Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: In these three studies, participants were instructed to call local emergency number. After the calling, participants had to follow the instructions of the dispatcher to initiate CPR while an autonomous flight of the drone was initiated from dispatcher [18–20]. In one study participants were split into two groups: one group of participants interacted in the situation alone and the other group of participants interacted in pairs [18]. The other two studies also used a dual situation, but one of the participants was instructed to search for a fixed defibrillator at one of five zones on campus. The other participant was instructed to initiate CPR and to wait for the AED to be delivered by drone [19, 20]. A pre- and post-survey found that 34% of the participants had previously interacted with a drone. Results of the post-survey indicated that 89% of the participants felt comfortable during drone approach [19]. Generally, the participants gave positive feedback about interacting with the drone [20]. Participants who expressed a more positive attitude towards technique performed better on all tasks they were assigned [18]. However, some participants expressed neutral or indifferent feelings such as uncertainty or anxiety. Nevertheless, most of the participants experienced the AED delivered by drone as an innovative and efficient way of obtaining medical help. They noted advantages of being able to deliver AEDs in remote areas and to stay close to the patient in need. The human drone interaction can be clustered into the following categories: (1) process/landing, (2) handover, and (3) communications. In the four studies identified, the drone landed after arriving at the OHCA location [17–20]. Claesson et al. [17] tested two other arriving scenarios: dropping the AED by using a parachute technique from minimum 25m altitude or dropping the AED using a latch-release from 3-4m altitude. The results showed that the best methods were landing or latch-release. When using a parachute-release technique, wind caused uncertainty about where the defibrillator would land. When using a latch-release, bystanders could fetch the defibrillator. This method of release was suggested as a low risk because people could not be hurt from rotors of the drone. Landing serves as a good alternative, in order to reduce risk for bystanders who want to intervene. However, users had many concerns about the process/landing. [SEP] Justify:

Output: The text corroborates the claim as it discusses the use of drones to deliver Automated External Defibrillators (AEDs) in emergency situations. It highlights that participants in the studies perceived drone delivery of medical supplies (in this case, AEDs) as an innovative and efficient way to obtain medical help. Specifically, it mentions that drones can deliver AEDs to remote areas, supporting the idea that companies are exploring drone delivery for medical supplies.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: Women eligible for Oncotype DX testing include those recently diagnosed with stage I or II invasive breast cancer; those in whom the tumour is oestrogen receptor (ER)-positive, AN-negative and those whom, with their consultant, are considering chemotherapy. Women recently diagnosed with ductal carcinoma in situ (DCIS) or having lumpectomy to remove the DCIS may also be candidates. After surgery, women can reduce the risk of recurrence by taking selective estrogen receptor modulators (SERMs), such as tamoxifen[4][5] or aromatase inhibitors, such as exemestane, letrozole and anastrozole[6]. DX provides a recurrence score (RS): a number from 0–100[7]. An RS of less than 18 means the tumour has a low risk of recurrence and the benefits of chemotherapy are unlikely to outweigh the adverse effects. An RS ≥18 and ≤30 means the tumour has an intermediate risk of recurrence and it is unclear whether chemotherapy exerts benefits. An RS ≥31 means the tumour has a high risk of recurrence and the benefits of chemotherapy are likely to outweigh the adverse effects. Evidence baseCrolley et al. reported that interpretation of the scores of intermediate risk of recurrence and the subsequently offered chemotherapy regimens has the widest variation in practice in the UK[8]. Loncaster et al. reported that capitalising on Oncotype DX in women with AN-negative and positive breast cancer significantly reduces the use of chemotherapy (P <0. 001) and its associated morbidity and costs[9]. Furthermore, Holt et al. reported that reconsidering chemotherapy based on Oncotype DX results was associated with improvements in survival and quality-adjusted life expectancy in the UK[10]. Gluz et al. reported a trial that included 3,198 women (median age 56 years) with HR-positive, HER2-negative, AN-positive or high-risk node-negative early breast cancer (median follow-up of 35 months), from 2009–2011[11]. The study recommended women with an RS ≤11 to abstain from adjuvant chemotherapy. The three-year disease-free survival for the 348 patients not treated with chemotherapy with an RS ≤11 was 98%. In light of the trial, around 5,000 women could be spared the harmful implications of chemotherapy each yearStemmer et al. [SEP] Justify:

Output: The text contrasts with the claim because it describes the limitations of genetic testing regarding predicting health problems. It focuses on Oncotype DX testing for specific breast cancer cases and emphasizes that this test provides a recurrence score but does not guarantee certainty in predicting future health outcomes. The text illustrates various scenarios where genetic testing assists in decisions about chemotherapy but notes the uncertainty involved with intermediate risk scores, indicating that genetic testing cannot predict all health problems with absolute certainty.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: 1039/c6fo00490c Finally, the Caco-2 cell bioassay has found that the fast-cooking trait, highly desirable to many bean consumers, has been linked to improved Fe delivery. Fast cooking is believed to be associated with the same polyphenolic compounds that promote Fe uptake, as well as genes that may control thickness of cotyledon cell walls. In summary, the above observations are all good news for bean growers, food producers and consumers who seek improved Fe nutrition from this staple food crop. This research gives new targets for bean breeders, and ultimately provides enhanced nutritional quality for consumers and value-added traits for producers. Other applications of the Caco-2 for Maize: The Caco-2 cell has identified the germ fraction (ie. embryo) of the maize kernel as the major component that inhibits Fe uptake from maize. Thus, degermed maize flour may represent an opportunity to provide improved Fe nutrition. In addition, these studies suggested that identifying and/or developing maize varieties with higher Fe density in the endosperm of the kernel should also provide more bioavailable Fe. Lentils: Red lentils are commonly dehulled post-harvest. The Caco-2 cell bioassay has identified the dehulling process as improving Fe delivery from lentils. Yellow bean breeding lines with fast cooking times and improved iron bioavailability being tested at the Farm, Michigan. Peas: Overall, peas have been identified as an excellent legume to deliver more bioavailable Fe. for Infants: As infants are particularly prone to Fe deficiency, complementary foods represent an excellent application of the Caco-2 cell bioassay to identify specific foods and food combinations to improve Fe nutrition for this vulnerable age group. Food Products: Major food companies routinely make use of the Caco-2 cell bioassay to identify optimal formulations to deliver bioavailable Fe while balancing sensory and other quality concerns. Poultry model for iron bioavailability Human studies of Fe bioavailability are expensive and time-consuming; thus, there is a critical need for the combination of the Caco-2 cell bioassay and an animal model to refine objectives for definitive human studies, and if possible reduce the number of human trials. Thus, to complement the bioassay, and his research team also developed a poultry model for iron bioavailability studies. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses research related to iron bioavailability in various staple food crops like beans, maize, lentils, and peas, without addressing the idea of ancient civilizations and their reliance on staple crops.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: Moreover, two studies intended to explore the delivery time of drone delivered AED compared to the time a bystander needed for searching for a fixed defibrillator [19] or to emergency medical services (EMS) [17]. Their results showed that the delivery time decreases when the defibrillator was transported via drone compared to ground search method (ranging from -2 minutes 56 seconds to 1 minute 42 seconds). The difference in response time for EMS was higher for rural than for urban areas (mean amount of time saved of 19 minutes). Another study was interested in time differences between a single bystander and dual bystander in a OHCA situation [18]. Their results showed that the bystander’s hand-off time was greater in the single situation compared to the dual situation. Claesson et al. [17] were additionally interested in the functionality of the AED after different release-techniques. The results showed that the AED was fully functional after its release, independent of the release-method. One study examined the best suitable placement of drones in by using a geographic information system (GIS) tool [17]. To find the suitable places for drones, the authors modeled the EMS delays and OHCA incidences and found twenty suitable locations in urban areas and ten in rural areas. DiscussionTo date, reviews focus on the applications, benefit, and challenges of drones in society [3, 11–13]. In addition to the increased use of drones in environment, conservation, and agriculture, drones are getting more and more attention in healthcare [3]. In order to realize the use of drones in the sector mentioned, thought must be given to how human drone interaction can be designed. To date, the role of users received little attention. Analyzing the literature focusing on human drone interaction and user experience in the context of medical supply of medicines and devices can provide insights on recent developments and future steps. Thus, the present scoping review is the first reviewing the current state of the literature on the human drone interaction in healthcare, especially in the delivery of medical goods such as devices and medications. This perspective is essential to develop comparative understanding how human drone interaction should be designed with regard to the requirements within the healthcare supply process. et al. [12] identified drone-based delivery of medicines as the most common identified application in healthcare, the present scoping review could not identify a study investigating the human drone interaction in the delivery of medicines with empirical design. [SEP] Justify:

Output: The text corroborates the claim by highlighting that drone-based delivery of medical goods, such as devices and medications, is a common application in healthcare, indicating ongoing pilot projects. It discusses the current state of literature on human-drone interaction in the context of healthcare delivery, specifically pointing out the increasing attention drones are receiving in delivering medical supplies.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: conducted a clinical analysis of 1,801 women (median age 60 years) with ER-positive, HER2-negative pN0-1 breast cancer (median follow-up of 6. 2 years) from 2006–2010[12]. In patients with an RS <18, the five-year risk of distant recurrence (where the cancer has spread to a region away from where the original cancer was located) was low. The rate of breast cancer-related death was also low. Endocrine therapy (ET) alone is supported in this group of patients. In addition, in women not treated with chemotherapy with an RS 11Â–25, the five-year distant recurrence rates were very low; chemotherapy is unlikely to exert clinical benefit in this group of patients. : the landmark trialOf the 10,273 women who took part in the trial, 6,711 had a mid-range an RS of 11ÂÂ–25 and were randomly assigned to receive either ET alone (most commonly tamoxifen for pre-menopausal women, and most commonly aromastase inhibitors for post-menopausal women) or chemoendocrine therapy (CET, most commonly taxane and cyclophosphamide). The primary end point was disease-free survival (recurrence of cancer in the breast, regional lymph nodes and/or distant organs, a second primary cancer in the opposite breast or another organ, or death from any cause). At a median follow-up of 7. 5 years, ET in women with a mid-range RS of 11–25 was not inferior to CET. Simply, this patient group would not benefit from chemotherapy and ET is as effective while less toxic and cheaper. will improve the lives of women who present with breast cancerWomen with RS ≥26 had a distant recurrence of 13% despite having chemotherapy and ET. Women with an RS <10 had very low recurrence rates with ET alone, regardless of age or other clinical variables. Women aged ≤50 years with an RS of 16–25 were shown to have some benefits from chemotherapy. ’s global financial and health benefitsIn light of the trial, around 5,000 British women in the UK could be spared the harmful implications of chemotherapy each year and the NHS could also be spared the financial burden; chemotherapy currently costs the NHS around £4,500 per patient. [SEP] Justify:

Output: The text contrasts the claim by discussing the results of a clinical analysis that suggests genetic testing, specifically the recurrence score (RS) in breast cancer patients, is not absolute in predicting health outcomes. For instance, it states that women with an RS <10 had very low recurrence rates with endocrine therapy (ET) alone, indicating that while genetic testing can inform treatment decisions, it does not provide certainty about all future health problems. Furthermore, women with an RS ≥26 still faced a recurrence rate of 13%, highlighting the limitations of genetic testing in predicting health outcomes with absolute certainty.


Input: Task: pass the claim using the given text. Claim: Every ancient civilization relied on the same staple crops. [SEP] Text: In combination with the bioassay, the poultry model has been validated in direct parallel comparison to human trials. In studies of crops such as beans and pearl millet, the bioassay and the poultry model correctly predicted the human efficacy studies. As a result, the combination of these research tools now represent a popular approach to studies of Fe nutrition. Lentil crop. Dr Glahn’s research has identified that the dehulling process improves Fe delivery in lentils. What can people do at home to minimise their risk of iron deficiency and to maximise the bioavailability of iron in their diet? <> Humans require a diversity of foods for optimal Fe nutrition, which also promotes other beneficial nutritional outcomes. Therefore, consumption of diverse diet of nutrient dense foods containing a variety of “protein foods“, such as legumes (beans and peas), lean meat (poultry and beef), seafood, eggs, and nuts. In addition, a variety of vegetables and whole fruits are highly recommended. Whole grains should make up at least half of all grain intake. Recommended amounts of dairy products should also be followed. Adherence to these dietary guidelines generates a healthy intestinal tract that facilitates Fe absorption and overall health. Improving the iron delivery from staple food crops and food products was last modified: November 8th, 2023 Keywords: Beansbioavailable ironCaco-2 cell bioassayFeflavonolsironiron bioavailabilityiron deliverymicronutrientsof Agriculture and this 193. Advance online publication. & Glahn RP. (2020). Polyphenolic profiles of yellow bean seed coats and their relationship with iron bioavailability. J Chem, 68(3), 769–778. & Tako E. (2019). An in vivo (Gallus gallus) feeding trial demonstrating the enhanced iron bioavailability properties of the fast cooking Manteca yellow bean (Phaseolus vulgaris L. ). Nutrients, 11(8), 1768. & Glahn RP. (2018). The fast cooking and enhanced iron bioavailability properties of the Manteca yellow bean (Phaseolus vulgaris L. ). Nutrients, 10(11), 1609. . (2014). Iron bioavailability in low phytate pea. Crop Science. 55(1):320-330. & Wiesinger JA. (2016). [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the bioavailability of iron from various crops and dietary practices, but does not provide any information on whether ancient civilizations relied on the same staple crops. The mention of diverse foods and specific crops such as beans, pearl millet, and lentils suggests a variety of dietary practices rather than uniformity across ancient civilizations.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: While a lot of media report about projects using drones in the delivery of medications [21–26], blood [27–29], or other medical goods [30], no empirical study was conducted and therefore, not evaluable for the present scoping review. However, these projects show the variety of scenarios and possibilities for drone use. There is little scientific evidence about the effectiveness, user experience and acceptance of medical drone delivery. Nevertheless, projects in different countries, e. g. in Ghana [21], Tanzania [22, 23], Vanuatu [24], or Germany [25], show that medicine transportation can be implemented. drones deliver birth control, condoms, and other medical supplies from a warehouse in an urban area to rural areas where local health workers pick up the supplies [30]. In Rwanda, drones deliver blood to clinics located in remote areas. Health workers request units of blood products via text message and 30 minutes later the blood parcels were dropped on parachutes via drones [27]. Another project in Malawi shows that drones can transport dried blood samples for early infant diagnosis of HIV [28, 29]. Drones can also deliver essential medicines like anti-venom or vaccines to hospitals from one building to another or to remote areas. In China, medical samples and quarantine materials were delivered via drones during the COVID-19 epidemic from hospitals to disease control centers in urban areas. This transportation reduced contact between samples and staff; furthermore, it reduced the time of delivery, providing a more efficient transportation for epidemic prevention and control [26]. One recent study calculated the number of drones and delivery times for the transportation of antiepileptic drugs from an urban hospital to pharmacies, gas stations, and mosques. The authors compared these to delivery times of transportation by road vehicles and found that drones dramatically reduced deliver time for routine and emergency delivery [31]. Nevertheless, the study used simulation methods and thus, human drone interaction was not assessed. These projects imply that the potential of drones in healthcare is enormous. Studies that investigate the human drone interaction by including user experience in the delivery of medicines are still lacking. However, to our understanding the interface of human drone interaction is the key to develop a service that is fitting to patient’s and health care provider’s needs and to the speed at which they adopt new technologies. Investigating user´s experience is important because the acceptance of drones will largely depend on how the process is perceived by the users. [SEP] Justify:

Output: The text corroborates the claim by detailing various projects where drones are actively being used to deliver medical supplies. It mentions specific examples, such as in Rwanda, where drones deliver blood to clinics, and in other countries like Ghana and Tanzania, where drones deliver various medical goods. These instances indicate that there are indeed pilot projects underway using drones for the delivery of medical supplies, thus supporting the claim.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: Oncotype DX is available to the NHS for a subsidised rate of around £2,580 per patient[13] and is available in the for around US$3,000 per patient[14]. As for ET, five years of tamoxifen treatment — much less toxic, relatively — would cost around 6p per patient per day, per patient and only £109. 50–£130. 00 over five years[15]. In the UK, anastrozole costs around 7p per day per patient[16] and only £127. 75 over five years. One estimate shows that if British women were to adhere to five years of tamoxifen treatment, 500 more lives could be saved a year, and £30m more could be saved in the NHS budget a year[17]. In 2006, LÃ¸nning reported that two to three years of tamoxifen followed by an aromastase inhibitor provided the lowest estimates of cost and highest number of quality-adjusted life years[18]. Personalised treatmentwill improve the lives of women who present with breast cancer. Its beauty lies in its reversion to a principle of cancer care: let the prognostic and/or predictive tests guide the treatment plan. The trial has encouraged the scientific and medical community to see precision medicine in a new light, which shines on treatments targeted to the correct patient populations, not only to the correct cellular targets. What our patients deserve is best described in the words of Roman emperor and stoic philosopher Marcus Aurelius: “Life is not merely being alive, but being well. ” is helping to foster that notion. Balkees Abderrahman, postdoctoral fellow, University of PhD candidate, University of Leeds, UK. Correspondence to: bhabderrahman@mdanderson. org10. 1056/NEJMoa1804710 [2] UK. Breast cancer statistics. Available at: (accessed June 2018) [3] Society. Breast cancer: facts and figures 2017–2018. Available at: (accessed June 2018) [4] Jordan VC. Tamoxifen as the first targeted long-term adjuvant therapy for breast cancer. Cancer 2014;21(3):R235–R246. doi: 10. 1530/ERC-14-0092 [5] Jordan VC. [SEP] Justify:

Output: The text contrasts the claim as it discusses the use of precision medicine and guides treatment based on prognostic and predictive tests, but it does not support the idea that genetic testing can predict all future health problems with absolute certainty. Rather, it implies that while tests can offer guidance for treatment, they do not ensure certainty in predicting all future health issues.


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 is irrelevant to the claim as it discusses nutritional physiology and iron bioavailability in various foods, such as beans and maize, without addressing the concept of staple crops or their reliance across ancient civilizations.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: Drone delivery of an automated external defibrillator—a mixed method simulation study of bystander experience. . 2019; 27:40. Epub 2019/04/08. pmid:30961651. View 19. of an Defibrillator. N Med. 2020; 383:1186–8. pmid:32937053. View 20. Zègre- Delivery of Defibrillators via Drones in Arrest: Users’ Experiences and the Human-Drone Interaction. Resuscitation. 2020; 157:83–8. pmid:33080371. View 21. Kelland K. Drones to deliver vaccines, blood and drugs across Ghana. Reuters 2019 [cited 18 May 2021]. Available from: 22. Mis M. UK-funded drone deliveries aim to save mothers, babies in Tanzania. Reuters 2019 [cited 18 May 2021]. Available from: Makoye K. Buzz as world’s biggest drone drug deliveries take off in Tanzania. Reuters 2017 [cited 18 May 2021]. Available from: 24. . An island nation’s health experiment: vaccines delivered by drone. 2018 [cited 18 May 2021]. Available from: 25. Nicas J, Sloat S. Deutsche post DHL to deliver medicine via drone. Journal 2014 [cited 18 May 2021]. Available from: 26. Cozzens T. China fights coronavirus with delivery drones. GPS World 2020 [cited 18 May 2021]. Available from: 27. Werber C. . Post 2016 [cited 18 May 2021]. Available from: 28. Africa’s first humanitarian drone testing corridor. 2017 [cited 18 May 2021]. Available from: 29. Drones could speed up HIV tests in remote areas. Reuters 2016 [cited 18 May 2021]. Available from: Bassett L. Contraception drones are the future of women’s health in rural Africa. Huffpost 2016 [cited 18 May 2021]. Available from: 31. é. A drone delivery network for antiepileptic drugs: a framework and modelling case study in a low-income country. . 2020; 114:308–14. pmid:31943110. View 32. -Exner I. TUI: Inventory: Vienna: FFG; 2012. View 33. Davis FD. [SEP] Justify:

Output: The text corroborates the claim by discussing various studies and projects where drones are being utilized to deliver medical supplies, such as automated external defibrillators and vaccines, highlighting companies and initiatives that are testing these delivery methods.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: Linking estrogen-induced apoptosis with decreases in mortality following long-term adjuvant tamoxifen therapy. J Inst 2014;106(11):dju296. doi: 10. 1093/jnci/dju296 [6] Jordan VC & Brodie AM. Development and evolution of therapies targeted to the estrogen receptor for the treatment and prevention of breast cancer. Steroids 2007;72(1):7–25. doi: 10. 1016/j. steroids. 2006. 10. 009 [7] Prediction of the oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis. 2013;26(5):658–664. doi: 10. 1038/m odpathol. 2013. 36 [8] The impact of Oncotype DX breast cancer assay results on clinical practice: A UK experience. 2017;28(Suppl 5):v43Â–v67. doi: 10. 1093/annonc/mdx362 [9] Impact of oncotype DX breast recurrence score testing on adjuvant chemotherapy use in early breast cancer: real world experience in Greater Manchester, UK. 2017;43(5):931–937. doi: 10. 1016/j. ejso. 2016. 12. 010 [10] Cost-effectiveness evaluation of the oncotype DX(R) breast cancer assay in clinical practice in the UK. 2012;71(24). doi: 10. 1158/0008-5472. SABCS11-PD06-02 [11] : first prospective outcome data for the 21-gene recurrence score assay and concordance of prognostic markers by central and local pathology assessment. J 2016;34(20):2341–2349. doi: 10. 1200/JCO. 2015. 63. 5383 [12] Clinical outcomes in patients with node-negative breast cancer treated based on the recurrence score results: evidence from a large prospectively designed registry. NPJ 2017;3:33. doi: 10. 1038/s41523-017-0034-6 [13] for Health and Care Excellence. Gene expression profiling and expanded immunohistochemistry tests for guiding adjuvant chemotherapy decisions in early breast cancer management: 4 and Mammostrat. [SEP] Justify:

Output: The text contrasts the claim by discussing various studies and outcomes related to cancer testing and treatments, specifically focusing on the recurrence score from the Oncotype DX assay. These studies suggest that while genetic testing can provide valuable prognostic information (e.g., related to breast cancer treatments), they do not imply that genetic testing guarantees absolute certainty in predicting all future health problems.


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 in ancient civilizations at all. It discusses the discovery of bamboo writing slips related to the legalist theories of the Qin state and provides information about institutional access and purchasing options for content, which does not contribute any relevant information to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: We developed an unmanned aerial vehicle (UAV) Tool to help health system decision makers identify their transport challenges and explore the potential utility and impact of UAVs on the broader health system. aerial vehicles (UAVs) or drones are increasingly explored as a solution to transport challenges for medical goods, including emergency blood supplies, vaccines, medicines, diagnostic samples, and even organs, particularly for “last mile” delivery. 1,2 Proof-of-concept tests have demonstrated the technological viability of UAVs to safely transport medical supplies3–6 and keep them within the required parameters for clinical viability. 7–9 A few research studies have determined the cost-effectiveness of adding UAVs to specific medical supply chains1,10 or the optimal placement for UAV stations. 11–13 Yet very few cases of successful scale-up of UAVs for medical transport exist. Recent work has focused on proving a UAV can successfully complete a flight but has neglected to address health-system integration and long-term sustainability. As a result, decision makers lack information on how to explore the potential utility of UAVs in addressing medical transport challenges and, if determined useful, how to add UAVs to health systems or achieve use at scale. Successful implementation of any health system change relies on a complex set of factors. 14 In the case of UAVs, not only will the selected technology need to be appropriate for the distance, weight, and size requirements of the transported items, but (1) it will need to operate within regulations, (2) the concept must be embraced by stakeholders, (3) financial resources need to be available, (4) human resources must be in place, and (5) operational procedures must be developed to effectively work within existing structures. When these aspects are not considered, operations can be delayed, inefficient, or fail entirely. In short, as with any intervention, the impact of UAVs on the broader health system should be considered before implementation. 15Using the framework of the Organization health system building blocks,16 this commentary describes challenges for integrating UAVs into complex health systems and presents a tool for considering whether UAVs could help address medical transport challenges and how they can be integrated into health systems. Under the assumption that readers may be unfamiliar with UAVs, we begin with some general information (Box). BOX an Vehicle (UAV)? [SEP] Justify:

Output: The text corroborates the claim by detailing the exploration and proof-of-concept tests for unmanned aerial vehicles (UAVs)—or drones—in transporting medical supplies. It mentions that UAVs are increasingly being examined as solutions for transporting emergency blood supplies, vaccines, and other medical goods, thus supporting the idea that companies are indeed piloting drone delivery systems for these items.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: Figure 2 with 1 supplement Download asset Open asset The ‘gene disruption score’, a gene-level prediction of the impact of genetic variants. (A) Schematic representation of how all substitutions affecting a particular gene are combined to compute the gene disruption score. (B) Average gene disruption score across all strains for four categories of genes conserved in all strains (‘core genome’). Conserved genes are defined as those genes found in more (or less) than 95% of the bacterial species present in the eggNOG orthology database (Huerta-Cepas et al. , 2016a). Statistically significant differences (Cohen’s d value >0. 3) are reported. (C) Gene-gene correlation profile of gene disruption across all strains shows clusters of potentially functionally related proteins. (D–E) The gene disruption profiles as a predictor of genes function. (D) Pairwise correlation of gene disruption scores inside each annotation set (colored boxes) and inside a random set of genes of the same size (grey boxes). (E) Gene-gene correlation profile of gene disruption scores in protein complexes; shown here a subset with high disruption score correlation. Figure 2—figure supplement 1 Download asset Open asset Additional properties of the gene disruption score. (A) Correlation between phylogenetic distance from the reference strain and average disruption across all reference genes. (B) Significant reduction in correlation after correction of the disruption score (see Materials and methods). (C–E) Prediction of gene functional associations using disruption score profiles. (C) ROC curve using disruption score profiles across all genes. (D–E) Higher predictive power of the gene disruption profile when restricted to accessory genes, including (D) or not (E) the information about gene presence absence. Figure 3 with 2 supplements Download asset Open asset Prediction of growth-defect phenotypes in the E. coli strain collection. (A) Schematic representation of the computation of the prediction score and its evaluation; for each condition the predicted score is computed using the disruption score of the conditionally essential genes. The score is then evaluated against the actual phenotypes through a Precision-Recall curve. (B) Higher predictive power for conditions with higher proportion of growth phenotypes. [SEP] Justify:

Output: The text contrasts the claim by discussing various aspects of gene disruption scores and their predictive capabilities. It highlights that while genetic testing can provide predictions about genes, it does not imply absolute certainty regarding future health problems. For example, it mentions 'higher predictive power' but does not claim that it can predict outcomes with absolute certainty, indicating that predictions are subject to variability and specific conditions.


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 does not address the claim regarding staple crops in ancient civilizations. Instead, it focuses on laws and legal structures from historical texts associated with the Shu (of Lord Shang) and other historical figures, which is unrelated to agricultural practices or staple crops. Therefore, it is deemed irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: 1,4UAVs are aerial vehicles guided without an onboard crew. They can be piloted remotely or programmed to fly autonomously. A variety of models exist, each suited to different applications based on distance, payload, maneuverability, fuel sources, durability, need for landing, and other factors. delivery of medical supplies via UAV is still relatively new. Until recently, there has been only 1 example of routine medical supply using UAV delivery. Since 2016, Zipline has operated drones for the Government of Rwanda, delivering up to 3 liters of blood within 30 minutes to health facilities that request it on demand. 17 In 2019, however, several other companies received approval to conduct routine flights. Matternet, a company that has conducted hundreds of test flights in Switzerland, routinely transports laboratory specimens within a health system. 18 Alphabet’s Wing will soon be delivering over-the-counter medications, via UAV in Canberra, Australia, after a year and a half of test deliveries. 19 Yet to date, none of these projects have published on the decision to implement UAV delivery, whether/how they integrated UAVs into existing health systems, or the impact the change has had on health care operations. In addition to these larger-scale operations, many other pilot projects delivering medical goods are being implemented worldwide,4,20,21 transporting items such as childhood vaccinations,22,23 automatic external defibrillators,11–13 snakebite antivenom,24 tuberculosis sputum samples,8,25 and sterile mosquitoes. 26 Although these projects are increasingly sharing information about operations, only a few resources for implementing UAV delivery projects exist 20,27,28 and none explore the feasibility and impact of adding this technology to the broader health system. Tools to explore feasibility and impact of UAVs in health systems do not yet exist. any new product or process to a large existing health system can be challenging. Companies that have been transporting medical goods via drone for multiple years or are preparing to do so have yet to share information about how they integrate their processes with the health system, what processes have to change, how those impact workflows, or the impact they have on health outcomes. Understanding the potential risks and benefits of a systemic change is important during the consideration and implementation of a new technology for evaluating sustainability and the true cost of implementation. [SEP] Justify:

Output: The text corroborates the claim by detailing that multiple companies, including Zipline, Matternet, and Alphabet’s Wing, are actively conducting pilot projects and routine deliveries of medical supplies using UAVs (uncrewed aerial vehicles). It specifically mentions Zipline's operation in Rwanda, Matternet's test flights in Switzerland, and upcoming deliveries by Wing in Australia, reinforcing the assertion that companies are indeed piloting drone delivery for medical items.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: For each condition set, the PR-AUC value for each condition is reported, together with the median and mean value (C) Significance of the PR-AUC value reported for the condition ‘Clindamycin 3 μg/ml’, against the distribution of three randomization strategies. ‘Shuffled strains’ indicates a prediction in which the actual strains’ phenotypes have been shuffled; ‘shuffled sets’ indicates a prediction where the conditionally essential genes of a different condition have been used, and ‘random set’ indicates a prediction where a random gene set has been used as conditionally essential genes. For all three randomizations we report a significant difference between the actual prediction and the distribution of the randomizations (q-values of 1E-30, 0. 05 and 1E-22, respectively). 3—figure supplement 2 for the other conditions. (D) Genome-wide gene associations are in agreement with the predictive score; the enrichment of conditionally essential genes in the results of the gene association analysis is significantly higher in conditions with higher PR-AUC. Figure 3—figure supplement 1 Download asset Open asset Detailed view of the predicted growth score and its properties. (A) Influence of the different predictors of the impact of mutations on each condition PR-AUC. ‘SNPs’ indicates single nucleotide variants only, ‘Accessory genome’ gene presence-absence patterns, ‘All predictors’ the combination of both, plus stop codon substitutions. (B–C) Proportion of well-predicted conditions (PR-AUC >= 0. 1 and Pearson’s FDR-corrected p-value<=0. 01) over total conditions with at least 1% and 5% sick strains. Marker’s size is proportional to the −log10 of the FDR-corrected p-value. (E) Conditions with higher predictive power (measured as PR-AUC) also have an enrichment of sick strains at the top of the predicted score, as measured by the (GSEA); sick strains are used as ‘gene sets’. A pseudocount of 10−4 has been added to the GSEA p-values. (F) Prediction performance improves when using the weighting scheme to account for conservation of gene essentiality, especially for well-predicted conditions. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexity of predicting health outcomes based on genetic testing. It references PR-AUC values and randomization techniques as part of the prediction process, suggesting that predictions are not absolute but rather probabilistic and influenced by the specific conditions and data used in the analysis. The text emphasizes the variability and limitations of predictive performance, indicating that while genetic testing can provide insights into health conditions, it does not guarantee absolute certainty in predicting all future health problems.


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 provides a series of references and titles without discussing staple crops or the agricultural practices of ancient civilizations. Therefore, it is irrelevant to the claim as it does not provide information that directly supports, rebuts, or relates to the assertion about ancient civilizations relying on the same staple crops.


Input: Task: pass the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: Although these issues apply to all UAV flights, they are particularly important to consider before health systems can utilize UAVs for transport, as most applications require long-range transport, either start or end in urban locations, and in emergency situations may not be able to wait for dawn to take flight. The complexity of health supply chains in low-resource settings requires dedicated stakeholder engagement. Often supply chains involve public, private, and nonprofit actors, national and international entities, siloed transport and tracking systems, and insufficient resources to strengthen them. However, UAV operations will be much more cost-effective if the technology can be used across silos and by multiple institutions. 1 Although using UAVs for public benefit is often met with enthusiastic response, stakeholders have demonstrated concerns about value for cost, privacy, security, how UAV regulations can be enforced,30–32 and noise. 33 These concerns can pose real barriers to implementation. Recently, the Government of Ghana’s plan to use UAV services to deliver blood products was opposed by the Association, a stakeholder that was not sufficiently engaged before decision making and felt the investment misplaced. 34,35Using UAVs for public benefit is often met with enthusiastic response, yet stakeholders have demonstrated concerns, including value for cost, privacy, and security. Many organizations have been working to ensure that decisions to use UAVs are made with as much information as possible. Over 5 years ago, a collaborative forum was developed to foster discussion and dissemination of UAV delivery work. for (UPDWG) currently has over 200 members from public, private, and nonprofit institutions. Recently, a more formal organizing body was created to strengthen coordination between stakeholders and share resources:. As UAV technology has evolved, challenges have arisen in aligning technology partners with stakeholder needs. Ensuring applications of this technology address relevant problems by teams who understand both local contexts and the parameters of the technology remains a challenge. In lower- and middle-income countries, the use of UAVs involves multiple entities: companies who develop and implement the technology, international health and development organizations who implement programs, and national entities who manage the delivery of health care and commodities and implement regulations. We observed a need for a decision-support tool for implementers who are considering UAV technology for transporting medical goods that educates both operators and implementors on relevant considerations. [SEP] Justify:

Output: The text discusses the challenges and considerations involved in utilizing UAVs for transporting medical goods but does not provide any specific information or evidence about companies piloting drone delivery for items like medical supplies. As such, it does not corroborate or contrast with the claim but is irrelevant to it.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: (B) Distribution of the number of predicted restored phenotypes per gene; red stripes indicate the genes that were experimentally tested. (C) Growth change between the target strain with the empty plasmid against the one expressing the reference copy of the target gene (complementation). Strains for which a change in phenotype is predicted are compared to those where no change is predicted. (D–F) Detailed representation of the results of the complementation experiment in three conditions. Mean colony area and the 95% confidence intervals are reported. Significant differences (t-test p-value<0. 01) between colony area of the strains with the empty and complemented plasmids are reported. ‘Other complementation’ reports strains expressing a different gene than the focal one, indicated between parenthesis. (G) Cartoon representation of AcrB 3D structure (PDB entry: 2dr6). Only one of the three monomers is highlighted in blue; colored spheres represent known non-synonymous variants in the reported strains. Figure 5—figure supplement 1 Download asset Open asset Detailed view of the experimental confirmation of the predicted phenotype-causing genotypes. (A) Replicability in colony size (measured in pixels) after outer frame and spatial correction between the two replicates. (B) Overview of the results of the complementation experiments. Mean colony area and the 95% confidence intervals are reported. Significant differences (t-test p-value<0. 01) between colony area of the strains with the empty and complemented plasmids are reported. Conditions CHIR090. and. 5UM have been excluded from further analysis, as the deletion strain from the KEIO collection (positive control) does not show a sick phenotype with an empty plasmid. Author response image 1 Download asset Open asset Author response image 2 Download asset Open asset Author response image 3 Download asset Open asset Additional files Source code 1 code used to analyze the genetic and phenotypic data, predict phenotypes and draw all the manuscript figures. Download elife-31035-code1-v2. gz Supplementary file 1 detailed list of the members of the strain collection Download elife-31035-supp1-v2. xlsx Supplementary file 2 detailed list of conditions on which the strain collection has been tested Download elife-31035-supp2-v2. [SEP] Justify:

Output: The text contrasts the claim by discussing experimental results related to genetic testing and phenotypes but does not support the idea of absolute certainty in predicting health problems. It mentions predictions made based on complementation experiments and describes variations in colony sizes that are contingent on experimental conditions and genetic complementation. This suggests that while genetic testing can predict some outcomes, it does not imply that all health problems can be predicted with certainty.


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 appears to be a list of historical references and documents related to various dynasties and laws in ancient China. It does not provide any information that supports, rebuts, or relates to the claim about ancient civilizations relying on the same staple crops. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: 2. ↵Zraick K. Like ‘Uber for Organs’: Drone delivers kidney to Maryland woman. Times. April 30, 2019. 4, 2019. 3. ↵-Procurement and Supply Management. Analysis: Applications in the Development Context. Washington, DC: Inc. ; 2017. 4. ↵for (FSD). Drones in Humanitarian Action: A Guide to the Use of in Humanitarian Crises. Geneva: FSD; 2016. 5. . Development of e-Juba, a preliminary proof of concept unmanned aerial vehicle designed to facilitate the transportation of microbiological test samples from remote rural clinics to laboratories. S J. 2007;97(11 Pt 3):1215–1218. pmid:18250941OpenUrlPubMed6. ↵. Drone transportation of blood products. Transfusion. 2017;57(3):582–588. doi:10. 1111/trf. 13900. pmid:278619677. ↵ Drone transport of chemistry and hematology samples over long distances. Clin Pathol. 2017;148(5):427–435. doi:10. 1093/ajcp/aqx090. pmid:290168118. ↵. Drone transport of microbes in blood and sputum laboratory specimens. J Clin Microbiol. 2016;54(10):2622–2625. doi:10. 1128/JCM. 01204-16. pmid:27535683OpenUrlAbstract/9. ↵. Can unmanned aerial systems (drones) be used for the routine transport of chemistry, hematology, and coagulation laboratory specimens? PLoS One. 2015;10(7):e0134020. doi:10. 1371/journal. pone. 0134020. pmid:2622226110. ↵ The economic and operational value of using drones to transport vaccines. Vaccine. 2016;34(34):4062–4067. doi:10. 1016/j. vaccine. 2016. 06. 022. pmid:2734009811. ↵. Locating AED enabled medical drones to enhance cardiac arrest response times. Care. 2016;20(3):378–389. doi:10. 3109/10903127. 2015. 1115932. [SEP] Justify:

Output: The text supports the claim by detailing various applications of drone technology in medical contexts, such as the 'drone transport of blood products' and 'the economic and operational value of using drones to transport vaccines.' These specifics indicate that there are uses for drones in the delivery of medical items, corroborating the idea that some companies are exploring this technology.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: DPYD genetic testing and the future of pharmacogenomic testing in routine care Genetic testing can identify which drugs and doses are best for individual patients, personalising care and optimising outcomes. Pharmacogenomics 14 June 2022 & William NewmanCopy link to page Download PDF A 2022 report by the of Physicians and the Society highlighted the potential for pharmacogenomic testing to be implemented on a broader scale in the UKJames King-Holmes PhotoAfter reading this 1. Figure 1: Decoding the nomenclature of pharmacogenomicsThe c in c. 1679T>G indicates that the change is within the coding region of the DPYD gene, followed by the number to represent the position of the change at 1,679 (i. e. the 1,679th nucleotide in the gene). T>G indicates that a thymine (T) has been replaced by a guanine (G). In this example a single nucleotide in a single position has been substituted and this genetic change is known as a single nucleotide polymorphism (SNP). It represents the most common type of genetic change[8]. Since the raw variant data demonstrated in Figure 1 is too detailed for the needs of most healthcare professionals, simpler star (*) allele names are given to raw genetic variants. In star-allele nomenclature, *1 is the first designated reference sequence to which polymorphic sites are then compared. This is usually the first sequence that was described to code for the functional protein product and may not be the most common allele in every ethnic population[9]. A unique number (e. g. DPYD*2A) is then given to each novel variant. Not all DPYD variants have been assigned a star allele, so the preferred nomenclature for DPYD variants is the or rsID number[7]. Depending on which version of the human genome is used as reference will change the rsID that the variant is compared to. Full discussion of this is beyond the scope of this 1. 5) and should have their fluoropyrimidine dose reduced according to the specific variant identified. Dose adjustments should be based on the advice given on the genetic report or other local or national guidance, such as the UK national guidance (depending on the standard operating policy at the treatment provider)[3]. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations of genetic testing. While it notes that DPYD genetic testing can provide valuable information regarding drug responses and dose adjustments, it does not support the idea that genetic testing can predict all future health problems with absolute certainty. Instead, it highlights the complexity of genetic variations and their implications, indicating that the outcomes depend on specific gene variants and their expression rather than guaranteeing predictions for all health issues.


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 provided is a series of references and annotations related to various documents from ancient Chinese history, specifically during the Qin and Han Dynasties. It does not contain any information regarding the staple crops of ancient civilizations or whether they relied on the same crops, making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some companies are piloting drone delivery for items like medical supplies. [SEP] Text: pmid:2685282212. Unmanned aerial vehicles (drones) in out-of-hospital-cardiac-arrest. . 2016;24(1):124. doi:10. 1186/s13049-016-0313-5. pmid:2772905813. ↵; Investigators. Optimizing a drone network to deliver automated external defibrillators. Circulation. 2017;135(25):2454–2465. doi:10. 1161/. 116. 026318. pmid:28254836OpenUrlAbstract/14. ↵Dearing JW. Organizational readiness tools for global health intervention: a review. Health. 2018;6(56):56. doi:10. 3389/fpubh. 2018. 00056. pmid:2955255215. ↵ Call for global health-systems impact assessments. Lancet. 2009;374(9688):433–435. doi:10. 1016/S0140-6736(09)61212-5. pmid:1957728916. ↵Organization (WHO). Everybody’s business: strengthening health systems to improve health outcomes: WHO’s framework for action. Geneva: WHO; 2007. 17. ↵Our Impact. Zipline website. 4, 2019. 18. ↵UPS partners with Matternet to transport medical samples via drone across hospital system in Raleigh, N. C. [press release] Atlanta, GA: UPS; March 26, 2019. 19. ↵Porter J. Google’s Wing drones approved to make public deliveries in Australia. The Verge. April 9, 2019. 4, 2019. 20. ↵Agency for (USAID). UAVs in Global Health: Defining a Forward. Washington, DC: USAID; 2018. 21. ↵Wingcopter, DHL and GIZ pilot drone delivery in Tanzania. Wingcopter website. 4, 2019. 22. ↵Held A. Drones deliver vaccines on island nation of Vanuatu. Radio website. 21, 2018. 4, 2019. 23. ↵Thorne J. Drones swoop into the Congo to strengthen the country’s vaccine supply chain. Geekwire. 8, 2019. 4, 2019. 24. [SEP] Justify:

Output: The text corroborates the claim by providing several examples of companies and organizations that are piloting drone delivery systems for medical supplies and vaccines, such as UPS partnering with Matternet to transport medical samples and Wingcopter, DHL, and GIZ piloting drone delivery in Tanzania. Additionally, the mention of drones delivering vaccines in Vanuatu and strengthening the vaccine supply chain in the Congo supports the claim that drone delivery is being implemented in the medical field.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: Patients may also have their dose modified on the basis of other factors, such as renal function and other comorbidities, since pharmacogenomics is just one aspect of medicines optimisation. Patients identified as homozygous or compound-heterozygous for a reduced functioning DPYD variant are categorised as DPYD poor metabolisers (DPYD-AS: 0) and will generally be considered for alternative treatments because of the severe risk of toxicity with fluoropyrimidines. However, in the absence of suitable alternatives and as part of a shared decision-making process with the patient, consultant oncologists and pharmacists may decide to proceed with fluoropyrimidine-based therapy at heavily reduced doses[3]. This conversation would be specific to the individual patient’s diagnosis and available treatment options, the variant(s) identified and other patient-specific factors to enable a risk versus benefit judgement to be made. Patient counsellingCounselling for DPYD testing does not require specialist genetic counselling services and is often undertaken at the time of consent for chemotherapy by an oncologist or non-medical prescriber. When discussing pharmacogenomic testing with patients, it is useful to provide the context in which the result will be used: to aid drug and/or dose selection according to guideline recommendations and to reduce the risk of severe or life-threatening side effects from fluoropyrimidine-based chemotherapy treatment. In this way, DPYD testing is not dissimilar to renal or liver function testing as it can guide prescribing decisions and optimise drug therapy[2]. Patient autonomy and informed consent are essential to the medical decision-making process. The consent process for pharmacogenomic testing is the same as for any medical procedure — patients and their carers must be provided with appropriate information to make informed decisions about their health. More detailed and technical information may also be required to ensure that patients get the right information for their needs. Written information and relevant online resources should also be offered to patients and carers. Box 2 lists the counselling points to discuss with patients. Box 2: Counselling pointsDPYD testing is being offered to guide treatment and/or dose selection and to reduce the risk of severe or life-threatening side-effects from fluoropyrimidine chemotherapy treatment;If a clinically relevant variant is identified, changes will be made to the chemotherapy regime, such as an initial dose reduction. [SEP] Justify:

Output: The text contrasts the claim by indicating that pharmacogenomic testing, which is a form of genetic testing, is used to guide treatment decisions rather than predict all future health problems. It specifies that DPYD testing is applied in a specific clinical context, particularly in optimizing drug therapy and reducing risks associated with chemotherapy, and not for predicting every health issue with certainty.


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 largely irrelevant to the claim as it does not discuss staple crops or their reliance in ancient civilizations. Instead, it lists various ancient legal texts and their authors, primarily from the Qin and Han Dynasties, which has no direct bearing on the agricultural practices of these civilizations.


Input: Task: corroborate the claim using the given text. Claim: Some bacterial strains can break down plastic in controlled environments over time. [SEP] Text: Can we use fungi to break down our plastic and rubber waste? Legaspi and Kaury KuceraBacked by. K. and 31 other backersöhler,. rexus, and : 10. 18258/0795$8,000Raised of $8,000 Goal100%Funded on 11/14/13Successfully Funded$8,000pledged100%fundedFundedon 11/14/13? How does this work? FollowOverviewMethods(9)Discussion (8)massive and rapid accumulation of our plastic and rubber waste is a problem that we cannot afford to ignore. Since certain types of plastic and rubber are held together by the same chemical bonds that are found in natural plant polymers, we are investigating the ability of fungi that live inside plants to degrade synthetic plastics and rubbers. Ask the ScientistsDiscussionWhat is the context of this research? Research on synthetic polymer biodegradation has been steadily growing over the past forty years. Several bacteria and fungi have been identified that produce enzymes capable of plastic and rubber degradation in various laboratory conditions. However, this field is still in its infancy and much work needs to be done to determine the viability of plastic and rubber biodegradation. Several plastics and rubbers contain the same chemical bonds that are found in natural plant polymers. Therefore, we are specifically targeting endophytes, organisms that grow symbiotically inside plants, in order to harness the endophytes’ ability to degrade natural plant polymers for the degradation of synthetic plastics and rubbers. Our group has previously identified degradation of the plastic polyester polyurethane by the endophytic fungus Pestalotiopsis microspora. This fungus secretes a small enzyme that is responsible for plastic degradation. Going forward, our project goals are to: 1) Characterize enzymatic degradation by Pestalotiopsis microspora - Isolate and characterize enzymatic degradation - Compare enzyme efficiency to other polyester-degrading enzymes - Evaluate degradation of solid polyester polyurethane and other plastics - Evaluate degradation of plastic by P. [SEP] Justify:

Output: The text corroborates the claim by mentioning that 'Several bacteria and fungi have been identified that produce enzymes capable of plastic and rubber degradation in various laboratory conditions.' This indicates that both bacteria and fungi, including a specific fungus, Pestalotiopsis microspora, have shown the ability to degrade plastics under controlled scientific research settings, thus supporting the assertion that certain strains can break down plastic in controlled environments.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: The dose can be increased subsequently if there are no serious side effects; If no clinically relevant toxicity-related variants are identified, there is still a risk of toxicity owing to other environmental, genetic or disease-related factors. Patients should be advised to report any side effects to the oncology unit without delay; Family members are not routinely tested when a patient is identified as carrying a clinically relevant variant, because a DPD deficiency does not usually cause symptoms unless fluorouracil or capecitabine chemotherapy is administered;Local procedures for the storage of blood samples should also be discussed with the patient; The DNA sample will not be used for other genetic tests without the patient’s consent. The genetic reportFigure 3 shows the type of information included on a genetic report, including the rationale for testing, a summary of the results and technical information about the test itself. If dosing recommendations are provided, these should be considered as part of a holistic assessment of the patient. Figure 3: Example of a DPYD testing reportThe GLH will return a genetic report similar to the one seen in Figure 3 to the requesting clinician. The provider is then responsible for incorporating the patient’s DPYD genetic report into their management plan and communicating results to the patient. Based on the individual patient’s result and the standard operating procedures at the trust, oncology teams may adjust the dose as described in the patient pathway. Targeted testing technologyMost of the genotyping is undertaken as per the requirements of the Test Directory, using simple targeted testing technology performed on a standard blood sample. The advantage of the targeted gene testing approach is that result turnaround time is 24 to 72 hours (the current NHS mandate is less than five working days)[6]. This means the results can be delivered in a clinically relevant timeframe to inform treatment decisions in the patient pathway. Future implicationsThe implementation of national DPYD screening is one of seven transformation projects delivered by the (GMSA) in 2021/2022 that aim to embed genomics into routine patient care pathways[10]. The DPYD project is aimed to optimise and improve the clinical effectiveness of DPYD gene testing for patients with cancer across England. GMSA regional pharmacy leads have been able to feed back on the positive contribution of pharmacists in chemotherapy provider trusts around the country in embedding DPYD pharmacogenomic testing into routine oncology pathways. [SEP] Justify:

Output: The text contrasts the claim by indicating that genetic testing does not provide absolute certainty in predicting health problems. It mentions that even if no clinically relevant toxicity-related variants are identified, there remains a risk of toxicity due to various factors, suggesting that genetic testing alone cannot guarantee prediction of future health issues.


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 does not provide any information relevant to the claim regarding staple crops used by ancient civilizations. Instead, it consists of citations and references presumably from historical documents without addressing the assertion that all ancient civilizations relied on the same staple crops. Therefore, it is marked as irrelevant.


Input: Task: corroborate the claim using the given text. Claim: Some bacterial strains can break down plastic in controlled environments over time. [SEP] Text: microspora in simulated landfill conditions (collaboration) 2) Screen for new plastic- and rubber- degrading fungi - Screen fungi collections for degradation of different synthetic polymers - For promising candidates, sequence the genomes and look for possible novel plastic- or rubber-degrading genes - Analyze candidates using gel permeation chromatography (molecular weight changes) and scanning electron microscopy (visual degradation) What is the significance of this project? Plastics and rubbers are examples of synthetic (or man-made) polymers that have become an indispensable part of our lives. From our disposable packaging to our grocery bags, from our water bottles to our car tires, we heavily rely on synthetic polymers on a daily basis. These materials are cheap to manufacture, versatile, and resilient -- which also means that they are produced in massive quantities and can last in the environment for hundreds of years. Given that these extremely durable materials are often used for single-use disposable applications, it’s important to think about what happens to plastics and rubbers after disposal. While we have seen an enormous boom in synthetic polymer production (over 250 million tons of plastic are produced every year! ); our methods of treating these materials after disposal have not been able to keep up. Recycling has helped reduce the amount of plastic waste, however only 15% of global plastic is successfully recycled. Additionally, Incineration, another common method of disposal, can form and release toxic chemicals into the environment. Therefore, we are investigating alternative (or complementary) methods of dealing with our plastic and rubber waste. What are the goals of the project? All funds raised will directly be applied to furthering the stated project goals of characterizing the biodegradation of plastic by Pestalotiopsis microspora and screening for new plastic- and rubber-degrading enzymes. A portion of the funds will be used to buy consumable lab supplies, which are necessary for the growth and maintenance of the fungal cultures, enzymatic characterization and materials for additional plastic and rubber screens. I already have access to the necessary equipment for polymer analysis; however, many instruments have fees associated with use and/or several accessory pieces of equipment or consumables need to be bought separately. I will apply the funds towards using equipment such as scanning electron microscopy and gel permeation chromatography. [SEP] Justify:

Output: The text corroborates the claim by discussing the biodegradation of plastic by the fungus Pestalotiopsis microspora. It mentions the project's goal of characterizing how this fungus can degrade plastic, which aligns with the claim that certain strains—presumably including bacteria or fungi—can break down plastic in controlled environments.


Input: Task: contrast the claim using the given text. Claim: Genetic testing can predict all future health problems with absolute certainty. [SEP] Text: The main messages identified by the project leads from the implementation of the DPYD pathway include:The importance of national commissioning to ensure testing is available across the country;The value of communication between clinical teams and regional GMSA leads;The importance of pharmacy teams in taking ownership/leadership of pharmacogenomic testing;The need for decision support tools/dosing guidelines (such as the UK Chemotherapy Board’s national dosing guidance[3]);The requirement for interoperability between electronic systems to permit reporting within ‘clinically relevant’ timeframes;That genomics is only one piece of a complex puzzle and that adverse drug reactions are influenced by other patient factors (e. g. comorbidities). Future work aims to characterise less common DPYD variants in patients who experience severe toxicity despite no variants being detected on initial screening. The future of pharmacogenomicsTo support the integration of pharmacogenomics into patient care pathways, consideration must also be given to alternative and newly emerging testing approaches. For example, pre-emptive testing with pharmacogenomic gene panels can test multiple genes simultaneously, improving efficiency and cost-effectiveness when compared with multiple individual genetic tests[11]. Having genomic data readily available in the electronic patient record at the point of prescribing would eliminate concerns related to turnaround time in clinical scenarios where there is an urgent need to initiate treatment; for example, before the use of clopidogrel in percutaneous coronary intervention[12]. Of course, there are challenges to this approach, not least the need to prove cost-effectiveness in the selected population and a requirement for comprehensive clinical decision support tools[13]. If successfully incorporated into the electronic patient record, and with sufficient integration to permit healthcare providers across sectors to view and act upon a patient’s pharmacogenomic information, the potential benefits are enormous[2]. 1Pharmacogenomics. Programme. (accessed Jun 2022). 2Personalised prescribing: using pharmacogenomics to improve patient outcomes. of Physicians. 2022. (accessed Jun 2022). 3Fluoropyrimidine-based Therapies. UK Chemotherapy Board. 2020. (accessed Jun 2022). 4 PharmGKB summary. Pharmacogenetics and Genomics. 2011;21:237–42. doi:10. 1097/fpc. [SEP] Justify:

Output: The text contrasts with the claim by stating, 'genomics is only one piece of a complex puzzle,' indicating that genetic testing alone cannot predict all future health problems. It emphasizes that adverse drug reactions are influenced by other patient factors such as comorbidities, and highlights the need for decision support tools, suggesting that genetic data, while valuable, does not provide absolute certainty in predicting health outcomes.


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 related to crop traits and dynamic modeling. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Some bacterial strains can break down plastic in controlled environments over time. [SEP] Text: Additionally, in the will be going to the as a for Strobel's and Laboratory class (all expenses paid; no donated funds will be used for travel). During this time, I will specifically collect fungi that may produce abundant lignocellulolytic enzymes to use in my plastic and rubber degradation screens. If promising candidates arise from these screens, I will use funds to sequence the genomes of the fungi to identify the responsible gene(s) and to synthesize genes that code for putative plastic or rubber degrading enzymes for future studies. wait. . . The proposed budget will be used to purchase laboratory supplies, equipment time, accessory equipment, and bioinformatic analyses for the purpose of: 1) Characterizing the enzyme from Pestalotiopsis microspora that is responsible for polyester polyurethane degradation and comparing the characteristics of this enzyme to other polyester-degrading enzymes 2) Assessing degradation of solid polyester polyurethane (as well as other types of plastic) and working in collaboration with a biodegradation testing facility to evaluate degradation of plastic by P. microspora in simulated landfill conditions 3) Screening endophyte collections for degradation of different plastics and rubbers and confirming degradation using gel permeation chromatography and scanning electron microscopy 4) Sequencing the genomes of potential candidates and looking for possible novel genes that code for plastic- or rubber-degrading enzymes. Meet the TeamMichelle LegaspiPh. D. CandidateAffiliatesYale University, Ph. D. candidate (2011-present). University of Florida, B. S. Chemistry (2010). . D. Candidate, I am driven by my desire to appreciate and learn from our natural environment in order to help integrate more sustainable systems into our lifestyles. I received my B. S. in Chemistry from the University of Florida. As an undergraduate, I spent 3 years working for the US Department of Agriculture analyzing chemically-mediated signaling interactions between plants and caterpillars in order to better understand plant defense mechanisms and increase agricultural crop yields without the use of harmful pesticides. I became increasingly interested in environmental research after studying abroad in and Fiji learning about human impact on the environment. After graduation, I worked with the Association teaching environmental education and building hiking trails in Massachusetts. I aim to combine my scientific knowledge and passion for the outdoors to tackle our environmental problems. [SEP] Justify:

Output: The text corroborates the claim by discussing the biodegradation of plastics, specifically mentioning the assessment of degradation of solid polyester polyurethane and plastic in collaboration with a biodegradation testing facility. It indicates research efforts with fungi and the exploration of their potential to degrade plastics, which supports the idea that certain microorganisms can break down plastic under controlled conditions.


Input: Task: contrast the claim using the given text. Claim: Genetic tests can be done without any expert interpretation needed. [SEP] Text: Listen to this story: Your browser doesn't support the audio element Back 15 seconds Forward 15 seconds 0:00 on social media linkedin x twitter facebook geneticists seem to agree on one thing: There are hundreds of genes potentially linked to the condition. But few agree on which ones should be added to the gene lists or “panels” for the commercial genetic tests that some clinicians rely on. To sort through the jumble of information, some of the scientists behind the Resource (ClinGen) — a U. S. federal program for evaluating clinical genetic evidence — formed a group in 2018 called the Panel (GCEP). This group is tasked with keeping researchers, clinicians and laboratories informed about whether current evidence supports clinical testing for any given gene. The GCEP started by scrutinizing a set of 156 genes used in more than one commercial test for autism or intellectual disability. In May, the group reported that 117 — 75 percent — reach its evidence bar for a definitive link to one of the conditions, but 22 lacked sufficient evidence for clinical testing; the remaining 17 had “moderate” evidence — enough to support their inclusion on a test, but still in need of more data. The group faces an almost Sisyphean task: At its current pace of four gene assessments per month, on average, the group would need more than six years to probe the 318 genes still on its list. And new genes — and new data for old genes — emerge all the time. Spectrum spoke with panel co-chair and coordinator Riggs about the challenges the team faces and the importance of constantly reevaluating an ever-shifting genetic landscape. This interview has been edited for length and clarity. Spectrum: How does the GCEP and its process differ from other groups evaluating autism-linked genes? Riggs: One big thing that our panel adds is giving people the concept of levels of evidence. One very commonly used resource is OMIM [Inheritance in Man], and that just catalogs when a gene-disease relationship has been proposed. But it doesn’t really tell you how much or how little evidence there is to support that relationship. Over the past few years, we’ve seen a wide gradation in the evidence for the genes we’ve evaluated. Some genes have evidence from many different affected individuals, lots of different papers and very good experimental evidence, and we feel very confident in those genes. [SEP] Justify:

Output: The text contrasts the claim by explaining the complexities involved in genetic testing. It highlights that geneticists have differing opinions on gene lists for testing and that organizations like the GCEP require ongoing evaluation of evidence to determine which genes can be reliably included in tests. The mention of the need for expert tasks, such as evaluating levels of evidence, indicates that expert interpretation is indeed necessary for understanding the results of genetic tests.


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 various predictive methodologies and their accuracies concerning plant traits over time, but it does not address the ability to accurately date plant remains. There is no indication about dating methods or the reliability of those methods in the provided text.


Input: Task: corroborate the claim using the given text. Claim: Some bacterial strains can break down plastic in controlled environments over time. [SEP] Text: I do this research with great faith that a remedy for plastic and synthetic rubber waste accumulation already exists in our environment and is waiting to be discovered and effectively harnessed. Kaury KuceraI love science research and education because I wake up every morning with confidence that I am working to fix important problems including contamination of our environment by persistent waste. I earned my Ph. D. at using x-ray crystallography to study the three-dimensional structure of two parasite proteins that are required for infection. Upon graduation I accepted a job teaching and doing research with undergraduates at Yale. I specifically work with students to study biological activities and bioactive natural products from endophytic fungi. Besides mentoring undergraduates it is my privilege to work with Michelle to identify and study the enzymatic proteins fungi use to degrade complex polymers. people are indigenous to the where we hunt for endophytes. They believe that where there is a poison in the jungle you can also find a cure. I do this research with great faith that a remedy for plastic and synthetic rubber waste accumulation already exists in our environment and is waiting to be discovered and effectively harnessed. Lab Notes9 PostedThis lab note is for backers onlyResearch ups and downsMay 27, 20150313This lab note is for backers onlyThe plastic degrading enzyme from Pestalotiopsis microsporaAugust 25, 201403430This lab note is for backers onlyCollecting latex producing plants in the Amazon RainforestMay 22, 20141171Relevant Publication: 1) Russell, J. R. , et al. "Biodegradation of by Endophytic Fungi" Appl. Environ. Microbiol. 77, 6076-6084 (2011). News Coverage: 1) "More than Mushrooms" - 2012. 2) "Researchers: Fungus can break down plastics" CNN, August 2011. 3) "Yale researchers find fungus that can break down plastic (video)" - Register, August 2011. Other links: 1) Researchers find organisms growing within fungi capable to degrade plastics 2) Find Plastic-Photo credit: EdinburghGreens from credit: for video recording/editing and for providing equipment Project Backers41Backers100%Funded$8,000Total Donations$195. 12Please wait. . . [SEP] Justify:

Output: The text corroborates the claim by suggesting that there are organisms, specifically enzymatic proteins from fungi, which can degrade complex polymers such as plastic. It states that a remedy for plastic waste accumulation already exists in the environment, particularly through the work being done to study biological activities of organisms that can potentially break down plastics. This aligns with the assertion that some bacterial or fungal strains can break down plastics over time in controlled settings.