in traditional clinical, reimbursement, and regulatory landscapes because it is costly to develop and introduces a wide range of scientific, clinical, ethical, and socioeconomic issues. PPM raises a multitude of economic issues, including how information on accurate diagnosis and treatment success will be disseminated and who will bear the cost; changes to physician training to incorporate genetics, probability and statistics, and economic considerations; questions about whether the benefits of PPM will be confined to developed countries or will diffuse to emerging economies with less developed health care systems; the effects of patient heterogeneity on cost-effectiveness analysis; and opportunities for PPM’s growth beyond treatment of acute illness, such as prevention and reversal of chronic conditions. This volume explores the intersection of the scientific, clinical, and economic factors affecting the development of PPM, including its effects on the drug pipeline, on reimbursement of PPM diagnostics and treatments, and on funding of the requisite underlying research; and it examines recent empirical applications of PPM. is the Louis E. in at the MIT of Management, and a research associate of the of Economic Research. : 10. 7208/chicago/9780226611235. 003. 0000[personalized medicine;precision medicine;economic issues;clinical issues;biologic issues;statistical issues;preventive care]Personalized and precision medicine (PPM) -- also called tailored, targeted, or stratified medicine -- matches therapies to patient sub-populations aided by clinical and diagnostic biomarkers. Catalyzed by the sequencing of the human genome, an accelerated expansion of the knowledge platform underlying biological disease processes, and advances in diagnostic technologies, PPM is rapidly evolving from a hypothetical concept to an observable reality. [SEP] Justify:

Output: The text corroborates the claim by stating that personalized and precision medicine (PPM) 'matches therapies to patient sub-populations aided by clinical and diagnostic biomarkers,' which indicates the use of genetic data to tailor treatments. It further explains that the advancement of PPM is linked to the sequencing of the human genome and the expansion of knowledge regarding biological disease processes, further supporting the idea that genetic data is a key component in developing tailored treatments.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Описывая присущее пользователям форума отрицание стандартных методов оценки, один из информантов подчеркивает значение любых эффектов, производимых ТКМП, которые ускользают от стандартизированных научных подходов. По его мнению, если при лечении психических заболеваний комбинация проверенных методов и плацебо облегчает состояние больного, ученые должны «уважать» этот опыт. [SEP] Justify:

Output: The text contrasts the claim by discussing skepticism towards standardized medical methods and implying that alternative treatments, like traditional Chinese medicine (ТКМП), challenge conventional science. This suggests that biohacking is not universally recognized as a replacement for traditional treatments, as it highlights the importance of scientifically established practices.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: “Ji” (of Huang) in (of the Grand Historian). 120. “Ji” (of Huang) in (of the Grand Historian). 121. “Ji” (of Huang) in (of the Grand Historian). 122. “Ji” (of Huang) in (of the Grand Historian). 123. “Ji” (of Huang) in (of the Grand Historian). 124. “Zhi” (of the Criminal Law) in (of Han Dynasty). 125. “Zhi” (of the Criminal Law) in (of Han Dynasty). 126. “Lie Zhuan” (of Li Si) in (of the Grand Historian). 127. “Ji” (of Huang) in (of the Grand Historian). 128. “Ji” (of Huang) in (of the Grand Historian). 129. “Kao” (A on Land Tax) in (A of Documents) (Book 1). 130. “Ji” (of Huang) in (of the Grand Historian). 131. “Tong Zhuan” (of Shu Suntong) in (of Han Dynasty). 132. (Inscriptions of Issued in the 26th Year of Huang’s Reign). 133. “Ji” (of Huang) in (of the Grand Historian). 134. “Ji” (of Huang) in (of the Grand Historian). 135. “Ji” (of Huang) in (of the Grand Historian). 136. “Zhi” (of and Economy) (Part 1) in (of Han Dynasty). 137. “Ji” (of the of Qin) in (of the Grand Historian). 138. “Lie Zhuan” (of Li Si) in (of the Grand Historian). 139. “Lie Zhuan” (of Li Si) in (of the Grand Historian). Author informationAuthors and Affiliationsof and author publicationsYou can also search for this author in PubMed 10. 1007/978-981-10-1029-3_4Download citation. RIS. ENW. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not provide any information regarding ancient civilizations or their reliance on staple crops. Instead, it contains references to historical records and authors without addressing the claim directly.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: The full promise of PPM extends beyond targeting therapies for already ill people, to identify healthy individuals at elevated risk of disease, enabling preventive measures to be targeted towards those who could most benefit, but perhaps at substantial additional cost. PPM has the potential to upend traditional models of providing health services, preventive care, health insurance, reimbursement and regulation, and raises issues involving not only medicine and biology, but economics, ethics, and statistics. In this introductory 10. 7208/chicago/9780226611235. 003. 0001[Personalized Medicine;Value of Information;Two-Part Pricing]Personalized medicine (PM) entails better tailoring therapies to patients through use of information about the patient that better predicts treatment response before undergoing treatment. We discuss the economic value of personalized medicine and the optimal pricing of the combination products involved. We build on previous work of Egan and Philipson (2015) who stress a link between rational adherence in health care and the value of personalized medicine. Personalized medicine converts experience goods to search goods by speeding up the learning process relative to trial and error. This explains the emergence of personalized medicine in cancer care as well as the timing of this emergence. It also predicts greater innovation- and merger incentives from Disneyland style two-part pricing of the combination products. (pages 9 - 20)This 10. 7208/chicago/9780226611235. 003. 0002[Pharmaceuticals;Genetics;Genome;Innovation;Therapeutical Translation;Network Medicine;GWAS]Many scientists predicted a swift revolution in human therapeutics after the completion of the Project (“HGP”). This revolution, however, has been slow to materialize in spite of the scientific advances. We investigate the role of biological complexity in slowing down this revolution. Our test relies on a disease-specific measure of biological complexity, constructed by drawing on insights from (Barabási et al. 2011). According to our measure, more complex diseases are associated with a larger number of genetic mutations—higher centrality in the Network (Goh et al. 2007). With this measure in hand, we estimate the rate of translation of new science into early-stage drug innovation by focusing on a leading type of genetic epidemiological knowledge (Genome-Studies) and employing standard methods for the measurement of R&D productivity. [SEP] Justify:

Output: The text corroborates the claim by discussing how personalized medicine (PM) better tailors therapies to patients through the use of information that predicts treatment response. It emphasizes the role of genetic data in personalizing treatments and highlights the broader implications and potential of personalized medicine in various aspects of healthcare. Thus, the information supports the notion that personalized medicine utilizes genetic data to customize individual treatments.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Интернациональный характер взаимодействий на форуме подчеркивает для биохакеров контраст с академическими исследованиями, зависящими от финансирования со стороны национальных государств, а потому далеких от идеалов свободной и демократической науки. Следовательно, ученые, по мнению некоторых пользователей не способны действовать в соответствии с декларируемыми принципами открытого и независимого исследования. [SEP] Justify:

Output: The text contrasts the claim by discussing the differences between biohackers and academics, implying that biohacking may not be viewed in the same light as traditional medical practices dependent on state funding and academic validation.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-4958737/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Under ReviewVersion 1posted You are reading this latest preprint versionAbstractMolecular and physiological changes across crop developmental stages shape the plant phenome and render its prediction from genetic markers challenging. Here we present dynamicGP, an efficient computational approach that combines genomic prediction with dynamic mode decomposition to characterize temporal changes in the crop phenotype and to predict genotype-specific dynamics for multiple traits. Using genetic markers and data from high-throughput phenotyping of a maize multi-parent advanced generation inter-cross population, we show that dynamicGP outperforms a state-of-the-art genomic prediction approach for multiple traits. We demonstrate that the developmental dynamics of traits whose heritability varies less over time can be predicted with higher accuracy. The approach paves the way for interrogating and integrating the dynamical interactions between genotype and phenotype over crop development to improve the prediction accuracy of agronomically relevant traits. Biological sciences/Plant sciences/Plant developmentBiological sciences/Biological techniques/High-throughput screeningBiological sciences/Genetics/Quantitative traitFiguresFigure 1Figure 2Figure 3Figure 4IntroductionThe phenome of a plant comprises the entirety of traits expressed at any given time, and is the integrated outcome of the effects of genetic factors, environmental conditions and their complex interactions. Understanding how the crop phenome changes over time can help predict individual traits at specific time points in crop development. However, this problem is challenging not only because of the intricate dependence between individual traits, but also due to differences in how the phenomes of specific genotypes change over the plant life cycle. The classical approach of genomic prediction (GP) in crops trains machine learning models using data on traits measured in a population of genotypes at a specific time point based on genetic markers1. These models can be used to predict the traits in other genotypes for which genetic markers are available, thus foregoing measurements; the accuracy of predictions depends on representativeness of the training set and on the genetic architecture of the predicted trait2. As a result, GP accelerates genetic gain and reduces the need for labor-intensive field phenotyping in a test set of genotypes. [SEP] Justify:

Output: The text discusses a computational approach to predicting crop traits and does not address the claim regarding the accuracy of dating plant remains. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: For less complex diseases, we find a strong and positive association between cumulative knowledge and the amount of innovation. This association weakens as complexity increases, becoming statistically insignificant at the extreme. Our results suggest that biological complexity is, in part, responsible for the slower-than-expected unfolding of the therapeutical revolution set in motion by the HGP. (pages 21 - 52)This 10. 7208/chicago/9780226611235. 003. 0003[Pharmacogenetics;Decision theory;Genetic testing;Cost-effectiveness;Precision medicine]Pharmacogenomics, or the application of genetic testing to guide drug selection and/or dosing, is often cited as integral to the vision of how precision medicine can be integrated into routine clinical practice. Yet despite a growing base of scientific discovery on genetic variation that predicts drug response, reimbursement for genetic testing among health systems and payers remains uneven. In large measure this is because the cascading impacts of genetic testing on individual and provider incentives and behavior, as well as downstream health care spending and outcomes, remain poorly understood. In this study, we couple evidence from a real-world implementation of pharmacogenomic testing with a discrete event simulation model. We use this framework to evaluate the cost-effectiveness of various genetic testing strategies. We find that the cost-effectiveness of multiplexed genetic testing (e. g. , whole genome sequencing) hinges on the ability of a health system to ensure that dense genotypic information is routinely utilized by physicians. Moreover, while much attention has been paid to lowering the cost of genetic tests, we demonstrate that in practice, other scientific and behavioral factors, focused on certain high-yield drug-gene pairs, are key to implementing precision medicine in ways that maximize its value. (pages 53 - 86)This 10. 7208/chicago/9780226611235. 003. 0004[personalized medicine;precision medicine;game theory;companion diagnostics;drug development]Precision medicines inherently fragment treatment populations, generating small-population markets, creating high-priced “niche busters” rather than broadly prescribed “blockbusters. " It is plausible to expect that small markets will attract limited entry in which a small number of interdependent differentiated product oligopolists will compete, each possessing market power. [SEP] Justify:

Output: The text corroborates the claim by discussing pharmacogenomics, which is described as the application of genetic testing to guide drug selection and dosing. This directly supports the concept of personalized medicine, as it emphasizes the usage of genetic data to tailor medical treatments to individual patients. Furthermore, it mentions that implementing precision medicine involves utilizing genetic information effectively within clinical practice, which aligns with the claim's assertion.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Описывая присущее пользователям форума отрицание стандартных методов оценки, один из информантов подчеркивает значение любых эффектов, производимых ТКМП, которые ускользают от стандартизированных научных подходов. По его мнению, если при лечении психических заболеваний комбинация проверенных методов и плацебо облегчает состояние больного, ученые должны «уважать» этот опыт. [SEP] Justify:

Output: The text contrasts the claim by discussing the denial of standard evaluation methods by users of the forum and emphasizing the importance of effects from alternative methods, suggesting that traditional methods may still be respected and considered in treatment.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: While GP has been extended to allow and improve the simultaneous prediction of multiple correlated traits, comprising the crop phenotype3–5, existing GP approaches have not yet addressed the problem of predicting the dynamics of plant phenotypes, i. e. , the expression of multiple traits at different time points across the entire period of growth of the plant. Advances in high-throughput phenotyping (HTP) technologies, including non-destructive approaches such as: hyperspectral, multispectral, fluorescence, and thermal imaging, have enabled the detailed capture of plant traits at various growth stages and have resulted in large-scale time-resolved heterogeneous data sets on crop phenotypes6–10. These developments offer the possibility of predicting time-resolved crop phenotypes from genetic markers, with the potential to revolutionize GP. Recent efforts have cast the prediction of the dynamics of crop phenotypes as a spatio-temporal sequence prediction problem. The proposed solutions rely on deep learning approaches, such as spatio-temporal long short-term memory (ST-LSTM) or Memory-in-memory (MIM) networks11, generative adversarial networks12 (GAN), and U-net encoder-decoder13. However, rather than directly predicting time-resolved crop traits, these approaches aim to predict a time series of images that are then used to infer the traits of interest. The time-resolved prediction of crop phenotypes can also be addressed by dynamic mode decomposition (DMD)14. DMD is an advanced data-driven method used in decomposing data from complex, time-dependent systems into spatio-temporal modes that provide low-dimensional description of the systems’ dynamics. These modes render DMD particularly useful for understanding and predicting the behavior of systems characterized by high-dimensional data. DMD has been applied across different fields, including: fluid mechanics, engineering, epidemiology14, and neuroscience15; however, no attempts have yet been made to apply DMD to data from HTP technologies or to combine this method with genetic markers. Here we combined DMD with GP to predict the genotype-specific dynamics of crop phenotypes using HTP data measured on a maize population of recombinant inbred lines (RILs). Our approach, termed dynamicGP, showed consistent prediction accuracy for multiple traits and across multiple time points. [SEP] Justify:

Output: The text does not address the claim regarding the accurate dating of plant remains. Instead, it discusses advancements in genetic prediction and high-throughput phenotyping technologies that relate to crop phenotypes but does not offer any information about the dating of plant remains.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Multiple precision medicine market situations now resemble game theory constructs such as the prisoners’ dilemma and Bertrand competition. The examples often involve drug developer choices created by setting the cut-off value for the companion diagnostics to define the precision medicine market niches and their payoffs. Precision medicine game situations may also involve payers and patients who attempt to change the game to their advantage or whose induced behaviors alter the payoffs for the developers. The variety of games may predictably array themselves across the lifecycle of each precision medicine indication niche and so may become linked into a sequentially evolving meta-game. We hypothesize that certain precision medicine areas such as inflammatory diseases are becoming complex simultaneous multi-games in which distinct precision medicine niches compete. Those players that learn the most rapidly and apply those learnings the most asymmetrically will be advantaged in this ongoing information pharms race. (pages 87 - 114)This 10. 7208/chicago/9780226611235. 003. 0005[precision medicine;clinical trials;pharmaceuticals;drug development;R&Dbiomarkers]Precision medicines—therapies that rely on the use of genetic, epigenetic, and protein biomarkers—create a better match between patients with specific disease subtypes and medications that are more effective for those patients. This heterogeneity in response has implications for the decision to develop therapies, their pricing, the design of clinical trials, and the relative importance of smaller biotech companies versus more traditional companies in pursuing early-stage R&D. To understand the scope of these effects, we use a comprehensive database of over 130,000 global clinical trials and describe the drug development pipeline for precision medicines over the past two decades. We identify clinical trials for likely precision medicines (LPMs) as those that use one or more relevant biomarkers. We then further segment trials based on the nature of the biomarker(s) used and other trial features with economic implications. Since cancers represent a disease setting in which precision therapies are already successfully used, and since cancer applications of precision medicine are expected to grow rapidly over the coming years, we separately characterize cancer LPMs. Finally, we consider the types of firms pursuing R&D in precision medicines, considering how LPM R&D activities have evolved over recent years. (pages 115 - 158)This 10. 7208/chicago/9780226611235. 003. [SEP] Justify:

Output: The text corroborates the claim by explaining that precision medicines rely on the use of genetic, epigenetic, and protein biomarkers to create a better match between patients with specific disease subtypes and the medications that are more effective for those patients. This aligns with the definition of personalized medicine, as it emphasizes tailoring treatments based on individual genetic data.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Интернациональный характер взаимодействий на форуме подчеркивает для биохакеров контраст с академическими исследованиями, зависящими от финансирования со стороны национальных государств, а потому далеких от идеалов свободной и демократической науки. Следовательно, ученые, по мнению некоторых пользователей не способны действовать в соответствии с декларируемыми принципами открытого и независимого исследования. [SEP] Justify:

Output: The text contrasts the claim by highlighting a difference between biohackers and academic research, suggesting that the former operates outside traditional frameworks. It discusses skepticism towards scientists and implies that biohacking may not be universally recognized or accepted as a legitimate alternative to conventional medical practices.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: These predicted operators were used to make longitudinal predictions of all 50 traits over the entire time domain using the two versions of dynamicGP, iterative and recursive, defined similarly to the usage of DMD (see Methods). We found that the iterative approach yielded more consistent accuracies across the investigated time points compared to the recursive approach (Fig. 3a). Across all traits and time points, the iterative approach resulted in a mean prediction accuracy of 0. 34 (± 0. 30) in 20 iterations of 5-fold cross validation. The average blue value of plant pixel colors, which quantifies the blue-yellow color space of visible light (see Table S1 for trait descriptions), emerged as the best-performing trait, with a mean prediction accuracy of 0. 79 (± 0. 07). In contrast, the plant average hue value in side images, quantified in the hue, saturation and value color space, showed the lowest prediction performance of -0. 38 (± 0. 12). Conversely, the recursive approach had a mean prediction accuracy of 0. 17 (± 0. 19) across all traits and time points. Here, the standard deviation of the y values in the fluorescent xyz color space from top images could be predicted with mean prediction accuracy of 0. 52 (± 0. 11), while the plant average hue value in side images, as quantified in the hue, saturation and value color space, again displayed the lowest mean prediction accuracy of -0. 30 (± 0. 13). The recursive predictions, as expected, tended towards zero at later time points as errors compounded. We observed that traits exhibiting consistent heritability over time, indicated by smaller values for the coefficient of variation, tended to demonstrate higher prediction accuracies across all time points. This relationship was supported by a moderate negative Pearson correlation coefficient of -0. 46 between the mean prediction accuracy for the traits from iterative dynamicGP across all time points and the coefficient of variation of the heritability estimates across the entire time points (Fig. 3d); the corresponding correlation coefficient for recursive dynamicGP was − 0. 37 (Fig. S10). Therefore, in line with expectations, traits whose heritability does not vary during development were found to be better predicted by dynamicGP approach. Performance of dynamicGP compared to baseline models To assess the predictive performance of dynamicGP, we compared it with a GP baseline approach using RR-BLUP models, which is the standard in breeding programs. [SEP] Justify:

Output: The text discusses the predictive performance of dynamicGP in assessing traits over time, including prediction accuracies across various methods. However, it does not address the claim regarding the accuracy of dating plant remains, nor does it provide any information about dating techniques or methodologies for plant remains. Therefore, the text is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: 0006[insurance;cost-effectiveness;technology;pharmaceuticals]This paper describes theory and current practice associated with insurance coverage of treatments and associated companion diagnostic tests for precision or personalized medicine. Coverage by public and private insurances is generally furnished under policy-level cost sharing terms for tests and treatments accepted in clinical practice, but there are some exceptions. Coverage of and implementation of cost effective tests and treatments may either reduce the use, cost, and side effects of treatments (if the alternative is to treat all without testing) or may increase the use of treatment that was previously discouraged by expectation of side effects and high cost. Examples of cost effective use and coverage are provided for breast, small cell lung, and colon cancer. Optimal coverage may involve positive cost sharing if there is heterogeneity in insureds’ values of health improvements or side effects, or if test results give varying probabilities of effective treatment. (pages 159 - 184)This 10. 7208/chicago/9780226611235. 003. 0007[personalized medicine;innovation;multiple sclerosis;pharmaceuticals;treatment heterogeneity;diagnostic testing]Individuals respond to pharmaceutical treatments differently due to the heterogeneity of patient populations. This heterogeneity can make it difficult to determine how efficacious or burdensome a treatment is for an individual patient. Personalized medicine involves using patient characteristics, therapeutics, or diagnostic testing to understand how individual patients respond to a given treatment. Personalized medicine increases the health impact of existing treatments by improving the matching process between patients and treatments and by improving a patient’s understanding of the risk of serious side effects. In this paper, I compare the health impact of new treatment innovations with the potential health impact of personalized medicine. I find that the impact of personalized medicine depends on the number of treatments, the correlation between treatment effects, and the amount of noise in a patient’s individual treatment effect signal. Using multiple sclerosis treatments as a case study, I find that personalized medicine has the potential to increase the health impact of existing treatments by roughly 50 percent by informing patients of their individual treatment effect and risk of serious side effects. (pages 185 - 216)This 10. 7208/chicago/9780226611235. 003. [SEP] Justify:

Output: The text corroborates the claim by explaining that personalized medicine utilizes patient characteristics, which likely includes genetic data, to understand individual responses to treatments. It emphasizes that personalized medicine enhances the matching process between patients and treatments, which aligns with the idea of tailoring treatments to individual patients. Additionally, the text discusses the potential health impact of personalized medicine by informing patients about their individual treatment effects, reinforcing the claim.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Описывая присущее пользователям форума отрицание стандартных методов оценки, один из информантов подчеркивает значение любых эффектов, производимых ТКМП, которые ускользают от стандартизированных научных подходов. По его мнению, если при лечении психических заболеваний комбинация проверенных методов и плацебо облегчает состояние больного, ученые должны «уважать» этот опыт. [SEP] Justify:

Output: The text contrasts the claim by discussing a user's denial of standard methods of evaluation and emphasizing the importance of effects from alternative treatments that do not follow standardized scientific approaches. This implies skepticism about the recognition of biohacking as a valid replacement for traditional methods.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: The RR-BLUP models were trained with data on each trait from the first time point in a training set and used to predict the trait in all subsequent time points for the testing set. Inspecting the difference of performance between dynamicGP and the baseline for traits with different predictability, we found that the iterative version of dynamicGP outperformed the baseline RR-BLUP models consistently across all investigated time points, while the recursive version performed competitively, outperforming the RR-BLUP models for all time points between day 16 and day 33 (Fig. S8). Specifically, the mean prediction accuracy across all traits for the first time point, on which the models were trained, was 0. 24 (± 0. 15). While this accuracy was maintained when the baseline RR-BLUP models were applied to predict the traits over the first four subsequent time points, already at the second time point, both versions of dynamicGP outperformed the baseline (Fig. S8). The recursive version of dynamicGP was superior to the baseline for 12 time points, after which the accuracies of the two models were closely aligned (Fig. S8). Moreover, the iterative version of dynamicGP outperformed both the baseline and the recursive version of dynamicGP for every time point. We examined the differences in mean prediction accuracy across all time points between dynamicGP and the baseline models for each trait. The best performing trait using the recursive method, the standard deviation of the y values in the fluorescent xyz color space from top-down images, showed mean prediction accuracies above 0. 5 of all time points, which was 60% higher than the best performing trait in the baseline models (Fig. 4). In the iterative method the best performing traits, namely the average blue value of pixels as well as the average brightness measurements of green pixels and pixels with 27% saturation (Table S1), showed mean accuracies above 0. 7 of all time points, which was ~ 2. 4-fold higher than the best trait from the baseline model predictions (t-test, p-values < 0. 001 for all time points, Fig. 4). Furthermore, both versions of dynamicGP yielded mean squared errors much lower than the RR-BLUP baselines (Fig. S9). DiscussionDeveloping computational approaches that can predict the dynamics of crop growth and developmental plasticity for unseen genotypes in new environments holds the promise to revolutionize breeding practices. [SEP] Justify:

Output: The text is irrelevant to the claim about the accurate dating of plant remains. It discusses the performance of various modeling approaches in predicting traits related to crop growth, without addressing plant dating or the reliability of such methods.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: Analyzing a unique dataset linking medical claims, cancer registry data and proxies for income between 2004 and 2015, we find that lower-income patients are more likely to be diagnosed with later stages of breast cancer, and this pattern renders NHI coverage of anti-HER2 therapy pro-poor even before full coverage of the diagnostic tests. Moreover, the expansion of NHI coverage—including the FISH diagnostic test and trastuzumab for early-stage breast cancer—strengthened the pro-poor distribution of genetic testing and target treatment, albeit only marginally. The extent of pharmaceutical company coverage of testing and its impact on patient access are topics of our ongoing research, contrasting breast cancer with colorectal cancer. (pages 237 - 272)This 10. 7208/chicago/9780226611235. 003. 0010[pharmacogenomics;cost-effectiveness;Clopidogrel]Dual antiplatelet therapy, combining a P2Y12 inhibitor and aspirin, is central to management of patients with acute coronary syndromes. Clopidogrel is a commonly prescribed thienopyridine P2Y12 inhibitor used to prevent secondary events following a myocardial infarction/percutaneous coronary intervention. Clopidogrel effectiveness has been linked to proper function of metabolic enzyme cytochrome P450 2C19 (CYP2C19). Testing for CYP2C19 genetic changes that result in decreased activity has been proposed as a mechanism by which to identify clopidogrel non-responders a priori. Robust real-world studies evaluating the impact of genotype-guided antiplatelet selection on clinical, utilization and outcome metrics are lacking. We linked clinical and financial data on 2,595 Geisinger patients prescribed antiplatelet therapy without pharmacogenomic insight. Leveraging post-hoc, research-generated pharmacogenomic information, we describe the potential value of pharmacogenomic information in the selection of clopidogrel as the P2Y12 inhibitor therapy. Among patients examined, CYP2C19 loss of function did not predict the probability of later adverse events, clinical utilization or total medical costs within the 12 months after clopidogrel initiation. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of genetic testing, specifically for the CYP2C19 enzyme, to guide the selection of clopidogrel therapy for patients. It highlights the importance of pharmacogenomic information in treatment decisions, suggesting that personalized medicine integrates genetic data to improve healthcare outcomes.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Размывая дисциплинарные границы, пользователи форума приходят к представлению об эффективности устройств транскраниальной микрополяризации, которое отличается от научного понимания. [SEP] Justify:

Output: The text contrasts the claim by indicating that forum users have differing views regarding the effectiveness of transcranial micro-polarization devices, which implies that the acceptance of biohacking methods is not universally recognized and may deviate from established scientific understanding.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: Such approaches can provide insights not only into how the genotype affects the time-resolved phenome, but also can highlight the temporal dependence between traits comprising the phenome. While there have been significant developments in GP of multiple-traits3–5, they essentially operate with snapshot data and do not capture the dynamics of crop traits. Here, we introduced dynamicGP, a computational approach that resolves the problem of predicting the growth dynamics across development in crops for which time-series phenome measurements for multiple genotypes are available from HTP platforms6–10. DynamicGP essentially applies GP to the building blocks of DMD, thus facilitating the prediction of multiple traits over time of unseen genotypes. Using a time-resolved HTP data collected for five days per week for five weeks beginning at day 15 after sowing from RILs of a maize MAGIC population, we showed that both the iterative and the recursive versions of dynamicGP outperformed the baseline GP approach. In addition, we showed that at the predictability threshold of 0. 5 for two of the traits, recursive dynamicGP exhibited better performance compared to the baseline GP approach. These traits were both top-down photographs measured in the fluorescence color space. For the iterative dynamicGP, we found three traits above a threshold of 0. 7 where dynamicGP outperformed the baseline, all measured in the visible colour space, namely the average blue-value of the plant pixel colors of images from above, average brightness of fraction of green-colored pixels in top-down images, and average brightness of fraction of pixels with mean 27% saturation in top-down images (Table S1). Further, we observed that the mean squared error of dynamicGP was lower for both the iterative and recursive versions than the baseline, with log-transformed MSEs of -3. 29 and − 3. 57 for iterative and recursive, respectively and − 0. 08 for the baseline (Fig. S9). Therefore, dynamicGP yields predictions which are closer to the true values than the RR-BLUP baseline models. The performance improvement of dynamicGP over the classical GP approach is due to the usage of time-resolved phenotypic data. While availability of such data is rapidly increasing due to deployment of HTP in controlled environments and on the field, dynamicGP is more resource intensive than the classical GP. However, dyanamicGP does not rely on model fitting (e. g. [SEP] Justify:

Output: The text does not address the claim regarding the accurate dating of plant remains. Instead, it discusses a computational approach for predicting growth dynamics in crops using time-series phenomic data. This information is unrelated to the claim about the dating of plant remains.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: . Nevzat Tarhan: "Genetic treatments provide personalized medicine. " Prof. Nevzat Tarhan: "Genetic treatments provide personalized medicine. " 12. 08. 2024 - 10:34 Haber ile ilişkili SDG etiketleri DOI : Noting that medication and psychotherapy are generally used together in the initial stage of psychiatric disorders, Psychiatrist Prof. expressed that "The role of the brain is critical in treatment. Drug treatment is the gold standard because psychiatric disorders cause disorders in the electrical and chemical communication of the brain. " Stating that the personalization of psychiatric treatments will play an important role in achieving more effective and safe results, Prof. Tarhan said that "Genetic treatments provide personalized treatment. It may be important to perform genetic evaluations, especially in cases where improvement cannot be achieved. " President of Üsküdar University and Psychiatrist Prof. evaluated current approaches in psychiatric diagnosis and treatment methods. Psychiatric illness is often called "disorders". . . Reminding that classical diagnostic methods were used in psychiatry diagnosis and treatment methods, especially in diagnosis, Prof. Tarhan noted that in these methods, the person is examined and diagnosed according to the symptoms and checklists, and the reason why psychiatric illness is generally called "disorders" is that biological evidence and their counterparts in the brain have not been fully confirmed. Stating that although there is a pathology in the brain, this pathology cannot be fully defined as a disease and therefore the term "disorder" is used, Prof. Tarhan said that "For example, terms such as depressive disorder, schizophrenic disorder and bipolar disorder are used in this way. Neuropathological evidence had to be present to identify a condition as a disease. However, in recent years, laboratory evidence has increased. Thanks to neuroimaging, neurobiological and neurophysiological studies, brain functions have been measured and the causality link between disorders has been revealed. Addiction is called ‘reward failure syndrome’, which is caused by an inadequate functioning of the reward area of the brain. Depression, on the other hand, can be defined as the asymmetrical functioning of the frontal region of the brain and the incompatible functioning of the pleasure and depression areas. In the future, diagnoses based on connectivity disorders of certain brain regions will be able to be made. [SEP] Justify:

Output: The text corroborates the claim by explicitly stating that 'Genetic treatments provide personalized medicine.' Prof. Nevzat Tarhan argues for the importance of genetic evaluations in the treatment of psychiatric disorders, suggesting that personalized treatment can lead to more effective results for patients. This aligns directly with the claim that personalized medicine leverages genetic data to customize patient care.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Даже происходящая зачастую подмена генерализации знания его общедоступностью, не отменяет стремления некоторых биохакеров к воспроизводимости собственных результатов. Пусть они считают идеальным иной баланс между надежностью и валидностью результатов исследования [4], чем это принято, например, в рамках доказательной медицины, био- и нейрохакеры все же признают важность этого баланса. [SEP] Justify:

Output: The text contrasts the claim by highlighting the ongoing debate within the biohacking community regarding the balance between reliability and validity of research results, indicating that biohackers do not universally agree on their approach as a replacement for traditional medical treatment. It acknowledges that bio- and neurohackers recognize the importance of this balance, which suggests a level of skepticism about positioning biohacking as a replacement.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: , of growth curves) and subsequent usage of the model parameters in GP, thus avoiding propagation of error and often unfounded assumptions about models that best describe the dynamics of single traits. Instead, dynamicGP builds on the advantages of DMD that allows the simultaneous investigation of multiple traits over time. Although dynamicGP is applicable with any time-resolved phenotypic data on multiple traits, we tested its performance with traits retained after correlation analysis. The selection of traits was conducted to avoid the consideration of highly correlated traits that may affect predictive performance. Like with any data-driven approach, we hypothesize that the performance of dynamicGP depends on the number of traits included and time points considered, which may vary between data sets. Both the recursive and iterative versions of dynamicGP offer the possibility to make predictions about plant phenotypes of unseen genotypes given measurements of specified time points in time, thus reducing the need for extensive temporal measurements. In this regard, while dynamicGP provides the means to overcome the challenge of predicting temporal phenomes for unseen genotypes, it inherits the limitations of GP, such as the transferability of the models to different populations and environments2. Future developments of dynamicGP can rely on extensions of DMD to consider effects of environmental factors18. These will facilitate further refinements of the proposed approach that are expected to have very substantial impact on breeding crop varieties adapted to particular regions as well as precision agriculture. generation In three independent high-throughput phenotyping experiments, 347 RILs and 9 founder lines of a MAGIC maize population19 were screened for natural variation in the HTP facility for large plants at the of Research in Gatersleben, Germany20. The panel was divided into three equal-sized subgroups and analysed in three consecutive experiments: 2113MH (116 RILs and 9 founders), 2121MH (116 RILs and 9 founders), and 2137MH (115 RILs and 8 founders). To ensure compatibility of the data, each HTP experiment was supplemented by an additional randomly drawn overlap of 21, 21 or 27 RILs, respectively, half of which came from each of the other two experiments. The experimental design followed a complete randomised block design with three replicates per genotype (three carriers with two plants each) overlapping with three blocks corresponding to four of the twelve lanes of the HTP system. Image acquisition began at 15 DAS for 31 time points per experiment and six days per week. [SEP] Justify:

Output: The text does not address the claim regarding the accurate dating of plant remains. It focuses on a complex method for analyzing plant phenotypes over time, discussing traits and model parameters without mentioning dating or the accuracy of dating plant remains.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: ” Tarhan also explained that “Such findings show that the disease occurs outside the will or control of the person and is caused by disorders that occur in certain regions of the brain. To tell someone to ‘look alive' or ‘do not overthink it’ in relation to depression or other psychiatric disorders would be to ignore disturbances in their brain chemistry or function. " Tarhan emphasized that such situations may be too complex to be overcome by will or control on their own, therefore, it is important to create appropriate treatment plans by understanding the biological and chemical condition of the individual in the treatment of psychiatric disorders. Not being understood contributes to the pain. . . Noting that people with psychiatric disorders suffer and not being understood increases the pain even more, Prof. Tarhan said that "There are patients who cry because the reason is understood. They blame themselves. They say, 'Why am I like this? ' However, the serotonin stores in the brain are empty, and the person is exhausted. Therefore, it is involuntary. " With newly developed technologies, it is becoming possible to repair disrupted networks in the brain Prof. Tarhan said that "With newly developing technologies, it is possible to repair and correct the damaged networks in the brain with methods such as brain modulation treatments. For example, magnetic stimulation therapy can correct receptors and open ion channels by delivering magnetic impulses to specific areas in the brain. This can enable drugs to reach the brain better and support the treatment process. " Noting that pharmacogenetic studies determine which drugs may be more effective by looking at the genetic structure of individuals, Prof. Tarhan stated that "Genetic information can help personalized treatment plans to the person and achieve more effective results. In this way, drug doses and duration of treatment can be determined based on the individual genetic profiles of individuals, thus increasing response to treatment and tolerance. " Personalized treatment gives more effective and safe results. . . Stating that the personalization of psychiatric treatments will play an important role in achieving more effective and safe results, Prof. Tarhan said that "Genetic treatments provide personalized treatment. Especially in cases where improvement cannot be achieved, genetic evaluations may be important. In both the elderly and children, when there is no response to treatment or when drugs do not work, evaluation of genetic factors can help identify new treatment options. [SEP] Justify:

Output: The text corroborates the claim by stating that 'Genetic information can help personalized treatment plans to the person and achieve more effective results.' It emphasizes that pharmacogenetic studies can determine which drugs may be more effective by analyzing individual genetic structures, thereby tailoring treatment based on these genetic profiles. This supports the idea that personalized medicine utilizes genetic data to create individualized treatment strategies.


Input: Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text: Пусть они считают идеальным иной баланс между надежностью и валидностью результатов исследования [4], чем это принято, например, в рамках доказательной медицины, био- и нейрохакеры все же признают важность этого баланса. В этой связи они могут быть союзниками ученых в противодействии рискам общественного отрицания биомедицинского научного знания (дениализма). [SEP] Justify:

Output: The text contrasts the claim by discussing the importance of reliability and validity in research results, suggesting that biohackers recognize the significance of empirical biomedical scientific knowledge, rather than viewing biohacking as a replacement for traditional medical treatment.


Input: Task: pass the claim using the given text. Claim: Plant remains can always be accurately dated. [SEP] Text: An image acquisition event was a carrier with two plants phenotyped by one image in top view and four images in side view at 22°, 45°, 112° and 135°. Altogether 347,740 images were taken (2113MH, 114710 images, 91768 side view, 22942 top view; 2121MH, 116840 images, 93472 side view, 23368 top view; 2137MH, 116190 images, 92952 side view, 23238 top view). Traits were derived from images by IAP version 2. 3. 021 and were analysed by alignment by days after sowing (DAS). A shift of the sowing date by one day in 2121MH allowed alignment to DAS for only 5 days per week, so that 2 days were missing each week. Consequently, the time points were not consecutive, but were organized in five-day blocks, with one measurement taking place each day and no measurements for two days over five weeks. The analysed data comprised measurements for 498 traits from side, top and combined categories derived from multi-colour-space image analysis (Fig. 3e, Tables S122 Heuermann et al. 2024). A linear mixed model with random effect of genotype, experiment, lane, genotype-by-experiment interaction and replicate nested in experiment was built for each time point. Trait heritability was calculated by the ratio between genotype variance component and total variance component. Summation of best linear unbiased prediction (BLUP) value of genotype and fixed effect of intercept were used as the final trait values. Genotyping data was available for 330 Maize RILs consisting of 79,557 high-quality SNPs derived from SPET genotyping23. Missing genotyping data were imputed using Beagle 5. 224. We then removed SNPs with a minor allele frequency < 0. 05, resulting in a final set of 70,846 SNPs for GP models. The phenotypic data sets used in this study are available at: Clustering and trait selection Traits were first clustered using the Mantel correlations over all genotypes and time points, represented as a matrix. To this end, a network was created with nodes representing traits and edges denoting inter-trait Mantel correlations of value above 0. 96. [SEP] Justify:

Output: The text provided does not address the claim regarding the accuracy of dating plant remains. Instead, it discusses methodologies related to imaging and analysis of plant traits without mentioning anything about the dating of plant remains or the accuracy of such methods.


Input: Task: corroborate the claim using the given text. Claim: Personalized medicine uses genetic data to tailor treatments to individual patients. [SEP] Text: " Explaining that the developments in the field of psychiatry and the increase in treatment options in recent years have increased the possibility of recovery of long-term disorders such as schizophrenia, Prof. Tarhan stated that for this reason, it is important for patients not to lose hope and continue treatment, and that psychiatric disorders are a condition that affects not only individuals but also families. The support and hope by both individuals and families is important. . . Stating that in some cases, examining genetic predisposition and evaluating genetic factors in the family can guide the treatment plan and help discover new treatment options, Prof. Tarhan expressed that "The support and hope by both individuals and families are important in the fight against psychiatric diseases. " Reminding that there is also a need for studies on applying genetic therapy from one's own stem cells, Prof. Tarhan said that “It is necessary to do something about autisms and that genetic treatments give hope for the coming period. Emphasizing that the relationship between neuroscience and psychiatry is getting stronger, Tarhan stated that the assistants working in the field of psychiatry who study for doctorate enables them to better understand the processes in the brain and the biological basis of psychiatric diseases, and in the light of this information, methods called neuro-navigation have been developed and it is aimed to treat certain regions in the brain by targeting them. Stating that in some treatments, it is aimed to activate the cells by stimulating the energy molecule called adenosine diphosphate in the nerve cells in the brain, Prof. Dr. Tarhan said that the use of some treatments for health and well-being is increasing. Üsküdar (ÜNA). Tarhan: "A pandemic of addiction awaits the world! " The book "Neuroscience: Science of Happiness" hit the shelves Author Tarhan's book 'Women's Psychology' is now a bestseller in Indonesia. . . A seminar titled "and Search for Meaning with the Mana-i Harf" was held “They competed with the motto "When ideas collide, minds win". . . Prof. Sevil Atasoy: "We used to be a transit country; however, now we became the users! " Joy of Year in Üsküdar Presentation by Üsküdar Scientists on 'Artificial intelligence and its use in psychiatric diseases' in Toronto attracted attention VPN provides secure communication with the right setup and encryption! [SEP] Justify:

Output: The text corroborates the claim by stating that examining genetic predisposition and evaluating genetic factors in the family can guide the treatment plan and help discover new treatment options. This supports the idea of personalized medicine, which relies on genetic data to tailor treatments specifically to individual patients.


Input:
Task: contrast the claim using the given text. Claim: Biohacking is universally recognized as a replacement for traditional medical treatment. [SEP] Text:

С другой стороны, как отмечено выше, необходимо учитывать, что био- и нейрохакеры все же разделяют большую часть «внутренних» норм науки. Даже происходящая зачастую подмена генерализации знания его общедоступностью, не отменяет стремления некоторых биохакеров к воспроизводимости собственных результатов. [SEP] Justify:

Output: The text contrasts the claim by indicating that biohackers still largely adhere to the 'internal' norms of science, implying that biohacking is not universally embraced as a replacement for traditional medical methods. The mention of a striving for reproducibility suggests that there is a scientific foundation to their practices, which counters the notion of biohacking completely replacing established medical treatments.


Input: Task: pass the claim using the given text. Claim: Ancient agricultural practices have remained unchanged until today. [SEP] Text: Full text Figures and data Peer review Side by side Figures 6 figures Figures Figure 1 with 6 supplements Download asset Open asset Disrupting TC10 level or function reduced AMPARs on the cell surface. (A) Representative somata of cultured rat hippocampal neurons (E18) expressing mCherry-tagged GluA1 subunits, free Venus (Control), shTC10RNA or Venus-tagged TC10WT, TC10DN or TC10CA. Intact, live neurons (DIV18) were stained with anti-RFP antibody to visualize surface AMPA-type glutamate receptors (AMPARs) and then fixed and processed. Images of the whole neuron for each of the shown somata are displayed in Figure 1—figure supplement 2. (Scale bar = 10 μm). (B) Representative dendrites of neurons expressing mCherry-GluA1 without TC10 or with TC10WT, TC10DN, or TC10CA. Arrows indicate dendrites expressing TC10 mutants (TC10DN or CA) with weak surface expression of GluA1; arrowheads mark dendrites expressing mCherry-GluA1 without TC10 mutant expression and normal GluA1 surface expression level. (Scale bar = 5 μm). (C) Representative dendrites of intact neurons expressing either free Venus (Control), TC10WT, TC10DN, or TC10CA and labeled with an N-terminal, anti-GluA1 mAb to visualize endogenous, surface GluA1 receptors. (Scale bar = 5 μm). (D) Quantification of the surface/total ratio of mCherry-GluA1 at the somata of transfected cells in (A). Data are shown as ± SEM; control cells (YFP) 100% ± 14%, n = 32; TC10WT cells 118% ± 22%, n = 17; TC10DN cells 53% ± 9%, n = 23; TC10CA cells 47% ± 9%, n = 14; and shTC10 cells 21% ± 7%, n = 10. (**p < 0. 03 relative to TC10WT). (E) Quantification of the surface/total ratio of mCherry-GluA1 in dendrites of transfected cells in (B). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the function of TC10 in neurons and the expression of AMPA-type glutamate receptors, with no mention of agriculture or agricultural practices. Therefore, it neither supports nor contradicts the claim concerning ancient agricultural practices.