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Factors influencing the enhancement of the new iron triangle 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 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´s Multiplication Appliqué´ 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

ADAM10's combined influence on the diagnostic usefulness of IL 22, IL 10, IL-17 A, and IL-17D in autism spectrum disorders: Predicted role on gut leakiness as co-morbidity.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with increasing global prevalence but a lack of reliable diagnostic biomarkers. Emerging evidence suggests that immune dysregulation, gut-brain axis dysfunction, and increased intestinal permeability play key roles in ASD pathophysiology. This study investigated the combined diagnostic value of ADAM10 and cytokines (IL-10, IL-22, IL-17 A, and IL-17D). Multivariable logistic regression produces an improved ROC curve that improves diagnostic accuracy over individual markers by combining numerous predictors into a single risk score (linear predictor). The technique, which frequently raises individual marker AUCs, entails modelling a binary result, calculating the probability, and visualizing ROC based on the projected probabilities. In this case-control study, plasma levels of ADAM10, IL-10, IL-22, IL-17 A, and IL-17D were measured in 37 male children with ASD and 37 age-matched controls. Group comparisons, correlation analyses, and receiver operating characteristic (ROC) curve analyses, including combined ROC models, were performed. ADAM10, IL-22, and IL-17 A levels were significantly reduced in children with ASD compared to controls, whereas IL-10 and IL-17D showed no significant differences. ADAM10, IL-17 A, and IL-22 demonstrated good diagnostic performance, with AUC values of 0.886, 0.855, and 0.812, respectively. In contrast, IL-10 and IL-17D showed poor discriminatory ability, with AUC values of 0.524 and 0.599, respectively. Combined ROC analysis markedly improved diagnostic accuracy, with all panels including ADAM10 achieving AUC values above 0.90, and some reaching as high as 0.988, with high sensitivity and specificity. The combination of ADAM10 with selected cytokines significantly enhances diagnostic performance compared to individual markers, supporting a link between immune dysregulation, barrier dysfunction, and gut permeability in ASD.

Humans

Integration of ear and hearing care services in low- and middle-income health systems: a systematic review and qualitative synthesis.

Hearing loss is a global public health burden and mostly affects those living in low- and middle-income countries (LMICs). One approach to address ongoing challenges is the World Health Organization's recommendation for the integration of ear and hearing care (EHC) services into healthcare packages. However, little is known about EHC integration approaches, particularly in LMICs additionally, these approaches have not been investigated through a health systems lens. This qualitative review aimed to describe the various approaches to the EHC service integration in LMICs and to identify enabling and constraining factors. We reviewed 17 studies, with a focus on LMICs, using adaptations of the Valentijn integration and World Health Organization EHC frameworks, following the PRISMA guidelines. Our investigation showed that most integration approaches were at micro or individual level. Enabling factors for integration of EHC services were training, mentorship, collaboration, technology, inclusion of EHC in healthcare packages and investment in EHC services. Barriers were challenges with training, facilities and equipment, policy implementation and resourcing of EHC services. We further described factors influencing healthcare seeking behaviour and the use of integrated EHC services, such as access and ability to pay, referral systems and communication and awareness. This study describes the complex nature of EHC integration and ways to support integration. Key considerations are the level of integration, training to address workforce issues and factors influencing service utilisation as we work towards health system strengthening.

Humans

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9

Access Block and Ambulance Ramping: The Canaries of the Healthcare System.

OBJECTIVE: To identify evidence-based factors leading to the global challenge of hospital access block and inform strategies to improve emergency access performance. METHODS: A mixed methods approach was followed comprising an umbrella review of published systematic reviews, qualitative analysis of the perspectives of patients and healthcare workers, and quantitative analysis of contextual factors and 6 years of ambulance, emergency inpatient and ward movement records for the 25 largest public hospitals in Queensland, Australia. RESULTS: A key set of findings and recommendations were identified to improve emergency access that are practical and actionable. These comprise the introduction of inpatient discharge metrics and monitoring to shift focus from the front door of hospitals to the 'back door'; increasing support for primary care, community care, aged care, NDIS and vulnerable groups; maintaining demand-side strategies such as increasing inpatient-equivalent care alternatives (e.g., hospital in the home, acute care within nursing home services); investment in prehospital flow; improving hospital processes such as extended-hour discharge lounges; improving workforce; and revising funding policies. CONCLUSIONS: The study findings fill a gap in the evidence regarding challenges and recommendations for improving patient flow within hospital emergency departments and across the broader health system. Focussing efforts at the 'back end' of the inpatient journey is a critical step to improve emergency care outcomes.

Humans

Effectiveness of Embedded Social Media Content on E-cigarette Attitudes and Behaviors: Results from a Randomized Control Trial.

BACKGROUND: This longitudinal randomized controlled trial examined the effects of anti-vaping social media content on e-cigarette attitudes and intentions among U.S. young adults (ages 18-24; n=3,400). METHODS: Targeted content was embedded directly into participants' social media feeds, with varying levels of impressions. RESULTS: Results indicate that increased exposure to anti-vaping messages significantly elevated perceived risk of harm (&#x3b2;=0.11, 95% CI: 0.03-0.20, p < .01) and social unacceptability of e-cigarette use (&#x3b2;=0.10, 95% CI: 0.03-0.18, p < .01), while decreasing intentions to vape (RRR = 0.59, 95% CI: 0.36-0.97, p < .05). Notably, these attitudinal shifts occurred even with relatively low ad exposure and over an extended intervention period, while controlling for the e-cigarette use status (never, former, or current) of participants. Discussion These findings support the effectiveness of digital media campaigns in influencing health-related behaviors and attitudes among young adults. Specifically, embedding anti e-cigarette content directly in the feed of young adults is shown to be effective in shifting attitudes in a space where these young adults are already engaged. Limitations include limited ad impressions and minimal change in ad awareness recall, suggesting future research should explore longer interventions and broader nicotine product messaging.

Humans

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans

Bacteroides cellulosilyticus-derived 2-hydroxyphenylacetic acid rectifies hepatic lipid homeostasis in MASLD by targeting the PPAR&#x3b3;-CD36 axis.

The gut microbiota plays an important role in the occurrence and development of metabolic dysfunction-associated steatotic liver disease (MASLD), but the specific molecular mechanisms involved have not been fully elucidated. In this study, human cohort studies were performed to identify that the relative abundance of Bacteroides cellulosilyticus (B. cellulosilyticus) was significantly decreased in patients with MASLD. Through the integration of metagenomic and metabolomic analyses, it was confirmed that B. cellulosilyticus and its metabolite 2-hydroxyphenylacetic acid (2HPAA) are key factors regulating the occurrence and development of MASLD. Single-cell sequencing and lipidomic analyses revealed that 2HPAA can enter the liver through the enterohepatic circulation to exert regulatory effects. Specifically, 2HPAA inhibits the peroxisome proliferator-activated receptor &#x3b3; (PPAR&#x3b3;) signaling pathway, thereby suppressing the expression of the fatty acid transporter CD36. Meanwhile, 2HPAA regulates lipid metabolism in hepatocytes by significantly enhancing palmitate conversion efficiency and inhibiting CD36 palmitoylation. This dual regulatory effect on CD36 expression and palmitoylation can reduce lipid accumulation in hepatocytes and ultimately alleviate MASLD progression. These findings reveal the mechanism by which B. cellulosilyticus and 2HPAA alleviate MASLD by targeting the PPAR&#x3b3;-CD36 pathway. This work provides a new perspective for the study of gut microbiota-host interactions in regulating liver diseases.

PPAR gamma

Insights into specific and nonspecific butyrate-producing pathways during the in vitro fecal fermentation of butyrylated starch.

Butyrylated starch is a special type-4 resistant starch with butyrate-carrying attribute. In this study, the unique butyrate-producing capability of butyrylated starch was deeply investigated by focusing on its specific and nonspecific butyrate-producing pathways, respectively, using specially designed substrates as controls. In vitro fermentation studies revealed that butyrylated and isobutyrylated starches generated high levels of butyrate and isobutyrate, respectively, highlighting the role of butyryl group metabolism in the specificity of butyrate production. Carboxylesterase assays have demonstrated that butyryl group metabolism is primarily facilitated by carbohydrate esterases expressed in the gut microbiota. Combined with 16S rRNA sequencing and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, it was found that butyrylated starch fermentation did not significantly enhance traditional butyrate synthesis pathways but modified the balance between the butyryl-CoA:acetyl-CoA transferase and butyrate kinase pathways by altering the gut microbiota composition, specifically by upregulating the relative abundance of indicator species such as Bacteroides, the Lachnospiraceae_NK4A136_group, and Parabacteroides. These insights offer theoretical guidance for designing butyrylated starch structures and regulating intestinal health.

Starch

Parallel evolutionary trajectories rewire enteropathogenic Escherichia coli adhesion to restore host attachment.

Enteropathogenic Escherichia coli (EPEC) causes disease in children, presenting as chronic diarrhea that can impair physical and cognitive development. The attachment of typical EPEC (tEPEC) to the gut epithelium via bundle-forming pili (BFP) is a key factor in its virulence. Yet, infections by atypical EPEC (aEPEC), which lack BFP, have become increasingly common. To investigate how aEPEC recover host-attachment in the absence of BFP, we performed experimental evolution using a non-adherent E. coli, constructed to mimic the ancestor of aEPEC, and selected adherent progeny. Highly adherent variants evolved through phase-variable activation of type I fimbriae (T1F), followed by two alternative trajectories: bacterial filamentation, which increases T1F avidity, or point mutations in the T1F adhesin FimH that enhance ligand affinity. Extending our analysis to the genomes of 327 aEPEC strains isolated from infected patients revealed that similar FimH mutations are common. We further demonstrated experimentally that these naturally occurring variants often increase epithelial-attachment. Our findings implicate T1F in aEPEC pathogenesis and suggest it may be clinically relevant for anti-adhesion therapy. More broadly, these results indicate that impaired host-attachment can be rapidly compensated by upregulating and optimizing an alternative adhesin, and that combining experimental evolution with comparative genomics can reveal evolutionary trajectories occurring in nature.

Bacterial Adhesion

Rates, Timing, and Predictors of Retreatment Across Risk-Cohorts in Retinopathy of Prematurity: Intravitreal Bevacizumab Injection Versus Laser.

OBJECTIVE: To characterize rates, timing, and predictors of retinopathy of prematurity (ROP) retreatment among infants treated with primary laser or intravitreal bevacizumab injection. DESIGN: Retrospective consecutive, comparative clinical study. PARTICIPANTS: Infants who underwent initial treatment for treatment-warranted ROP (TW-ROP) with either intravitreal bevacizumab or laser photocoagulation between 2017 and 2023. METHODS: Patients were stratified into two treatment groups: primary laser group vs primary bevacizumab group. MAIN OUTCOME MEASURES: Retreatment within the first 3 months (0-90 days) was assessed and classified as early (&#x2264;30 days) or late (31-90 days). RESULTS: Two hundred and thirty eight eyes of 122 infants were treated for ROP; of those, 181 (76.1%) eyes of 93 (76.2%) patients were included. There were 116 (64.1%) eyes in the bevacizumab group, and 65 (35.9%) eyes in the laser group. Thirty-three (18.2%) eyes-all micro- or nano-premature (<27 weeks GA and/or <800 grams)-required retreatment for TW-ROP. Sixteen (8.8%) required early retreatment at a median postmenstrual age (PMA) of 40.4 weeks (IQR, 38.44-43.3). There were differences in the proportion of early retreated infants (21.5% for laser vs 1.7% for injection, P < .001). Seventeen (9.4%) eyes required late retreatment. The median PMA at late retreatment was 45.6 weeks (IQR, 43.7-47.4). Infants in the bevacizumab group had lower odds of retreatment within three months than those with laser (OR, 0.23; 95% CI, 0.06-0.82). Similarly, patients in the bevacizumab group had lower odds of requiring early retreatment compared to those with laser (OR, 0.08; 95% CI, 0.04-0.18). Within eyes with retreatment, infants in the bevacizumab group had a later PMA at retreatment than those in the laser group (B = 6.81; 95% CI: 4.68-8.93). AROP was associated with earlier PMA at retreatment (B = -7.72; 95% CI, -9.36 to -6.10). CONCLUSION: In this study, early retreatment was low (8.8%), with most eyes initially treated with laser (21.5%) rather than bevacizumab (1.7%). Aggressive ROP was associated with earlier retreatment, highlighting its role as a marker of more severe disease. Compared to laser, bevacizumab was associated with lower overall and early retreatment, and delayed need for additional intervention when necessary. All retreatments occurred in micro- or nano-premature infants, suggesting that medium-to-low risk infants may require less strict post-treatment monitoring.

Humans

Ten-Year Update of Nurse Practitioner Service Impact on Patient and Health Service Outcomes in Emergency Care Settings-A Systematic Review.

AIMS: To provide a 10-year update on the best available evidence evaluating the impact of nurse practitioner services on cost, waiting times, patient satisfaction, representation rates, and length of stay in emergency and urgent care settings. DESIGN: Systematic review. DATA SOURCES: The search was completed on January 28, 2025, in Embase (Elsevier), Medline (EBSCOhost), CINAHL (EBSCOhost), Cochrane Library (Wiley), Emcare (Ovid), Web of Science Core Collection (Clarivate) and Scopus (Elsevier). The data range (2014-2024) was used to limit the search. METHODS: The search was conducted with results imported into Covidence. In Covidence, two reviewers conducted screening, data extraction, and quality appraisal of articles, and findings were analysed using a narrative synthesis approach. Eligible studies examined nurse practitioner services in emergency or urgent care settings, reporting outcomes of cost, waiting times, patient satisfaction, representation rates, and length of stay. RESULTS: Title and abstract screening were performed on 2329 records. Of these, 236 full-text articles were reviewed, and 17 underwent critical appraisal and data extraction. Narrative analysis of outcome measures yielded mixed results, with both favourable and unfavourable findings reported regarding nurse practitioner services. CONCLUSIONS: Global evaluation of nurse practitioner services in emergency care remains inconsistent. Nevertheless, emerging evidence supports their positive impact, particularly in improving patient outcomes. To effectively inform policy, workforce planning and clinical integration, there is a need for professional benchmarks that provide clear frameworks for the evaluation of patient-centred outcomes and operational impacts in emergency departments. IMPLICATIONS: Evidence related to nurse practitioner services in emergency and urgent care clinics highlights the positive impact of nurse practitioner services on patient wait times and satisfaction; however, there is limited and variable evidence of impact on health care costs and outcomes. IMPACT: This paper recommends that evaluating emergency nurse practitioner services requires homogeneous research using consistent professional benchmarks and evaluation frameworks. REPORTING METHOD: This systematic review follows the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. PATIENT OR PUBLIC CONTRIBUTION: This study did not include patient or public involvement in its design, conduct, or reporting. TRAIL REGISTRATION: PROSPERO 2025 CRD420250645148.

Humans

Long-term microbiome and clinical effects of a microbiome-guided personalized diet versus low-FODMAP diet in irritable bowel syndrome: A 12-month follow-up randomized controlled trial.

Dietary therapy is central to irritable bowel syndrome (IBS) management, yet the long-term durability of the low-FODMAP diet (LFD), and of microbiome-guided personalization, remains unclear. We assessed the long-term clinical and gut-microbiome effects of a microbiome-guided personalized diet (PD) compared with a standard LFD in adults meeting Rome IV criteria for IBS. In this multicenter, open-label randomized controlled trial with blinded outcome assessment, participants who completed a 6-week dietary intervention (PD or LFD) were followed at 6 and 12 months without further dietary intervention. Outcomes included the IBS Severity Scoring System (IBS-SSS), IBS Quality of Life (IBS-QOL), and the Hospital Anxiety and Depression Scale (HADS); gut microbiota were profiled by 16S rRNA sequencing. Longitudinal changes were evaluated using linear mixed-effects models, responder analyses, PERMANOVA, and PERMDISP. Both diets reduced IBS-SSS at 6 weeks. PD maintained symptom improvement at 6 and 12 months (-82.0 and -78.3 points from baseline), whereas LFD benefits regressed by 12 months (+29.3 points; between-group p&#x2009;=&#x2009;0.001). At 12 months, IBS-SSS responder rates were higher with PD than LFD (62.5% vs 34.5%; absolute risk difference&#x2009;+28.0%, 95% CI 4.2-47.7; Fisher p&#x2009;=&#x2009;0.029), and IBS-QOL, HADS-anxiety, and HADS-depression showed more favourable trajectories with PD. PD was associated with sustained Shannon alpha-diversity gains (+0.488 at 6 weeks;&#x2009;+0.205 at 12 months; both p&#x2009;<&#x2009;0.01). A modest between-group beta-diversity difference at 6 months (R2&#x2009;=&#x2009;0.035; p&#x2009;=&#x2009;0.011) was not significant at 12 months. This hypothesis-generating follow-up suggests more durable benefit with PD; larger trials powered for long-term clinical and microbiome outcomes are warranted.

Humans

Future promise, current clinical ambiguity: a systematic review of machine learning algorithm outputs predicting risk of cardiovascular disease.

OBJECTIVE: To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovascular disease (CVD) address known deficiencies of the Framingham Risk Score (FRS) and improve risk estimates. METHODS: For this critical review, Medline, Embase and IEEE were searched from inception to 1 January 2025. Included were studies describing machine learning algorithms designed to specifically compare output of cardiovascular risk assessment with the FRS. Commentaries, letters, unpublished work or non-peer-reviewed papers were excluded.Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, two reviewers screened titles and abstracts independently, then populated a purpose-built data extraction form. A subsequent qualitative thematic analysis focused on algorithms' strengths, added value, potential harms, unintended consequences and equity implications.The main outcome assessed was whether, among healthy adults, the algorithm improved CVD risk prediction relative to the FRS. RESULTS: Of 707 studies retrieved, 29 met inclusion criteria. 23 reported improved predictive ability relative to the FRS. Most datasets and/or medical records used included sociodemographic predictors of CVD not included among FRS inputs. Some added costly diagnostic tests like CT angiography to FRS screening indicators. When they were defined, inputs and outcomes such as hypertension or myocardial infarction did not always adhere to FRS values. Statistical significance was generally taken as a proxy for clinical significance. Some algorithms overestimated the number at risk compared with the FRS without discussing whether that larger proportion might be at risk of overdiagnosis rather than CVD, while a few decreased the proportion found to be at risk. CONCLUSIONS: Use of artificial intelligence to improve accuracy of risk assessment for CVD demonstrates the technological capacity to merge known sociodemographic predictors with biologic variables and examine non-linear interactions among these. Still needed to achieve patient benefit is clinical insight, adherence to screening principles and cost-benefit assessment of inputs selected.

Humans

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

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor&#x2012;recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation

Effects of multistrain probiotic supplementation on hepatic function and anthropometric parameters in patients with metabolic dysfunction-associated steatotic liver disease: a double-blind, randomized controlled trial.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly prevalent on a global scale. The gut microbiota is integral to its pathogenesis, prompting extensive research into microbiota modulation as a potential adjunctive therapeutic strategy. AIM: The study aimed to evaluate the effect of multistrain probiotics supplementation on hepatic function in patients with MASLD in a double-blind, randomized, controlled trial. The primary outcomes were changes in Fibrosis-4 index (FIB-4) and fatty liver index (FLI). Secondary outcomes included changes in anthropometric parameters, selected biochemical markers, and other liver-related indices. METHODS: A total of 64 patients with MASLD were randomly assigned to two groups receiving either placebo (C) or a probiotic mixture (PRO) containing the following bacterial strains: 50% Lactococcus lactis Rosell-1058, 25% Lacticaseibacillus casei Rosell-215, 12.5% Lactobacillus helveticus Rosell-52, 12.5% Bifidobacterium bifidum Rosell-71 for 12 wk. RESULTS: Significant group &#xd7; time interactions were observed for FIB-4 (Q = 0.007), with reduction in the PRO group and increase in the C group (-0.05 vs. 0.10; P = 0.002). No significant interaction was found for FLI (Q = 0.942). Significant group &#xd7; time interactions were also observed for aspartate aminotransferase (-2.87 vs. 1.87 U/L; Q = 0.003) and APRI (-0.03 vs. 0.02; Q = 0.001), favoring the PRO group (P < 0.001 for both). No significant changes were observed in anthropometric parameters, glucose levels, or lipid profile. CONCLUSIONS: In patients with MASLD, the 12-wk probiotic supplementation had a modest but statistically significant effect on FIB-4, aspartate aminotransferase, and APRI, with no significant effect on FLI or anthropometric and metabolic parameters. These findings suggest that this probiotic formulation may have potential benefits for liver function in MASLD. However, long-term studies incorporating imaging-based and histological endpoints are required to determine the clinical significance of these findings.

Humans