Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Following blue light illumination, AsLOV2 domain of membrane-targeted iLID induces a conformational change and exposes SsrA peptide, which forms hetero-dimer with Nano-fusions. Upon termination of light illumination, Nano-fusion dissociates from the SsrA with a half-life of <30 s (Guntas et al. , 2015). (B) Time-lapse images of RFP-Nano from a single z-section showing different patterns of cortical RFP-Nano recruitment in response to light illumination. A metaphase HeLa cell transiently expressing RFP-Nano (Addgene #60415) and Venus-iLID-caax (Addgene #60411) was illuminated with a single 488 nm laser pulse (250-msec exposure, 25 mW) at the indicated regions (circles with 1. 95 μm diameter). 1. (C) Genomic PCR showing clone genotype after Puromycin (Puro) selection. The clone No. 2 was used as a parent in the second, and third selection. (D) Live images of Mem-BFP-iand DIC in the clone No. 2 selected in (C). (E) Genomic PCR showing clone genotype after Neomycin (Neo) selection. All clones displayed a single 4. 4 kb band, indicating that the RFP-Nano (Neo) cassette was inserted in both NuMA1 gene loci. The clone No. four was used as a parent in the third selection. (F) Genomic PCR showing clone genotype after Hygromycin (Hygro) selection. DHC-SNAP (No. 8, and 9) and p150-SNAP (No. 15) display a single band, as expected, indicating that the SNAP (Hygro) cassette was inserted in both gene loci. The clone DHC-SNAP (No. 8) and p150-SNAP (No. 15) were used in this study. (G) Western blot probing for anti-NuMA, anti-DHC, anti-p150, anti-SNAP, and anti-α-tubulin (TUB, loading control) showing the bi-allelic insertion of the indicated tags. [SEP] Justify:

Output: The text does not relate to the claim regarding CRISPR technology. It discusses experimental procedures involving light illumination and various genetic selections but does not provide information about CRISPR or its abilities in genomic editing.


Input: Task: corroborate the claim using the given text. Claim: Digital resources provide access to educational materials in remote areas. [SEP] Text: Maternity care in the bush: using the Internet to provide educational resources to isolated practitioners 1 PhD, Midwifery * Lesley Barclay2 3 PhD, Professor of Development & * 1, 2 Insititute of 3 Centre for Midwifery and Family Health, University of 5 July 2006 : 8 February 2006 : 3 May 2006 : 5 July 2006. Maternity care in the bush: using the Internet to provide educational resources to isolated practitioners. Rural and 2006; 6: 559. © 2006 A licence to publish this material has been given to ARHEN, arhen. org. au Pubby download PDF Tweet this 1. In 2003, three (NT) Government sponsored reports, (including a 3 year strategic plan) were released, detailing the challenges of providing remote IT infrastructure2-4. Notable was the NT government's aim to provide broadband telecommunication infrastructure to all remote communities by 20083. In Australia, rural and remote area nurses have identified difficulties finding information on the internet5. Internationally, these difficulties led to the development of 'navigators': websites and software that guide people to information6. Examples of navigators include search engines such as Google? and databases such as Ebay? . Navigators often have a specialist focus6, such as the Cochrane Collaboration. There are three factors thought to affect the utility of navigators6. These are: 'reach', the number of people sharing the information; 'agency affiliation', meeting the needs of the target audience; and 'richness', delivering quality, reliable information6. Where agency affiliation and richness are focused on a particular field then reach does not have to be broad, but does need to be specific. These factors were used to develop and evaluate a process that enabled remote practitioners in the NT to access targeted information on maternity care. The researchers believed that a navigator could guide remote-area maternity service providers to a resource library specifically targeting their educational needs. Discussions with remote practitioners suggested an educational resource library would be valuable if it was easy to access and use. A survey of the Council of Nurses of Australia (CRANA) members in 2000 (102 respondents), found 48% required training in IT, with this need increasing with remoteness7. The quality of telecommunications was identified by 74% as affecting their ability to access the internet7. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of the Internet to provide educational resources specifically to isolated practitioners in remote areas. It highlights efforts to develop navigators and resource libraries that target the educational needs of remote-area maternity practitioners. The text also references the challenges faced by healthcare providers in remote areas, emphasizing the importance of accessible educational materials through digital means.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: PMC will actively support legislation, emerging guidance documents, policies, and initiatives at the FDA, which ensure personalized therapies and products reach patients in a timely and efficient manner. Modernizing coverage and payment policies. To ensure that patients have access to personalized therapies, PMC will continue to work with Congress and the Centers for Medicare and to ensure adequate payment rates and flexible coverage policies for personalized medicine products and therapies. Modernizing value assessment methodologies. The PMC notes that, by influencing decisions made by patients, providers, payers, and policymakers, value-based payment frameworks “could accelerate or undermine progress in personalized medicine. ” strategic plan calls for health technology assessments and value-based reimbursement that fully account for the value of personalized medicine. Among the studies cited in PMC's new research report is “Defining the of in Cancer Care,” which is now in progress. The report states, “The consistent use of biomarker testing faces implementation challenges related to insufficient awareness and education; a lack of recognition by payers and providers of the clinical value of testing; and outdated practices, policies, and procedures. ” PMC will develop recommendations to broaden the definition of the clinical utility of multiplex genomic testing in patient care. PMC notes that many organizations have emphasized the need to better understand the clinical utility of genomic profiling in cancer care, and “this project is PMC's answer to that call. ” This study will be done in two phases; will include a stakeholder roundtable event with discussions and case studies. A second study cited in the PMC's new research report is “Gaps in the Implementation of in Cancer Care. ” This study focuses on improving the integration of biomarker testing into clinical cancer care. A previous PMC report found that, although more than 30 percent of patients with non-small cell lung cancer (NSCLC) have tumors linked to specific driver mutations, only 65-75 percent of NSCLC patients with an actionable mutation—as determined by genomic testing—actually receive targeted therapies based upon testing results. And, as cited in the new PMC research report, a recent analysis by the firm Diaceutics, a diagnostics data analytics and implementation services company, estimated that 30 percent of U. S. cancer patients never receive targeted therapies that might benefit them. [SEP] Justify:

Output: The text contrasts the claim by emphasizing the ongoing challenges in the implementation of personalized medicine. It cites that despite the advancements in biomarker testing and genomic profiling, there are significant gaps in patient access and actual use of targeted therapies. For example, the text states, 'only 65-75 percent of NSCLC patients with an actionable mutation—as determined by genomic testing—actually receive targeted therapies based upon testing results' and '30 percent of U.S. cancer patients never receive targeted therapies that might benefit them.' This indicates that personalized medicine is not yet fully replacing general medications, and barriers still exist that prevent the complete shift away from traditional treatments.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Protein levels were not significantly affected by tagging with RFP-Nano and SNAP. (H) Western blot showing the efficiency of the RNAi-based depletion for LGN. Tubulin was used as a loading control. (I) Live fluorescent images of NuMA-RFP-Nano and DHC-SNAP. NuMA and DHC accumulate at the cell cortex during anaphase (Kiyomitsu and Cheeseman, 2013). (J) Quantification of cortical NuMA-RFP-Nano and DHC-SNAP signals around the polar cell cortex or light-illuminated region (n = 5). Error bars indicate SEM. Scale bars = 10 μm. Figure 1—figure supplement 2 Download asset Open asset Light-induced cortical targeting of NuMA is sufficient for dynein-dynactin recruitment and spindle pulling. (A) Live fluorescent images of NuMA-RFP-Nano (upper) and DHC-SNAP (lower) in the indicated conditions. Both NuMA-RFP-Nano and DHC-SNAP signals dissociated from the cell cortex following the termination of light illumination (t = 6:00), supporting that light-induced NuMA recruits dynein at the cell cortex. Unexpectedly, the displaced spindle gradually returned toward the center of the cell despite the fact that dynein was unable to accumulate at the distal cell cortex to generate opposing cortical pulling forces to center the spindle (t = 20:00), suggesting that additional mechanisms exist independently of cortical dynein to center the spindle, and explain why the spindle is roughly positioned in the center of the cell in LGN depleted cells (t = 0:00) (Kiyomitsu and Cheeseman, 2012) (B) Left: live fluorescent images of NuMA-RFP-Nano (upper) and DHC-SNAP (lower). Images on the right show a higher magnification of the indicated area. [SEP] Justify:

Output: The text does not provide any information about CRISPR technology or its ability to edit genomic sequences. Instead, it discusses live fluorescent imaging and observations related to protein interactions and cellular mechanics. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Digital resources provide access to educational materials in remote areas. [SEP] Text: In the same survey, 61% reported having a work-based email account, 44% accessed the internet at work and 57% had internet access at home7. Sixteen per cent had no internet access at all; reasons identified included decisions by management and problems with telephone lines or computers7. With government plans to roll out broadband, it seemed reasonable to investigate the internet as a vehicle for delivering educational support to remote practitioners. Many variables can influence the success of such a strategy and these were to be investigated. They included5: telecommunication infrastructure: hardware, speed, reliability, accessibility, cost, support and maintenance contextual factors: time available, management constraints, knowledge of its availability the human factor: comfort with the technology, education and training, motivation and interest in the resources and technology. aim was to establish and evaluate an internet-based resource library targeting the needs of remote-area maternity service providers. Research question What information do remote-area maternity service providers want to access from an internet based resource library and, if this is provided, what are the barriers and facilitators that influence its use? participatory action research (PAR) approach was used for this project with CRANA (a national organisation supporting the remote health workforce) agreeing to host the website. Planning was undertaken with a PAR team and action and evaluation were cyclical as the research team actively contributed to the development of the resource library. A 'navigator' was built and guided practitioners to the resource library which was evaluated against 'reach', 'agency affiliation' and 'richness', with the barriers and facilitators influencing its use described. The research approach is shown (Fig 1). Figure 1: Diagrammatic representation of the research. approval was granted by the University of Technology, Department, the in Darwin NT and the of the NT. the target group was important for recruitment and then promotion of the resource library. The target group included maternity service providers involved in the care of women living in remote areas, particularly in the NT. Exact figures for this target group (midwives and doctors with obstetrics training) are uncertain8 with the added complication that registered nurses and Aboriginal health workers, who together make up 95% of the remote workforce9, provide maternity care in some areas. [SEP] Justify:

Output: The text supports the claim by discussing the investigation of an internet-based resource library targeting remote-area maternity service providers. It emphasizes the potential of the internet as a medium for delivering educational support, indicating that digital resources are being specifically developed to improve access for practitioners in remote regions. The mention of a participatory action research approach aimed at understanding what information remote-area maternity service providers require further corroborates the idea that digital resources are intended to support educational needs in these locations.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: Biomarker analysis of postherpetic neuralgia patient skin biopsies demonstrates individual differences among receptors for neuroactive topical agents among keratinocytes, demonstrating novel potential mechanisms of action. 1. numerous chronic pain conditions, morphological and physiological alterations among primary small caliber nociceptor innervation and the peripheral tissues are detected, including potential interactions of intraepidermal nerve fibers (IENF) and epidermal keratinocytes. 2,5,9,22,30,53,66 Small fiber neuropathy (SFN) refers to a loss of small caliber IENF detected within the epidermis and has been demonstrated in several diverse conditions with pain as a chief complaint, including, for example, the neuropathic pain (NP) condition postherpetic neuralgia (PHN) and the largely described as nociplastic pain condition fibromyalgia. 2,3,24 The epidermis is the richly innervated outermost layer of skin that functions as a sensory transduction organ and includes a nociceptor population, and a β-endorphin–mediated cannabinoid receptor 2 (CB2)–activated inhibitory mechanism among the keratinocytes. 2,37,41,54,62 Although somewhat counterintuitive that a loss of nociceptive fibers would lead to enhanced chronic pain, accumulated evidence demonstrates additional peripheral mechanisms involved in the generation of nociceptor hyperexcitability, particularly signaling from cutaneous terminal structures and cells, including epidermal keratinocytes, dermal vasculature, adnexal organs, and/or immune (mast or Langerhans) cells, as means that damaged or remaining innervation becomes hyperactive and/or ectopically active. 2,13,15,37,48,66 Pathologies related to either the primary sensory endings and/or cutaneous terminal structures, such as epidermal keratinocytes, represent potential targets for topically applied compounded pharmaceuticals. 2,6,17,40,54,55,61 Peripheral inflammation is often a main culprit of pain and many efficacious analgesics target peripheral inflammatory mechanisms (eg, cyclooxygenase), while the most potent analgesics act via the central nervous system, through well-described mechanisms, particularly the opiate system. [SEP] Justify:

Output: The text contrasts the claim by discussing the continued relevance of general medications in managing chronic pain conditions. It highlights that, despite individual differences in receptor efficacy, numerous chronic pain conditions are addressed with general analgesics and mechanisms related to central nervous system actions. It suggests that while personalized medicine may provide novel approaches and targets, it does not eliminate the need for general medications as efficacious analgesics often act on broader mechanisms like peripheral inflammation and central pain processing.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: DHC-SNAP signals were initially observed along the cell cortex similarly to NuMA-RFP-Nano (t = 1:30), but were selectively diminished from the cell cortex in proximity to the spindle (t = 4:30), supporting our model that spindle-pole derived signals negatively regulate the cortical dynein-NuMA interaction in a distance dependent manner (Kiyomitsu and Cheeseman, 2012). Right: line scan showing the relative fluorescence intensity of cortical NuMA-RFP-Nano (upper) and DHC-SNAP (lower) around the cell cortex on the left at 4:30. Arrow indicates a decrease in DHC-SNAP signals near the spindle pole. (C) Live fluorescent images of NuMA-RFP-Nano (upper) and p150-SNAP (lower). Similarly to dynein, p150-SNAP was also recruited to the light illuminated region by NuMA-RFP-Nano (t = 2:00), but was subsequently excluded by the spindle proximity (t = 4:00). (D) Live fluorescent images of RFP-Nano (upper) and DHC-SNAP (lower) in LGN-depleted cells arrested with MG132. RFP-Nano was expressed from the Rosa 26 locus following Dox treatment (see Figure 4—figure supplement 1A–B and Figure 5—figure supplement 1B). (E) Left: live fluorescent images of NuMA-RFP-Nano (upper) and DHC-SNAP (lower) in a Gαi1 (1 + 2 + 3) depleted cell. Right: kymograph obtained from image sequences on the left. The spindle was displaced toward the light-illuminated region. (F) Western blot showing the efficiency of the RNAi-based depletions for Gαi-1. Tubulin was used as a loading control. An asterisk indicates non-specific bands recognized by the anti-Gαi-1 antibody. Scale bars = 10 μm. Figure 2 Download asset Open asset Light-induced cortical NuMA-dynein complex pulls on taxol-stabilized astral microtubules. (A) Fluorescent images of astral microtubules in fixed HCT116 cells treated with drugs as indicated. [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or genomic editing. Instead, it focuses on the dynamics of DHC-SNAP and NuMA-RFP-Nano during cellular processes, which is unrelated to CRISPR's editing capabilities.


Input: Task: corroborate the claim using the given text. Claim: Digital resources provide access to educational materials in remote areas. [SEP] Text: 03) In response, the report was placed on the website in PDF format, under the section entitled 'Reports of Interest'. Statistics were collected on the number of 'hits' to the resource library. All email (n = 166), questionnaires and field notes were imported into a qualitative analysis software program (ATLASti: ATLAS. ti Development GmbH; for data storage, management and retrieval. Descriptive analyses were undertaken with major themes that emerged from the data described and categorised. resource library, hosted on the CRANA website, went 'live' in November 2002 (www. crana. org. au - maternity care in the bush). The information was catalogued under separate sections: Clinical-Courses, Clinical-Antenatal, Clinical-Birth and Postnatal, Guidelines, Reports of Interest, 05. 03). In response, two clinical sections were placed on the site, one for antenatal care and one for birth and postnatal care, with a focus on the issues that are particularly pertinent in remote Australia (eg preterm labour). Table 2 is an example of how agency affiliation worked. Table 2: Reflection and action used to improve agency affiliation involves delivering relevant information, including reliability, security and bandwidth6. Again, the PAR process assisted with this, although some factors were beyond the control of the research: for example, bandwidth. Most of the comments received indicated that the target audience felt the information provided was: 'Contemporary, relevant reports and 03. 03). Feedback included statements such as: 'Women's health site is great for checking on management options out bush' (RAN, 03. 03) and: Have just visited the above site and it's great. Am looking forward to spending more time with the links. Last year I completed my Masters of Public Health. . . I am very interested in cultural safety issues. Is it possible to get more info at this stage? (RAN, 03. 03) Practitioners in leadership and education positions identified the site as a valuable resource enabling access to professional knowledge which could be further distributed to the remote based practitioners: I utilise the site prior to facilitating courses, for updated information, and if an inquiry comes from a RAN about a particular subject. I can either send the link or print it and send by snail mail. The links are good if I need to extend my search. It is on my 'favorites' list. [SEP] Justify:

Output: The text corroborates the claim by illustrating how the resource library hosted on the CRANA website offers valuable educational materials specifically targeted at issues pertinent to remote practitioners in Australia. It highlights that the information was categorized under relevant clinical sections and was identified as a significant resource for professionals in remote areas, enabling them to access updated information and educational content. For example, the feedback from practitioners emphasizes its utility in checking management options and staying informed, directly supporting the idea that digital resources facilitate access to education in underserved locations.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: 17,60,80 Therapeutic classes of actives often seen in topical compounds for NP include NMDA receptor antagonists, alpha-2 adrenergic receptor agonists, anticonvulsants, ion channel modulators, vasodilators, NSAIDs, muscle relaxants, opioids, cannabinoids, and others that can be concentrated locally in the periphery with potential reduction of systemic exposure. 6,40,55 Since our initial discovery of the opiate peptide beta-endorphin in epidermal keratinocytes in 2003, the role of keratinocytes in communicating between the environment and the IENF, particularly via the release of neural signaling mediators, has become widely recognized. 2,34,37,41,65,66 The epidermis is a vital sensory organ that functions as a polymodal nociceptive structure. 11,21,35 In particular, epidermal keratinocytes have been shown to express numerous mediators of nociceptor hyperexcitability in vitro and/or in vivo, including NMDA and AMPA glutamate receptors,13,49 voltage-gated calcium channels and sodium channels,20,78 alpha-adrenergic receptors,52 GABA receptors,21 the neuropeptide calcitonin gene-related peptide (CGRP),34 endothelin-1 (ET1) and the cognate receptors type A (endothelin receptor type A [ETA]) and type B (ETB),41 the transient receptor potential vanilloid 1 (TrpV1), and, as noted, the cannabinoid receptor 2 (CB2),19,33,76 among several others. Many of these various signaling family members have been used as drug targets for topical agents, and clear advantages exist when using compounded pharmacotherapy, including the personalized medicine principle and flexibility to be able to make adjustments based on patients' identified biomarkers and response. Presumptive druggable targets associated with nociceptor hyperactivity identified among cutaneous structures, such as epidermal keratinocytes, could provide novel avenues of treatment for PHN and other NP conditions, using currently available active pharmaceutical agents via targeted topical delivery. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that while personalized medicine can be advantageous, as highlighted in the statement 'clear advantages exist when using compounded pharmacotherapy, including the personalized medicine principle,' it does not suggest that general medications will be completely eliminated. Instead, it discusses the role of various drug targets and how they can be clinically relevant, implying that general medications still have a place in treatment. The phrase 'using currently available active pharmaceutical agents via targeted topical delivery' indicates that traditional medications remain important in conjunction with personalized approaches.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Cells were arrested at metaphase with MG132 for 1 hr, and DMSO/nocodazole or taxol were then added for 30 or 1 min, respectively. Images are maximally projected from 15 z-sections acquired using 0. 2 μm spacing. (B and C) Live fluorescent images of NuMA-RFP-Nano (upper) and DHC-SNAP (lower) treated with DMSO (B) or nocodazole (C). (D) Kymographs obtained from image sequences in (B) and (C) showing the movement of the spindle at 30 s intervals. (E) Pole-to-cortex distance for control (black, n = 5), and nocodazole-treated cells (blue or light-blue). Blue and light-blue graphs indicate immobile (n = 5/9) and partially mobile pools (n = 4/9), respectively. Error bars indicate SEM. (F and G) Live fluorescent images of NuMA-RFP-Nano (upper), and SiR-tubulin and SiR-DNA (Lukinavičius et al. , 2015) (lower), treated with DMSO (F) or taxol (G). DMSO and Taxol were added at −1:00, and light illumination began at 0:00, when SiR-tubulin images were selectively abolished by taxol treatment. (H) Kymographs obtained from image sequences in (F) and (G) at 30 s intervals. In taxol-treated cells, the spindle did not attach to the cell cortex as indicated with an asterisk, likely due to stabilized astral microtubules. (I) Pole-to-cortex distance for control (black, n = 4), and taxol-treated cells (red, n = 5). Error bars indicate SEM. Scale bars = 10 μm. Figure 3 with 1 supplement Download asset Open asset Dynein activity is required for spindle pulling, but light-induced cortical dynein targeting is not sufficient to pull on the spindle. (A) Schematic of experimental procedures. The FBS concentration in the culture medium was changed from 10 to 0. 5% at the 68 hr mark. DMSO or ciliobrevin D was added at the 69. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses experimental procedures involving cell treatment with various substances and their effects on the spindle apparatus, without mentioning CRISPR technology or genomic editing.


Input: Task: corroborate the claim using the given text. Claim: Digital resources provide access to educational materials in remote areas. [SEP] Text: (WHE, 08. 03) Thus, even if the remote practitioners did not have internet access they were still able to access the material, through the regional support positions. In contrast, some thought the site was 'a bit boring' visually. '. . . I hate the white spaces on the web, the front page is boring and needs to be more interesting, also you need road signs to know where to go' (WHE, 11. 02). Initially, lack of visually appealing graphics was intentional to hasten access, as use of high quality graphics affect opening and download speeds. Speed is thought to be an essential component of a usable website with 15 seconds recommended as a general guide for download times16. Some of the participants were using standard phone lines for internet access, resulting in very slow download speeds. Many of the documents on the library required PDF format which remained a problem for many users: '. . . the PDF files are very slow to download' (RANM, 07. 02). However, based on feedback, changes were made to improve the visual appearance of the site without markedly compromising speed. Other comments relating to richness included: 'Very user friendly' (RAN, 05. 03). Internet access Access issues are grouped under the headings: Telecommunications Infrastructure, Contextual Factors, and Human Factors5. Telecommunications infrastructure: Initially, most remote practitioners cited inadequate computer hardware. Nonetheless, IT provision was dynamic with improvements occurring during the research. Initially, one member of the research group did not have access when travelling in remote areas; however, by November 2003, she emailed that: '. . . the remote here have just got computers with internet access' (WHE, 11. 03). Other responses were less positive. For example, one remote community had been paying the lease on computers for 2 years but they had remained in their boxes. Staff unfamiliar with the technology had shown no interest in setting up the computers and had not been supported to do so. Some health centres had computers but no satellite dish, and others had satellites delivered but not installed: 'We've had the satellite dish on the roof for ages but it doesn't work yet' (RANM, 04. 03). Other reasons included buildings that were not strong enough to hold the satellites and trees needing to be cut down. These extra costs had not been budgeted for, and respondents claimed no-one was prepared to pay for these unforeseen requirements. [SEP] Justify:

Output: The text corroborates the claim by indicating that even when remote practitioners lacked internet access, they were still able to access educational materials through regional support positions. This suggests that digital resources have enabled access to educational materials, even in situations where direct digital access is limited. Furthermore, it discusses the evolution of technology access, exemplifying how improvements in telecommunications infrastructure have facilitated access for remote communities.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: Importantly, the degree of differential labeling of keratinocyte biomarkers across the small fiber innervation-similar enriched cohort identifies discreet subgroups of patients with PHN. This suggests that each of these 9 distinct molecular signaling systems may contribute to PHN pathology on an individual basis. Furthermore, these data highlight the essential need for assessing individual patient biomarkers to direct personalized and targeted efficacious therapy. The neurosignaling systems associated with each of the keratinocyte biomarkers have been shown to be involved in functional pain processing and also have specific compounds available for targeted pharmacologic manipulation. Specifically, the NMDA receptor can be inhibited by ketamine, the voltage-gated calcium ion channel CACNA1S can be inhibited by gabapentin, and the voltage-gated sodium channel Nav1. 6 can be inhibited by lidocaine. The alpha2A receptor can be activated by clonidine, and GABAB receptors can be activated by baclofen. Calcitonin gene-related peptide inhibitors have been developed and recently approved for treating migraine, although a topical CGRP antagonist is not yet available. The CB2 receptor can be activated by endocannabinoids and by exogenous cannabinoids (THC and CBD), and have recently been shown to be effective in animal models of chemotherapeutic-induced peripheral neuropathy (CIPN). 10,18,32,43,45 ETA can be activated by the endogenous molecule endothelin-1 and also by specific pharmacologic compounds. 41 As well, the TrpV1 receptor can be activated by capsaicin and modulated by CBD. 36,38,72 The use of any of these compounds alone or in combination may provide relief for individual patients; however, choosing the correct active ingredients to achieve that benefit remains based mostly upon the diagnosed conditions with limited other considerations. The current data demonstrate that not all similarly diagnosed patients will respond to the same mix of active ingredients and individual biomarker evaluations will greatly hasten the process of finding the correct combinations for each patient. As well, the effects of these compounds on keratinocyte sensory signaling mechanisms remain unclear. Keratinocyte CB2 receptor function may be indirectly regulated by exogenous cannabinoids, such as CBD and/or THC. Particularly, CBD, the major nonpsychoactive constituent of the plant C. sativa, has recently been incorporated in topical preparations. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that while personalized medicine is important for selecting specific therapies based on individual patient biomarkers, it does not suggest that general medications will be completely eliminated. It specifically states that choosing the correct active ingredients for personalized therapy remains based mostly upon diagnosed conditions, indicating that general medications still play a role in treatment—there is no complete substitution. Furthermore, the mention of various pharmacologic agents and their role in treating conditions further implies that general medications will continue to coexist with personalized approaches in medical practice.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: 5 hr mark and the cells were analyzed for 1 hr. (B and C) Live fluorescent images of NuMA-RFP-Nano (upper) and DHC-SNAP (lower) treated with DMSO (B) or ciliobrevin D (C). (D) Kymographs obtained from image sequences in (B) and (C) showing the movement of the spindle at 30 s intervals. (E) Cortical complexes formed by light-induced targeting of Nano-mCherry-DHC. (F) Left: live fluorescent images of Nano-mCherry-DHC (upper) and p150-SNAP (lower). Right: kymograph obtained from image sequences on the left. (G) Quantification of cortical Nano-mCherry-DHC and p150-SNAP signals around the light illuminated region (n = 6). Error bars indicate SEM. (H) Live fluorescent images of Nano-mCherry-DHC (upper) and NuMA-SNAP (lower). (I) Measurement of the pole-to-cortex distance (n = 10). Error bars indicate SEM. Scale bars = 10 μm. Figure 3—figure supplement 1 Download asset Open asset Generation of knock-in cell lines for the DHC and mitotic phenotypes caused by ciliobrevin D treatment. (A) Genomic PCR showing clone genotype after Neomycin (Neo) selection. Both clones display a single 5. 4 kb band, which indicates that the mAID-mClover-3FLAG (mACF) (Neo) cassette is inserted at both the DHC1 gene loci. Here, clone No. 1 was used. (B) Schematic of the experimental procedures. Cells were treated with RO-3306 and MG132 to synchronize at G2 and to arrest cells at metaphase, respectively. The FBS concentration in the culture medium was changed from 10 to 0. 5% at the 44 hr mark. Cells were treated with DMSO or ciliobrevin D at the 44 hr mark and analyzed for 1 hr from the 45 to the 46 hr mark. (C) Live fluorescent images of DNA (upper) and DHC-mACF (middle) in ciliobrevin D-treated cells showing the mitotic chromosome-misalignment phenotype. [SEP] Justify:

Output: The text does not address the claim related to CRISPR technology. Instead, it discusses experimental procedures and results related to live imaging and genetic analysis in cell lines but does not mention CRISPR or precise genomic editing.


Input: Task: corroborate the claim using the given text. Claim: Digital resources provide access to educational materials in remote areas. [SEP] Text: of professional competence is a key area of concern for health providers in remote areas who experience difficulty in accessing current research, guidelines and educational updates19-20. Barriers to providing education for remote practitioners are many, including the expense involved in travelling for education being prohibitive, and relief staff often unavailable. At the commencement of this research there was little known about the viability of providing education and training to remote practitioners via IT. This research has provided information in this area. Overall, the evaluation of the resource library was very positive. Practitioners in leadership and education positions identified it as a valuable resource enabling them to access professional knowledge, which could then be distributed to the remote based practitioners, who experienced difficulties with access themselves. Issues of access are still a major problem for potential users, despite anecdotal evidence suggesting recent improvements in remote telecommunications, and initiatives targeting remote communications21. Using PAR and involving the remote practitioners directly proved to be effective, as the agency affiliation of the resource was greatly strengthened through this approach. Feedback from the PAR team described the resource as contemporary, useful and relevant with one participant suggesting it was essential. The 'navigator' evaluation framework of reach, agency affiliation and richness, most often used in the business world, was also helpful in this setting. One of the research objectives was to identify the facilitators and barriers to accessing resources via the internet. Telecommunications infrastructure, contextual factors and the identified human factors all need better resourcing for the internet to achieve its potential in this setting. Hardware inadequacies, access difficulties, the lack of management support for staff to utilise the resource, and not being familiar with computers were all identified barriers. In some health centres, access and log-in decisions were made by the local manager, yet in other areas staff had been told the decisions were policy directives from the NT Department of Health and Community Services. The lack of management support was also an identified barrier in the CRANA survey conducted in 20007. This evaluation highlighted difficulties in determining who was ultimately responsible when technical or structural barriers prevented the hardware from working. This situation seemed to be exacerbated in a climate where the NT government is moving towards Aboriginal control of health services. Some communities had received telecommunication grants to provide satellites, sophisticated hardware and software. However, there is little funding for the education and training of staff in the use of equipment, or to assist in the transfer of existing health data onto new computer systems3. [SEP] Justify:

Output: The text corroborates the claim by discussing how digital resources, including a resource library, are seen as valuable by practitioners who experience difficulties accessing educational materials in remote areas. The text notes that health providers have issues with accessing current research and educational updates, and the resource library is highlighted as a means for practitioners in leadership positions to distribute professional knowledge to those in remote settings. This supports the idea that digital resources can enhance educational access in areas where traditional means are prohibitive.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: Baclofen has been used topically with variable benefit,1,39 and topical capsaicin has been used for some chronic pain conditions, particularly PHN,14,46,51,75 and both are associated with activity directly on nerve fibers. However, differential GABAB and/or TrpV1 keratinocyte biomarker function may be associated with the variable outcomes of topical use. Yet, the actions of these active ingredients on keratinocyte function(s) remain unknown. An examination of individual patient keratinocyte labeling reveals a differential profile of the 9 biomarkers among the enriched PHN cohort. This type of heterogeneous functional biomarker expression among the cohort likely underlies why PHN is a difficult-to-treat disease and why so many patients fail to achieve benefit from standard therapies. Compounding a personalized and targeted topical preparation would potentially be a more viable therapeutic approach. For example, one patient profile revealed significantly decreased Alpha2AR, CB2, and NMDAR2b keratinocyte labeling in the ipsilateral painful skin, suggesting that topical clonidine and THC might act to lower the algesic signals, whereas ketamine would likely not be a beneficial addition. By contrast, a different patient had significantly increased labeling of 7 of the 9 biomarkers. For that patient, targeting NMDAR with ketamine, Nav1. 6 with lidocaine, GABA with baclofen, and maybe the CGRP would likely be effective; however, the use of clonidine, THC, or gabapentin might exacerbate painful symptoms. A list of potentially effective topical regimen based from the keratinocyte biomarker profiles of each patient is presented (Fig. 4). Additionally, the cohort contained patients who might be representative of the treatment-resistant population, demonstrated with lowered CACNA1S and NMDAR labeling, and only small changes of the other biomarkers. This type of biomarker profile would likely limit the success of many common therapies. For this 20-patient PHN cohort with very similar clinical presentations, including pain VAS scores and ipsilateral IENF loss, using the same topical regimen for each patient would most likely be ineffective in many of them and would therefore not reach a statistically significant outcome for treatment efficacy. [SEP] Justify:

Output: The text contrasts the claim by discussing the challenges faced in treating PHN (Postherpetic Neuralgia) with standard therapies. It highlights that despite potential for personalized treatments based on biomarker profiles, many patients still fail to achieve benefit from these general therapies. The individualized approach does not suggest a complete elimination of general medications; instead, it illustrates the necessity to modify treatments according to specific patient profiles, indicating that general medications may still be required for some patients.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Cells labeled with the light- or dark-blue squares indicate mild or severe chromosome misalignment phenotypes, respectively. (D) Histogram showing the quantification of the chromosome misalignment phenotype. Note that ciliobrevin D worked under the 0. 5%, but not the 10% FBS condition, and induced severe phenotypes in a dose-dependent manner. (E) Schematic of the experimental procedures. Metaphase-arrested cells were treated with DMSO or ciliobrevin D at the 45. 5 hr mark under 0. 5% FBS culture condition and analyzed for 1 hr from the 45. 5 to the 46. 5 hr mark. (F) Live fluorescent images of DNA (upper, magenta), SiR-TUB (upper and middle, green), and DHC-mACF (bottom) in DMSO (left)- and ciliobrevin D (right)-treated cells. (G) Histogram showing abnormal spindle quantification following ciliobrevin D treatment. Note that the bipolar spindle structure was maintained for ~30 min even in the presence of ciliobrevin D and disrupted during the subsequent 30–60 min. (H) Genomic PCR showing the genotype of clones after Blasticidin (BSD) selection. Both clones display a single 2. 2 kb band, indicating that the Nano-mCherry (BSD) cassette was inserted at both DHC1 gene loci. The clone No. 1 was used as a parent in the third selection. (I) Genomic PCR showing the genotype of clones after Hygromycin (Hygro) selection. P150-SNAP (No. 10) and NuMA-SNAP (No. 7, 8) display a single band, as expected, indicating that the SNAP (Hygro) cassette was inserted at both gene loci. The clone p150-SNAP (No. 10) and NuMA-SNAP (No. 8) were used in this study. Figure 4 with 1 supplement Download asset Open asset A Spindly-like motif in NuMA is required for cortical dynein recruitment, but not sufficient for spindle pulling. (A) Cortical complexes formed by light-induced targeting of NuMA fragments fused with RFP-Nano. [SEP] Justify:

Output: The text is irrelevant to the claim as it focuses entirely on chromosome misalignment phenotypes, experimental procedures involving treatment with ciliobrevin D, and various genomic PCR results without any reference to CRISPR technology or genomic sequence editing. There is no indication or mention of CRISPR in the provided information.


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: > Vol. 15 No. 7, July 2024 to Needs () Yousif Binhammad1, Azzam Othman1, Laila Abuljadayel2, Mheiri3, Muna Alkaabi4, Mohammad Almarri5 1Department of. 2Department of Cybersecurity, Dar Al-Hekma University, Jeddah, Saudi Arabia. 3Department of. 4College of. 5Department of. DOI: 10. 4236/ce. 2024. 157091 234 Downloads 1,390 Views 1523. doi: 10. 4236/ce. 2024. 157091. 1. IntroductionThe education sector is no behind as the intelligentsia of AI enthusiasts march in their fortress of innovation. Generative AI, a sort of AI, is what is called the generated personalized learning content, which movable is according to the student’s needs and level. Demonstration on that analyzing data of students, for instance, learning style, performance reviews and the engagement level, generative AI will be empowered to personalize learning materials in accordance with the individual student’ strengths and learning habits. The offering of adaptive AI for individualized learning keeps one remarkable benefit that pupils will be able to manage and comprehend the content provided with appropriate difficulty according to the performance of learners (Brown & Yarowsky, 2000). The same as another example, the system may be able to generate easily changing reports with more difficult questions as students show ability and proficiency in a certain area, so they will be able to get the right level of support and challenge Generative AI is not only capable of re-shaping the traditional way of learning by means of customized lesson plans, but it also perfectly fits the students who differ by their personal p1. 1. BackgroundIndividualized learning is an educational model presuming teaching, pace, and learning atmosphere is geared towards individual students. It recognizes the existence of different types of learning styles and p1. 2. Research AimThe purpose of the study is to examine how generative AI could be employed to generate educational resources that are customized to meet the needs of personalized learning for students in education (LeCun et al. , 2015). 1. 3. Research ObjectivesTo conduct a literature review on the use of generative AI in education for personalized learning. To analyze case studies of educational institutions or organizations using generative AI for personalized learning. [SEP] Justify:

Output: The text corroborates the claim by discussing how generative AI is used to generate personalized learning content tailored to students' needs and levels. It explains that by analyzing data such as learning styles and performance reviews, AI can customize educational materials to align with individual strengths and learning habits, thereby supporting the premise that AI is employed in EdTech for individualized learning.


Input: Task: contrast the claim using the given text. Claim: Personalized medicine will completely eliminate the need for general medications. [SEP] Text: Perhaps, this is a fundamental issue with the data from a recent study demonstrating a limited effect of topical therapies, in so much as that study included patients with pain across a very wide and diverse population. 12 Despite the failure of compounded topical pain creams in that clinical trial, the authors agreed with the possibility that only specific pain conditions responded to the compounded cream that was administered to all patients. 12 Overall, there have not been consistent results from multiple independent clinical studies regarding the efficacy of compounded topical pain medications. 6,12,80 The heterogeneity of pain mechanisms have also been acknowledged by other researchers. The heterogeneity may underlie the difficulties in treating neuropathic pain using standard approaches; however, compounding using a personalized approach and flexibility should be able to overcome this barrier. The value of an extemporaneous compounding approach is in its capability to deliver potentially effective active ingredients that are specific to the individual patient-verified biomarkers by a topical route that mitigates the risk of systemic adverse reactions and allows for relatively simple therapeutic adjustment based on the patient's response. Another clinical implication brought about by this study is that biopsy profiling may provide a means to stratify patients and enhance clinical study design. Whether for clinical practice or for designing a clinical trial to evaluate a topical pain therapy, performing a skin punch biopsy and creating keratinocyte biomarker profiles before starting treatment will provide essential data and valuable guidance on regimen selection and patient stratification. However, we do not yet know how to correlate the levels of increased or decreased keratinocyte biomarker expression to the level of pain perception and a prediction of therapeutic outcomes. We also do not know whether targeting one pathway would affect the expression of other pathways, eventually affecting the choice of concurrent targeted drugs. Further studies are desired to answer these questions. Several limitations exist with the current study, including that only two 3-mm punch biopsies are being compared in each patient with PHN, each representing a very small fractional area of the overall ipsilateral and contralateral dermatome. Previous work on PHN biopsies has demonstrated a wide variability of innervation among the affected dermatome site compared with healthy control sites. It remains unknown how this rash-site innervation variability effects keratinocyte expression of various signaling mediators. [SEP] Justify:

Output: The text contrasts the claim by discussing the challenges and limitations of personalized medicine in the context of treating pain. It explains that while personalized approaches have potential benefits, particularly the ability to deliver specific active ingredients to individual patients, there remain significant uncertainties and variations that hinder their effectiveness. For instance, the text points out that the efficacy of compounded topical pain medications has not been consistent across multiple independent studies, and the complex nature of pain mechanisms makes it difficult to determine the best treatment. Furthermore, the text suggests that further studies are necessary to establish reliable connections between biomarkers and therapeutic outcomes, implying that personalized medicine may not completely replace general medications due to these complexities and unanswered questions.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: (B) Full-length NuMA and the tested NuMA truncation fragments. Globular domains at N- and C-terminal regions of NuMA are indicated in light-gray and gray, respectively. (C) A summary of the frequency of cortical dynein recruitment and spindle displacement by targeted constructs. 4—figure supplement 1I–J for details. (D) Amino acid sequence alignment of the Spindly-motif like region of NuMA proteins in H. Sapiens (NP_006176), R. norvegicus (NP_001094161), M. musculus (NP_598708), G. gallus (NP_001177854), X. laevis (NP_001081559), D. rerio (NP_001316910), and human Spindly (NP_001316568) and Hook3 (NP_115786) aligned by ClustalWS. The conserved L and E substituted by alanine are indicated with red triangles. (E) Lupas coils prediction (window 21). Spindly motif (purple) is commonly located at the C-terminal region of the coiled-coil, with 200 ~ 280 residues. (F) Live fluorescent images of NuMA (1-705) WT (upper) and SpM mutant (lower). DHC-SNAP images are shown to the right. (G–I) Left: live fluorescent images of NuMA constructs (upper) and DHC-SNAP (lower). Right: kymographs obtained from image sequences of DHC-SNAP on the left at 30 s intervals. Scale bars = 10 μm. Figure 4—figure supplement 1 Download asset Open asset The N-terminal region of NuMA is required for cortical dynein recruitment. (A) A schematic illustration of exogenous gene expression of Mem-BFP-iLID and NuMA-Nano fusions from the AAVS1 and Rosa 26 loci, respectively. Whereas Mem-BFP-iLID is stably expressed, NuMA-Nano fusions are conditionally expressed following the treatment with Doxycycline (Dox). The SNAP-tag was also inserted at the DHC1 gene loci. (B) Schematic of experimental procedures. [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology or genomic editing at all. It discusses various biological concepts and experimental methodologies related to NuMA proteins, dynein recruitment, and gene expression, none of which are related to the claims of CRISPR technology's precision in genome 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: To explore the potential benefits and challenges of using generative AI for personalized learning in education. To develop a framework for implementing generative AI in education for personalized learning. To validate the framework through expert feedback and pilot studies in educational settings. To provide recommendations for educators and policymakers on implementing generative AI for personalized learning in education. 2. Literature ReviewArtificial intelligence with the ability to generate (generative AI) is being pursued with a lot of vigor nowadays, and there is a possibility that its integration to educational settings could lead to the development of personalized learning. This paper investigates the latest approaches in the field of generative AI for the design of self-paced learning materials that meet the needs of each and every student. The review takes in account the applications, benefits, challenges and ethical issues of generative AI in education and highlights the foremost findings and existing knowledge gaps (Mikolov et al. , 2013). 2. 1. Evolution of models have a long history, starting with basic statistical algorithms and culminating with complex deep learning models that are based on an increase in the amount of computing power, the availability of data, and the development of algorithms. At first stages, n-gram-based models failed to render complicated linguistic peculiarities and coherent output. Recurrent neural networks and LSTM networks that capture long-range dependencies in text as well as generate contextually relevant output were the ground-breakers in the generative AI field that enabled neural network-based approaches. Yet, such models are still encountered with the difficulties of boring and monotonous language. architecture, firstly introduced in 2017, laid the foundation for the self-attention mechanism to play a role in the reweighting of the importance of different words in a sentence, and consequently, generated more contextually relevant texts. Therefore, the capability of models like GPT-2, GPT-3, as well as Llama-2 possessed by Meta, kept on improving significantly. The further development of generative AI units is a necessity that is driven by large-scale datasets, the growth of computing power, and algorithm improvements (Radford et al. , 2018). 2. 2. Applications of Generative AI in EducationThe role of AI applications within the framework of the education sector is diverse, and one of the areas is the development of individual learning materials with the help of the generative AI. [SEP] Justify:

Output: The text corroborates the claim by stating that 'AI applications within the framework of the education sector is diverse, and one of the areas is the development of individual learning materials with the help of the generative AI.' This indicates that AI is indeed being utilized to create personalized learning materials designed to meet the specific needs of each student.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: Close navigation menu 138. 138. Download citation file: Ris (Zotero) toolbar search Menu toolbar search search input Search input auto suggest filter your search : Personalized medicine (PM) aims to offer tailored health care to individuals on the basis of their genetic profile. This paper explores the types of behaviors and practices that citizens are expected to adopt under PM, examines whether such expectations are realistic, and proposes strategies that could support citizens in the adoption of these behaviors. Methods: Recent reports from national and international medical organizations and funders of PM are reviewed to investigate the types of behaviors and practices that citizens are expected to adopt under PM. These behaviors are examined in light of the current knowledge regarding citizen involvement in health care. Results: Under PM, citizens are expected to be much more educated, proactive, and engaged in their health care than under conventional medical models. Actualizing such behaviors and practices may, however, be difficult or even unattainable for some groups of citizens. Conclusions: Educating citizens in PM, as proposed in the reports, is important but may not suffice for the adoption of new behaviors and practices by a majority of citizens. Approaches taking into consideration the heterogeneity of backgrounds, abilities, and resources among citizens are needed and include modifying reimbursement and pricing mechanisms, diversifying research, and developing low-cost PM programs. Keywords: Personalized medicine, Ethics and society, Citizen behavior, Since the mapping of the human genome in 2003, enormous progress has been made in understanding molecular and genetic pathways underpinning human health and disease. The acquisition of new knowledge coupled with rapid developments within genetic sequencing and testing as well as plummeting costs of new technologies continually improve our potential to provide better health care. Genetic and genomic information can be used to unveil disease predisposition and onset in individuals much earlier and more accurately than previously possible, and an increasing number of therapies will target disease-specific molecules and biological pathways, rather than simply treating the symptoms of diseases [1]. The traditional one-size-fits-all approach to disease prevention, diagnosis, and treatment, which has proved to be inefficient, expensive, and sometimes even hazardous, is expected to be progressively replaced by a more individualized and tailor-made approach. This ‘personalization' of health care has captured worldwide attention, with various strategies under development to facilitate its realization. [SEP] Justify:

Output: The text contrasts the claim by acknowledging that while personalized medicine (PM) aims to provide tailored healthcare based on genetic profiles, it highlights the challenges faced by citizens in adopting PM behaviors. The conclusion states that educating citizens about PM may not be enough for widespread adoption, indicating that not all health conditions may be effectively treated with PM due to factors such as individual backgrounds, abilities, and resources. This suggests a limitation in the effectiveness of personalized medicine for all health conditions.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: LGN siRNA, Dox, and SiR-647 were used to deplete endogenous LGN, to induce expression of NuMA-Nano fusions, and to label endogenous DHC-SNAP, respectively. Cells were treated with RO-3306 and MG132 to synchronize at G2 and to arrest cells at metaphase, respectively. Cells were observed by microscopy 1 hr after the release from G2 arrest, and analyzed for 3 hr. (C) Left: the tested NuMA truncation fragments. Right: A summary of the cortical dynein recruitment. (D–G) Live fluorescent images of indicated NuMA constructs (upper) and DHC-SNAP (lower). NuMA (1-505) was sufficient to recruit dynein to the cell cortex, and both its N-terminal globular domain (aa: 1–213) and short coiled-coil region (aa: 414–505) were required for cortical dynein recruitment. Similar to NuMA (1-705) WT, NuMA (1-505), but not other truncated fragments, accumulated around spindle pole adjacent to light-illuminated region following cortical recruitment. (H) Merged images of NuMA(1-705)-RFP-Nano (magenta) and DHC-SNAP (green) from Figure 4F. NuMA(1-705)-RFP-Nano WT, but not 4A mutant, asymmetrically accumulates around the spindle pole, indicating that NuMA N-terminal fragments containing the Spindly motif are sufficient to recruit dynein-dynactin to the mitotic cell cortex, and likely to activate dynein’s motility, which in turn transports these NuMA fragments toward the spindle pole. (I) The definition of spindle displacement. For cases where Dmax (maximal spindle displacement distance) is longer than Dt=0 (starting pole-to-cortex distance)×1/2, the spindle is assessed as displaced. (J) Scatterplots of Dmax as a percentage of Dt=0 for each condition. Cells with displaced spindles are plotted to the right side of the red line, which indicates 50% of the spindle displacement distance. [SEP] Justify:

Output: The text does not address or provide any information related to CRISPR technology or the precise editing of genomic sequences. It focuses on experimental procedures involving LGN siRNA, NuMA fusions, and cell microscopy, which are irrelevant to the 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: Essentially, it enables the generation of formative assessments and quizzes in real-time, which change based on students’ performance. This ensures that the tasks presented to the students are challenging enough but not too difficult (Ruder, 2018). Syntrophically with the published study that illustrates numerous opportunities of the adaptive assessments in enhancing student learning outcomes, the current research investigates the application of generative AI in designing personalized assessments. This study builds upon the previous literature by exploring how the integration of generative AI with LMS affects the learners’ engagement and motivation (Silver et al. , 2016). 2. 3. GenerationAutomatic question generation (AQG) is a recently come up application of generative AI, that enables educators to build customized tests and quizzes for students who have different needs. Through natural language processing and machine learning approaches, AQG systems work with you to provide questions that are contextually pertinent and belong across various subjects and levels of difficulty. It facilitates a greater level of student engagement as well as learning achievements by providing formative and important assessments. In addition, it makes life easier because the process of creating assessments is automated and its quality is not compromised. AQG extends personalized learning by asking questions that cater to the unique needs of each learner. Nevertheless, issues of easily producing low-quality and single-minded questions as well as biases in AI systems still exist (Socher et al. , 2013). 2. 4. of Free-Format AnswersThe effective spelling change feature is one of the powerful usages of generative AI in education as it enables educators to make individualized corrections when response to free formation answers is required. This technology has the capability to handle written language and it uses of natural language processing and machine learning algorithms to analyze and present student responses, identifying whether the sentences that they have created are correct, complete and coherent. It has the power to provide items like immediate feedback, figure out subjects of weakness, and lessen the time when evaluating students’ works. Automated recognition systems can parse out common errors and wrong notions, and thus likewise they might direct students to the helpers who specialize on the very areas that need help. While these AI systems bring a number of benefits including increased efficiency, they may also pose issues of system accuracy and reliability, considering ethical issues like student privacy and data security. [SEP] Justify:

Output: The text corroborates the claim by describing how generative AI enables the creation of personalized assessments and quizzes that adapt to students' performance levels and individual needs. It emphasizes that Automated Question Generation (AQG) systems allow educators to create customized tests tailored to various subject areas and difficulty levels, thereby enhancing engagement and learning outcomes. This directly supports the claim that AI is employed in EdTech to customize learning experiences according to each student's requirements.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: For instance, precision medicine aims to create a new taxonomy of diseases based on molecular biology with the objective to improve disease classification and inform health-care treatment and decisions [2]. Stratified medicine aims to group patients based on their genetic risk of disease or response to therapy with the objective to offer treatment that specifically targets those groups [3]. Personalized medicine (PM) aims to use information about an individual's genotype to guide decisions regarding the prevention, diagnosis, and treatment of diseases [4]. These strategies work towards the common objective to provide ‘the right patient with the right drug at the right dose at the right time' [5]. The production, integration, and use of genetic and genomic information in health care requires significant changes in the way such care is organized and provided to individuals. Recent reports discussing precision medicine [2], stratified medicine [3], and PM [6,7,8,9] have highlighted the roles and actions that relevant stakeholders of PM should undertake to enable a smooth integration of genetic and genomic information into health care and, thus, facilitate the transition to a tailor-made approach to medicine, which we hereafter refer to as personalized medicine (PM). These reports (published by national and international medical organizations and funders) provide practical recommendations to researchers, health-care professionals, policy makers, health authorities, and pharmaceutical companies. For instance, researchers are encouraged to develop data management infrastructures to handle the growing amount of data produced from genetic sequencing, health-care suppliers are advised to reorganize their clinical services to enable the integration of genetic and molecular information in the electronic health records of patients, and pharmaceutical companies are encouraged to identify and qualify a range of new biomarkers that predict clinical response [9]. However, the successful integration of genetic and genomic information into health care also depends upon the actions of another central group of stakeholders, namely citizens. While many of the reports emphasize the importance of citizen engagement in PM and propose strategies to educate and engage citizens regarding new medical developments, they do not systematically provide recommendations for what citizens could do to enhance the realization of PM but rather describe the behaviors and actions that are important for individuals to adopt. In this paper, we scrutinize the content of these reports to identify the specific behaviors and practices that are targeted, examine obstacles that could prohibit many citizens to adopt these behaviors, and propose strategies that may facilitate such adoption. [SEP] Justify:

Output: The text contrasts the claim by addressing the limitations and challenges in the implementation of personalized medicine (PM). It highlights that, while PM aims to tailor treatments based on genetic information ('the right patient with the right drug at the right dose at the right time'), it also emphasizes the need for significant changes in healthcare organization and citizen engagement for effective integration. Furthermore, the text discusses obstacles to the adoption of personalized medicine practices among citizens, which suggests that not all health conditions may be effectively treated with PM due to these challenges.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: For NuMA fragments, all samples (except #2 and #11) show statistical difference (p<0. 05) when compared to control (#1) using the Mann-Whitney test. Purple lines indicate mean ±SD. 4C and Figure 5B for the number of cells. (K) Genomic PCR showing the genotype of clones after Blasticidin (BSD) selection. Both clones display a single 4. 6 kb band, indicating that the SNAP (BSD) cassette was inserted in both DHC1 gene loci. The clone No. 11 was used as a parent in the 3rd selection. (L) Genomic PCR showing the genotype of clones after Hygromycin (Hygro) selection. A 1. 6 kb band confirms the insertion of NuMA-RFP-Nano (Hygro) cassettes with different NuMA fragments at the Rosa 26 locus. The following clones were used; ΔNLS (#1: No. 7), 1–1700 (#2: No. 28), 1–705 (#3: No. 5), 1–705 4A (#4: No. 18). 214–705 (#5: No. 2), 1–505 (#6: No. 21), 1–413 (#7: No. 23), and 1–213 (#8: No. 8), Scale bars = 10 μm. Figure 5 with 1 supplement Download asset Open asset NuMA’s C-terminal microtubule-binding domains and central coiled-coil are required for spindle pulling. (A) Full-length NuMA and the tested NuMA truncation fragments. Microtubule binding domains (MTBDs) are indicated in green. (B) Summary of the frequency of cortical dynein recruitment, dot signal formation and spindle displacement by targeted constructs. Figure 4—figure supplement 1I–J for details. (C–E) Left: live fluorescent images of indicated NuMA constructs (upper) and DHC-SNAP (lower). Right: kymographs obtained from image sequences of DHC-SNAP on the left at 30 s intervals. (F) Live fluorescent images of NuMA Δex24-RFP-Nano (upper) and DHC-SNAP (lower). [SEP] Justify:

Output: The text does not address CRISPR technology or genomic sequence editing, focusing instead on the analysis of NuMA fragments and associated constructs in a biological context. 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: However, automated correction has the height of helping to transform student and marking assessment whereby speed and efficiency are the most common keywords (Vaswani et al. , 2017). 2. 5. for Teaching MaterialsNatural language processing generative AI is a good educational tool that can be easily used by a teacher to create bright and individual lessons. It is applied to assessing educational content and generating various teaching materials (for example, lesson plans and the learning goal in this way, students can be included in the process of teaching and learning which will make them interested and likely to grasp what has been taught; In addition, it became the basis for the diversity and learning materials that also reflected the diversity and experience of cultural background and focused on the use of this study also considers the issues related to the reliability and the absence of biases in the content created by AI, the aspect which has been investigated rather marginally in the existing literature (Xie et al. , 2017). 2. 6. Use of Generative AI in Technical FieldsGenerative AI has brought about dramatic changes in emerging fields like programming that empower students to produce and perceive learning materials in a completely different way. This channel can be used to create various exercises, provide explanations of code and create interactive simulations in order to remind the learning process (Zoph et al. , 2018). This aids students in mastering programming concepts and developing coding abilities. Thus, they will be able to easily implement the ideas and figure coding problems by themselves. In the areas like engineering and physics; generative AI could take the simulation of ideas to let the person conceptualize complex concepts in their areas that will facilitate the understanding of theoretical principles better. Not in all, it has increased the education level in technical activities into a more sense of grasp (Branco et al. , 2017). 2. 7. Challenges in AI in EducationGenerative AI in education is likely to interact with the system and change the model. Thus, it has advantages and disadvantages. The quality and correctness of generated content may be misinterpreted with untruth, leading to disinformation. Additionally, AI models trained on massive data sets must be bias-free to be credible in instructional materials. Data privacy and security challenges arise when generative artificial intelligence algorithms ask students for their data to generate personalised learning material. Data privacy and security in AI-based educational systems have been highlighted, but the current research provides a more comprehensive review of the ethical problems of generative AI in education. [SEP] Justify:

Output: The text corroborates the claim by discussing how generative AI can be used as an educational tool that helps create individualized lessons and teaching materials. It emphasizes the role of AI in assessing educational content and generating various resources, which aligns with tailoring content based on individual student needs. The text states that this process can engage students and enhance their learning experience, supporting the idea of AI's adaptability to meet specific educational demands.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: October 2013, we conducted an internet search using Google and the following search terms: [‘personalized medicine'] and/or [personalised medicine] and/or [‘stratified medicine'] and/or [‘precision medicine'] combined with [report] and [pdf] to identify publicly available reports discussing the realization of PM. Reports from national and international medical organizations and funders published between January 2008 and October 2013, written in English and providing recommendations for the adoption of PM, were selected. The reports were reviewed using a qualitative content analysis method [10] according to the following steps. First, the content in the reports that describes behaviors and/or practices of citizens and/or patients was identified, extracted, and compiled into a list of verbatim texts. Next, the substantive content of these texts was examined in order to code and categorize it according to the type of behavior and/or practice it describes. Then, the categories were further examined to identify overarching themes into which the specific types of behaviors and practices could be grouped. Each category of behavior and/or practice was then analyzed in light of current knowledge regarding citizen and/or patient involvement in health care to determine the extent to which citizens and/or patients may realistically adopt, wholly or partly, such behaviors and practices. Hurdles that may impede such adoption were identified and discussed, and potential strategies to overcome these challenges were proposed. publicly available reports were identified (table 1) [2,3,5,6,7,8,9,11,12,13,14,15,16,17,18,19,20,21]. Importantly, these reports do not make a clear distinction regarding when expectations apply to citizens in general or to patients in particular. All the reports use the term ‘patient' at least once to refer to the end users of PM. Eight reports either use the term ‘citizen' or a combination of ‘citizen' and ‘patient'. For instance, some reports emphasize the importance of patients sharing their data for research purposes [2,6,14], while others refer to citizens when describing this type of activity [7,21]. Similarly, some reports mention that patients will be involved in the decision-making processes regarding treatment [2,6,9,21], while other reports state that patients and citizens will be involved [7,21]. [SEP] Justify:

Output: The text contrasts the claim by detailing the findings from publicly available reports on personalized medicine (PM) that discuss the adoption and realization of PM in health care. It indicates that while PM can offer some benefits, the reports highlight limitations and hurdles in its adoption, as well as the involvement of citizens and patients, suggesting that not every health condition may be effectively treated with personalized medicine. This implies a more nuanced view that either acknowledges challenges in the application of PM or does not guarantee its effectiveness across all health conditions.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Expression level of NuMA Δex24-RFP-Nano was lower than that in (E), but the spindle was still displaced. (G) Left: live fluorescent images of NuMA (N + C ΔNLS)-RFP-Nano (upper) and DHC-SNAP (lower). Right: kymographs obtained from image sequences of DHC-SNAP on the left at 30 s intervals. (H) Enlarged images of NuMA (N + C ΔNLS)-RFP-Nano (upper) and DHC-SNAP (lower) at indicated times. (I) Live fluorescent images of NuMA-C-RFP-Nano (upper) and DHC-SNAP (lower). Scale bars = 10 μm. Figure 5—figure supplement 1 Download asset Open asset Light-induced targeting of exogenously expressed NuMA fragments lacking C-terminal MTBDs and central coiled-coil. (A) NuMA C-terminal fragment with known domains. 4. 1-binding domain (4. 1-BD) and microtubule binding domains (MTBDs) are indicated in light-blue and green, respectively. The amino acid numbers of NuMA conform to isoform 1 (aa: 1–2115; NP_006176). LGN binding domain (BD) (Zhu et al. , 2011) is indicated in red. NuMA C-terminal fragment containing MTBD1 (aa: 1811–1985, called NuMA-TIP) accumulates at microtubule tips, and remains associated with stalled and/or deploymerizing microtubules (Seldin et al. , 2016). (B) Genomic PCR showing the genotype of clones after Hygromycin (Hygro) selection. Arrows indicate a 1. 6- or 3. 2 kb band, which confirms the insertion of NuMA-RFP-Nano (Hygro) cassettes with different NuMA fragments at the Rosa 26 locus. [SEP] Justify:

Output: The text does not address the claim about CRISPR technology or its ability to edit genomic sequences. It focuses on the expression levels of specific protein fragments and their interactions with microtubules, which are unrelated to CRISPR technology.


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: This study also emphasises the necessity for ongoing research and development to overcome these difficulties and ensure ethical AI use in education (He et al. , 2016). 3. 3. 1. models of which GPT-3 is an example are leaders in the education sphere by boosting customization of learning resources. These models, powered by deep learning methods, can sufficiently handle this task with human-looking outputs depending on the prompt they get (Kim, 2014). These models, regarded as educational, can be used to construct various types of personalized instructional materials that are designed to meet the needs of the individual student. As an example, they can create diagnostic questions or paraphrase the source material and even make simulations while enhancing learning experiences (Brown & Yarowsky, 2000). 3. 2. Educational ContextA learning space involved factors that differentiate the impact of generative AI application in education. It includes the subject, grade level, and learning objectives. One way might be, say, mathematics, where generative AI can be employed to make individualized problem sets based on the learner’s skill level (Chen & Guestrin, 2016). In language arts, it may serve as a vehicle for producing writing activities grouped together by the students’ interests and skills. Additionally, the educational context refers to the role of instructors in providing the instructions for someone using computer-generated materials and feedback to students (Devlin et al. , 2018). 3. 3. Personalization TechniquesThe humanized learning process executable by AI allows personalization through different methods. This may involve using student assessment data to find out the areas where such students are strong and weak and adapting by personalizing their learning. Real-time feedback is also part of such a process. Personalization techniques can be customized by integrating students’ p3. 4. Pedagogical PrinciplesAn important part of teaching are the pedagogical principles that underpin generative AI in education to match instruction with the set educational standards and goals. This includes for instance thinking of how the content gives students the chance to be engaged, supports the formative assessing and encourages the ability to think critically. Moreover, about instructional principles it is stressed that AI-based materials be utilized as a supplement to and not a substitution for old-school teaching methods (Hinton et al. , 2012). 3. 5. [SEP] Justify:

Output: The text corroborates the claim by stating that AI models, such as GPT-3, are utilized to boost the customization of learning resources tailored to individual students. It describes how generative AI can create personalized instructional materials, diagnostic questions, and individualized problem sets based on learners' skill levels. This supports the notion that AI is indeed used in EdTech to meet the varied educational 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: This may reflect that PM, due to its proactive nature, will progressively blur the patient/non-patient dichotomy that has characterized traditional health-care models. For the purpose of our analysis, we use the term ‘citizen' when referring to citizens and patients; many of the behaviors and practices described in the reports do not require that the end users of PM are patients when they endorse the expected behaviors and practices. Table 1PM reports View largeOur review of the reports reveals that citizens are expected to adopt a range of new behaviors and practices in relation to their health care. These are grouped into three overarching themes as described below and summarized in table 2. Table 2Behaviors and practices expected of citizens as described in the reports View large(1) Expected to in are expected to increasingly participate in the decision-making process regarding prevention, diagnosis, and treatment [2,6,7,9,13,14,21]. For instance, they may discuss information about their individual genetic risk predisposition with their health-care provider and contribute to the design of tailor-made prevention strategies to reduce their risk of becoming ill [7,13,14,21]. One report mentions that they may also discuss the choice of genetic tests and therapeutic options [9]. To ensure that prevention strategies are efficient, citizens may regularly enrich and update their personal health information, including genetic risk predisposition information, through the use of technologies such as web-based interfaces, self-tracking systems, personal health records, smart phone applications, and biofeedback systems [6,7,9,13,14,21]. They may decide to voluntarily share information about their genetic predisposition with their relatives in order to increase the possibility that their relatives also take necessary measures to prevent disease onset [7,16]. Some reports foresee that groups of citizens will purchase services from direct-to-consumer genetic testing companies and seek help from their public health-care services to interpret the results of genetic tests [13,14]. Finally, one report assumes that citizens will endorse targeted treatment strategies and understand that access to conventional treatment may be restricted when no positive effect for the individual's specific genetic profile is documented [18]. (2) Expected to to the Citizens are expected to contribute many different types of data about themselves such as ‘-omics' data and imaging, clinical, environmental, behavioral, and socioeconomic data [2,6,7,16,17,21]. [SEP] Justify:

Output: The text contrasts the claim by suggesting that while personalized medicine (PM) allows for more tailored approaches in healthcare, it also indicates limitations. For instance, it mentions that access to conventional treatments may be restricted when there is no documented positive effect for an individual's specific genetic profile. This implies that personalized medicine does not guarantee effective treatment for every health condition, as some conditions may not have suitable tailored strategies or documented effectiveness based on individual genetic profiles.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: The following clones were used; 1–1895 (#9: No. 4), 1–1985 (#10: No. 19), Δex24 (#11: No. 17), N + C ΔNLS (#12: No. 4), NuMA-C (#13: No. 5), ΔNLS(5A-3) (#14: No. 4), and RFP-Nano (No. 18). (C) Live fluorescent images of NuMA(1–1985)-RFP-Nano (upper) and DHC-SNAP (lower). Whereas DHC was recruited to the cell cortex following light-induced NuMA(1–1985)-RFP-Nano targeting in 78. 6% of cells (n = 14), DHC was not detectable in the remaining 21. 4% of cells, in which NuMA(1–1985)-RFP-Nano fusion apparently aggregates at the cell cortex, suggesting that NuMA C-terminal fragment containing MTBD2 is also required to prevent hyper-clustering of NuMA. (D) Live fluorescent images of NuMA(N + C ΔNLS)-RFP-Nano (upper) and DHC-SNAP (lower). In 77% of cells (n = 13), DHC was recruited to the cell cortex following light-induced targeting of NuMA (N + C ΔNLS)-RFP-Nano, but not in the remaining 23% of the cells. Scale bars = 10 μm. Figure 6 with 1 supplement Download asset Open asset Clustering of the DDN complex by NuMA is critical for spindle pulling. (A) GFP-tagged NuMA C-terminal fragment and the tested NuMA mutant fragments. (B) Live fluorescent images of nocodazole-arrested HeLa cells expressing GFP-tagged NuMA-C 3A fragments. (C) Amino acid sequence alignment of the clustering domain of NuMA proteins aligned by ClustalWS. Accession numbers are indicated in Figure 4D. (D–E) Left: live fluorescent images of indicated NuMA constructs (upper) and DHC-SNAP (lower). Right: kymographs obtained from image sequences of DHC-SNAP on the left. [SEP] Justify:

Output: The text does not address the claim regarding CRISPR technology and its applications in genomic editing. Instead, it focuses on the experimental setup, use of various clones, and observations regarding the behavior of certain proteins in cells, which is unrelated to the topic 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: Ethical and Privacy ConsiderationsAlthough generative AI in education is exciting, decisions governing its usage need to be made to reconcile with the ethical and the privacy challenges. There are also some complexities that need to be taken into account, such as data protection, no bias in AI generated content and also good governance to make sure that AI is implemented well in educational settings. Besides, the fact that the instructors and the creators who design AI machines to personalize the learning process also assume the responsibility of identifying the possible ethical implications and making sure that the students are not going to be disfavored or discrimination because of the requirement of AI-based materials (Kingma & Ba, 2014). 3. 6. Evaluation and ImpactThe impact of AI in the development of personalized instructional materials is appraised with different parameters such as students’ performance outcomes, level of engagement, and satisfaction with quality of teaching. The role of AI in education is not limited to the teaching process only but it is also evaluated regarding educators’ workload, students’ inclination, and the learning outcomes in general. The calculations of these data give educators the opportunity to check the efficiency of AI created content and make deliberate choices about whether to use it in the educational establishment (LeCun et al. , 2015). 3. 7. Adopting educational strategies of generative AI is beset with numerous challenges like the requirement for proper school infrastructure and trained educators as well as gaining acceptance from various stakeholders. Teachers should also be mindful that AI-generated content forms an integral component of the curriculum and the current teaching procedures (Mikolov et al. , 2013). The best frameworks for integrating AI into education consists of starting with a few AI tools and progressing from there until the teachers are sufficiently experienced, offering training and support for educators, and evaluating the results of AI on students’ outcomes frequently. Largely, by giving solutions to the problems and following suit of the best practices, then educators will be able to tap into the maximum positive sides of AI in crafting individual learning materials (Pennington et al. , 2014). 4. Methodology4. 1. Research DesignThis research scrutinizes the use of a generative AI to build personalized learning content for students. An integrated-data approach will be used, a mixture of both the qualitative and quantitative methods. A survey will be initiated among educators and AI builders to be clear about their experiences and thoughts on the field of AI. [SEP] Justify:

Output: The text supports the claim by discussing the use of generative AI in education, specifically mentioning its role in building personalized learning content for students. It emphasizes that AI helps educators tailor educational materials according to individual student needs and acknowledges the evaluation of AI's impact on students' performance and engagement.


Input: Task: contrast the claim using the given text. Claim: Every health condition can be effectively treated with personalized medicine. [SEP] Text: data we reviewed reveal that citizens are expected to adopt a whole range of behaviors and practices considered to be critical for the realization of PM. Citizens are seen as proactive, engaged, educated, responsible, and contributing partners of PM. These knowledgeable, rational, and resourceful citizens not only engage in healthful behaviors by following early prevention strategies, participating in the decision-making process regarding their medical follow-up, and sharing their genetic information with relatives and public health authorities, they also actively contribute to the development of PM by, for instance, providing access to their health data, taking the initiative to produce more data to feed both their own health records and research databases, and participating in public debates to discuss the design and development of PM. Additionally, they actively seek to access more comprehensive information about their health by using the services of direct-to-consumer genetic testing companies and buying technological devices and applications to manage personal health information in real time. These new behaviors and practices represent a radical change in the role of citizens compared with the way citizens traditionally have been involved in their health care. This change echoes recent developments which encourage a move away from the rather paternalistic model, under which citizens are primarily passive recipients of health care, to a participatory model of health care under which citizens are responsible drivers of their health, contributors to the health-care system, and partners sharing decisions with health-care providers [25]. Although PM offers the opportunity for citizens to be more proactive and engaged in their own health care, there are several challenges towards the realization of such citizen engagement as described below. Challenges towards the Realization of in PM Citizens must have sufficient health literacy to be able to actively engage in their health care. However, such literacy is not widespread in the population. As an illustration, a recent comparative study on health literacy in 8 member states reports that nearly every second respondent has limited health literacy and that a majority of respondents find it easier to follow instructions from their health-care provider than to make their own decisions or judgments [26]. Empirical data show that individuals who receive information about their personal genetic risk predisposition often fail to interpret it, either overestimating or minimizing it [27], and may prefer more intuitive, experience-based types of evidence [28]. [SEP] Justify:

Output: The text contrasts the claim by highlighting that, although personalized medicine (PM) offers opportunities for individuals to become more proactive and engaged in their health care, there are significant challenges in realizing this citizen engagement. Specifically, it points to health literacy issues, noting that nearly half of respondents have limited health literacy and that many individuals struggle to interpret information about their genetic risks. This suggests that not every health condition can be treated effectively with personalized medicine if the population lacks the necessary understanding and engagement.


Input: Task: pass the claim using the given text. Claim: CRISPR technology allows for precise editing of genomic sequences. [SEP] Text: Asterisk in (D) indicates the duration in which one of the spindle poles moves away from the focal plane. Scale bars = 10 μm. Figure 6—figure supplement 1 Download asset Open asset Identification of a clustering domain on NuMA’s C-terminal region. (A) Live fluorescence images of nocodazole-arrested HeLa cells showing mCherry-NuMA-C 3A and PLCδ-PH-GFP, an indicator of PtdIns(4,5)P2 (Kotak et al. , 2014). NuMA-C 3A, but not PLCδ-PH, displays punctate signals. The localization of PLCδ-PH was not affected by the expression of mCherry-NuMA-C 3A. DNA was visualized with SiR-DNA. (B) Live fluorescence images of endogenous NuMA-mACF and 4. 1G-mCherry in HCT116 cells. NuMA-mACF, but not 4. 1G-mCherry, shows punctate signals during prometaphase. (C) Live fluorescent images of HeLa cells showing GFP-NuMA-C 3A (upper) and SiR-DNA/SiR-actin (middle/left) following cytochalasin-D treatment (right). The NuMA foci preferentially accumulated at actin-poor cortical regions (left), and still localized following the disruption of actin polymerization (right). (D) GFP-tagged NuMA C-terminal fragment and the tested NuMA mutant fragments. 5A mutation sites are indicated in red. 3A mutation sites for CDK phosphorylation are shown in black AAA. (E) Amino acid sequence alignment of the 1700–1828 aa region of NuMA proteins aligned by ClustalWS. Highly conserved 5A mutation sites (5A-1 to 5A-4) are indicated by red triangles. (F) Live fluorescent images of nocodazole-arrested HeLa cells expressing GFP-tagged NuMA-C 3A fragments. NuMA C3 fragment (aa: 1990–2115) is sufficenet for cortical localization. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses live fluorescence imaging of cells and various experiments with NuMA proteins, without any mention of CRISPR technology 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: Study is not limited to AI models, their technical components, design processes, and ethical issues of AI usage in education. The quantitative one will be addressing student performance data’s analysis of the consequence of smart learning materials on learning outcomes. An evaluation of different AI models, of which the best performing one will be selected, is part of this project. Ethical standards will be maintained by the researcher following informed consent being obtained and confidentiality and privacy will be kept throughout the process (Radford et al. , 2018). 4. 2. ParticipantsGenerative AI will be tested on student-specific learning materials with 20 teachers and developers from diverse fields. Saturation was used to determine sample size when no new themes or insights emerged from successive interviews. The findings may be limited by the sample size, but it provides valuable insights into educators’ and AI developers’ perspectives. AI designers debate technology, design, and ethics while participants share their real-life experiences, thoughts, and difficulties. Conclusions will assist integrate AI in education, help students grasp personalised learning benefits and downsides, and help design customised resources (Ruder, 2018). 4. 3. Data CollectionThe course content variants were evaluated based on the overall experience and understanding of the material presented in each lesson. The role-playing teaching approach was found to be more effective than traditional methods, making the lessons more memorable. The course’s teaching style was recommended for future studies. If given the choice, the role-based approach would be the one for all lessons. A specific concept or lesson from the course stayed with the student. The role-based approach was deemed more or less effective than traditional methods. If given the option, the student would choose this style for future courses. The role-based teaching approach had long-term effects on the student’s learning experience (Brown & Yarowsky, 2000) (Table 1). Table 1. The student’s usage data on the LMS revealed features such as CS, WA, and BM, which correspond to computer scientists, Wednesday Addams, and Batman respectively as shown in Table 1: (Chen & Guestrin, 2016). [SEP] Justify:

Output: The text corroborates the claim by discussing the role of AI in creating personalized learning experiences. It mentions that 'Generative AI will be tested on student-specific learning materials,' indicating that AI is utilized to tailor educational content. Additionally, the text reflects on the evaluation of various AI models and their effectiveness in addressing students' learning needs, supporting the claim about AI's role in EdTech.