Abstract: Introduction and aim: Liver disease is associated with obesity, diabetes, and steatotic liver, aside from viral causes and alcohol consumption. Likewise, chronic kidney disease shares metabolic risk factors and a viral etiology with liver disease, contributing to its development and accelerated progression. The clinical data for both pathologies is very similar, which makes early identification of liver damage difficult when they overlap. The aim of this study was to identify chronic liver disease using the fibrosis-4 index (FIB4) in end-stage renal disease undergoing hemodialysis patients, also describing etiology and biochemical variables. Patients and Methods: The study was realized at a secondary-level referral hospital for hemodialysis of the Mexican Social Security Institute in Northeast Mexico. Results: All patients with end-stage renal disease undergoing hemodialysis between 2017 and 2019 were included. Of the 362 patients evaluated, 56.6% were men with an average age of 58 years. The main etiology attributable to chronic kidney disease was hypertension in 92.8%, followed by type 2 diabetes in 71.8%, primary glomerulopathies in 6.9%, and hepatitis C and human immunodeficiency viruses in 0.3% each. The time in hemodialysis was 19 months. Anemia was identified in 93%. The risk of liver fibrosis was identified at 29.5%, and of these, 8% had a FIB4 > 2.67, indicating advanced liver fibrosis. Conclusions: The FIB4 is an accessible and useful method for identifying the risk of liver fibrosis in end-stage renal disease patients undergoing hemodialysis and can be used as an initial tool for assessing liver disease.

Abstract: The endocannabinoid system (ECS) has been extensively mapped at the level of receptors, ligands, enzymes, and signaling pathways, forming a detailed component inventory of a major homeostatic network. However, prevailing ECS models largely omit the nutritional substrates required to sustain ligand synthesis, membrane composition, signaling capacity, and regenerative function, leaving the system operationally incomplete from a systems-biology perspective. This Hypothesis identifies this gap by integrating evidence from nutritional biochemistry, lipid metabolism, and regenerative physiology, and argues that inclusion of dietary inputs is necessary to advance toward a nutritionally complete model of the ECS.By reframing the ECS as a metabolically sustained regulatory network rather than a purely signaling system, this framework has implications for understanding resilience, regeneration, and system failure under chronic stress, nutritional insufficiency, and environmental disruption. This synthesis is intended as a hypothesis-generating foundation to guide future experimental and clinical investigation.

Abstract: This scoping review represents the first concerning 2020–2025, peer-reviewed publications to investigate possible relationships among burnout, nutrition, and nutrition/food literacy during and following the COVID-19 pandemic. 9 January 2026 searches were of the keywords (burnout OR job stress) AND (nutrition OR diet OR eating pattern OR food intake) AND (nutrition literacy OR food labeling) AND (food literacy OR health literacy). Eight databases were searched (CINAHL Plus, Google Scholar, JSTOR, OVID, PubMed, Science Direct, Scopus, Web of Science). With 160 returns, the included reports from these searches were from Google Scholar alone (n = 6). The addition of four relevant reports from the 3 June 2025 searches of “burnout AND nutrition AND (nutrition literacy OR food literacy)” increased the included studies to 10. Although 2020 was the lower date limit, publication of the results was between 2023 and 2025. The finding is that research con-ducted during this period reports co-occurring issues of burnout, nutrition, and nutrition/food literacy in specific populations. The primary discovery is that assessing the relationships among these terms was not the aim of the included studies. This lack of dedicated research on this topic presents an opportunity for burnout and nutrition re-searchers to investigate these relationships intentionally.

Abstract: Background: COVID-19 severity shows marked interindividual variability, suggesting a role for host genetic factors. Polymorphisms in genes involved in the renin–angiotensin system and inflammatory response, such as the angiotensin-converting enzyme (ACE) and the tumor nrecorsis factor-alpha (TNF-α), have been proposed as potential modulators of disease severity. Objectives: To evaluate the association between the ACE I/D (rs4646994) and TNF-α −308 G/A (rs1800629) polymorphisms and COVID-19 severity in a Mexican population. Methods: A total of 236 individuals with RT-PCR–confirmed SARS-CoV-2 infection were included. Patients were classified as hospitalized (severe, n = 155) or non-hospitalized (asymptomatic–mild, n = 81). Genotyping was performed by PCR–RFLP. Genotype distributions were analyzed using χ² tests under dominant and recessive genetic models, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: The ACE I/D polymorphism showed a significant association with COVID-19 severity. Carriers of the I allele (ID + II) had a higher risk of hospitalization compared with DD homozygotes (OR = 2.78, 95% CI: 1.53–5.06, p = 0.001). Sex-stratified analysis revealed that this association was significant only in male patients. No significant association was observed between the TNF-α-308 G/A polymorphism and disease severity. Conclusions: The ACE I/D polymorphism is associated with COVID-19 severity in a Mexican population, with a stronger effect observed in males. These findings underscore the relevance of host genetic background and sex-specific effects in COVID-19 outcomes. Further studies including larger cohorts, healthy controls, and multivariable analyses are required to confirm these associations.

Abstract: Background. The factors driving Coronavirus disease 2019 (COVID-19) severity and its long-term respiratory sequelae remain poorly understood. This study evaluates whether baseline lung function (LF) influences COVID-related clinical outcomes, mortality, and post-infection LF decline. Methods. Data from 602 participants in the Prospective Urban Rural Epidemiology (PURE)-Colombia study were analyzed. Among these, 200 with con-firmed SARS-CoV-2 infection and 402 controls (65% women; 68% aged ≥60 years). All underwent baseline spirometry prior to 2010 and follow-up testing 1-40 months post-recovery. Among infected individuals, 51 (26%) died. Spirometric parameters Forced Expiratory Volume in 1 Second (FEV1), Forced Vital Capacity (FVC), and Peak Expiratory Flow (PEF) were compared using paired t-tests and Cohen's d. Non-parametric data were compared using Wilcoxon s (z statistic). Results. Compared to baseline LF, hospitalized COVID-19 patients showed significant declines in follow-up LF: FEV1 (2.84 vs 2.34 liters; p=0.002), FVC (3.01 vs 2.53 liters; p=0.006), and PEF (399 vs 328 liters; p=0.001). Non-hospitalized COVID-19 cases showed a non-significant downward trend, while con-trols maintained stable LF. Risk factors for post-COVID FEV1 < 80% predicted included hospitalization, elevated waist-to-hip ratio, and incomplete or absent COVID-19 vaccina-tion. Moderate-to-high physical activity was protective. Post-COVID PEF< 80% predicted was associated with female sex, diabetes mellitus, and subsidized healthcare enrollment. Mortality risk was elevated among individuals with low baseline LF, age>65, male sex, hypertension, obesity, low physical activity, and reduced handgrip strength. Discussion. Significant LF decline was observed in hospitalized COVID-19 patients, with minimal changes in outpatients and controls. Identifying clinical and demographic predictors of post-COVID LF impairment may inform targeted interventions to mitigate long-term pulmonary complications.

Abstract: Objective of the study: This study utilized Latent Profile Analysis (LPA) to identify distinct personality profiles in a sample of 523 adults with Substance Use Disorder (SUD) from Punjab, Pakistan. Methodology: Using the NEO-120-IPIP inventory, a statistically optimal four-profile solution demonstrated an excellent model fit (Entropy = 0.875). One-way ANOVA confirmed highly significant differences between profiles across all five personality domains (p < 0.001), with particularly large effect sizes for Conscientiousness (η² = 0.75) and Agreeableness (η² = 0.55). Results: The derived profiles were labeled as: (1) Conscious-Warrior (high neuroticism and conscientiousness); (2) Socially Expressive (high extraversion, lower agreeableness); (3) Highly Expressive and Emotionally Intense (extremely high extraversion, neuroticism, openness); and (4) Agreeable-Achiever (high conscientiousness and extraversion). These results reveal significant personality heterogeneity within the SUD population. Conclusions: The findings highlight the clinical utility of person-centered approaches for culturally informed assessment, individualized treatment planning, and targeted relapse prevention strategies.

Abstract: Large language models have demonstrated remarkable capabilities across diverse reasoning tasks, yet their performance on algorithmic reasoning remains limited. To handle this limitation, we propose PRIME (Policy-Reinforced Iterative Multi-agent Execution), a framework comprising three specialized agents, an executor for step-by-step reasoning, a verifier for constraint checking, and a coordinator for backtracking control, optimized through group relative policy optimization. For comprehensive evaluation, we introduce PRIME-Bench, the largest algorithmic reasoning benchmark to date, comprising 86 tasks across 12 categories with 51,600 instances. Tasks span sorting algorithms, graph and tree structures, automata and state machines, symbolic reasoning, and constraint-based puzzles, with execution traces reaching over one million steps. Compared to baseline approach, PRIME improves average accuracy from 26.8% to 93.8%, a 250% relative gain. The largest improvements occur on tasks requiring sustained state tracking, with Turing machine simulation improving from 9% to 92% and long division from 16% to 94%. Ablation studies identify iterative verification as the primary contributor, preventing the error propagation that causes baseline approaches to fail catastrophically. Analysis across model scales (8B–120B parameters) reveals that smaller models benefit disproportionately, achieving accuracy comparable to models 8× larger.

Abstract: Background: Fungal symbionts are critical for host plant survival but are vulnerable to abiotic stresses such as low temperature, which limits their agricultural utility. Armillaria mellea is an essential fungal partner for the cultivation of the valuable medicinal orchid Gastrodia elata (G. elata). Enhancing its cold tolerance is a key step toward stabilizing G. elata production. Methods: Based on G. elata transcriptome data, a manganese superoxide dismutase gene (GeSOD7) was identified and heterologously expressed in Escherichia coli for enzymatic characterization. The gene was then overexpressed in A. mellea via Agrobacterium tumefaciens-mediated transformation. Transgenic and wild-type strains were subjected to cold stress (13 °C for 45 days), after which physiological, biochemical, and molecular responses were analyzed. Results: Recombinant GeSOD7 showed optimal activity at pH 6.0 and 60 °C, with inhibition under high concentrations of metal ions, especially Mn2+ and Cu2+. Overexpression of GeSOD7 in A. mellea significantly improved hyphal growth and fresh weight under cold stress. Transgenic strains exhibited higher activities of catalase and glutathione peroxidase, increased accumulation of glutathione and proline, and reduced levels of hydrogen peroxide and malondialdehyde. Expression of genes involved in glutathione synthesis and peroxide detoxification was coordinately upregulated. Conclusions: This study demonstrates that heterologous expression of a plant-derived Mn-SOD can effectively enhance the cold stress tolerance of a symbiotic fungus by boosting its enzymatic and non-enzymatic antioxidant systems. These findings provide a novel genetic strategy for improving stress resilience in agriculturally important fungi and contribute to the sustainable cultivation of G. elata.

Abstract: We reviewed the recent fire regimes in the semi-arid savannas of Etosha National Park and adjacent areas in northern Namibia using MODIS satellite imagery from 2001 – 2025 across gradients of mean annual rainfall (200 – 500 mm), land ownership, and vegetation types. Fires were highly seasonal, concentrated in the two driest months of the year (September and October). The average fire return period over 25 years was 6.9 years in Etosha National Park, but more than four times greater (31.8 years) on adjacent freehold farms. The proportion of the area burned annually ranged from zero to over 30% and the fire regime was dominated by a few episodic but extreme fire events. Some findings were counter-intuitive in that certain vegetation types in areas of low mean annual rainfall (< 300 mm) burned frequently (fire return period 4.3 years) while others experienced infrequent fires (fire return periods 34 – 206 years) in higher rainfall areas (> 400 mm). Current fire management practices have attempted to reconstruct natural fire regimes and are not based on ecological understanding, and further research, based on monitoring of dynamic interactions between rainfall, fuel accumulation, levels of herbivory and the extent of fires are needed to explain these findings.

Abstract: Background and Objectives: Communication gaps contribute substantially to anxiety, depression, and post-traumatic stress disorder (PTSD) among relatives of critically ill patients. This study evaluated whether supplementing routine bedside meetings with a concise, co-designed informational brochure was associated with reduced psychological distress and improved satisfaction among family members in the intensive care unit (ICU). Materials and Methods: We conducted a single-centre prospective before–after observational study in a mixed medical–surgical ICU in Naples, Italy. Relatives of adult patients with an ICU length of stay &gt;72 h completed the Hospital Anxiety and Depression Scale (HADS) and the Short Screening Scale for PTSD (SSS-PTSD) at ICU discharge. The pre-intervention phase enrolled 12 relatives (May–September 2018); following a co-design and staff training period, the post-intervention phase enrolled 23 relatives (April–October 2019). Primary outcomes were the prevalence of anxiety (HADS-A ≥8), depression (HADS-D ≥8), and probable PTSD (SSS-PTSD ≥4). Groups were compared using Fisher’s exact test and the Mann–Whitney U test. Results: Anxiety remained highly prevalent (100% pre vs. 95.7% post; p = 1.00). Depression severity decreased, with median HADS-D scores declining from 13 (IQR 10–18) to 9 (IQR 7–12) (p = 0.021), while the prevalence of HADS-D ≥8 was lower post-intervention (91.7% vs. 73.9%; p = 0.38). The prevalence of probable PTSD was numerically reduced from 58.3% to 30.4% (p = 0.116). Perceived comprehension improved (7.9 ± 1.1 vs. 8.6 ± 0.9; p = 0.037), whereas objective comprehension remained unchanged. Overall family satisfaction increased (FS-ICU-24: 66 ± 15 vs. 75 ± 12; p = 0.041). Staff depersonalization decreased from 35% to 10% (p = 0.048). Conclusions: In this real-world before–after study, integrating a low-cost, co-designed brochure into clinician–family communication was associated with reduced depressive symptom severity, a numerical reduction in PTSD prevalence, and improved satisfaction, without adverse effects on staff well-being. These findings support the use of structured written information in family-centred ICU care.

Abstract: Against the sustained growth of China’s live streaming commerce, immersion is pivotal for consumer decision-making, yet existing studies overlook continuous moderators and systematic transmission mechanisms. Based on the SOR theory, this study explores how immersion influences purchase intention via trust, with shopping involvement as a moderator. Data from 455 Chinese live streaming shoppers were collected via Wenjuanxing and analyzed using SPSS 27.0, PROCESS macro, and AMOS 31.0. Results show immersion positively impacts trust, trust fully mediates the immersion-purchase intention link, and shopping involvement strengthens the immersion-trust effect for high-involvement consumers. This study enriches SOR theory’s application in digital consumption, offers marketers insights for immersive design and differentiated strategies, and contributes to sustainable consumption by reducing impulsive purchases through trust.

Abstract: Architect Vladimir Potočnjak (1904-1952), a cofounder of Croatian Modern Movement is almost nonexistent in the recent Croatian architectural history. The research of archival sources, accompanied by acquired drawings and books from his library, comprised thor-ough analysis of his realizations, projects and publications. Potočnjak graduated from the Architectural Department of Zagreb’s Institute of Technology in 1926 and apprenticed to Adolf Loos in Paris where he improved drawing skills, subsequently to Ernst May in Frankfurt a/M and finally to Hugo Ehrlich in Zagreb. Between 1931 and 1945 he was li-censed architectural engineer in Kingdom of Yugoslavia and successively in the Inde-pendent State of Croatia, additionally an architectural critic and theoretician preoccupied with problems of standardization. After 1945 he was appointed senior manager for archi-tecture in the collectivized Croatian Stately Design and Planning Institute. Cooperating with Zlatko Neumann, junior architects Antun Ulrich and Dragica Perak, in 1947 he won Yugoslav competition for the Federal Government Presidency Palace, later the Federal Ex-ecutive Council Palace, today the Palata “Srbije”. Fully preoccupied to its construction un-til his death, he concurrently translated Ernst Neufert’s “Bauordnungslehre” in Serbo-Croatian. Although classically educated, Potočnjak blended Modern Architectural narrative with layers of German Expressionism, visible on seminal drawings of Palata “Srbije”.

Abstract: Staphylococcus aureus remains to be one of the leading causes of global mortality. The most common class of antibiotics used to treat S. aureus infections are Next-Generation β-lactams (NGBs), as they are highly efficacious and have low adverse effects. NGB resistance in S. aureus is classically attributed to Penicillin-Binding Protein-2a (PBP2a), but previous studies from our group have also implicated altered expression of Penicillin-Binding Protein-4 (PBP4) with high-level NGB resistance. PBP4 is the only low-molecular mass (LMM) PBP present in S. aureus; it is also the only known LMM PBP with transpeptidase activity, giving it the unique ability to bring about peptidoglycan cross-linking. In this article, we review some of the recent findings from our group, which reveal that mutations associated with PBP4 lead to altered protein expression and NGB resistance in both MSSA and MRSA backgrounds. We discuss the clinical relevance of PBP4-associated mutations, particularly in Methicillin Resistant Lacking mec (MRLM) isolates, as well as the combined effect of altered expression of PBP4 and GdpP. Finally, this review summarizes the potential role played by PBP4 in S. aureus virulence. Together, we highlight the increasing relevance of PBP4 as a mediator of NGB resistance and discuss its potential to be an important factor during infection diagnosis and therapy.

Abstract: Surgical resection of liver and lung metastases in breast cancer is increasingly considered a viable option for select patients with oligometastatic disease. Historically regarded as palliative, surgery is now supported by retrospective data suggesting potential survival benefits, particularly in patients with hormone receptor-positive or HER2-positive tumors, long disease-free intervals, and limited metastatic burden. This narrative review summarizes recent evidence on the surgical management of breast cancer metastases to the liver and lung, with a focus on patient selection, perioperative outcomes, and long-term survival. Liver metastasectomy has shown 5-year overall survival rates of up to 60% in well-selected patients, while pulmonary metastasectomy offers comparable outcomes when resection is complete and nodal involvement is absent. Minimally invasive techniques and non-surgical approaches, such as microwave ablation and stereotactic radiotherapy, expand treatment options for patients unfit for surgery. The review also explores emerging tools influencing surgical decision-making, including circulating tumor DNA for minimal residual disease detection, transcriptomic profiling to predict organotropism, and artificial intelligence (AI)-driven platforms that assist with surgical planning and multidisciplinary case evaluation. While prospective validation remains limited, these technologies may help redefine surgical candidacy through biologically informed algorithms. Ultimately, the integration of surgery within a multimodal, personalized treatment strategy – guided by systemic control, tumor biology, and evolving digital tools – represents a promising direction for selected patients with visceral breast cancer metastases.

Abstract: Glycine N-methyltransferase (GNMT), a S-adenosylmethionine (SAM)-dependent methyltransferase, is primarily expressed in the liver and plays a key role in regulating liver metabolism and protecting against liver injury. Several studies have shown that deficiency or downregulation of GNMT is strongly associated with the pathogenesis of hepatocellular carcinoma (HCC), highlighting its critical role as a tumor suppressor. Other studies have shown that GNMT is also strongly correlated with the pathogenesis of metabolic dysfunction-associated fatty liver disease (MAFLD). Although many factors regulate GNMT expression, recent studies have identified microRNAs (miRNAs), such as miR-873-5p and miR-224, as key post-transcriptional regulators that directly target GNMT mRNA and suppress its expression in HCC and MAFLD. This review provides an overview of GNMT’s role in liver physiology and how its dysregulation contributes to the progression of HCC and MAFLD, with a focus on the regulation of GNMT by miR-873-5p and miR-224. We also highlight the potential of these two miRNAs as biomarkers and therapeutic targets for HCC and MAFLD, discussing emerging strategies such as antisense-based inhibition, gene therapy, and small-molecule inducers aimed at restoring GNMT expression.

Abstract: Chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd) continues to threaten amphibian biodiversity; however, Bd-associated microbiome signatures in salamanders remain inconsistent across studies. Here, we tested whether Bd detection is linked to shifts in salamander skin bacterial communities and, critically, whether it alters the architecture of microbial associations. We reanalyzed publicly available 16S rRNA amplicon data from Eurycea bislineata, Notophthalmus viridescens, and Desmognathus monticola, comparing Bd-detectable (Bd+) and Bd-non-detectable (Bd−) samples. Standard diversity and compositional analyses (alpha/beta diversity, PERMANOVA) showed no significant Bd-associated differences at broad community scales, and the dominant phyla were conserved across conditions. In contrast, differential abundance approaches (LEfSe and ANCOM-BC) identified the targeted Bd-associated taxa. Network inference and community detection revealed pronounced reorganization of the modular structure, with minimal overlap in module membership between Bd+ and Bd− networks and strong condition-specific turnover in stringent “core” networks. Modularity and robustness patterns were host-dependent and highlighted clearer contrasts between tolerant and susceptible hosts under targeted node removal. Together, these results show that Bd detection may leave the overall composition largely intact while reshaping the microbial association structure, supporting network topology as a sensitive complementary lens for detecting disease-linked community changes in amphibian skin microbiomes.

Abstract: A field experiment was conducted during 2022–23 to 2024–25 at the AICRPDA Research Farm, Tamil Nadu Agricultural University, Kovilpatti, India, to evaluate climate-smart agri-horti systems integrating aonla (Phyllanthus emblica Gaertn.) and custard apple (Annona squamosa L.) with annual intercrops under rainfed conditions. The experiment, laid out in a split-plot design with three replications, included fruit tree species as main plots and blackgram (Vigna mungo L.), greengram (Vigna radiata L.), clusterbean (Cyamopsis tetragonoloba L.), and foxtail millet (Setaria italica L.) as sub-plot treatments. Custard apple–based systems consistently produced higher fruit yield (2674–3306 kg ha⁻¹), intercrop biomass, and blackgram equivalent yield (1337–1653 kg ha⁻¹) than aonla-based systems (1980–2538 kg ha⁻¹ of fruit yield), and 891–1142 kg ha⁻¹ of blackgram equivalent yield of intercrops, respectively), primarily due to improved light availability and favourable canopy architecture. Clusterbean and foxtail millet recorded the highest intercrop yields, whereas pulse intercrops enhanced tree growth, soil nitrogen availability, and system sustainability through biological nitrogen fixation. Maximum rainwater use efficiency and land equivalent ratio were achieved under custard apple + clusterbean and aonla + foxtail millet combinations, indicating superior resource-use efficiency. Relative economic efficiency peaked in aonla + foxtail millet (341.2%), while the highest system profitability was recorded in custard apple + foxtail millet (₹352.4 ha⁻¹ day⁻¹). Soil fertility improved significantly over the study period, with increases in soil organic carbon (1.05–1.76 g kg⁻¹), available nitrogen (9–11 kg ha⁻¹), and potassium (8–14 kg ha⁻¹), particularly under pulse-based systems, whereas available phosphorus in soil remained unchanged. The study demonstrates that integrating short-duration legumes and millets with perennial fruit trees enhances productivity, profitability, rainwater-use efficiency, and soil health, providing a resilient and sustainable strategy for intensifying rainfed agroecosystems.

Abstract: This study examines the impact of digital transformation on the operational efficiency and sustained competitive advantage of SMEs in the context of a developing country. Rather than analyzing digitalization in isolation, this research integrates three key dimensions - digital strategic orientation, digital adaptive capability, and digital technology sophis-tication - into a comprehensive framework offering a holistic perspective on the effects of digital transformation in SMEs. Based on a survey of 216 Turkish SMEs, this research employs structural equation modeling using Smart PLS to assess the relationships be-tween these digital transformation dimensions and firm performance. The findings reveal that all three sub-categories of digital transformation positively influence operational efficiency. Furthermore, operational efficiency positively impacts sustained competitive advantage highlighting the transformative role of digital transformation in sustaining SME competitiveness. This multi-dimensional approach provides a comprehensive view of how digital transformation enhances SME efficiency beyond simple technology adoption. The study advances our theoretical understanding by demonstrating that digital transformation requires digital strategy integration into corporate strategy, awareness of emerging digital technologies, and the development of digital adaptive capabilities to drive SME performance. The findings suggest that SMEs should embed digitalization into daily business and e-commerce operations, enhance their capacity to adopt digital tools, and invest in technological infrastructure to achieve sustained competitiveness.

Abstract: National Institute for Health and Care Excellence (NICE) and National Clinical Guideline for Stroke 2023 (NCGFS23) guidelines recommend specialist TIA clinic assessment within 24 hours of symptom onset of suspected TIA. There is limited evaluation of TIA clinic services in the United Kingdom (UK) and Republic of Ireland (ROI). This study aims to assess attendee characteristics, NICE/NCGFS23 adherence, and clinical outcomes across the UK and ROI.DelAys in TIA Evaluation and Service (DATES) is a prospective national audit and service evaluation delivered through an established collaborative (The Neurology and Neurosurgery Interest Group (NANSIG)). All UK and ROI outpatient rapid-access TIA clinics are eligible. All index suspected TIA presentations will be included, irrespective of final diagnosis. Centres will register as an audit/service evaluation without altering routine practice. Data will be collected electronically, with blinded independent validation. The primary outcome is adherence to the NICE/NCGFS23 recommended 24-hour target. Secondary outcomes include presenting symptoms, diagnosis, investigations, treatment, and onward referral.DATES is anticipated to be the largest prospective study presenting in-depth evaluation of UK/ROI TIA clinic attendances. Our results will provide real-world data on TIA pathways and potentially improve existing services.

Abstract: Large language models (LLMs) now form a regular part of scientific research practice, where they are used to assist with hypothesis formulation, literature synthesis, and various forms of formal reasoning. Their use builds on earlier ideas of \emph{delegated cognition} and brings into sharper focus questions about how epistemic agency and moral responsibility are distributed across human--machine arrangements. This paper develops a conceptual and formal framework for examining these hybrid modes of reasoning, drawing on an analogy with familiar academic hierarchies in which a principal investigator (PI) coordinates and supervises junior collaborators. Within this framework, three related operators are distinguished: \emph{verification} $V(g)$, which concerns logical consistency and empirical adequacy; \emph{responsibility mapping} $R(g)$, which assigns epistemic and moral accountability to human agents; and \emph{epistemic value} $E(g)$, which characterizes the justificatory status and cognitive standing of a result, regardless of whether it is produced by a human or an artificial system. Verification and moral authorship are treated as closely connected aspects of epistemic responsibility, in the sense that verifying a claim amounts to accepting responsibility for its truth. On this view, the ethical boundary in scientific research is not drawn between human and machine reasoning, but between \emph{responsible} and \emph{negligent} forms of delegation within a distributed cognitive system. The paper also introduces the notion of an \emph{epistemic audit} as an institutional mechanism, comparable to established quality-assurance practices, for documenting transparency, reproducibility, and coherence in AI-assisted research. The analysis contributes to ongoing discussions in cognitive epistemology and the philosophy of AI concerning authorship, verification, and responsibility in extended systems of scientific reasoning.