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The impact of sex, age, and genetic ancestry on DNA methylation across tissues.

Understanding the consequences of individual DNA methylation variation is crucial for advancing our knowledge of human biology and disease, yet the collective impact of individual traits on DNA methylation and their downstream effects on gene expression across human tissues remains poorly understood. Here, we quantify the contributions of sex, age, genetic ancestry, and BMI on autosomal DNA methylation variation across nine human tissues and 424 individuals from the Genotype-Tissue Expression project. We show that genetic ancestry and age have a greater impact on DNA methylation compared with sex, with aging effects being more widespread but less pronounced. On average, <10% of the gene expression variation in sex, age, and ancestry is mediated by DNA methylation differences, with ancestry showing the largest proportion of mediation. We further show that ancestry-associated DNA methylation differences accumulate at CpG sites with extreme methylation states and are largely under genetic control. The female autosomal genome exhibits consistent hypermethylation across tissues at Polycomb-repressed regions. Ultimately, we show that age-related Polycomb target hypermethylation is observed across multiple tissues but not in the gonads. Our multi-individual, multitissue approach defines the key drivers of human DNA methylation variation in healthy conditions, establishing a baseline for the interpretation of DNA methylation changes in disease contexts.

Humans

Exploring the mechanism of aroma production in fermented cherry juice by L. brevis LD1.0600 using flavomics and whole genome analysis.

This study focused on L.brevis LD1.0600 with excellent fermentation traits: it analyzed genome-wide key regulatory genes for micro-metabolites, combined with fermented cherry juice flavor metabolomics data, and used machine learning to explore correlations between gene regulation, metabolite production, and flavor formation. The SVM model screened and verified fermented cherry juice VOCs; through OAV and flavor wheel analysis, LD1.0600 emerged as the top-performing strain, with a sweet, fruity dominant aroma. Key aroma-active components (OAV&#xa0;>&#xa0;100) included 2-methoxy-4-vinylphenol, benzaldehyde, 2-methyl-butanoic acid and hexanoic acid, and 2-methoxy-4-vinylphenol and hexanoic acid elevated by LD1.0600-regulated genes (Chrom1-001884, Chrom1-000925, fabF and Chrom1-000199). At the same time, through research, a "strain screening-SVM screening of DVCs-OAV screening of key aroma components-whole genome sequencing of flavor regulatory genes" system was established. This system can not only be applied to the screen fermentation strains, but also can be extended to the application of other fermentation products.

Fermentation

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation

Assessing AI literacy and attitudes among medical students: implications for integration into&#xa0;healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical

Gastric carcinoma classification in the WHO 6th edition (2026): Updated framework and emerging entities.

The sixth edition of the WHO Classification of Digestive System Tumours (2026) represents an important step in the continuing evolution of gastric carcinoma classification. While preserving morphology as the foundation of diagnosis, it incorporates advances in molecular pathology, genotype-phenotype correlations, tumour evolution, and predictive biomarker assessment. This review summarizes the development of the WHO classification from the third edition (2000) to the sixth edition (2026) and highlights its relationship with other major classification systems, including those of Laur&#xe9;n, Nakamura, and the Japanese Gastric Carcinoma Association (JGCA). Major histological categories remain largely unchanged; however, several important conceptual and diagnostic refinements have been introduced. These include recognition of crawling-type adenocarcinoma as a distinctive variant of tubular adenocarcinoma, subclassification of poorly cohesive carcinoma into signet-ring cell and non-signet-ring cell subtypes, introduction of the concept of pure signet-ring cell carcinoma, and increased emphasis on tumour evolution. The sixth edition also expands and refines the spectrum of uncommon gastric carcinoma subtypes, including gastric carcinoma with lymphoid stroma, AFP-producing carcinoma, micropapillary adenocarcinoma, gastric adenocarcinoma of fundic-gland type, and gastric sarcomatoid carcinoma. Crucially, molecular subgroups originally proposed by The Cancer Genome Atlas (TCGA) and actionable biomarkers-including HER2 (ERBB2), Claudin 18.2, mismatch repair deficiency/microsatellite instability (dMMR/MSI), and programmed death-ligand 1 (PD-L1)-have transitioned from research-based categories into essential tools for precision oncology. Rather than providing exhaustive diagnostic criteria, this review offers a conceptual framework and encourages consultation of the original WHO text for full details. These advances illustrate the transition of gastric carcinoma classification from a predominantly morphology-based system toward an integrated histomolecular framework that more closely links pathological diagnosis with tumour biology, prognostication, and therapeutic stratification.

Crawling-type adenocarcinoma

Structural and tissue-specific organisation of endocrine Fgf19 and Fgf21 signalling in rainbow trout.

Endocrine fibroblast growth factors (FGF19 subfamily) play a key role in regulating metabolic homeostasis in vertebrates. However, their functional diversification in salmonids remains poorly understood. In this study, we conducted an integrative characterisation of Fgf19 and Fgf21 signalling in rainbow trout (Oncorhynchus mykiss) by combining phylogenetic, structural and expression analyses. Phylogenetic analyses revealed the conservation of single fgf19 and fgf21 genes, despite the extensive expansion of receptors post-Ss4R (salmonid-specific fourth-round whole genome duplication). Structural modelling and molecular dynamics simulations demonstrated the stable interactions of both ligands to multiple Fgfr isoforms, with receptor-specific energetic profiles and conserved core interaction residues. Tissue expression profiling revealed clear differences from mammalian models, such as predominant hepatic fgf19 expression and the absence of hepatic fgf21 under basal conditions. In addition, there were complex and tissue-dependent distributions of fgfr and klotho transcripts. These findings support a receptor-driven diversification model of endocrine Fgf signalling in salmonids, suggesting enhanced endocrine plasticity associated with the retention of receptors following post-genomic duplication. Taken together, our findings provide new insights into the structural and regulatory organisation of endocrine Fgf signalling, as well as its potential role in metabolic regulation in rainbow trout.

Animals

Mechanistic insights into flavor deterioration in bitter sturgeon caviar: Evidence from lipidomics and metagenomics.

This study systematically compared the flavor and multi-omics differences between normal caviar and bitter caviar based on quantitative descriptive analysis (QDA), volatile compounds (VOCs) analysis, untargeted lipidomics, and metagenomics. The results showed that bitter caviar was characterized not only by increased bitterness, but also by decreased positive sensory attributes, including buttery, nutty, and marine fresh. VOCs analysis indicated that the volatile profile of bitter caviar was reorganized. Compounds such as 3-hydroxy-2-butanone, 1-octen-3-ol, and (E, Z)-2,6-nonadienal showed higher relative odor activity values (rOAVs); however, these changes did not improve its overall sensory experience. Untargeted lipidomics identified 492 differential lipids. These changes were mainly characterized by decreased PC and increased DG and LPC in bitter caviar. KEGG pathways analysis showed that these differential lipids were mainly associated with glycerophospholipid metabolism, choline metabolism in cancer, and retrograde endocannabinoid signaling. Metagenomic analysis showed that bacteria dominated the microbial community of caviar. Among them, Bacillus and Micromonospora showed relatively high abundance in the caviar microbiota. They were also closely associated with lipid metabolic changes involving PC, DG, and LPC, suggesting their potential as candidate targets for future microbiota-directed regulation of caviar quality. These findings provide new insights into the mechanisms underlying sensory deterioration and flavor formation in bitter caviar, and offer a theoretical basis for improving caviar quality in industrial production.

Animals

Mapping the immune-genetic architecture of Epstein-Barr virus-related phenotypes and multiple sclerosis through a single-cell genetic framework for target prioritization and pharmacologic hypothesis generation.

BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.

Humans

A translational framework for early-phase inner-ear gene therapy: clinical trial design, regulatory strategy, and ethical considerations.

PURPOSE OF REVIEW: Hereditary hearing loss has historically been approached as a diagnostic category rather than a therapeutically modifiable disease. Recent advances in molecular genetics, cochlear gene delivery, and first-in-human clinical trials are changing that. This review summarizes contemporary progress in the genetics of hearing loss, with emphasis on emerging gene-based therapies, clinical trial design, regulatory and ethical considerations, and practical implications for otolaryngologists as biologic treatment enters clinical practice. RECENT FINDINGS: Early clinical trials targeting OTOF -related DFNB9 deafness have demonstrated satisfactory safety profiles and meaningful auditory recovery, establishing the first proof-of-concept for cochlear gene therapy in humans, culminating in the April 2026 FDA approval of Otarmeni. Genetic diagnoses are increasingly informing prognosis, cochlear implant counseling, and therapeutic candidacy. Preclinical research continues to expand toward recessive, dominant, and syndromic hearing loss using gene replacement, antisense, RNA interference, and genome-editing strategies. Substantial challenges remain, including heterogeneous outcome measures, uncertain long-term efficacy, regulatory complexity, and inequitable global access. SUMMARY: The genetics of hearing loss is transitioning from a diagnostic modality to an interventional one. Widespread clinical impact will require advances in vector engineering, equitable implementation, multidisciplinary counseling, and integration with established rehabilitation pathways. For otolaryngologists, genetic literacy is becoming essential to contemporary hearing care.

Humans

From pathobiology to prescribing in obesity-driven HFpEF: A systematic review and practical therapeutic framework.

Heart failure with preserved ejection fraction (HFpEF) is increasingly driven by obesity and cardiometabolic dysfunction. In this phenotype, the dominant biology extends beyond congestion alone and includes visceral and epicardial adiposity, systemic inflammation, impaired myocardial energetics, endothelial dysfunction, and exertional elevation in filling pressures. We performed a PRISMA-compliant systematic review with structured narrative evidence synthesis to evaluate pharmacological therapy in obesity-driven HFpEF, searching PubMed/MEDLINE, Scopus, Web of Science Core Collection, ClinicalTrials.gov, and WHO ICTRP through December 2025. Eighteen reports were included in the final qualitative synthesis. The available evidence supports sodium-glucose cotransporter 2 inhibitors as the pharmacological foundation because they provide the most mature outcome data across the preserved ejection fraction spectrum. Semaglutide improves symptoms, physical limitations, exercise capacity, and body weight in dedicated obesity-related HFpEF trials, whereas tirzepatide extends this signal by improving clinical status and reducing worsening heart failure events. Finerenone broadens the therapeutic platform in HF with mildly reduced or preserved ejection fraction, although obesity-specific data remain indirect. Conventional neurohormonal therapies retain a selective role, but they are not the principal biological match for this phenotype. Obesity-driven HFpEF should therefore be managed as a cardiometabolic syndrome with heart failure expression, using a phenotype-based sequence that links diagnosis, decongestion, SGLT2 inhibition, obesity-directed therapy, and selective adjunctive intensification.

Humans

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans

Genome-wide characterization of the TGF-&#x3b2; superfamily identifies bmp15, gdf9, and gsdf as sex-biased candidate regulators of gonadal differentiation in the synchronous hermaphrodite Plectropomus leopardus.

The transforming growth factor-&#x3b2; (TGF-&#x3b2;) superfamily plays conserved roles in vertebrate reproduction and gonadal sex differentiation. However, its genomic repertoire and sex-biased expression patterns remain unclear in the leopard coral grouper (Plectropomus leopardus), a species with synchronous hermaphroditism. Here, we performed a genome-wide identification of the TGF-&#x3b2; superfamily, identifying 42 genes from the chromosome-level genome. Phylogenetic and synteny analyses indicated that segmental duplication under purifying selection contributed to family expansion. Expression profiling across multiple tissues and four gonadal developmental stages (undifferentiated, 120 dph; early differentiated, 15&#xa0;months; mature testis, 3&#xa0;years; mature ovary, 3&#xa0;years) identified eight gonad-enriched genes, among which bmp15 and gdf9 exhibited pronounced female-biased expression, with transcripts localized exclusively to the oocyte cytoplasm, particularly in stage II-III oocytes. In contrast, gsdf showed male-biased expression and was localized in spermatogenic cells of the testis. These reciprocal expression patterns indicate that bmp15/gdf9 and gsdf are candidate factors associated with gonadal sex differentiation. Our study provides the first comprehensive characterization of the TGF-&#x3b2; superfamily in P. leopardus and highlights bmp15, gdf9, and gsdf as candidate sex-differentiation factors in this hermaphroditic species.

Animals

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5&#x200b; concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution

Paediatric penile length: a systematic review and meta-analysis.

OBJECTIVE: To assess geographical variation in stretched penile length among prepubertal boys and evaluate temporal trends over the past two decades, as defining reference values for genital organ size remains crucial for early identification of development disorders. METHODS: The PubMed, Cochrane and Scopus databases (no deadlines for publishing were imposed) were searched according to the Preferred Reporting Items for Systematic Review and Meta-analyses statement. Five authors independently extracted individual participant data and assessed the risk of bias. Studies with quantitative penile lengths were included; those involving congenital malformations were excluded. The review protocol was prospectively registered in the International Prospective Register of Systematic Reviews (registration number CRD42022335643). RESULTS: A total of 55 studies from 2000 to 2024 were evaluated, including data from 31&#x2009;915 boys. Pooled mean stretched penile length estimates were 3.07&#x2009;cm (95% confidence interval [CI] 2.88-3.26&#x2009;cm) for the 1-week-old boys, 3.73&#x2009;cm (95% CI 3.53-3.93&#x2009;cm) for the 1-year-old boys, 4.69&#x2009;cm (95% CI 4.49-4.88&#x2009;cm) for the 2-5&#x2009;year-old boys, and 5.43&#x2009;cm (95% CI 5.20-5.66&#x2009;cm) for the 5-10&#x2009;year- old boys. When comparing data from the 2000s to the 2020s, stretched penile length decreased by 16.2% (from 3.46 to 2.90&#x2009;cm), 16.3% (from 4.17 to 3.49&#x2009;cm), 21.5% (from 5.31 to 4.17) and 26.2% (from 6.46 to 4.77&#x2009;cm) in the 1-week-old, 1-year-old, 2-5-year-old and 5-10-year-old boys, respectively. Subgroup analysis for those aged >2&#x2009;years showed significant variations by geographical region (P&#x2009;<&#x2009;0.001). CONCLUSIONS: The present study observed large variations in penile length across geographical regions and among prepubescent boys of different ages, while also suggesting a possible decline over the past two decades.

Humans

Evidence of genome-wide relaxed selection on mildly deleterious mutations in an ancient subterranean catfish.

About one hundred subterranean catfish species have been described, resulting from repeated colonization of cave environments by multiple surface lineages. Most cave-dwelling species are found in the Americas, in particular in South America, but a few species also live in Central and North America. Despite the availability of high-quality genome assemblies for two cave species, the Mexican blind catfish Prietella phreatophila and the Colombian blind catfish Trichomycterus rosablanca, genomic approaches to investigate genetic changes associated with subterranean life or to estimate cave colonization times remain largely unexplored. To fill this gap, we additionally sequenced the genomes of four blind and depigmented subterranean catfishes from Peru (three Trichomycterus and one Astroblepus), as well as the genomes of four close surface relatives. We first extracted a large set of light-related genes, such as phototransduction and crystallin genes, and found contrasting decays of these sequences in different cave species, from 1% of pseudogenes in T. rosablanca to 48% in P. phreatophila. Two independent molecular dating methods gave congruent ages, indicating that these catfishes colonized subterranean habitats at different times, ranging from Early Pliocene to Late Pleistocene, supporting the hypothesis that surface catfishes repeatedly and rapidly adapted to subterranean habitats. The oldest cave species, P. phreatophila, appears to have been thriving in the dark for over 3.5 million years. Moreover, a genome-wide analysis of protein-coding genes suggests weaker purifying selection on mildly deleterious mutations in this cavefish than in other catfish lineages, likely reflecting a long-term small effective population size.

cavefishes

Factors influencing the enhancement&#xa0;of the new iron triangle&#xa0;in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The&#xa0;healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise&#xb4;s Multiplication Appliqu&#xe9;&#xb4; a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium

Micro- and nanoplastics-induced neurotoxicity: a CNS-centered, evidence-graded adverse outcome pathway framework based on systematic weight-of-evidence assessment.

Micro- and nanoplastics (MPs/NPs) are ubiquitous anthropogenic particulate pollutants posing emerging threats to human neurological health. Severe heterogeneity in particle physicochemical properties, environmental aging status, exposure paradigms and experimental platforms has created persistent mechanistic uncertainties in MP/NP neurotoxicology, hindering reliable hazard characterization and risk translation. Here, we systematically consolidate empirical toxicological evidence and construct a dedicated central nervous system (CNS)-targeted adverse outcome pathway (AOP) network integrated with rigorous weight-of-evidence (WoE) grading to elucidate the hierarchical, particle-specific toxic cascades underlying MP/NP-induced neural injury. Our synthesis overturns the conventional linear toxicity paradigm, demonstrating that MPs/NPs trigger neurotoxicity via a complex multi-input mechanistic network. We definitively establish oxidative stress as a robust early convergent key event-rather than a universal molecular initiating event-orchestrating ROS overproduction, lipid peroxidation, mitochondrial dysfunction, and neuroinflammation to propagate neuronal damage. This core module is driven by five distinct particulate upstream triggers: particle-biomolecule interfacial perturbation, corona-facilitated cellular internalization, plastic-associated chemical leaching, aging-derived free radical reactivity, and gut-borne systemic neurotoxic signaling. Downstream pathogenic outcomes encompass glial overactivation, neurotransmitter dyshomeostasis, autophagy-lysosome dysfunction, metabolic reprogramming, regulated neuronal cell death, and behavioral impairments. Tiered WoE analysis confirms strong validation for early oxidative/inflammatory cascades, moderate support for gut-brain axis crosstalk and intracellular trafficking disruption, and nascent evidence for synaptic dysfunction and neurodegeneration-linked proteostatic defects. Extrapolation to human health risk remains constrained by the frequent use of high-dose exposure paradigms, limited validated data on internal dosimetry in the human brain, discrepancies between effective concentrations in experimental models and environmentally relevant human tissue burdens, and insufficient causal validation of distal adverse outcomes. We highlight key research priorities including aged mixed-particle exposure systems, leachate-controlled assays, quantitative internal dose evaluation, and mechanistic intervention verification. This evidence-stratified AOP framework resolves longstanding mechanistic ambiguities in particulate neurotoxicity, providing a standardized, causality-based foundation for future mechanistic exploration and health risk assessment of global plastic pollution.

Adverse outcome pathway