Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: The same individuals often do not change their lifestyle [29], either because they do not understand the information provided, do not want to change their life style, cannot afford to change it, or because genetic counseling protocols fail to raise some groups' awareness of risk predisposition [30]. Educational interventions developed to improve risk perception do not seem to influence the way people understand their genetic risk [31]. The lack of health literacy is worrisome knowing that citizens are not always accompanied by professionals to interpret their genetic information. For instance, citizens who decide to order genetic tests through commercial companies may not be able to assess the validity and clinical utility of these tests and may make misguided health-related decisions. The recent US Food and Drug Administration's [32] ban on 23andme personal genetic tests demonstrates that information produced through commercial genetic tests may not be reliable. Citizens must also have sufficient technology literacy to be able to fully benefit from PM. However, groups of citizens, for instance the elderly, who are the heaviest users of health-care services, often do not have the necessary skills and abilities to use new technologies such as web-based health platforms or self-tracking devices, or are reluctant to use them [13]. Other groups, although more interested in technology, may not have access to it if the e-infrastructures are missing or if the technology is too expensive. Lack of Interfacing regularly with health-care provider, purchasing genetic tests, and endorsing the prescription of targeted therapies require economic resources that some groups may not have. This may be particularly true in countries where health care is funded through a variety of private insurers that can decide to restrict access to genetic tests and targeted therapies if considered too expensive or ‘investigational' [21,33]. Even in countries where health care is publicly funded, public payers may decide not to cover additional costs of targeted drugs and require that the patients cover such costs themselves. To illustrate our point, we refer to ongoing plans in the UK to modify pricing systems with the objective to increase prices for targeted drugs [34] and allow drug producers to achieve sufficient return on investment [35]. For the time being, it is still unclear who will cover potential additional costs related to the use of targeted drugs. to contribution to the research endeavor, for instance through participation in research trials, may be impeded by traditional research practices. [SEP] Justify:

Output: The text contrasts the claim by highlighting several barriers that may prevent effective treatment of health conditions with personalized medicine (PM). It mentions issues such as lack of health literacy, economic constraints, and accessibility challenges regarding genetic tests and targeted therapies. These factors indicate that PM may not be able to effectively treat every health condition, especially when individuals cannot engage with or afford the necessary resources and technologies to utilize PM successfully.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: NuMA-C 5A-1 and 5A-4 mutants still displayed punctate foci. (G) Live fluorescent images of nocodazole-arrested HeLa cells expressing GFP-tagged NuMA-C 3A fragments. Whereas NuMA (1700–1895: C6) diffused in the cytoplasm, this fragment was required for the NuMA (1990–2115: C3) fragment to display dots-like signals, which was abolished by 5A-2 mutation (C5). (H) Left: NuMA (1–2115 ΔNLS) 5A-3 (#10) mutant showing no cortical punctate signals of NuMA (top) and DHC-SNAP (bottom). Right: a kymograph obtained from image sequences of DHC-SNAP on the left at 30 s intervals. The metaphase spindle was not fully displaced regardless of cortical dynein recruitment. Scale bars = 10 μm. Figure 7 with 1 supplement Download asset Open asset Clustering activity of NuMA is required for spindle positioning, but not for spindle pole focusing. (A) Diagram summarizing auxin inducible degradation (AID) system (Natsume et al. , 2016). In the presence of OsTIR1 and auxin (IAA), mAID fusion proteins are rapidly degraded upon poly-ubiquitylation by proteasome. Because RNAi-mediated depletion of NuMA is insufficient to completely deplete NuMA proteins even after 72 hr (Kiyomitsu and Cheeseman, 2013), we sought to degrade endogenous NuMA using the auxin-induced degron technology. (B) Left: metaphase NuMA-mACF cell lines showing live fluorescent images of NuMA-mACF, mCherry-NuMA WT, or 5A3 mutant, and SiR-tubulin (SiR-TUB) after 24 hr following the treatment of Dox and IAA. The degradation of endogenous NuMA-mACF was induced by the treatment with Dox and IAA. The expression of mCherry-NuMA WT or 5A-3 was also induced by the Dox treatment. Right: histogram showing frequency of the focused bipolar spindle in each condition. [SEP] Justify:

Output: The text does not address the claim about CRISPR technology and its capacity for precise editing of genomic sequences. Instead, it discusses the behavior of NuMA (Nuclear Mitotic Apparatus protein) in certain mutant cell lines and their relationship to spindle positioning, which is unrelated to genomic editing techniques. Therefore, the text is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: student’s unique id number CS_rating a given student left for the computer scientist variant WA_rating a given student left for the variant BM_rating a given student left for the Batman variant CS_Total_time spent on computer science variant CS_Average_time spent on computer science variant WA_Total_time spent on variant WA_Average_time spent on variant BM_Total_time spent on Batman variant BM_Average_time spent on Batman variant Points_student obtained on the first exam before the role-based functionality Points_student obtained on the second exam, after the role-based functionality Point_in points between the second and first exam The students proceeded with the course till the second test and then we used a questionnaire to find their views on using a novel approach for creation and delivery of educational materials and materials. The study involved in 10 students who completed the questionnaire. In six months from now, we will send participants a new questionnaire to assess the permanent influence of the proposed instrument on their college life. These questions of both questionnaire she presented in Table 2 (Devlin et al. , 2018). Table 2. Questions were sent to the students to have their say on how useful the proposed instrument had been for them just after course completion and again in six months’ time. (Goodfellow et al. , 2016). you decide that the existing course content varieties that were open to you are sufficient or not? 5-point Likert First, after subject completion Teaching through a role-playing approach definitely made me have a pretty good time 5-point Likert First, after subject completion The teaching methods were such that the lessons I learn here remain in my mind throughout. Yes/No First, after subject completion I have tried such instruction with other students and would definitely recommend this kind of teaching. Open-ended Second, 6 months later Let us say, you had not only to build a lesson plan for the rest of your studies, but you had to create all the course program for the next four years. Flip it! How would you do it? Open-ended Second, 6 months later You can picture the topic or the lesson in your mind, isn’t it? Please elaborate. Multiple choice Second, 6 months later 5. Data AnalysisThe research intends to scrutinize the prevalence of AI in educational practice, which will involve data examination by both qualitative and quantitative approaches. [SEP] Justify:

Output: The text corroborates the claim by stating that 'the research intends to scrutinize the prevalence of AI in educational practice,' suggesting that AI is being used to analyze and possibly tailor educational content to students’ specific experiences, preferences, and needs, which aligns with the claim.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: For instance, ethnic groups and minorities are often excluded from research and deprived of the opportunity to contribute and benefit from medical progress [17]. As an illustration, 9 out of 10 genome-wide association studies are reported to be conducted on populations of European descent, unveiled gene-disease correlations therefore primarily applying to Caucasians [17]. Paradoxically, groups of population who are given the opportunity to contribute to the scientific endeavor may not be willing to do so. For instance, 44% of Europeans are not willing to provide personal information to a biobank, and 67% prefer being asked to consent to every new piece of research instead of consenting only once to a broad range of research uses [36]. Finally, broad citizen engagement in the public debate may be difficult to realize in practice. Current initiatives to engage a variety of citizen groups - other than the white and educated - in the design of research and health care often fail to reach groups which are usually underrepresented. As an illustration, a recent review of citizens' juries - a frequently used tool for engaging citizens in health policy decision-making - demonstrates that even when the organizers intend to recruit juries that are representative of the community, such juries primarily gather the most privileged groups of populations and fail to engage less advantaged groups [37]. Numerous initiatives are currently being developed which may make it possible for groups of citizens to adopt the new behaviors and practices that are needed for the realization of PM. For instance, patient-activated social networks such as the ‘quantified self' [38] network offer individuals the opportunity to use simple technological devices to take their own health measurements [39], disease-oriented social networks such as ‘Patients like me' [23] offer patients the opportunity to share experiences and even launch research projects [39], and participant-centric initiatives in biomedical research enable research participants to actively engage in the research process [40]. More and more citizens are taking the initiative to collect and gather medical information through the use of web-based technologies and participation in e-patient networks [22,23,24]. However, a general concern is that the early adopters of PM may primarily be citizens who are resourceful, highly educated, and socioeconomically advantaged. Adopting new behaviors and practices may be much more challenging for those who have lower levels of education and fewer socioeconomic resources. Some of the reports we have reviewed acknowledge this challenge but propose few solutions to address it. [SEP] Justify:

Output: The text contrasts the claim by highlighting significant barriers to the implementation of personalized medicine (PM), including the exclusion of ethnic minorities from research and the socioeconomic challenges that hinder broader adoption. It states that underrepresented groups often fail to engage in the scientific process and that early adopters of PM may primarily be those who are resourceful and educated. These points suggest that while PM has potential, current systemic issues prevent it from being effectively applied to every health condition.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: * indicates statistical significance according to a Student’s t-test (p<0. 0001). Error bars indicate SEM; n > 25, from three independent experiments. (C) Left: orthogonal views of the metaphase spindle on the x-y (top) and x-z (bottom) plane. In each case, endogenous NuMA was replaced with either mCherry-NuMA WT or 5A-3. Right: scatterplots of the spindle orientation on the x-z plane. Red lines indicate mean ± SD; n > 27, from three independent experiments. (D) Model showing multiple-arm capture and pulling of an astral microtubule by the cortical DDN cluster. Scale bars = 10 μm. Figure 7—figure supplement 1 Download asset Open asset Auxin-inducible degradation of endogenous NuMA and its replacement with NuMA 5A-3 mutant. (A) Left: genomic PCR showing the genotype of clones after Neomycin (Neo) selection. All clones displayed a single 4. 3 kb band, indicating that the mAID-mClover-3FLAG (mACF) (Neo) cassette was inserted at both NuMA1 gene loci. The clone No. 1 was used as a parent in the third selection. Middle: genomic PCR showing the genotype of clones after Blasticidin (BSD) selection. Both clones displayed a single 4. 6 kb band, indicating that the SNAP (BSD) cassette was inserted in both DHC1 gene loci. The clone No. 18 was used as a parent in the fourth selection. Right: genomic PCR showing the genotype of clones after Hygromycin (Hygro) selection. Arrows indicate a 2. 0 kb band, which confirms the insertion of mCherry-NuMA WT or 5A-3 mutant cassette (Hygro) at the Rosa 26 locus. The clone WT (No. 7) and 5A-3 (No. 4) were used in this study. (B and C) Live fluorescent images of endogenous NuMA-mACF and DHC-SNAP (B) or SNAP-LGN (C) showing punctate signals at mitotic cell cortex. These images were single z-sections, and the images in (B) are captured with camera binning 1. [SEP] Justify:

Output: The text does not address the claim about CRISPR technology specifically or its ability to edit genomic sequences precisely. Instead, it provides detailed information about genomic PCR and the genotyping of clones, which is unrelated to the assertion regarding CRISPR.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: The number of sampling could be few thus restricting the credibility of the experiment. The analysis may be exposed to bias, technical issues and also to the resources and manpower limitations. Nonetheless, these drawbacks could not prevent the study from giving useful information about the AI applications in education, which may be a significant contribution to the intellectual literature in this area (Mikolov et al. , 2013). 5. 3. Validity and ReliabilityThe research aims to prove that its results and findings are both reliable and valid by examining the credibility and trustworthiness of each data and information used. The validity is attributed to truthfulness and accuracy of the data. In this case, data will be collected through various methods that include surveys and examination of the student performance statistics. Throughout the process of research reliability meaning how good the findings could be copied and repeated having in mind the rigid and transparent methods and analysis data, will be applied. The goal is to conduct studies that give “true” results, that are reliable, and that are robust or strong enough, building on the science of generative AI in education. 6. Results6. 1. of Generative AISurveyed educators were divided on the fact that the generative AI would improve educational system or reduce it to the disastrous level. They came to conclude that AI would hypothetically bring about a radical change in the realm of educational content creation and teaching resources with the materials molded to the particular demands of the students. This, in turn, would spell a more impactful and memorable session which the students would enjoy. Moreover, they thought AI may augment the engagement of learners with different backgrounds, thereby improving the delivery and the effectiveness of the learning process (Radford et al. , 2018). In contrast to that, although some educators viewed AI-generated learning materials skeptically, stressing the importance of human judgment and control, others expressed confidence in AI-powered automation. As well, they pointed out the role of bias in AI models and importance of data responsibility. The essay also highlighted the role of bias in AI models and the need for care in data collection and utilization. Although fair employment and job security issues were among the main concerns of the educators, some of them still believed AI can contribute to the education. They regarded AI as a useful tool for improving the learning process, which they believe would assist the face-to-face teaching also through the provision of more customized instructions and student care. [SEP] Justify:

Output: The text corroborates the claim by stating that AI can bring about a 'radical change in the realm of educational content creation and teaching resources with the materials molded to the particular demands of the students.' This indicates that AI applications in education are indeed designed to tailor content based on individual student needs. The discussion around AI improving learner engagement and the effectiveness of the learning process further supports the idea that AI is used to customize educational experiences.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: Instead, the focus is put on the importance of educating citizens in PM [2,3,7,8,13,14,16,20,21]. Citizen education, for instance, encompasses introducing genetics and genomics in the educational program of students, developing websites and television channels to inform citizens about genetics and the use of genetic tests, and organizing public forums and debates. These strategies are of great importance but may not suffice to address the socioeconomic, cultural, and generational challenges we have described. In recognition of these challenges, we review below recently proposed strategies which may enable larger groups of citizens to participate in PM. At first glance, some of these strategies may seem too expensive and resource-demanding to implement. However, the current resources of health-care systems are allocated inefficiently [41,42,43]. If such resources can be used in a more efficient and coherent manner, implementing the strategies we describe may not be unrealistic or insurmountable. to of may be developed with local media, community representatives, and advocacy groups [44] to reach out to groups that usually are underrepresented in research and health care, such as low-income groups, ethnic minorities, and groups living in rural areas [17]. These groups could be involved in the design of educational tools and interventions that they know will be useful to them [30]. Similarly, research programs may be developed in close cooperation with local communities to include a wider variety of populations. For instance, clinical trials which focus on genetic variation instead of ‘race' or ‘ethnicity' could be designed [17]. Community-based participatory research programs under which communities and researchers work together in all phases of research may be particularly fruitful [45]. and reimbursement processes may be modified to provide quicker access to genetic tests and targeted treatments [15]. For instance, patient outcome and risk-sharing models [46] could be more systematically used to document the efficiency of biomarkers and companion diagnostics rather than stringent clinical data [47]. Limitations may also be put on the pricing of targeted drugs [35]. Such limitations, albeit controversial, can be more acceptable for pharmaceutical companies if financial incentives are offered, for instance through internationally financed funds [48], for the development of targeted drugs that benefit large numbers of people, such as drugs used for the treatment of infectious diseases and cancer [49]. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations and challenges associated with personalized medicine (PM). It suggests that while educating citizens on PM is important, this alone may not adequately address the socioeconomic and cultural challenges that exist. The text implies that the effectiveness of PM may be hindered by resource allocation issues and the need for community involvement, rather than asserting that it can universally treat every health condition.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: DNA was visualized with Hoechst 33342. (D) Western blot probing for anti-NuMA, anti-OsTIR1, anti-α-tubulin (TUB, loading control), and anti-histone H3S10P (a mitotic marker) at 24 hr following treatment. Band shifts in NuMA-mACF indicate bi-allelic insertion of mAID tag. Treatment with both Dox and IAA caused degradation of NuMA-mACF and accumulation of phosphorylated Histone H3S10, indicating mitotic arrest or delay. (E) Live fluorescent images of NuMA-mACF, SiR-tubulin (TUB) and DNA showing the spindle un-focusing phenotype. Intensity of SiR-TUB images was enhanced compared to Figure 7B to improve clarity of the phenotypes. DNA was visualized with Hoechst 33342. (F) Live fluorescent images of endogenous NuMA-mACF, ectopically expressed mCherry-NuMA WT or 5A-3, and SiR-tubulin (TUB) showing spindle mis-orientation in the NuMA 5A-3 mutant cells. Single z-section images on the x-y plane are shown. (G) Model showing recruitment (#1) and assembly (#2) of the DDN cluster at the mitotic cell cortex, and multiple-arm capture and pulling of a single astral microtubule by the cortical DDN cluster (#3). The ring-like structure for a NuMA cluster is an imaginary structure based on Harborth et al. , (Harborth et al. , 1999). for details. Scale bars = 10 μm. Author response image 1 Download asset Open asset 1 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Light-induced cortical targeting of RFP-Nano. The dynamic cortical targeting and repositioning of RFP-Nano, in response to illuminations, are shown in this movie; it is played at five fps. Video 2 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or genomic sequence editing. It appears to focus on DNA visualization and various experiments with cell components, without mentioning CRISPR or its capabilities.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: On the one hand though, they contemplated the reality that it was secured the deed be produced or monitored closely to ascertain its distinctions with real life and its objectives (Ruder, 2018). 6. 2. AI Developer InsightsResearchers into AI have published their case for the design and deployment of generative AI applications for education, pinpointing the tech challenges and moral dilemmas downstream. They advocated that inclusion of data from different sources may help to eliminate the bias and create courseware suitable for learners of diverse level and background. Additionally, they made the case for constant updates to the data-set to increase the precision and relevance of materials created by AI systems (Silver et al. , 2016). The feasibility of figuring out AI models as another feature plus the company highlighted necessity of the provided materials by educators and students to be undoubtedly understandable and transparent. They also delved into the application of XAI methodologies to enhance the ethicalness of these approaches. Ethical issue of AI in teaching was also outlined and developers were requesting the need for responsible app development procedures such as data privacy, security, and transparency. They continue to highlight the area of ethics to build an agreed upon trust and acceptance of AI-made content by educators, students, and parents (Socher et al. , 2013). 6. 3. Impact on OutcomesAI-made content has varied effects on student learning. Freshmen computer engineering students at a European institution and 20 students born 2020-2023 were polled in the second half of their first semester. This sample size may limit generalizability, yet it gives valuable insights into students’ AI-generated learning material experiences. Some students’ test scores and grades improved after using AI-based teaching tools, demonstrating better knowledge application. They benefited from relevant materials and received personalised training based on their learning level (Vaswani et al. , 2017). Not all pupils’ test scores or grades increased after using AI-generated materials. This variety shows that AI-made materials may be better for learner engagement and background knowledge, although model quality is crucial. OOP was used to evaluate project performance in two equal independent evaluations. The professor posted lesson names, substance, and outcomes following class. The professor connected LMS to to generate content for student learning (Xie et al. , 2017). 6. 4. [SEP] Justify:

Output: The text corroborates the claim by indicating that AI-based teaching tools provide 'personalised training based on their learning level' and that students benefited from 'relevant materials.' This aligns with the assertion that AI is utilized in EdTech to customize content to meet the individual needs of students.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: Develop Low- or low-cost programs offering access to genetic tests and targeted therapies may be proposed to groups that are susceptible of not being able to afford those or may not want to use them [50]. Such programs may, for instance, consist of publicly funded annual health check including mapping of genetic risk predisposition and lifestyle intervention provided free of charge [51]. In general, low-cost solutions should be preferred to expensive solutions. For instance, health-care providers may prioritize investment in wireless medicine, which is cheaper than traditional technology and offers the possibility to perform medical tests remotely and at reduced cost while simultaneously limiting the number of medical consultations [13]. health and technology literacy among large groups of citizens may be difficult to achieve. Alternative solutions could be proposed to citizens who do not have the ability to assess their own health or use modern technology but may benefit from personalized strategies. For instance, personal accompaniment and counselling could be proposed to senior citizens. Finally, systematically mapping disparities in the access and use of genetic tests and targeted therapies and making the results publicly available may motivate changes in policy in areas where disparities are the most striking [50]. One may question whether these strategies can guarantee that citizens will make the necessary efforts to adopt new behaviors and practices. Although no guarantee can ever be provided that people will behave in certain ways, investing in programs which target specific groups of populations may be the helping hand that is needed to motivate the adoption of new behaviors among specific groups. For instance, publicly funded programs which offer genetic risk mapping and lifestyle intervention free of charge have proved to increase the participation rate of high-risk patients in prevention programs while simultaneously potentially reducing future treatment costs [51]. reports we have reviewed envision citizens as educated, engaged, resourceful, and responsible partners rather than passive recipients of health care. This new role of citizens offers exciting opportunities but requires levels of health and technology literacy as well as socioeconomic resources that some groups of citizens may not have. Although some of the reports acknowledge that educational, technological, and socioeconomic hurdles may be encountered, they primarily focus on the importance of educating citizens in PM and propose few other solutions to address such challenges. Education in PM is critical. However, we suggest that the promoters of PM take into greater consideration the heterogeneity of citizens and develop policies and programs which specifically address the needs of the less educated and resourceful citizens. In Europe, discussions are currently taking place to reduce inequalities in access to PM [21]. [SEP] Justify:

Output: The text contrasts the claim by highlighting the challenges and disparities in access to personalized medicine (PM). It suggests that although PM has potential benefits, such as targeted therapies improving participation in prevention programs, there are significant barriers such as socioeconomic status and health literacy that may prevent effective treatment of every health condition. The text emphasizes the need for programs that cater to less educated and resourceful citizens, indicating that without addressing these inequalities, PM may not be universally effective.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Download as MPEG-4 Download as WebM Download as Ogg Light-induced cortical targeting of NuMA-RFP-Nano and spindle pulling. Light-induced cortical recruitment of NuMA-RFP-Nano (left), and DHC-SNAP (right), and spindle displacement toward NuMA/DHC-enriched cell cortex have been shown in this movie; it is played at five fps. Video 3 Download asset This video cannot be played in place because your browser does support HTML5 video. You may still download the video for offline viewing. Download as MPEG-4 Download as WebM Download as Ogg Light-induced cortical repositioning of NuMA-RFP-Nano and spindle rotation. Light-induced cortical repositioning of NuMA-RFP-Nano (left), and dynamics of SiR-tubulin (right) have been shown in this movie. The spindle rotation was coupled with cortical repositioning of NuMA. This movie is played at five fps. resources table Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional informationChemical compound, drugSiR-tubulinSpirochromeCat# SC00250 nMChemical compound, drugSiR-DNASpirochromeCat# SC00720 nMChemical compound, drugSiR-actinSpirochromeCat# SC00150 nMChemical compound, drugSNAP Cell 647-# S9102S0. 1 μMChemical compound, drug-starBioLabsCat# S9105S0. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses light-induced cortical targeting and spindle dynamics without mentioning CRISPR technology or genomic editing. It provides detailed descriptions of experimental setups and reagents but fails to address or corroborate the claim regarding the capabilities of CRISPR.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: LMS Integration and AI-GenerationAI content generation mechanism utilizing a new system was adopted to replace the one that had been used by students before in learning management system (LMS) where they used to learn. This category of editorial uses Genai’s GPT language model to create a myriad of instructional material that suits the different teaching methods and personas. There is the gap that was covered by appealing to audience in the manner of what would be with pop-culture characters. Students chose two variations: Batman and participate in a battle between two greatest antiheroes—Batman lavishes in his status as a cultural icon, while remains popular and mysterious. Ryder’s movie in particular, was picked out because it went most viral on the popular streaming platforms. After that, a third variant that dealt with a computer science teacher’s mode of interaction was integrated. This was because OpenAI charged for accessing their API at the time of the experiment in comparison to other competing applications with free access (Zoph et al. , 2018). Figure 1. Visual representation of the steps included in the experiment (Bahdanau et al. , 2014). Figure 1 above shows that approach is aimed that students are to be provided with the vast variety of learning resources, with the machine-generated content available in the app is readable and can be studied in three different formats. The course is then broken down into the actual content, where the content is generated, double-checked, and approved by the professor after class. This will provide for an environment that is generative in a controlled way and the final proof check. This lessens the ethical problems of AI that are generative. Students can surf between various options and choose from different methods for deeper understanding or enjoyment. In the description, the methodology is used (Branco et al. , 2017). 6. 5. Input and ProcessInside the LMS, in the resource upload section, a new option was shown to professors: generation of content using AI. When selected, the professors were asked to fill 3 fields representing the 3 core teaching elements: this cover may include the name of the lesson, the content or subjects in the lesson, and the achievement goals. The form was submitted editing the 3 API calls parameters seen in Table 3 below the form was submitted to a console commands (He et al. , 2016). Table 3. requests parameters (Branco et al. , 2017). [SEP] Justify:

Output: The text corroborates the claim by describing how artificial intelligence (AI) is integrated into learning management systems (LMS) to generate instructional material tailored to various teaching methods and student personas. Specifically, it highlights that students can choose between different content formats and subjects, which aligns with the idea of AI being used to meet individual student needs. Additionally, the method described allows professors to customize lesson content based on specific teaching elements, further supporting the claim about AI's role in personalizing educational content.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: Such discussions should particularly be encouraged in countries where health is financed by a variety of private actors and individual access to PM may be depending on the socioeconomic resources of each individual. Citizens will be more receptive to adopting new behaviors and practices and contribute to the realization of PM only if educational, socioeconomic, cultural, and generational hurdles are properly addressed. 1. : Personalized medicine: revolutionizing drug discovery and patient care. 2001;19:491-496. 2. Committee on a Framework for Development of a of Disease; Council of the National Academies: Medicine: Building a of and a of Disease. Washington, Academies Press, 2011. Academy of Medical Sciences: Realising the Potential of Stratified Medicine. 2013. Research Institute: of Genetic Terms. Food and Drug Administration: Paving the Way for Personalized Medicine. 2013. (PMC): for Personalized Medicine, ed 3. 2011. Science Foundation: ESF Forward Look: for the European Citizen. Towards more precise medicine for the diagnosis, treatment and prevention of diseases (iPM). 2012. of Ontario: Report: Mapping a the Double Helix. 2011. for Bioindustries (EuropaBio): Personalised Medicine: and Challenges. S, Kyngäs H: The qualitative content analysis process. J 2008;62:107-115. 11. European Commission: Working Document: Use of ‘-omics' Technologies in the Development of Personalised Medicine. 2013. Foundation: in an Era of Genome-Based and Personalised Medicine. 2010. Council on Bioethics: : of ‘Care' in a Consumer Age. 2010. Foundation: in the Sequence. 2011. (PMC): to Personalized Medicine: A of Systems. 2011. Commission for the Study of Bioethical Issues: Privacy and Progress in Sequencing. 2012. Progress: and Genetics. in the Age of Personalized Medicine. 2011. Commission: in Personalised Medicine. Conference report. 2011. Research Directorate: Personalised Medicine: Opportunities and Challenges for Care. Workshop 5 report. 13th Forum Gastein. 2010. President's Council of Advisors on Science and Technology: Priorities for Personalized Medicine. 2008. Alliance for Personalised Medicine: Report from Conference: Innovation and to Personalised Medicine. 2013. the data. www. free-the-data. org. 23. Patients like me. www. [SEP] Justify:

Output: The text contrasts the claim by emphasizing the socioeconomic and educational hurdles that must be addressed for personalized medicine (PM) to be effective. It implies that not all individuals may have equal access to PM based on these factors, suggesting that personalized medicine may not be universally effective for every health condition due to these disparities.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: 1 μMChemical compound, drugHoechst 33342Sigma-AldrichCat# B226150 ng/mLChemical compound, drugNocodazoleSigma-AldrichCat# M1404330 nM (high dose) for 18–24 hr and 30 nM (low dose) for 1–4 hrChemical compound, drugPaclitaxelSigma-AldrichCat# T740210 μMChemical compound, drugCytochalasin DSigma-AldrichCat# C82731 μMChemical compound, drugMG132Sigma-AldrichCat# C221120 μMChemical compound, drugRO-3306Sigma-AldrichCat# SML05699 μMChemical compound, drugImatinib mesylateSigma-AldrichCat# SML102710 μM for 24 hrChemical compound, drugCiliobrevin DCalbiochemCat# 25040175 μMChemical compound, drugPuromycin dihydrochlorideChemical IndustriesCat# 160–231511 μg/mLChemical compound, drugG-418 solutionRocheCat# 04727894001800 μg/mLChemical compound, drug# 084–07681200 μg/mLChemical compound, drughydrochlorideFunakoshi BiotechCat# KK-4008 μg/mLChemical compound, drugDoxycycline hyclateSigma-AldrichCat # D98912 μg/mLChemical compound, drug3-Indoleacetic acid (IAA)Chemical IndustriesCat # 098–00181500 μMChemical compound, drugDirectPCR (cell)Viagen BiotechCat #302 CAntibodyAnti-a-tubulin (clone DM1A)Sigma-AldrichCat# T90261:2000AntibodyRabbit polyclonal anti-NuMAAbcamCat# ab36999 (RRID:AB_776885)1:1000AntibodyRabbit polyclonal anti-# sc-91151:500AntibodyMouse monoclonal anti-p150BD Transduction LaboratoriesCat# 6104731:1000AntibodyRabbit polyclonal anti-# A303-032A (RR [SEP] Justify:

Output: The text is irrelevant to the claim about CRISPR technology, as it lists various chemical compounds and drugs along with their details without mentioning CRISPR or genomic editing.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: Please give detailed explanations with examples. Without the assumption that the app has been used previously, users don’t have to provide their answer or a response to a particular prompt; instead, simply explain its job. Learning outcomes: students should comprehend the idea of recursion, should include instances and should know how to write simple recursive functions. To show the whole statement to in Figure 2, please look at the request as follows:These are all repeated for the cases for the other two variants, changing the message system only with the messages as shown in Table 4 (Mikolov et al. , 2013). Figure 2. Submitted the system query to for turning the content into one variant. AI-supplies data in the requested format that can be JSON formatted for questions, therefore, LMS can accept the data and store it in the architecture that is compatible with such format. The LMS loads up a new octet of learning material and questions into its database, separating it by five hashtags. The mentioned blueprint consists of the first part, which is stored as a topic content, and the second part, which is decoded from JSON. Every question and every answer is logically saved in the LMS’s knowledgebase. LMS is able to display content and quiz questions either made manually or using auto-generated questions. These will be data read from a database. The integration process involves both receiving content from the server and the LMS storing database (Radford et al. , 2018) (Figure 3). Figure 3. Outputs. 6. 6. Quantitative ResultsThe research work investigates the effect of gamified role-based instruction on student learning. Unlike most other forms of communication, which are primarily written or spoken, nonverbal communication is the silent language we use unconsciously to communicate more efficiently. The figure plots that in only 19 seconds a total of 19 students—after outliers were “fitted”—spent time on AI-generated content, the bars in the graphs representing the total time spent on each case. The outcomes get to emphasize on the increase of the student success brought about by this strategy (LeCun et al. , 2015) (Figure 4). Figure 4. Amount of time in seconds that each student spends on each content variant. The study reported that teacher video guide version drew most of the students viewing time, and their preference was towards, the old style of content delivery. [SEP] Justify:

Output: The text corroborates the claim by discussing the role of AI in learning management systems (LMS) where AI facilitates the generation and storage of custom content based on student interactions. It mentions that the LMS is capable of loading new learning materials and questions, which supports the idea that AI tailors educational content to meet individual student needs. Furthermore, the text highlights that AI-generated content led to an increase in student success, indicating its effectiveness in personalizing education.


Input: Task: pass the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: patientslikeme. com. 24. Patients know best. for Participatory Medicine. Consortium: of in Eight EU Member States. -EU, Online Publication. 2012. Perceived risk following melanoma genetic testing: a 2-year prospective study distinguishing subjective estimates from recall. J 2014;23:421-437. 28. : The value of personalised risk information: a qualitative study of the perceptions of patients with prostate cancer. BMJ Open 2013;3:e003226. 29. : Effects of communicating DNA-based disease risk estimates on risk-reducing behaviours. 2010:CD007275. 30. A: Gaining Perspective: Issues and from Other Populations. Presentation at the 9thConference on Health Disparities, May 29-30, 2014. Improving subjective perception of personal cancer risk: systematic review and meta-analysis of educational interventions for people with cancer or at high risk of cancer. Psychooncology. 2014;23:613-625. 32. BBC News Technology: FDA bans 23andme personal genetic tests. Personalized medicine. Part 2. Ethical, legal, and regulatory issues. PT 2010;35:624-642. 34. Chinthapalli K: Higher drug prices will boost development of personalised medicine, says new report. BMJ 2013;347:f4549. 35. : Personalizing healthcare: from genetics through payment to improving care? J R 2013;106:41-44. 36. European Commission: Europeans and Biotechnology in 2010: Winds of Change? 2010. A: The use of citizens' juries in health policy decision-making: a systematic review. Med 2014;109:1-9. 38. Quantified Self. L, Auffray C: Participatory medicine: a driving force for revolutionizing healthcare. 2013;5:110. 40. : From patients to partners: participant-centric initiatives in biomedical research. Genet 2012;13:371-376. 41. Garber AM, Skinner J: health care uniquely inefficient? J 2008;22:27-50. 42. Godman B, Malmström RE, Diogene E, et al: Are new models needed to optimize the utilization of new medicines to sustain healthcare systems? 2015;8:77-94. 43. : Will biomedical innovation change the future of healthcare? Today 2009;14:1037-1044. 44. [SEP] Justify:

Output: The text provided discusses a variety of studies and presentations related to personalized medicine, but it does not explicitly support or contrast the claim that every health condition can be effectively treated with personalized medicine. Instead, it includes references to risk communication, patient perceptions, and healthcare policy that are not directly relevant to the efficacy of personalized medicine for every health condition.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: ID:AB_10749181)1:2000AntibodyMouse monoclonal anti-Gαi-1BiotechnologyCat# sc-565361:100AntibodyRabbit polyclonal anti-# P9310S1:1000AntibodyRabbit polyclonal anti-OsTIR1(Natsume et al. [SEP] Justify:

Output: The text is largely a collection of technical identifiers and does not provide any information related to CRISPR technology or its capabilities for genomic editing. Therefore, it is considered irrelevant (pass) to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: I am going to incorporate Likert scale in the first questionnaire with 3 categories which is presented below. To be exact, only one person indicated medium satisfaction with roleplay teaching, he said that it had an effect on learning and made academics more memorable. Students would promote this approach to their peers; five students will be choosing a CS teacher like (traditional), four students will choose Batman, and the remaining one will choose Wednesday Addams. Table 6 summarizes the versions that are best suited to both questionnaires (Ruder, 2018). Table 6. Our questioners after the first survey, preferred by the tutors of learning content, which had been carried out immediately after subject completion and 6 months after subject completion. (after Subject Completion) Votes (6 Months after Subject Completion) Computer science teacher 5 10 Batman 4 2 1 0 6 above shows that the implementation was followed by a second survey six months post completion of subjects, to determine the lasting impact of the previously proposed method. Five categories were identified: those who are game for quizzes, for characters, who favor platforms that are more valuable for them and are inclined to choose the traditional way simply because they like it more. However, there was one student which talked against the valuable content and its reliability. The choice of recommendation differed from one student to another, all students willing to pass onto a friend the new approach following the first questionnaire while only two of them would be open to the fictional character style (Ruder, 2018). 6. 8. 1: Duolingo’s AI-LearningIn addition, this study implementation was followed by a second survey six months post completion of subjects, to determine the lasting impact of the previously proposed method. Five categories were identified: those who are game for quizzes, for characters, who favor platforms that are more valuable for them and are inclined to choose the traditional way simply because they like it more. However, there was one student which talked against the valuable content and its reliability. The choice of recommendation differed from one student to another, all students willing to pass onto a friend the new approach following the first questionnaire while only two of them would be open to the fictional character style (LeCun et al. , 2015). 6. 9. 2: Knewton’s PlatformKnewton is an AI-powered educational platform that works on the basis of the individuals’ performance and sets up learning materials accordingly. [SEP] Justify:

Output: The text corroborates the claim by discussing Knewton, which is described as an 'AI-powered educational platform that works on the basis of the individuals’ performance and sets up learning materials accordingly.' This demonstrates the use of AI in EdTech to customize content to fit the distinct needs of each student.


Input: Task: contrast the claim using the given text. Claim: There is no ethical concern in the collection of genetic data for personalized medicine. [SEP] Text: It is worth mentioning that specific guidelines do not yet exist for the selection and application of PRO measures in MS clinical practice, and neither are these questionnaires part of a wider medical software applications. High quality clinical profiling is prerequisite to understand individual disease courses and treatment responses (Fig. 2). Fig. 2Combining individual treatment and big data RWE approach as a combined treatment approach: Individual clinical profiling is essential to characterize the individual patient in detail which is essential for individual treatment decisions. On the other side, collecting all individual patients profiles using big data approach can predict disease course and treatment responses again making personalized medicine possibleFull size imageAdditional parameters to be collected alongside clinical parametersDuring the last decades, establishing satisfactory biomarkers for multiple sclerosis has been very difficult due to the clinical and pathophysiological complexities of the disease [50]. The emergence of immunogenetics, neuroimmunology and neuroimaging, means that detailed clinical profiling ought be complemented by assessment of potential biomarkers to inform decision making concerning strategic and individualized therapeutics [51]. However, with some exceptions, many biomarkers evaluated thus far have yet to be shown to have useful prognostic capability. The the only way to investigate their prognostic role is to combine these data on biomarkers with detailed clinical monitoring data in MS registries [25, 52]. Regardless of data type, all parameters collected as an adjunct clinical profiling depend on the quality of the medical documentation, and their quality is critical of they are to corellated with laboratory and imaging data. The availability of reliable biomarkers could radically alter our management of MS at critical phases of the disease spectrum. Identification of markers that could predict the development of MS in high-risk populations would allow for intervention strategies that may prevent evolution to established disease [53]. MS registries as tool to collect real world dataMost studies, in particular those concerning the therapeutic effect of immunomodulatory therapies, usually occur over of 2 – 3 years of follow-up [54]. This is counter to the disease course of MS, which runs over several decades. In order to reveal long-term aspects of the disease, so-called register studies for MS patients were initiated some time ago with the goal to provide valuable information pertaining to prevalence, current therapy pattern and disease progression data [55, 56]. Such data can be collected over long periods of time, for example, more than 20 years [57]. These MS registers enable correlations of disease progression with demographic and clinical characteristics [58]. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and requirements surrounding the collection of personalized medicine data, such as the need for high-quality clinical profiling and the establishment of guidelines for biomarkers. It implies that there are significant ethical and practical considerations that must be addressed in the collection of genetic and clinical data, suggesting that ethical concerns do indeed exist.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: , 2016)In-house antibody1:1000AntibodyRabbit polyclonal anti-phospho S10 histone H3AbcamCat# ab5176-251:500AntibodySheep anti-mouse IgG-# NA9311:10,000AntibodyDonkey anti-rabbit IgG-# NA9341:10,000Software, algorithmPhotoshop CS5, version 12. 0algorithmFiji(Schindelin et al. , 2012) algorithmMetamorphalgorithmGraph6, version 6. 0 cGraphalgorithmExcelfiles Supplementary file 1 Cell lines used in this study. Download elife-36559-supp1-v2. docx Supplementary file 2 sgRNA sequences forCas9-mediated genome editing. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not provide any information regarding CRISPR technology or its capabilities in genomic editing. Instead, it includes details about antibodies, software algorithms, and supplementary files unrelated to the claim of precise genomic editing.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: It essentially analyses where the student’s strengths and weaknesses lie and alters the content to suit their needs. For demonstration, if the student finds issues with algebraic equations, the platform might offer supplementary practice tests or resources. Additionally, the platform considers and accounts for every student’s learning modes and pace, so he or she receives the information in a way that benefits him or her most. This approach of personalizing has already shown to rise the result of the student, while the engagement and understanding are higher. Knewton also provides live analyses to educators, so that they can track their students’ progress and look for areas where extra attention might be needed. These data-based tactics support teachers in better know their students’ needs and adjust teaching on the basis of their findings (LeCun et al. , 2015). 7. DiscussionAI has an exceptional ability to change for good the way students interact with educative sources due to its capacity to offer individual students learning opportunities that meet all their needs. Through the data analysis of students and rewriting or editing of the content, generative AI can provide a better learning experience for students and reduce the time learning spent to a minimum. Ultimately, student success is the result, which is shown in a higher academic performance and higher involvement of students in learning. Technology can be beneficial in this aspect too as one of the advantages it provides is to absolve the educators of routine chores like marking and lesson planning which consequently enable them to direct their focus to skills enhancement (Mikolov et al. , 2013). Nevertheless, there is a alongside challenge of ensuring the accuracy and quality of AI content as well as its capacity to cause bias in AI models. In order to realize the aim of self-sustainable content supply, generative artificial intelligence (Generative AI) can be harnessed to develop content that is automatically synchronized into the learning management systems without necessarily having to dedicate any time or resources to its production. This paper gives a step-by-step guide for an integrated system of authentication between the given systems with OpenAI, serving the purpose of linking current educational systems with the most recent AI techniques. The integration process involves two primary types of messages: a variety of the system messages stipulated in LMS, the user messages from Bank and the teachers’ inputs within LMS. [SEP] Justify:

Output: The text corroborates the claim by detailing how AI analyzes students' strengths and weaknesses and alters educational content to suit their individual needs. It states that the platform offers supplementary practice tests based on specific challenges, accounts for various learning modes, and personalizes the learning experience. Moreover, it mentions that these personalized approaches contribute to improved student results and higher engagement, aligning perfectly with the claim about AI's role in customizing educational content.


Input: Task: contrast the claim using the given text. Claim: There is no ethical concern in the collection of genetic data for personalized medicine. [SEP] Text: Consequently, register studies can provide data on the long-term progression of MS, wish is information urgently needed by the clinical community. Of course, MS registers have their limitations, in particular concerning the generalizability of the data [55]. A MS register only allows conclusions to be drawn for the cohort of patients documented within the scope of the register [26]. MS registers can be physician-oriented or patient-oriented with different advantages and disadvantages in each case [26, 30, 59]. The clear advantage of physician-centered registers is the detailed clinical and demographic documentation. However, the disadvantage is the high documentation effort from the physician’s side, which makes a long-term documentation of large cohorts difficult. Patient-based registers allow the collection of data from large patient numbers and they are relatively cost-effective [59]. However, the lack of medical screening as well as data validation by a physician can lead to significant errors (for example a missing MS diagnosis). Despite these problems, there are patient-centered MS registers with high response rates and 90 % or more correct MS diagnoses. Observations of register studies are particularly valuable and clinically relevant if several register studies can confirm their findings reciprocally. However, it is important to note that real world data for different cohorts are different, and this can make correlations of this type difficult [60]. Each database is unique and usually emphasizes different features. Altogether, a lack of consistency is mostly related to quantitative and qualitative differences in data collection [54]. MS registers are the only meaningful opportunity to collect long-term data – these data cannot be collected by other means because it is not possible to track such a large number of patients over such a long time period within the scope of a clinical study. Methodologically, a prospective, standardized data collection like this overcomes the limitations in statistical power that characterize most clinical studies [56]. Nevertheless, these register databases are widely criticized for their lack of statistical power relating to poor associations and the prediction of rare events as well as their incompleteness. In addition, guaranteeing high data quality is a huge challenge, particularly when there are limited financial resources. MSDS 3D – combining documentation and management of MSSince 2008 the eHealth MSDS3D project group in Dresden has been developing the patient management system (MSDS) 3D, which is a new development of MSDS Klinik in practice throughout Germany [16]. [SEP] Justify:

Output: The text contrasts the claim by highlighting that there are significant challenges and criticisms related to data collection processes in MS registers, such as 'limited financial resources' and the 'huge challenge' of ensuring high data quality. These aspects suggest ethical concerns regarding the collection and use of genetic data, as they affect the reliability and integrity of such data in personalized medicine.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Applying genome-editing tools to human induced-pluripotent stem cells (iPSCs) has provided new directions for regenerative medicine and in vitro disease modeling (Robinton & Daley, 2012). Several studies have successfully generated cell lines to recapitulate genetic diseases using theCas9 system (Ben Jehuda, Shemer & Binah, 2018). Despite the advantages, the efficiency of creating mutations via NHEJ or HDR remains relatively low in human iPSCs (Mali et al. , 2013; Wang et al. , 2013). Single-stranded DNA oligonucleotides (ssODNs) have been used as repair templates to efficiently introduce single-nucleotide mutations, and double strand DNA donor plasmids are used for fragment insertion via HDR (Chen et al. , 2011). However, HDR rates vary depending on cell type and status (Saleh-Gohari & Helleday, 2004). Researchers have proposed strategies to enhance the success rate of genome editing, including cell cycle synchronization, introduction of selection markers, and pre-treatment with small molecule NHEJ inhibitors (Chu et al. , 2015; Guo et al. , 2018; Yu et al. , 2015). Recently, researchers applied Cas9 ribonucleoproteins in combination with AAV-mediated repair template delivery to increase integration frequency (Martin et al. , 2019). Although the efficiency is improved from the original technique, the timing of drug treatment and administration of -Cas9 are difficult to control due to the cell cycle variation between cell lines. Cardiac glycosides have been used to treat heart failure by targeting ATP1A1, a subunit of Na+/K+-ATPase (McDonough et al. , 2002; Smith, 1984). With exposure to relatively high concentrations of such drugs, cell viability is reduced via the accumulation of intracellular Ca2+ levels (Belusa et al. , 2002; Lin et al. , 2017). The binding site of cardiac glycosides on ATP1A1 has been identified, and N-terminal amino-acid substitution of ATP1A1 encoded by exon4 (Q118R and N129D) is sufficient to confer drug resistance by preventing the binding of the cardiac glycosides (Treschow et al. , 2007). In 2017, Agudelo et al. [SEP] Justify:

Output: The text discusses various genome-editing tools and methods applied to human induced-pluripotent stem cells, mentioning the Cas9 system and techniques like HDR and NHEJ. However, it does not directly support or contradict the claim that CRISPR technology allows for precise editing of genomic sequences; it instead provides a broader context about genome editing challenges and advances that are somewhat related but ultimately irrelevant to the specific claim about CRISPR.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: The uniqueness of this part is that the generation of content can be implied in different ways for every student, without involving any other person to the procedure, to ensure the validity of the results on the receiver’s side. is the vendor’s latest offering which provides a choice of JSON communication only instead. It facilitates quick integration into the system (Mikolov et al. , 2013). 7. 1. Student’s Engagement with AI-TutorsThe research investigated the efficacy of an AI organizing the education in the classes to students using in a role based teaching style. Students noticed that choosing the characters was hugely enjoyable to them and their wish was that we used this method to more classes. They felt the automatic and immediate response to their questions had a great educational value, because it helped them to test their comprehension and were sure they got the answers right. AI systems demonstrate much more flexibility as they can interactively generate feedback, and when prompted with open-ended questions, they can provide explanations for selected topics as well as support multiple practices for better understanding of subject materials and also give students personalized learning materials. Concerning, the favor of the students four sessions after was about the original teacher style. The story-based method, despite the fact that it was successful six months after completion of the subject, was still the most preferred because people keep folklore and mimic behavior of main characters when they are scared, sad or happy. The narrative approach was the one that makes people feel as they have this kind of creatures around and they could be able to act the same if they were in a particular situation. It turned out that those students who applied to AI-content in LMS from the beginning revealed significantly higher scores, which is the evidence that different learning material variations are beneficial for those students who, otherwise, have not shown basic knowledge on the topic. Although this finding requires additional validation studies with bigger sample sizes to substantiate it, it is absolutely right (Silver et al. , 2016). 7. 2. LimitationsGenerative AI, as it is a promising technology that helps to develop individualized learning resources, however, has, at the same time, numerous drawbacks. The AI education is not limited to the quality and the accuracy of the content; that it is the training process requiring the large data-sets that is the biggest challenge in an educational environment. [SEP] Justify:

Output: The text corroborates the claim by stating that AI systems can 'interactively generate feedback' and 'provide explanations for selected topics' as well as 'support multiple practices for better understanding of subject materials and also give students personalized learning materials.' This clearly indicates that AI is used in educational technology to create tailored content that meets individual student needs.


Input: Task: contrast the claim using the given text. Claim: There is no ethical concern in the collection of genetic data for personalized medicine. [SEP] Text: Due to ever more complex diagnosis and therapy algorithms and a variety of innovations over the last years, this is an attempt to go a step further and provide not only a patient documentation system but also an electronically supported adaptive patient management system for multiple sclerosis [13, 61]. In highly specialized diseases such as MS, a specific, intelligent management system, which goes beyond a mere MS documentation, is needed by all parties involved in the treatment process [38, 62]. For prospective data collections, eg. innovative drug-specific phase IV trials, a simple documentation system that does not support the user with prospective data entry, or that does not remind him if important data are missing is not adequate [36, 63–65]. The entire process for the MSDS3D system includes the patient, nurse and physician in the system. Furthermore, the system can be used both for the collection and interpretation of patient data, and for conveying information to the patient interactively. Interaction with the patient takes place either via online multi-touch systems, such as a touchscreen or a touchpad as an interactive patient terminal, or via mobile devices such as smartphones (Fig. 3a). The interview system for the questionnaire-based data collection integrated into MSDS3D is equipped with a user interface that was specifically designed for MS patients [44, 45]. In addition, the medical staff manages the process of the interview (for example the start of the interview) and provides any necessary assistance with answering. Mobile devices are controlled by the MSDS3D system located in the local treatment center via a specific server that also controls the data flow to and from the patient. Anonymity and data protection are guaranteed by a complex process that includes an encrypted transmission. An expert advice system is included in the software to enable specialists involved in special cases to provide their opinion [64]. Neurologists who make use of clinical expert advice at any time during the study and radiologists seeking an MRI second opinion reading are asked to document these requests. Fig. 3a MSDS3D as interdisciplinary platform to manage MS patients using the MSDS3D cloud connected with devices (b) MSDS3D as both local and web-based data entry system using module- and task box based technology and the MS overviewFull size imageMSDS3D is a module-based, web-based or locally-installed software which is connected to a single central database (Fig. 3b). [SEP] Justify:

Output: The text contrasts the claim by discussing the importance of anonymity and data protection in the context of collecting patient data through the MSDS3D system. It emphasizes that data protection is guaranteed through a complex process, which indicates that there are ethical considerations involved in the collection of genetic data, suggesting there are concerns that the claim overlooks.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: To construct donor plasmids, dsDNAs from GeneArt™ synthesis were cut with restriction enzymes and cloned into p(+) (Addgene, MA, US). The sequences from all constructs were sequenced and verified before proceeding with the experiment. Donor templates for each targeted locus are listed in Table S1. Cell lines, cell culture and electroporation Two human induced pluripotent stem cell lines, K3 hiPSCs (Si-Tayeb et al. , 2010) and SV20 hiPSCs (Yang et al. , 2015), which were characterized in previous studies, were used for this study. Provenance of all cell lines and use in these experiments were approved by the protocol #8. Cells were cultured in mTeSR feeder-free defined medium (Ludwig et al. , 2006) supplemented with 4 ng/mL zebrafish basic fibroblast growth factor. All iPSCs were maintained as colonies on E-cadherin-IgG fusion protein matrix at 37 °C with 4% O2/5% CO2 (Nagaoka & Duncan, 2010). Electroporation of plasmids and ssODNs used electroporator ECM630 () following the manufacturer’s instruction. Briefly, iPSCs were expanded until 80% confluence on one 100 mm dish to give approximately 4 × 107 cells and were harvested in small clumps using 0. 05% EDTA. Cells were mixed with purified DNAs in 4 mm electroporation cuvette and immediately electroporated at 250 volts/200 Ω/700µF. Transfected cells were cultured onto 100 mm dish coated with Matrigel (2 mg/ml) (Invitrogen, MA, US) in mTeSR medium supplemented with 4 ng/mL zebrafish basic fibroblast growth factor and 10 µM of Y27632 () for 24 h. For ATP1A1 co-targeting, cells were transfected with PX459 plasmids containing guide sequence of ATP1A1 and second gene of interest, along with linearized donor plasmids following the electroporation protocol above. After 24 h of Y27632 treatment, transfected cells were selected by culturing with 1µg/mL of puromycin for 48 h. [SEP] Justify:

Output: The text primarily describes experimental procedures involving the use of donor plasmids and electroporation in human induced pluripotent stem cells but does not specifically mention CRISPR technology or its capability for precise genomic editing. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: Furthermore, the training data may also be biased and that bias can be reflected in the base LMs produced. Ethical concerns should be considered in generative AI models too since they can result in bias based on the training data. The current study has two main limitations: not having that much of a sample size and having a limited number of variants that are available to a lab. To ensure that the enhanced usage of the suggested approach has capabilities to accommodate and support the needs of individual classes, such as instant feedback, self-paced learning, making learning more interesting, focusing on student’s learning needs and time spent on learning, a larger population size is needed for confirmations. Researchers are testing endless new design of variations in hopes of enabling students to gain more experience with the teaching material (Mikolov et al. , 2013). 8. Conclusions and Future WorkThe use of generative AI reveals high potential in the development of the learning materials and resources which have to be unique for every student. As the data of the student is incorporated in the content, it is easier to modify it thus improving the learning system and likely to increase student results and motivation. The adaptive learning and feedback technologies could enable educators to make better use of the personalised resources that may be provided. However, the integration of generative AI in education has some hurdles as explained below. These include quality and accuracy of brand content created through AI, bias in AI solutions, and protection of data in the use of AI. It may also be the case that some study materials based on AI are more effective than others depending on how engaged the students are and the quality of the AI model used. However, the theory of generative AI can greatly improve the educational results in spite of these difficulties. In the future work, the research should be directed towards the improvement of the personalization methods using better adaptive learning models and the models that involve the multimodal AI. Thus, the enhancement of the interpretability of AI models through the creation of explainable AI algorithms could enhance the confidence of educators in the use of AI-created content. The ethical problem and its relation to privacy is a significant issue that must be tackled through the development of stringent ethical policies, enhancement of the security of data, and investigation of the consequences of AI-created content on student privacy and agency. [SEP] Justify:

Output: The text corroborates the claim by discussing how generative AI in education has the potential to create unique learning materials tailored for every student. It mentions that adapting content based on student data improves the learning system and potentially increases student motivation and outcomes. The text emphasizes the use of personalized resources and adaptive learning technologies to better meet individual student needs, which aligns perfectly with the claim regarding the role of AI in customizing educational content.


Input: Task: contrast the claim using the given text. Claim: There is no ethical concern in the collection of genetic data for personalized medicine. [SEP] Text: comparative drug effectiveness, pregnancy exposure outcomes, safety registries and long-term disease trends) In this way, computerized MS registries are set to form part of the future MS cloud computing and big data (Fig. 4). Fig. 4Profiling patients and collecting data. As part of the personalized medicine approach, MS patients should be characterized by a detailed clinical profiling which is the base of all long-term documentation. All patients should be documented during the course of the disease to understand treatment response, document relapses and disease progression as well as quantitative inflammatory and neurodegenerative magnetic resonance imaging (MRI) markers. Physician- and patient-centered parameters should be collected by intelligent software systems as MSDS software. MS big data can be used to analyze treatment response patterns and allow personalized treatments. Therefore, the available information (big data MS) of all included MS patients can assist in complex treatment decisions in futureFull size imageBig data analysis in MS: challenges and problemsComputational analysis of biological processes plays a key role in the transition to personalized MS treatment. et al. the following specific contributions of information technology to tailored therapy are crucial: (1) the ability to integrate genomic, molecular, and epigenetic data about each individual patient in a unified framework, (2) the capability to effectively analyze this information using complex queries and data mining methods, and (3) to apply computational procedures that predict the patient’s response to treatment based on his or her genomic make-up, epigenetic tendencies, and environmental data [9]. Big data analysis in MS raises several methodological issues that need to be addressed to succeed in clinical practice. Major points include the limitations of observational data, poor data quality, data inconsistency, poor data stability, patient privacy, patient consent, and other potential legal barriers. Many data sources have significant quality limitations. The results can be valid, stable, and clinically useful only if high-quality clinical data are inputted. A related issue is the lack of documentation standards in MS care, which exacerbates the inconsistency in different data sources. The potential threats to the validity of real world data from observational studies include both unmeasured confounding factors and treatment selection bias. [SEP] Justify:

Output: The text contrasts the claim by highlighting several ethical concerns related to the collection of genetic data for personalized medicine. It mentions 'patient privacy' and 'patient consent' as significant issues, indicating that there are ethical implications in the data collection process for personalized treatments. The discussion of 'methodological issues' and potential 'legal barriers' further suggests that ethical concerns are very much in play when dealing with genetic data.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: The survived cells were then recovered for an extra 48 h with the normal mTeSR medium before digoxin selection. To obtain digoxin-resistant cells, 1 µM of digoxin (Sigma, MO, US) was added on to the medium for 72 h with medium changes performed on a daily basis. The surviving cells were harvested for genomic DNA extraction. RFLP and TIDE(R) analysis for genome modification The genomic DNA of iPSCs was harvested using QuickExtract™ DNA extraction solution following the manufacturer’s instruction (). Each single cell colony or the whole population of cells in a 100 mm dish were harvested in 50 µL or 1 mL of QuickExtract reagent, respectively. Out-out PCR amplification was performed using Herculase II fusion DNA polymerase (Agilent, CA, US) with the following conditions: (95 °C for 5 min; 40×: 95 °C for 30 s, 60 °C for 30 s, 72 °C for 30 s; 72 °C for 5 min). PCR primers were located at least 100 bp outside of donor templates region to prevent amplifying donor template. Primers for each targeted locus are listed in Table S2. For RFLP analysis, PCR amplicons were purified via (Qiagen, MD, US), and 400 ng of purified amplicons were digested EcoRI or NruI, respectively. Digested DNA was then separated on a 2% agarose gel stained with ethidium bromide. For TIDE(R) analysis, purified PCR products were sequenced by Retrogen (CA, US), and the sequence signal of the experimental group was compared with wild-type or donor template as negative or reference control, respectively. TIDE(R) data analysis is described by Brinkman et al. (2018), and a free web tool is available at Immunostaining and cell viability assay Wild-type and ATP1A1Q118R∕N129D iPSCs were treated with 15. 625, 31. 25, 62. 5, 125, 250, 500, and 1,000 nM of digoxin and ouabain for 72 h in a 96-well plate coated with Matrigel (2 mg/ml) (Invitrogen, MA, US). [SEP] Justify:

Output: The text does not address the claim about CRISPR technology or its capability for precise editing of genomic sequences. Instead, it discusses processes related to genomic DNA extraction and PCR analysis, which are unrelated to CRISPR technology. Therefore, the text is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is used in EdTech to tailor content based on individual student needs. [SEP] Text: In order to optimize the impact of generative AI in education, the research needs to be expanded to larger samples of students and from diverse learning environments in order to confirm the results and determine possible strategies to incorporate generative AI in different educational settings. It is capable of increasing access of quality, customized education and revolutionizing the traditional models of education. With the advancement of AI technology especially in the generative AI, it is important to make sure that these technologies are implemented in the right manner to the benefit of students and educators alike while avoiding the worst possible scenarios. In addressing these areas, researchers and educators can strive for designing better, individualized, and ethical application of AI in learning process to enhance the educational system and the learners’ results. Conflicts of authors declare no conflicts of interest regarding the publication of this paper. 1409. 0473. [2] Branco, P. , Torgo, L. , & Ribeiro, R. P. (2017). A Survey of on Imbalanced Domains. ACM Computing Surveys, 49, 1-50. [3] Brown, P. F. , & Yarowsky, D. (2000). Processing with Small Feed-Forward Networks. of the 6th Conference on Learning (10. 1145/2939672. 2939785 [5] Devlin, J. , Chang, M. W. , Lee, K. , & Toutanova, K. (2018). Bert: Pre-Training of Transformers for Language Understanding. of NAACL-HLT 2019 (10. 1109/cvpr. 2016. 90 [8] Hinton, G. , Deng, L. , Yu, D. , Dahl, G. , Mohamed, A. , Jaitly, N. et al. (2012). Networks for in Speech Recognition: Views of Groups. 29, 82-97. [9] Kim, Y. (2014). Networks for Sentence Classification. of the 2014 Conference on in Processing (EMNLP) (10. 3115/v1/d14-1181 [10] Kingma, D. P. , & Ba, J. (2014). Adam: A Method for Stochastic Optimization. arXiv: 1412. 6980. [11] LeCun, Y. , Bengio, Y. , & Hinton, G. (2015). Deep Learning. [SEP] Justify:

Output: The text corroborates the claim by discussing how AI, particularly generative AI, has the capability to enhance the educational system by providing access to quality, customized education. It explains the importance of tailoring educational strategies to meet the individual needs of students and emphasizes the goal of creating better and individualized applications of AI in the learning process.


Input: Task: pass the claim using the given text. Claim: Genetically modified crops can have higher yields than traditional crops. [SEP] Text: These guidelines ensure comprehensive information to take decisions on scientifically sound risk assessments and on the precautionary approach in use of LMOs and/or GMOs. 2. 2 India’s initiative on biosafetyIn India, Ministry of Environment & Forests (MoEF) plays the role of the nodal ministry for implementation of and undertakes several initiatives to meet its obligations to the Protocol. It also organised various capacity building programmes to strengthen of the regulatory framework, particularly on transboundary movement of LMOs or genetically modified organisms, risk assessment and its management, training and human resource development and information sharing. Authorities for implementation of regulations and guidelines in the country [5](RDAC)of (RCGM)(GEAC)Committees (IBSC)(SBCC)Committees (DLC) Advertisement 3. Risk assessment of GM cropsRisk assessment identifies potential hazards and/or adverse impacts of GM crops or derived product on non-target organisms and/or environment. This involves a number of coordinated steps like risk identification, risk characterisation and risk categorisation. The first and foremost practice i. e. risk identification involves identification of risk or possible hazard to the non-target species or the environment, if any, associated with release and use of transgenic or GM crops and associated products. This is followed by overall characterisation of risk i. e. , whether its effect are direct or indirect, chronic or acute, immediate or delayed in action, etc. Finally, risk categorisation is done which involvves grouping of identified and well characterised risk under various categories viz. , negative health effects on target population; adverse effect on non-target population, the evolution of resistance or resurgence in the targeted pest/pathogen population, flow of transgene to another species, etc. In the process of risk assessment if a potential risk is identified the appropriate measures are taken for its management. 3. 1 Steps of risk assessment Advertisement 4. Risk management in use of GM cropsRisk management involves strategic techniques to reduce the adverse effect of GM crops and associated products on non-target species or environment and also to reduce the chances of development of resistance in target pest population. Several tactics viz. application of alternate or mix insecticides with different modes of action or use of refuge strategy could be effectively employed to minimise the risk of development of insecticidal resistance in insects. These techniques are also helpful in avoiding the problem of resurgence in insects. [SEP] Justify:

Output: The text discusses risk assessment and management of genetically modified (GM) crops but does not provide any information or evidence regarding crop yields, either supporting or contrasting with the claim about higher yields from genetically modified crops compared to traditional crops.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: A cell viability assay was performed using CellTiter-Glo® luminescent cell viability assay kit following the manufacturer’s instructions (Promega, WI, US). For nucleus immunostaining, cultured cells were fixed with 4% paraformaldehyde for 20 min following 0. 5% Triton X-100 treatment for 15 min. Cells were blocked with 3% bovine serum albumin in PBS for 30 min and incubated with DAPI (1 µg/ml) at room temperature for 30 min. Fluorescence intensity was assessed with ZOE™ Imager (Bio-rad, CA, US). Experimental and control groups were processed identically. Statistical analysis Results generated by cell viability assay, survival colonies counting, and TIDE(R) analysis were expressed as mean SD. Data were analyzed by ANOVA followed by Tukey’s or by Student’s t-test, as appropriate. Statistical significance was achieved at P <. 05. -Cas9 system to edit ATP1a1 locus Cardiac glycosides inhibit Na+/K+-ATPase pump activity by binding to the ATP1A1 subunit. The blockage leads to the accumulation of Ca2+ and causes cell apoptosis (Riganti et al. , 2011). Treschow et al. identified two amino acids in exon 4, Q118 and N129, that are responsible for the binding of cardiac glycosides to the Na+/K+-ATPase (Treschow et al. , 2007). With Q118R and N129D substitutions, cells became resistant to high doses of ouabain without affecting the function of the Na+/K+-ATPase (Treschow et al. , 2007). We, therefore, proposed to facilitate endogenous selection of targeted events in iPSCs using the -Cas9 system to introduce the Q118 and N129 mutations into ATP1A1. We designed a guide RNA targeting intron 4 of ATP1A1, with the PAM site twenty base pairs downstream of exon 4 (Fig. 1A). [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses on cell viability assays, statistical analysis, and the effects of cardiac glycosides on ATP1A1 without directly addressing CRISPR technology or its capabilities in genomic editing.


Input: Task: corroborate the claim using the given text. Claim: Crop rotation is a traditional practice that enhances soil fertility. [SEP] Text: According to Lal (2004), land management practices have the potential to enhance SOC accumulation, thereby easing the gaseous C load to the atmosphere and enriching the soil. The decomposition of SOM, and thus the loss of C from the soil through the conversion of SOC into the gaseous compounds of CO2 under aerobic conditions and CH4 under anaerobic conditions is promoted by an array of factors, such as location in the soil, fibrous composition of the substrate, nutrient content, soil texture, soil pH, moisture conditions, and soil temperature (Denman et al, 2004; Wolf and Snyder, 2003; Seiter and Horwath, 2004; Alvarez and Lavado, 1998; Bayer, 1996; Filcheva and Mitova, 2002). The SOM content present in the soil is a reflection of a long-term balance between additions and losses, thus the SOM content is greater when there is a large annual plant productivity rate and a low decomposition rate (Weil and Magdoff, 2004). Therefore, crops that produce large amounts of above-ground biomass have a greater contribution to the overall SOM content. The length of time SOC can be stored in the soil is controlled by the chemical composition of the biomass, which in turn determines the microbial breakdown potential of the substrate (Debusk et al. , 2001; Farquhar et al. , 2001). In relation to nutrient content, a large portion of the total nitrogen (TN) within soil (90 to 95%; Smith et al. , 1993) occurs along with SOC in the constituents of SOM, and the ratio of N available in the substrate directly affects the rate of microbial SOM decomposition (McGill and Cole, 1981; Weil and Magdoff, 2004). Thus, the C and N cycles are directly linked and the C cycle of an ecosystem and cannot be properly examined or modeled without giving reference to N cycling (McGill and Cole, 1981; Weil and Magdoff, 2004). Furthermore, the presence or absence of O2 plays an important role in the process dynamics and management responses of decomposition systems. Generally, an abundant O2 supply promotes rapid decomposition, whereas a deficiency in O2 results in a substantially lower decomposition rate (DeBusk et al. , 2001; Shaffer and Ma, 2001). Under extremely wet conditions, decomposition can become limited by O2 availability (Wolf and Snyder, 2003). [SEP] Justify:

Output: The text corroborates the claim by discussing how land management practices, particularly those that enhance soil organic carbon (SOC) accumulation, contribute to soil enrichment. The mention of the relationship between crop productivity and soil organic matter (SOM) supports the idea that practices like crop rotation, which may include varying crops that produce substantial biomass, can enhance soil fertility by improving SOC content. This relationship is evident as it states that crops producing large amounts of biomass contribute greatly to SOM, which is aligned with the claim about crop rotation enhancing soil fertility.


Input: Task: pass the claim using the given text. Claim: GMOs are universally accepted and supported worldwide. [SEP] Text: pects of religion (212) Religious institutions & organizations (205) Religious social & pastoral thought & activity (204) Religious & spiritual figures (1) Religious life & practice (3) Religious instruction (2) Spirituality & religious experience (2) Theology (2) Religion: general (141) History of religion (84) Philosophy of religion (49) Religious issues & debates (12) Religion & politics (6) Comparative religion (1) Interfaith relations (1) Judaism (16) Christianity (7) Christian Churches, denominations, groups (6) Roman Catholicism, Church (3) Protestantism & (2) (1) Ecumenism (1) Orthodox & Churches (1) Islam (7) Islam: branches & groups (1) Islamic groups: Sunni, Alsalaf (1) History & Archaeology (490) History (490) History: specific events & topics (292) Social & cultural history (257) Genocide & ethnic cleansing (17) (4) Invasion & occupation (9) War (6) Colonialism & imperialism (5) Industrialisation & industrial history (2) Maritime history (2) National liberation & independence, post-colonialism (2) Revolutions, uprisings, rebellions (1) European history (102) European history: medieval period, middle ages (17) European history: Reformation (6) European history: the Celts (1) European history: the Romans (1) History: theory & methods (78) Historical research: source documents (70) Historiography (4) Military history (54) Specific wars & campaigns (18) War (13) War (5) General & world history (10) History of the Americas (2) Ancient history (1) Archaeology (1) Archaeology by period region (1) Biography, Literature & Literary studies (305) Biography & non-fiction prose (196) Biography: general (167) Biography: historical, political & military (26) Autobiography: historical, political & military (1) Collected biographies (3) Biography: science, technology & medicine (2) Autobiography: general (1) Biography: literary (1) Biography: philosophy & social sciences (1) Biography: religious & spiritual (1) Diaries, letters & journals (147) Memoirs (4) Literary essays (1) Literature: history & criticism ( [SEP] Justify:

Output: The text is irrelevant to the claim about GMOs as it discusses various aspects of religion, history, biography, and literature without any mention of GMOs or their acceptance. Therefore, it does not corroborate or contrast the claim.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Seven days after electroporation, cells were treated with 1 µM of digoxin for 72 h. (B) The number of surviving iPSC colonies for each group was counted. The experiment was conducted in triplicate (n = 3). Data are shown as mean ± SD. Statistical differences were determined by ANOVA followed by Tukey’s test (*p <. 05). (n = 3, df = 4, F = 21. 17, p = 7. 19 × 10−5). Download full-size image DOI: 10. 7717/peerj. 9060/fig-3 Co-editing an independent locus by selecting for mutation of ATP1A1 in iPSdetermine if selecting digoxin-resistant cells by modifying ATP1a1 locus increases the efficiency of HDR-driven events at a second locus of interest, we used the -Cas9 system to co-target ATP1A1 and deoxyguanosine kinase (DGUOK) gene in iPSCs. genetic alteration that we chose to introduce results in a loss of function mutation, 170X, which is observed in patients with 3 (Hepatocerebral type) (MTDPS3); the patients with this syndrome commonly die from liver failure and suffer from progressive dysfunction of neural and muscular tissues (Mandel et al. , 2001). Two different Human iPSC lines (SV20 and K3) (Jing et al. , 2018; Si-Tayeb et al. , 2010; Yang et al. , 2015) were co-transfected with plasmids targeting ATP1A1 and DGUOK respectively, along with the linearized donor plasmids designed to introduce point mutations to each locus (Fig. 4A). Transfected cells were then cultured until colonies were observed. At this point, cells were treated with or without 1 µM of digoxin for 72 h. In order to calculate the efficiency of HDR, genomic DNA was collected and PCR using primers outside the targeted homology arms of DGUOK exon4 (out-out PCR) was performed to identify restriction fragment length polymorphisms (RFLP). Amplicons were also sequenced and the frequency of indels and targeted mutations determined using TIDE/TIDER analyses (Brinkman et al. , 2018). [SEP] Justify:

Output: The text does not directly address the claim about CRISPR technology. Instead, it focuses on a specific experimental protocol involving electroporation and treatment with digoxin in relation to iPSC colonies and does not provide information or evidence supporting or contradicting the precision of CRISPR technology in editing genomic sequences.


Input: Task: corroborate the claim using the given text. Claim: Crop rotation is a traditional practice that enhances soil fertility. [SEP] Text: Decreased decomposition rates result in greater accumulations of SOM in saturated soils, which essentially increase the amount of stored SOC and TN within the soil (DeBusk et al. , 2001). Since soil moisture conditions substantially influence the availability of O2, and consequently, the overall storage of SOC and the cycling of N in the soil, examining crop production systems that contain periods of both aerobic and anaerobic conditions is an important component in accurately estimating the global storage of SOC and TN in agricultural production systems. The most essential aspect of soil management practices is to maintain soil physical properties in a way that supports crop growth and ensures an adequate amount of the biomass gets recycled back to the soil to serve as a long-term organic nutrient source (Lal, 2007). There have been a number of studies examining the changes in SOC due to different production practices, such as crop variety, tillage, fertilization and climate. However, much of the previous research has been conducted in dryland cropping systems across the globe or in paddy-grown rice in Asia. Hence, there is a great deficiency in research pertaining to SOC and TN storage and cycling in other production systems, such as the dry-seeded, delayed-flood rice production system common in the main rice-production region of the United States. 1. 1. Research objectives and hypothesesThe objective of this study was to evaluate the long-term effects of rice-based crop rotations [i. e. , with corn (Zea mays L. ), soybean (Glycine max L. ), and winter wheat (Triticum aestivum L. )], tillage [conventional tillage (CT) and no-tillage (NT)], and soil fertility (optimal and sub-optimal) on SOC and TN contents, the partitioning of SOC and TN in SOM, and C:N soil ratios in the top 10 cm of a silt-loam soil after 11 years (1999 to 2010) of consistent management. Furthermore, SOC and TN contents were modeled for the 11-year period and into the future using the Century soil organic model (Parton et al. , 1987; NREL, 2006). [SEP] Justify:

Output: The text corroborates the claim by discussing the long-term effects of rice-based crop rotations on soil organic carbon (SOC) and total nitrogen (TN) content. It indicates that the research evaluates how different crop rotations, including corn, soybean, and winter wheat, alongside management practices such as tillage, influence soil properties that are essential for crop growth and fertility. This supports the idea that crop rotation is a traditional practice aimed at enhancing soil fertility by maintaining and improving soil nutrient levels.


Input: Task: pass the claim using the given text. Claim: GMOs are universally accepted and supported worldwide. [SEP] Text: Nelson: Commission for the International Sea-and for the for the Law of the Sea: 31 I. Introduction 31 II. Membership and Participation 31 III. Structure 32 IV. of Work 32 1. of Resolution II 32 2. of Draft Agreements, Regulations and Rules of Procedures for the Authority 37 3. of the Interests of Developing Land-based (1) 38 4. (2) 38 5. of the (3) 39 6. (4) 39 V. Commission and the Convention on the Law of the Sea 40 VI. Conclusion 44 Cristian Maquieira: Statement on the Implementation of Resolution II of the on the Law of the Sea by the for the International Sea-45 Rüdiger Wolfrum: Decision-making in the Council: and Comparison 59 I. Introduction 59 II. Composition and Decision-making in the Council according to 1. Composition 61 2. 65 III. Assessment and Conclusion 70 1. Evaluation and Assessment 70 2. Suggestions 72 Discussion 75 Hjalmar Thiel: Resulting from Deep Sea- 87 I. Principle 87 II. Problem: 88 III. 88 1. Impacts 89 2. Impacts 90 a) Disturbance from 90 b) Disturbance from 91 3. 92 IV. 93 1. 93 2. 94 V. 95 VI. 95 Literature 96 Discussion 97 Barbara Kwiatkowska/Etty R. Agoes: Archipelagic Waters: of 107 I. Introduction 107 II. 108 1. of and 108 2. Concerning Non-Self-Territories 110 3. Non-Concerning Non-112 4. Conforming to the Rules on 113 5. Conforming to the Rules on but 119 6. to the Rules on anti 119 7. the Rules on but those on 120 8. of the Philippines 122 9. of Indonesia 130 III. Evaluation 137 1. Definition of and Construction of 137 2. of the Archipelagic State's Competence 138 3. Right of 139 4. Right of 140 5. of - of Controversy 146 Discussion 152 Günther Jaenicke: for Sea-Bed Activities: A 165 Discussion 174 Klaus Dicke: Deciding upon the Budget of the United Nations: A Comparison 189 I. Introduction 189 II. "Budget" 192 1. Objective-of-192 2. 195 III. [SEP] Justify:

Output: The text provided is unrelated to the claim regarding GMOs. It lacks any mention or discussion of genetically modified organisms (GMOs) and instead contains headings and topics related to international law and sea conventions. Therefore, it does not provide any information to corroborate or contrast with the claim.