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PubMed2026

Risk prediction models for blood transfusion in patients undergoing total hip and knee arthroplasty: a systematic review and meta-analysis.

OBJECTIVE: To systematically review and evaluate published risk prediction models for perioperative blood transfusion in patients undergoing total hip or knee arthroplasty (THA/TKA). METHODS: We systematically searched PubMed, Web of Science, the Cochrane Library, and Embase from inception to May 31, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability using the Prediction model Risk Of Bias Assessment Tool (PROBAST). The area under the receiver operating characteristic curve (AUC) values were pooled via a meta-analysis using Stata 18.0. RESULTS: d Fourteen studies containing 36 prediction models were included. The incidence of blood transfusion among THA/TKA patients ranged from 3.2% to 30.8%. Preoperative hemoglobin (Hb) level, tranexamic acid (TXA) use, operative duration, intraoperative blood loss, and age were the most frequently incorporated predictors. Model sensitivity ranged from 58% to 94.5%, and specificity ranged from 71.3% to 94%. Meta-analysis showed that the pooled AUC value of the 13 validated models was 0.87 (95% CI: 0.85-0.90), suggesting good discriminatory performance. All models were rated as having a high risk of bias. The applicability of four studies was rated as unclear. CONCLUSION: Although the included studies demonstrated promising discriminative ability of prediction models for blood transfusion in THA/TKA, all were assessed as having a high risk of bias using the PROBAST tool. Therefore, future research should prioritize the development of models with larger sample sizes, rigorous study designs, and multicenter external validation.

Humans↗

PubMed2026

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 31 915 boys. Pooled mean stretched penile length estimates were 3.07 cm (95% confidence interval [CI] 2.88-3.26 cm) for the 1-week-old boys, 3.73 cm (95% CI 3.53-3.93 cm) for the 1-year-old boys, 4.69 cm (95% CI 4.49-4.88 cm) for the 2-5 year-old boys, and 5.43 cm (95% CI 5.20-5.66 cm) for the 5-10 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 cm), 16.3% (from 4.17 to 3.49 cm), 21.5% (from 5.31 to 4.17) and 26.2% (from 6.46 to 4.77 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 years showed significant variations by geographical region (P < 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↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

Humans↗

PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans↗

PubMed2026

Validated UPLC-MS/MS quantification and intracellular PK-PD Modeling of periplocin-related cardiac glycosides in H/R-injured H9c2 cells.

Reliable intracellular quantification is essential for characterizing the target-site disposition and exposure-response relationships of bioactive natural products. In this study, an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed and validated for the simultaneous determination of periplocin and four related cardiac glycoside metabolites in H9c2 cell lysates. Acceptable linearity, precision, recovery, and stability were achieved for intracellular quantification. Cells were treated with each compound at 50 μM, and intracellular concentrations and cell viability were monitored over 48 h. In hypoxia/reoxygenation (H/R) -injured cells, the time to maximum intracellular concentration was shortened for all five compounds, indicating altered cellular disposition under injury conditions. Cell viability was improved by all compounds during the observation period. Pharmacokinetic-pharmacodynamic (PK-PD) integration was performed using a sigmoid Emax model, and acceptable model fits were obtained, with Akaike information criterion (AIC) values ranging from 79.22 to 130.46. Low apparent EC50 values were estimated under this single-dose design, whereas the estimated Ke0 values suggested delayed equilibration with the effect compartment. These findings indicate that sustained cytoprotective responses can be produced by periplocin and related metabolic markers in injured cardiomyocytes. This intracellular bioanalytical strategy provides a quantitative approach for linking cellular exposure to pharmacodynamic response and may support further evaluation of periplocin-related cardiac glycosides.

Tandem Mass Spectrometry↗

PubMed2026

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics↗

PubMed2026

Oil and gas well development and coccidioidomycosis risk in Kern County, CA, USA: a case-crossover study.

BACKGROUND: Coccidioidomycosis is an emerging fungal disease caused by inhaling Coccidioides spp spores. As spores reside in soil, activities that disturb soil and generate dust can aerosolise and transport the pathogen. The oil and gas industry has been extensively developed in some regions that are endemic for Coccidioides spp and has been associated with dust emissions. Although several adverse health outcomes have previously been associated with oil and gas development, its impact on coccidioidomycosis risk has not been investigated. We aimed to estimate the association between exposure to oil and gas well development (ie, wells in preproduction) and risk of coccidioidomycosis among residents living near new wells. METHODS: In this case-crossover study, we obtained information on reported coccidioidomycosis cases and oil and gas well development between 2007 and 2022 in Kern County, CA, USA. We then compared exposure to preproduction wells within 5 km of each individual's place of residence during both hazard (ie, the 49-139 days before case onset) and control periods using conditional logistic regression. FINDINGS: During the study period, 658 108 (72·4%) of 909 282 of Kern County residents lived within 5 km of at least one preproduction well, and 116 020 (12·8%) lived within 5 km of 23 or more preproduction wells within a single 90-day period. We estimated that the odds of coccidiomycosis incidence were 12·5% (95% CI 5·8-19·6) higher in the 90 days following exposure to at least one preproduction well within 5 km of an individual's place of residence and that the odds of infection increased by 0·7% (0·4-0·9) for each additional preproduction well developed within this distance. INTERPRETATION: These findings support a previously-unrecognised association between the development of oil and gas wells and transmission of coccidioidomycosis, potentially driven by dust generation. Given the prevalence of oil and gas development in the study region, its impact on coccidioidomycosis incidence might be large. FUNDING: National Institutes of Health, National Science Foundation.

Journal Article↗

PubMed2026

Efficacy of afoxolaner (NexGard®) for the treatment of myiasis caused by the zoonotic tumbu fly, Cordylobia anthropophaga, in domestic dogs under field conditions.

Cordylobia anthropophaga is a major cause of furuncular myiasis in dogs and humans in sub-Saharan Africa, yet evidence for pharmacological control remains limited. Current management relies mainly on mechanical larval removal, and no controlled studies have assessed the efficacy of modern antiparasitic agents. This study evaluated the curative and preventive efficacy of a single dose of afoxolaner (NexGard®) in dogs with naturally acquired C. anthropophaga infestation under field conditions and explored a possible indirect protective effect in puppies after maternal treatment. A randomized, blinded, negative-controlled field study was conducted in Samburu County, Kenya, and included 104 naturally infested dogs allocated to a treated group (n = 53) or an untreated control group (n = 51). Clinical evaluations were performed on Days 0, 15 (±2), 30 (±2), and 45 (±2). Efficacy was assessed based on the presence of active nodules and clinical scores. Additional observational data were collected from puppies born to or nursing from treated bitches. Compared to the control group, parasiticide efficacy was 94% on Day 15 and 100% on Day 30. The number of parasite-free dogs reached 86.3% on Day 15, 100% on Day 30, and 95.3% on Day 45. Treated dogs showed a significant clinical improvement from the first post-treatment assessment, whereas infestation persisted in controls (nodules: OR = 0.003, 95% CI 0.001-0.017; skin lesions: OR = 0.010, 95% CI 0.002-0.051; lymph node: OR = 0.013, 95% CI 0.002-0.074; body condition: OR = 0.073, 95% CI 0.027-0.195; all p < .001), with large effect sizes at the final visit for all outcomes (r = 0.521-0.793). No C. anthropophaga infestations were detected in examined puppies from treated dams, including puppies exposed during pregnancy or lactation, up to 4 weeks after birth and up to 11 weeks of age, respectively. Afoxolaner appears effective to control canine cordylobiosis and may offer indirect protection to puppies, warranting further investigation.

Animals↗

PubMed2026

Adaptive proteomic remodeling and eNOS upregulation in luminal endothelium and perivascular adipose tissue of patent saphenous vein grafts after CABG.

OBJECTIVE: Long-term patency of saphenous vein grafts (SVGs) remains a significant challenge in coronary artery bypass grafting (CABG). The biological factors underlying successful human grafts are poorly understood. We aimed to characterize the structural and molecular features associated with successful graft function. METHODS: Patent and occluded SVG and internal thoracic artery (ITA) grafts were obtained from explanted hearts of CABG patients undergoing heart transplantation for end-stage heart failure not attributable to graft failure, along with freshly harvested ITA and SVG controls. Samples underwent histomorphological analysis, immunohistochemistry (IHC), and liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics. RESULTS: Patent ITA (ITA-P) showed minimal intimal hyperplasia with medial reinforcement, whereas patent SVGs (SVG-P) had organized, α-smooth muscle actin (αSMA)-positive myofibroblast-rich neointima. Endothelial nitric oxide synthase (eNOS) was markedly upregulated in patent grafts at two sites-the luminal endothelium and adventitial microvessels within perivascular adipose tissue (PVAT)-and lost at both sites in occluded SVG (SVG-O). Adventitial CD31-positive microvessels were significantly increased in patent grafts. Proteomically, ITA-P and SVG-P shared a largely common adaptive proteome enriched in translation, RNA processing, and extracellular matrix (ECM) organization, with shared upstream activation of NR4A3, EGFR, and STAT1, and conduit-specific signatures (IGF-1/RUNX2 in ITA-P; RETN/SRC/PTGES in SVG-P). PTGES was strongly expressed in the adventitia of SVG-P. CONCLUSIONS: Patent arterial and venous bypass grafts exhibited a shared adaptive phenotype characterized by dual-site upregulation of eNOS in both the luminal endothelium and the perivascular microvessels/PVAT. In SVG-P, PTGES was co-upregulated alongside eNOS, indicating a mechanistic link between the proteomic and IHC findings. These findings highlight the perivascular compartment as a site of adaptive, eNOS-associated changes in patent vein grafts.

Humans↗

PubMed2026

PHACE syndrome: a systematic literature review and illustrative case report of a patient with severe cerebrovascular and neurodevelopmental sequelae.

BACKGROUND: PHACE syndrome is a rare neurocutaneous disorder defined by the association of large segmental infantile hemangiomas of the head and neck with malformations of the posterior fossa, cerebral and cervical arteries, heart, eyes, and ventral midline structures. Although facial hemangiomas are often the presenting feature, the cerebrovascular, neurodevelopmental, and airway manifestations are responsible for the greatest long-term morbidity. METHODS: A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching PubMed, Web of Science, EMBASE, and PsycINFO. After removal of duplicates and screening of 308 records, five studies meeting the inclusion criteria were retained for qualitative synthesis. We additionally present the case of a now 12-year-old girl with PHACE syndrome characterized by a left V1-distribution facial hemangioma, ocular abnormalities, multiple cerebrovascular venous and arterial malformations, neonatal intraventricular hemorrhage with hydrocephalus, and a subsequently diagnosed dural arteriovenous fistula requiring repeated embolization. RESULTS: The five included studies collectively describe epidemiology and early supportive care needs, long-term health outcomes and quality of life into adulthood, airway hemangioma prevalence and management, and the clinical spectrum of infantile hemangiomas with minimal or arrested growth (IH-MAG) as a cutaneous marker of PHACE syndrome. Across studies, cerebrovascular arteriopathy (72-91%) and facial hemangioma residua (> 90%) were the most consistent findings, while progressive arteriopathy, headaches, learning differences, and airway involvement emerged as the principal sources of long-term morbidity. The reported case illustrates an unusually severe cerebrovascular phenotype, including neonatal hemorrhagic hydrocephalus, dural venous sinus thrombosis, and a late dural arteriovenous fistula, culminating in ataxic cerebral palsy and mild intellectual disability. CONCLUSIONS: PHACE syndrome requires a multidisciplinary, lifelong follow-up strategy. The presented case underscores that cerebrovascular complications may evolve over years to decades after the initial diagnosis, reinforcing the need for long-term neuroradiological surveillance even after apparent clinical stability.

Humans↗

PubMed2026

How the Social Context and Peer Helping Contribute to Better Alcohol Outcomes Among Sober Living House Residents: Mediation Analyses.

BACKGROUND: Sober Living Houses (SLHs) adopt a social model approach, which emphasizes peer helping. Although SLHs appear to be effective, little is known regarding why. This longitudinal study examined whether higher SLH social model adherence produces better resident outcomes by increasing resident helping. METHODS: Baselines were conducted with 205 residents entering 28 SLHs, with follow-ups through 6 months. Measures included 1-month perceived SLH social model adherence; 2-month help given to and received from SLH residents; and 6-month alcohol use and severity. Analyses were lagged, multivariate mediation models accounting for clustering within SLH. Separate models examined help given and received for each outcome, yielding four model tests. RESULTS: The hypothesized model was unsupported, with all four tests showing nonsignificant indirect effects. However, exploratory post-hoc tests showed significant indirect effects between higher 1-month resident helping and better 6-month alcohol outcomes via higher 1-month SLH social model adherence. Effects held across three of four model tests. CONCLUSIONS: Results suggest that residences adhering to social model principles do not achieve better outcomes by stimulating helping, but rather that more resident helping may foster a supportive SLH social environment, which itself drives better outcomes. Thus, residences might emphasize both resident helping and social model principles.

Sober living↗

PubMed2026

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals↗

PubMed2026

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n = 5), support vector machines (n = 4), k-nearest neighbor (n = 3), decision trees (n = 3), random forests (n = 5), neural networks (n = 2), linear discriminant analysis (n = 1), and pre-trained CNNs (n = 1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n = 12 to n = 39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed2026

Efficacy of pharmacological and microbiota-based therapies in preclinical models of autism spectrum disorder: a systematic review.

BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental condition in which pharmacological and microbiota-targeted interventions are emerging as promising therapeutic avenues. Animal models are the main tool to investigate etiology, molecular mechanisms and screening for pharmacological therapies. Methodological differences, outcome measure variability, incomplete reporting, biological confounders, and overgeneralization of the results made evaluating innovative pharmacological agents challenging. These limitations in the field highlight a need for systematic and standardized research to reliably assess and translate pharmacological interventions from ASD animal models to human clinical relevance. SUBJECTS: This systematic review synthesized efficacy evidence for pharmacological and microbiota-based therapies across established ASD animal models. RESULTS: We identified 52 recent (2010-2025) studies that reported key ASD behavioral outcomes after pharmacological or microbiota-focused treatments. Interventions were grouped into therapeutic classes - including oxytocinergic agents, E/I balance therapeutic targets, metabolic drugs, cannabinoids, purine-based interventions and emerging targets - alongside microbiota-directed strategies such as probiotics, prebiotics, and fecal microbiota transplantation. By integrating effect directions and robustness across models, we identified most potential drug candidates, evaluated the efficacy of novel strategies, and recognized critical translational gaps. The reviewed studies demonstrate that ASD-like behavioral deficits in preclinical models can be modulated through interventions targeting diverse biological systems, including neurotransmission, neuroinflammation, metabolism, and the gut-brain axis. CONCLUSIONS: These findings support the multifactorial nature of ASD pathophysiology which arises from a network of interacting systemic processes rather than a single molecular defect. It could explain the limited success of traditionally narrowly targeted interventions and suggest a paradigm shift into a more systemic approach.

Animals↗

PubMed2026

Nimodipine in animal models of demyelination relevant to multiple sclerosis: a systematic review.

BACKGROUND: Multiple sclerosis (MS) is the most common inflammatory neurodegenerative disease in which axonal injury, neuronal death, and demyelination occur. Treatment for MS relapses remains limited, which alleviates acute loss of function but has no impact on long-term disability. This study aimed to perform a systematic review of the effects of nimodipine on experimental demyelination models, including experimental autoimmune encephalomyelitis (EAE) and Cuprizone models in rodents. METHODS: This study was conducted following the PRISMA statement. A systematic search was performed in PubMed, Scopus, the Cochrane Library, and Google Scholar. The primary outcome was EAE clinical disease severity (peak clinical score and/or cumulative disease burden). Secondary outcomes included relapse activity (when reported), histological myelin outcomes, oligodendrocyte lineage markers, neuroaxonal injury markers, and inflammatory readouts. Risk of bias was assessed using the SYRCLE tool. RESULTS: Out of 4660 results, 5 studies were included in the systematic review (four EAE studies and one cuprizone model). Nimodipine was administered using heterogeneous regimens (oral, intravenous, intraperitoneal, subcutaneous, or osmotic pump delivery; 1-30 mg/kg/day). The included studies reported the variable effects of nimodipine on relapse-related outcomes, myelination, inflammatory processes, and neuroprotection in the EAE model of MS. Across EAE studies, nimodipine generally reduced clinical disease severity or cumulative burden, although relapse-related outcomes were inconsistent. CONCLUSIONS: Preclinical evidence suggests that nimodipine may attenuate disease severity and demyelination and may promote repair-related processes in rodent models relevant to MS. However, to evaluate the clinical applicability of nimodipine in MS patients, well-powered, transparently reported preclinical replication and early-phase clinical studies are required before clinical translation.

Animals↗

PubMed2026

Rationale, design, and experiences from the vanguard phase of the bariatric surgery for the reduction of cardiovascular events (BRAVE) trial.

BACKGROUND: Observational studies suggest that metabolic/bariatric surgery (MBS) reduces mortality and major adverse cardiovascular events in patients with obesity, but adequately powered randomized trials (RCTs) are lacking. The Bariatric Surgery for the Reduction of Cardiovascular Events (BRAVE) trial was designed to address this evidence gap. METHODS: BRAVE is an investigator-initiated, multi-center, open-label RCT with blinded endpoint adjudication comparing MBS vs guideline-based medical weight management (MWM) in adults with obesity and high-risk cardiovascular disease (CVD). Eligible participants have a body-mass index ≥35 kg/m² or ≥30 kg/m² with type 2 diabetes or age >55 years, and prior myocardial infarction (MI), coronary intervention, heart failure (HF), atrial fibrillation (AF) with elevated CHA₂DS₂-VASc score, cerebrovascular disease, or peripheral arterial disease. Participants are randomized 1:1 to MBS (sleeve gastrectomy, Roux-en-Y gastric bypass, or duodenal switch) or MWM, which includes dietary, behavioral, and pharmacologic therapies. The primary outcome is the composite of all-cause death, MI, stroke, HF events, coronary revascularization, AF hospitalization, and renal events. A vanguard phase of 200 participants was implemented to optimize recruitment and logistics. RESULTS: As of October 2025, 2,514 individuals have been screened from 17 centers in Canada, Brazil, Italy and Spain, with 444 entered MBS work-up, and 200 have been randomized. The randomized cohort (mean age 59.8 years; 37% female; mean BMI 44.0 kg m⁻²) has high burden of hypertension (82%), diabetes (45%), coronary artery disease (44%), HF (39%), and AF (48%). Recruitment barriers were identified and addressed through targeted education and enhanced patient engagement. CONCLUSIONS: BRAVE is the first large RCT evaluating whether MBS safely reduces major cardiovascular events compared with medical therapy in high-risk patients with obesity. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05531474.

Humans↗

PubMed2026

Modelling peak microbial pollution events caused by combined sewer overflows in a source-to-sea system.

Predicting peak microbial pollution events in downstream coastal bathing waters caused by combined sewer overflows (CSOs) is essential for protecting public health. In urban areas, wastewater effluents, CSOs, and surface runoff can contribute to elevated microorganism loads to downstream waters. These pressures are likely to be intensified by growing population density and more frequent heavy rainfalls due to climate change. This study developed a process-based model to simulate Escherichia coli (E. coli) emissions, transport, and fate from the initial sources to coastal beaches. A three-year retrospective simulation (2017-2019) shows that E. coli concentrations in CSO discharges varied widely across the catchment (4.6 - 7.3 (log10 CFU 100 ml-1)). 99th percentile E. coli concentrations (4.0 (log10 CFU 100 ml-1)) at the inland water outlet were dominated by local CSO emissions, whereas 90th percentile E. coli concentrations (3.6 (log10 CFU 100 ml-1)) reflected cumulative upstream contributions from both CSO and effluent emissions. With the simulation accuracy of 89%, the model reliably reproduced the E. coli dynamics on the downstream beach and showed strong performance in representing peak concentrations based on Complementary Cumulative Distribution Function (CCDF) analysis. The process-based model enables quantitative tracking of source contributions and identification of pollution hotspots, providing support for mitigation measures. The study lays down a source-to-sea modelling framework for representing pollution transport across the aquatic continuum and provides a transferable tool for microbial pollution forecasting and climate adaptation planning.

Climate projection↗