Search Results (1,476)

Ship self-sinking accidents threaten maritime safety, human life, property, and the marine environment, and understanding their causal-factor associations is essential for developing effective preventive measures. This study aims to identify the multi-level factors, recurrent association patterns, and critical structural nodes involved in ship self-sinking accidents. A hybrid framework integrating grounded theory, the Human Factors Analysis and Classification System (HFACS), FP-growth association rule mining, and complex network analysis was applied to 150 accident investigation reports released by the China Maritime Safety Administration between 2014 and 2024. Findings suggest that adverse weather and sea conditions, inadequate ship safety management, and crew incompetence are the most frequent factors. Thirty causal factors were identified and classified into four HFACS levels, and 229 association rules were generated to construct a directed weighted causal-factor association network with 19 nodes and 229 edges. Network results indicate that inadequate ship safety management, crew incompetence, ship unseaworthiness, insufficient maintenance of hull weathertight integrity, and improper or untimely emergency measures occupy critical positions in the association structure. This research offers insight into ship self-sinking accidents and identifies priority intervention points for more targeted maritime supervision, safety management and accident prevention. Full article

Background: The oral microbiome has emerged as a potential contributor to cardiovascular physiology through its role in the enterosalivary nitrate–nitrite–nitric oxide pathway. Oral nitrate-reducing bacteria convert dietary nitrate into nitrite, which can subsequently be reduced to nitric oxide, a signaling molecule associated with vascular tone, endothelial function, platelet activity, and blood pressure regulation. Disruption of this pathway has been associated with reduced nitric oxide bioavailability and impaired vascular responses. Methods: This narrative review summarizes current evidence regarding the relationship between the oral microbiome, nitrate metabolism, and cardiovascular function. Relevant literature was identified through searches of PubMed/MEDLINE and Google Scholar up to May 2026. Evidence from mechanistic, observational, and interventional human studies was reviewed and synthesized thematically. Results: Available evidence suggests that oral nitrate-reducing bacteria may influence nitric oxide bioavailability and vascular function. Studies have reported associations between oral microbiome disruption and changes in blood pressure, endothelial responsiveness, plasma nitrite concentrations, and other surrogate cardiovascular markers. However, findings remain heterogeneous and are influenced by factors such as diet, oral hygiene practices, smoking status, medication use, oral health, and underlying cardiometabolic conditions. Most studies are limited by small sample sizes, short intervention durations, and reliance on surrogate outcomes rather than major cardiovascular events. Conclusions: The oral microbiome may influence cardiovascular health through its role in nitrate metabolism and nitric oxide bioavailability. However, current evidence is largely limited to surrogate vascular outcomes, while data on major cardiovascular events remain scarce. Further longitudinal and interventional studies are needed to clarify causality and evaluate microbiome-targeted interventions. Full article

Over the last years, incretin receptor agonists—including glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1 RA) and the dual glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor agonist tirzepatide—have dramatically improved the management of type 2 diabetes, overweight and obesity. However, as the use of incretin receptor agonists continues to increase worldwide, micronutrient deficiencies—including iron deficiency—have emerged as newly recognized adverse effects of these drugs. The present article aims to discuss recent preliminary observational evidence on the potential relationship between incretin receptor agonist-based therapies and the development of iron deficiency and iron deficiency anemia (IDA), as well as the potential mechanisms by which incretin receptor agonists may affect iron homeostasis. Potential mechanisms and factors underlying the development of iron deficiency and IDA in patients treated with incretin receptor agonist-based therapies include inadequate dietary iron intake (due to incretin receptor agonist-mediated reduction in food intake and/or gastrointestinal adverse effects of incretin receptor agonists), low dietary variety, monotonous diets, and changes in food preferences, as well as impairment of intestinal iron absorption (due to delayed gastric emptying, reduced small intestinal motility and/or decreased gastric acid secretion caused by incretin receptor agonists). Moreover, vitamin B2 (riboflavin) deficiency and changes in gut microbiota composition are hypothetical mechanisms that may partly explain iron deficiency in patients treated with incretin receptor agonists, although these hypotheses require confirmation through mechanistic studies. Even though iron deficiency and IDA currently appear to be uncommon adverse effects of incretin receptor agonist-based therapies, clinicians should be aware of the possibility of their occurrence to ensure appropriate prevention and management of these nutritional complications. Nevertheless, future prospective studies are certainly needed to better establish the causal relationship between the initiation of incretin receptor agonist-based therapies and the development of iron deficiency/IDA, as well as the exact mechanisms underlying the potential development of these nutritional complications in patients treated with incretin receptor agonists. Meanwhile, the prescription of incretin receptor agonists should not be unjustifiably restricted by the possible and modest risk of iron deficiency and IDA in patients with one or more approved indications for therapeutic use of these agents. Since no established guidelines currently exist for the prevention and management of iron deficiency and IDA in patients treated with incretin receptor agonists, we herein propose practical strategies to address these possible nutritional complications of incretin receptor agonist-based therapies. These proposed strategies should only be regarded as practical clinical approaches deriving from the existing recommendations for the prevention and management of iron deficiency and IDA, although their cost-effectiveness for the prevention and management of incretin receptor agonist-associated iron deficiency/IDA should be appropriately assessed in future clinical trials. Full article

Autoimmune and immune-mediated inflammatory diseases (IMIDs) develop when genetically and environmentally susceptible hosts lose stable immune tolerance. The gut ecosystem is increasingly recognized as a biologically active interface in this process. Its bacterial, fungal, and viral components may shape mucosal and systemic immunity through antigenic stimulation, barrier regulation, and metabolite-dependent signaling, although the strength of evidence is uneven: bacteriome data are currently the most mature, whereas mycobiome, virome, and phageome findings remain more disease-specific and emerging. Dysbiosis may influence autoimmunity through overlapping routes, including epithelial barrier failure, altered short-chain fatty acid, bile acid, and tryptophan metabolism, molecular mimicry, and cross-kingdom microbial interactions. Nutrition is central to this network because dietary substrates determine microbial growth, metabolic output, epithelial integrity, and immune-cell differentiation. In this narrative review, we integrate evidence on disease-associated bacteriome, mycobiome, and virome patterns in systemic autoimmune diseases, with emphasis on rheumatoid arthritis, systemic lupus erythematosus, Sjögren’s syndrome, systemic sclerosis, spondyloarthritis, vasculitides, and idiopathic inflammatory myopathies. COVID-19 is considered not as a proven causal driver of autoimmunity, but as an example of an environmental and infectious insult capable of perturbing microbiome–barrier–immune communication. Finally, we discuss diet-based and microbiome-targeted approaches, including probiotics, prebiotics, synbiotics, and postbiotics, as adjunctive strategies that may help restore microbial resilience and immune balance. A better understanding of the diet–microbiome–host immunity axis may support more personalized preventive and therapeutic concepts in autoimmune disease. Full article

This study investigated undergraduates’ conceptualization of systems thinking (ST). An open-ended question was administered pre- and post-course. Pre-test findings revealed limited conceptualization, with most students unable to articulate core ST attributes. Post-course responses showed reasonable improvement, with seven key attributes—interconnectedness, feedback, causality, systems boundary, mapping, emergent behaviour, and synthesis—emerging to varying extents in their responses. While nearly all students indicated interconnectedness and mapping, fewer mentioned feedback and systems boundary, indicating these as higher-order cognitive skills. A continuum was also developed to categorize students’ conceptualization from inadequate to canonical; this also indicated that only a few students demonstrated engagement with the key attributes of ST. Novel analytical approaches such as attributes prevalence tables, attributes continuum, and evolution of threshold concepts have contributed to different modes for exploring ST in the responses. Findings underscore the complexity of ST and the challenges in fostering holistic conceptualization. Overall, the study highlights a nuanced engagement with the attributes of ST from the intervention and suggests that further work is necessary to better foster these among the students. Full article

This study examines the relationship between insurance market development and economic performance measured by GDP per capita levels in mature OECD economies, focusing on whether insurance depth, market size, and life insurance structure have distinct long-run implications. Although the insurance–income nexus is documented in developed and emerging markets, the literature rarely separates the qualitative depth of insurance use from the mechanical size of the sector relative to GDP, and seldom examines life insurance structural features such as retention and foreign participation within a non-stationary panel framework; this study addresses that gap. Using a balanced panel of 33 OECD countries from 2011 to 2021, the analysis applies panel time-series methods that account for non-stationarity, cointegration, cross-sectional dependence, and heterogeneous country dynamics. The results show that total insurance density is positively associated with GDP per capita, and life insurance density remains positive and significant across the long-run estimators, suggesting that more intensive insurance use remains economically relevant even in advanced financial systems. By contrast, life insurance penetration is negatively associated with GDP per capita, even after accounting for its mechanical link to GDP. Life insurance retention also enters negatively, while foreign insurer participation shows no statistically significant association in the panel. The findings support a depth-not-size interpretation of the long-run association between insurance market structure and income levels in mature OECD markets, and suggest that policy attention should shift from expanding insurance-sector scale toward improving efficiency, risk allocation, and market sophistication. These results reflect long-run associations within the OECD panel and should not be interpreted as evidence of direct causal effects. Full article

Soybean root rot, a destructive soilborne disease complex caused by a consortium of pathogenic fungi, poses a persistent threat to global soybean productivity. During 2022–2023, a total of 990 fungal isolates were recovered from symptomatic soybean roots across Heilongjiang Province, Northeast China. Of these, 279 isolates were identified as Fusarium equiseti through integrated morphological characterization and multilocus phylogenetic analysis. Notably, F. equiseti exhibited markedly elevated isolation frequencies (5.6–58.9%) across surveyed regions, confirming its status as the emerging dominant causal agent of root rot in this agroecological zone. Pathogenicity evaluations revealed that 76.67% of isolates displayed moderate virulence, with one strain classified as highly virulent (3.33%). In vitro fungicide sensitivity assays indicated that F. equiseti was most susceptible to prochloraz (mean EC₅₀ = 0.0010 µg·mL⁻¹) and fludioxonil (mean EC₅₀ = 0.0042 µg·mL⁻¹). When deployed as seed treatments, these two fungicides achieved 53.61% and 47.32% control efficacy against root rot, respectively, while significantly enhancing soybean seedling emergence, root length, and fresh weight. Collectively, these findings provide a scientific foundation for the precise, sustainable management of F. equiseti-mediated root rot in cold-region soybean production systems. Full article

High levels of low-density lipoprotein cholesterol (LDL-c) have been recognized as the main causal factor of atherosclerotic cardiovascular disease (ASCVD) and are influenced by both genetic and environmental factors. Among genetic determinants, Familial Hypercholesterolemia (FH) is the most common monogenic disorder, caused by rare high-impact variants in genes involved in LDL uptake. Other monogenic causes of hypercholesterolemia include sitosterolemia, cerebrotendinous xanthomatosis and lysosomal acid lipase deficiency (LALD). However, monogenic disorders only account for a small proportion of inherited hypercholesterolemia. In many individuals, increased LDL-c levels are caused by the contemporary presence of different single-nucleotide polymorphisms (SNPs) with a moderate/low impact. These SNPs could be summarized through polygenic risk scores (PRS) that attribute relative weight to each of these. Another genetic determinant of hypercholesterolemic phenotypes is high levels of lipoprotein(a)—Lp(a). Lp(a) is an LDL particle modified by the binding of apolipoprotein(a)—apo(a)—which represents an independent risk factor for ASCVD. Lp(a) levels are mainly genetically determined by variation in the number of kringle IV type 2 (K-IV₂) repeats, as well as by several SNPs, and remain stable throughout life. The aim of this narrative review is to report an updated overview of the genetic mechanisms underlying hypercholesterolemia, including monogenic disorders, PRS and Lp(a), focusing on their potential repercussion in clinical practice by the integration into cardiovascular risk stratification beyond traditional clinical assessment. This integration could lead to a more comprehensive and individualized approach to cardiovascular prevention, with emerging perspectives including the possible use of artificial intelligence (AI). Full article

The rapid expansion of molecular point-of-care (POC) diagnostics into decentralized settings, including emergency departments, retail pharmacies, and home environments, has shifted the burden of diagnostic performance from laboratory professionals to heterogeneous, often non-expert users. While traditional evaluation frameworks focus on analytical and clinical validity, they often overlook the impact of human-system interactions on real-world reliability. This review introduces the concept of Operational Validity: the ability of a diagnostic system to preserve its intended performance when operated by intended users within the constraints of real-world workflows and environments. To establish a rigorous foundation for this concept, this study provides a critical comparative analysis contrasting Operational Validity against traditional clinical evaluation dimensions (analytical validity, clinical validity, and clinical utility) and post-market metrics. While existing literature outlines isolated usability principles, the significance of this study lies in its synthesis of these fragmented concepts into a formalized, lifecycle-based “Operational Validity” framework that explicitly maps the causal mechanisms connecting initial user interaction directly to downstream clinical outcomes. By synthesizing international standards (IEC 62366-1) alongside the newly finalized May 2026 U.S. Food and Drug Administration (FDA) guidance on the Content of Human Factors Information in Medical Device Marketing Submissions, we examine how human factors engineering (HFE) and usability engineering serve as the methodological foundation for operational validity. We analyze the specific complexities of molecular workflows, identify key parameters of use-related failure modes in pre-analytical and interpretation stages, and detail the mandatory role of iterative formative and final summative usability testing in mitigating these risks. Finally, we propose a lifecycle-based approach to HFE that integrates design, simulated-use validation, and post-market surveillance. Establishing operational validity is essential to ensure that the high analytical sensitivity of molecular POC platforms translates into consistent clinical utility across the full spectrum of decentralized care. Full article

Selenium (Se) is a beneficial element involved in plant growth, metabolism, stress adaptation, and crop quality improvement, but its effects are strongly influenced by chemical form, application dose, plant species, growth stage, and environmental conditions. To integrate mechanistic understanding with global research trends, this study combines a concise mini-review with a bibliometric analysis of Se research in plants from 2000 to 2025. The mini-review summarizes Se speciation and bioavailability in the soil–plant–microbe system, root uptake and long-distance transport, metabolic assimilation and detoxification, physiological regulation, stress tolerance, biofortification, and nano-Se applications. Bibliographic data were retrieved from the Web of Science Core Collection and analyzed using CiteSpace, VOSviewer, and Scimago Graphica. A total of 3451 valid publications were identified, showing a sustained increase in annual output, especially after 2018. The field has expanded from early studies on Se speciation, uptake, assimilation, and antioxidant responses toward broader themes involving crop biofortification, molecular regulation, stress physiology, foliar application, nano-Se applications, green synthesis, and phytoremediation. Overall, plant Se research has evolved into an interdisciplinary field linking mechanistic studies with safe agricultural application. Future work should emphasize standardized experimental frameworks, causal mechanism validation, precise biofortification, field-based evaluation, and safety assessment of emerging Se-based technologies. Full article

Vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic (VEXAS) syndrome is an adult-onset inflammatory disorder caused by acquired mutations in UBA1, the gene encoding the primary ubiquitin-activating enzyme. The recognition of VEXAS has transformed the current understanding of autoinflammatory disease by demonstrating that somatic alterations arising within hematopoietic stem cells can precipitate severe, multisystem inflammation in later life. While pathogenic UBA1 variants are essential to disease pathogenesis, many affected individuals also harbor additional somatic mutations associated with clonal hematopoiesis, most commonly involving DNMT3A and TET2. These concurrent mutations may contribute to clonal architecture; however, their independent impact on inflammatory phenotype and hematologic manifestations remains incompletely defined. Emerging evidence suggests that co-occurring clonal hematopoiesis mutations may be independently associated with poorer overall survival, though their causal role remains unestablished. This review examines the evolving genetic framework of VEXAS syndrome, emphasizing UBA1 as the obligate driver mutation while reviewing current evidence regarding non-Met41 UBA1 variants and co-occurring somatic mutations. Full article

Background/Objectives: Postpartum haemorrhage (PPH) remains a leading cause of maternal morbidity, and the relationship between labour-induction duration and haemorrhagic risk has not been translated into a practical intrapartum risk-stratification framework. We aimed to derive a clinically interpretable induction-duration threshold for PPH risk stratification and to explore an internally validated parsimonious clinical decision-support model. Methods: In this retrospective cohort of 1128 induced singleton labours at ≥37 weeks at a Turkish tertiary centre, laboratory-defined PPH was operationalised as a haemoglobin drop ≥ 2 g/dL. Multivariable logistic regression identified independent predictors; receiver operating characteristic (ROC) analysis with 2000-replicate bootstrap internal validation derived a duration threshold; calibration, decision curve analysis, and a probability-scaled nomogram were additionally evaluated. Results: PPH occurred in 143 patients (12.7%). Four predictors were independently associated with PPH: induction duration (adjusted odds ratio 1.243 per hour; 95% CI 1.191–1.298; p < 0.001), parity, emergency caesarean, and maternal age. Induction duration achieved an apparent area under the curve of 0.773 (optimism-corrected 0.773); a Youden-optimal threshold of 10.1 h yielded 86.7% (95% CI 80.2–91.3%) sensitivity and 96.8% (95% CI 95.0–97.9%) negative predictive value. The model showed favourable calibration and positive net clinical benefit on decision curve analysis. Conclusions: Induction duration was independently associated with PPH; the internally validated 10.1 h threshold therefore represents a hypothesis-generating risk-stratification benchmark—reflecting an association rather than a demonstrated causal effect—that requires prospective external validation in independent populations before clinical application. Whether this association is causal or reflects an underlying myometrial phenotype requires prospective study. Full article

AI technologies are changing the world of work in ways that are hard to predict, and this uncertainty is felt particularly strongly by young people who are just beginning to think about their futures. This study explores how high school students in Turkey perceive AI’s potential impact on their career choices, using Social Cognitive Career Theory (SCCT) and Uncertainty Management Theory (UMT) as interpretive lenses rather than formally tested models. SCCT helps frame AI as an environmental force that shapes how students think about their career options, while UMT helps explain how students emotionally and cognitively respond to uncertainty that cannot easily be resolved. Using a cross-sectional survey of 354 12th-grade students, we developed and validated the AI-Related Career Perception Questionnaire (AICP-Q), which yielded four factors: AI Anxiety and Career Precarity, AI Literacy and Technological Awareness, Proactive Career Adaptation, and Socio-Technical Uncertainty. Students showed moderate AI awareness but relatively high levels of socio-technical uncertainty. Academic track emerged as an exploratory statistical correlate of AI Anxiety, a descriptive association suggesting that students’ sense of threat from AI may relate more to the specific skill demands of their chosen field than to the prestige of their school, though no causal inference can be drawn from these cross-sectional data. A key finding is “the planning gap”: students recognized the potential career disruptions associated with AI but did not consistently respond with adaptive behaviors. Drawing on UMT, we advance the tentative hypothesis, to be tested in future research, that this pattern may relate to a lack of the appraisal resources needed to translate awareness into action; because these constructs were not directly measured, this remains an interpretive suggestion rather than an empirical finding. Full article

Insulin resistance (IR) is traditionally viewed within the context of type 2 diabetes. However, it increasingly appears to represent a broader systemic metabolic risk state with potential relevance for carcinogenesis. Chronic hyperinsulinemia can activate insulin-like growth factor-1-dependent pathways, including phosphoinositide 3-kinase/protein kinase B/mechanistic target of rapamycin and mitogen-activated protein kinase signaling, promoting cellular proliferation while limiting apoptosis. At the same time, IR is closely linked to oxidative stress, chronic low-grade inflammation, and epigenetic alterations, together shaping a tumor-promoting microenvironment. Epidemiological studies report consistent associations between IR and increased cancer risk, particularly for endometrial, liver, and colorectal cancers. Yet causality remains uncertain and likely varies by tumor type. Notably, metabolic dysfunction may also occur in individuals with normal body mass index (BMI), underscoring the limitations of BMI-based risk assessment. Unlike previous reviews that primarily focused on individual mechanisms or epidemiological associations, this review examines IR as a systemic metabolic risk state by integrating molecular, epidemiological, biomarker-based, and prevention-oriented perspectives. Particular emphasis is placed on strategies for earlier risk identification using integrated biomarker approaches, including fasting glucose, homeostatic model assessment of insulin resistance, triglyceride-to-high-density lipoprotein ratio, high-sensitivity C-reactive protein, and insulin-like growth factor-1. Emerging tools such as continuous glucose monitoring and hepatokine profiling may further refine risk detection. Sustained lifestyle modification—diet, physical activity, sleep, and stress regulation—remains central to prevention. Pharmacological therapies, including glucagon-like peptide-1 receptor agonists and dual incretin agents, offer additional metabolic benefits, although their long-term impact on cancer risk is still unclear. Therefore, IR is best understood not as an isolated risk factor, but as a systemic metabolic risk state that may influence cancer development, with implications for prevention and early risk stratification. Full article

The convergence of artificial intelligence (AI), explainable AI (XAI), and neuroscience is fostering new opportunities for understanding both machine and biological intelligence through interpretable and human-centered learning paradigms. In this Perspective, we introduce XAI2Brain as a conceptual framework for brain–AI alignment, positioning mechanistic interpretability as an intermediate layer connecting neural network representations, human understanding, and neuroscience-inspired AI design. Rather than viewing XAI solely as a post hoc transparency tool, we emphasize its emerging role in enabling mechanistic analysis of internal model representations, concept-level reasoning, and interactive human–AI alignment. We define XAI2Brain as a multi-level conceptual framework rather than a deployable system, explicitly aimed at structuring brain–AI alignment across representation-level, mechanism-level, and interaction-level perspectives. We survey the evolution of XAI methodologies—from feature attribution and concept-based explanations to mechanistic and human-centric interpretability approaches—and discuss how these methods may support bidirectional knowledge transfer between AI systems and cognitive neuroscience. Importantly, we adopt a cautious stance on brain–AI analogy, explicitly recognizing that artificial neural representations are not equivalent to biological neural representations, and instead focusing on functional and informational correspondences rather than structural equivalence. Unlike conventional human-in-the-loop or reinforcement learning from human feedback paradigms that primarily optimize behavioral outputs, XAI2Brain focuses on cognitively interpretable and mechanistically grounded alignment between AI systems and human reasoning processes. This alignment promotes interactive human-in-the-loop intelligence, empowering humans to comprehend, guide, and refine AI systems, while enabling AI systems to better interpret human instructions, intentions, and contextual reasoning. We further discuss the challenges of scaling explainability to large generative and multimodal models, including issues of interpretability robustness, cognitive compatibility, evaluation, and ethical accountability. We also highlight key limitations of current mechanistic interpretability methods, including explanation instability, representation superposition, and lack of causal guarantees, underscoring that these challenges remain open research problems. Rather than proposing a complete artificial brain architecture, this Perspective outlines a research roadmap toward more interpretable, adaptive, and neuroscience-inspired AI systems capable of supporting future brain–AI integration and collaborative intelligence. We additionally clarify that this work follows a narrative perspective review methodology with structured thematic synthesis of the literature. By framing explainability as a bridge between mechanistic AI understanding, cognitive science, and human-centered interaction, XAI2Brain highlights the importance of interpretable alignment for the next generation of brain-inspired AI systems. Full article