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PubMed2026

Umbilical Cord-Derived Cell-Based Interventions for Bronchopulmonary Dysplasia and Related Complications in Preterm Infants: A Bayesian Sparse-Data Meta-Analysis.

Bronchopulmonary dysplasia (BPD) is a major complication of prematurity with limited disease-modifying therapies. We evaluated umbilical cord-derived cell-based interventions for BPD and related complications in preterm infants. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020-based systematic review and meta-analysis were registered in PROSPERO. PubMed, Cochrane Library, Web of Science, CNKI, and Wanfang were searched from inception to June 14, 2026. Comparative clinical studies of umbilical cord-derived cell-based interventions in preterm infants at risk of or diagnosed with BPD were included. Outcomes included BPD, BPD severity, death, persistent pulmonary hypertension of the newborn (PPHN), patent ductus arteriosus (PDA), intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), late-onset sepsis (LOS), and adverse events (AEs). Bayesian random-effects meta-analysis used a binomial-normal hierarchical model to estimate pooled odds ratios (ORs), 95% credible intervals (CrIs), prediction intervals, and heterogeneity. Twelve studies were included. Umbilical cord-derived cell-based interventions showed a possible protective effect on overall BPD (OR, 0.48; 95% CrI, 0.14-1.20). Stronger associations were observed for severe BPD (OR, 0.17; 95% CrI, 0.01-0.85), moderate or severe BPD (OR, 0.28; 95% CrI, 0.09-0.70), and ROP stage ≥3 (OR, 0.17; 95% CrI, 0.02-0.65). No conclusive benefit or harm was observed for death, PPHN, PDA, IVH, NEC, or LOS. No treatment-related serious AEs were identified. However, prediction intervals were generally wide, and the certainty of evidence was low to very low for most outcomes. Umbilical cord-derived cell-based interventions may reduce the risk of moderate or severe BPD in preterm infants, with an additional potential benefit for ROP stage ≥3. Current evidence remains limited, and larger randomized trials with standardized outcomes and long-term follow-up are needed.

Humans↗
PubMed2026

Operationalizing Local Ecological Knowledge for Aquatic Biodiversity Conservation: A Systematic Review and Management Framework.

Effective conservation and management of aquatic biodiversity is severely constrained by the absence of long-term ecological data in small-scale, tropical, and data-poor fisheries, where roughly one-quarter to one-third of freshwater fish species and 37.5% of elasmobranchs are threatened with extinction once Data Deficient species are accounted for. Conventional monitoring and stock-assessment tools are often financially and technically inaccessible in these systems, leaving managers without the evidence needed to prioritize conservation action or implement precautionary governance. Local Ecological Knowledge (LEK) is a largely underutilized resource for natural resource management that can provide temporal depth, spatial resolution, and species-specific ecological insights unavailable from scientific records. We conducted a systematic review and bibliometric synthesis of 60 peer-reviewed studies (1997-2025) applying LEK to assess fish conservation status, examining how, where, and through what methods this knowledge has been used. Our analysis identifies four complementary pathways through which LEK informs conservation management: reconstructing multi-decadal population changes, documenting spatial contraction and habitat loss, detecting extreme rarity and local extirpation, and characterizing intrinsic sensitivity to exploitation based on life-history traits. Despite growing methodological rigor, freshwater systems and African fisheries remain critically underrepresented, and formal integration of LEK into fisheries governance and biodiversity assessment remains the exception rather than the rule. We propose a practical three-stage framework to operationalize LEK within existing management and conservation systems. Recognizing fishing communities as legitimate co-producers of ecological knowledge is both scientifically necessary and an equity imperative for achieving global biodiversity commitments under the Kunming-Montreal Global Biodiversity Framework.

Biodiversity↗
PubMed2026

Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review.

AIM: To describe contemporary peer-reviewed literature on artificial intelligence in nurses' clinical decision-making. METHODS: An umbrella review of literature reviews. DATA SOURCES: Four major databases were searched for reviews published between 2019 and 2024. RESULTS: Sixteen literature reviews reported on 965 nursing artificial intelligence primary studies. The studies focused on technology development and emerging performance evaluations, whilst real-world testing or implementation in nursing clinical settings was rare. Rigorous comparative analyses were lacking. While artificial intelligence demonstrates promise in decision-making, challenges such as a lack of controlled studies, algorithmic bias, limited reproducibility and insufficient clinical trials hinder its practical impact. Ethical concerns, transparency and patient data privacy issues pose barriers to AI integration in nursing practice. Ethical and legal guidelines for patient privacy are needed and should be taught along with AI literacy training for nurses. CONCLUSIONS: Artificial intelligence has the potential to enhance clinical nursing decision-making, although evidence is limited by too few examples of nurse participation during development. Underutilisation in administrative nursing functions hinders implementation. Nurses should assume a central role in the design and development of AI applications to ensure that these technologies address the realities of nursing practice. With such improvements, artificial intelligence can transform nursing practice, improve nurses' clinical decision-making and ultimately enhance consumer healthcare outcomes. PATIENT OR PUBLIC INVOLVEMENT: No Patient or Public Involvement. REPORTING METHOD: While there is no reporting checklist for umbrella reviews, the PRISMA guide for systematic reviews was followed.

Artificial Intelligence↗
PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗
PubMed2026

Pedagogical Efficacy of LLM-Generated Synthetic Data Versus Real-World Clinical Records: A Randomized Controlled Non-Inferiority Trial.

BACKGROUND: Expert-reviewed clinical cases generated by large language models (LLMs) may supplement case resources in medical education, but their short-term educational performance relative to real-case-derived teaching materials remains uncertain. We compared immediate post-training test performance after teaching with the two types of case materials and assessed non-inferiority against a prespecified margin. METHODS: We conducted a prospective, parallel-group, randomized non-inferiority trial. Through the Wenjuanxing online platform, participants were randomized 1:1 to learn with either real-case-derived teaching cases compiled by clinicians and reviewed by experts or AI-generated clinical cases produced by Gemini 3.0 Pro from fully de-identified matched real cases and reviewed by three senior general surgery specialists with full-professor rank. The primary outcome was the total score on an independent 10-item immediate post-training test (0-10 points), with a prespecified non-inferiority margin of -0.5 points. Secondary outcomes included the training-phase performance score, learning efficiency index, single-item mental effort rating, case realism, and case-source judgment. RESULTS: A total of 403 participants were randomized, of whom 386 were included in the modified intention-to-treat analysis: 192 in the real-case group and 194 in the AI-generated case group. The mean post-training test score was 4.95 (SD, 3.35) in the real-case group and 4.61 (SD, 3.35) in the AI-generated case group. The mean difference (AI-generated minus real-case group) was -0.335 points (95% CI, -1.006 to 0.337). Because the lower bound of the confidence interval was below the prespecified non-inferiority margin of -0.5 points, non-inferiority was not demonstrated (one-sided P = 0.314). No significant between-group differences were observed in the training-phase performance score, learning efficiency index, or single-item mental effort rating. AI-generated cases received lower realism ratings for Level 3 cases. The proportion of participants with at least one high-confidence completely incorrect response was 1.6% in the real-case group and 2.1% in the AI-generated case group. CONCLUSIONS: In this short-term, text-based online case-learning setting, no statistically significant between-group difference was observed in immediate post-training test performance; however, non-inferiority of AI-generated clinical cases relative to real-case-derived teaching materials was not demonstrated.

Humans↗
PubMed2026

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↗
PubMed2026

Temporal Trends and Spatial Variation in Preterm Prelabour Rupture of Membranes: A Population-Based Study.

OBJECTIVE: To describe the temporal trends in Preterm prelabour rupture of membranes (PPROM) in metropolitan France and the geographical distribution at the administrative division level. DESIGN: Exploratory population-based study using administrative data of the French National Health Data System. SETTING: Metropolitan France, 2015 to 2023. POPULATION: Pregnancy with a diagnosis of PROM before 37 SA. METHODS: Annual crude incidence of PPROM was calculated by dividing the number of pregnancies with PPROM diagnosis by the number of live births recorded during the same period. Annual trend was estimated by a binomial negative mixed model. Smoothed standardised incidence ratios were estimated based on a BYM2 model, which accounts for spatial variability between departments. MAIN OUTCOME: PPROM cases, defined as pregnancies with first hospitalizations with a diagnosis of PROM before 37 weeks. RESULTS: Over the study period, we included 150 615 PPROM cases representing 16 735 (±596) per year. Incidence of PPROM cases showed an ascending trend over time (incidence rate ratio 1.023 per year; 95% CI: 1.017-1.030) with an annual crude incidence ranging from 2.2% in 2015 to 2.7% in 2023. A decrease in the incidence was observed in 2020 relative to other years (incidence rate ratio 0.903, 95% CI: 0.887-0.920). A map of smoothed SIRs of PPROM cases at the French administrative division level revealed geographical inequalities. CONCLUSIONS: This first population-based study describing PPROM cases in metropolitan France paves the way for further studies to explore environmental hypotheses. Identifying temporal and geographical disparities in PPROM incidence is relevant to public health policy and practice as such disparities argue for the development of targeted prevention strategies in high-risk areas.

French national health data system↗
PubMed2026

Cancer statistics for Asian American, Native Hawaiian, and Pacific Islander people, 2026.

BACKGROUND: Cancer statistics for Asian American and Native Hawaiian and Pacific Islander (NHPI) people are usually aggregated, masking substantial variation within this heterogeneous population. Herein, the American Cancer Society reports cancer incidence and survival for 8 Asian American and 3 NHPI ethnic groups. METHODS: The authors used population-based cancer registry data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program, for Asian American and NHPI ethnic groups from 2000 through 2022. RESULTS: During 2018-2022, overall cancer incidence ranged from 218.3 per 100,000 Kampuchean people to 474.5 per 100,000 Native Hawaiian people, which was 1.5 times higher than the rate for the aggregated Asian American and NHPI population (307.3 per 100,000). High incidence among Native Hawaiian people is largely driven by the highest rates of female breast, colorectal, and prostate cancers, whereas infection-related cancers were highest among Asian American ethnic groups. For example, liver and stomach cancer incidence is highest among Vietnamese (22.2 per 100,000) and Korean people (17.8 per 100,000), respectively, both of which were nearly twice that in Native Hawaiian people (12.9 and 9.6 per 100,000, respectively). Native Hawaiian and Samoan women are twice and 3 times as likely, respectively, to be diagnosed with uterine corpus cancer as aggregated Asian American and NHPI women or White women. Five-year relative survival ranges from 42% in Laotians to 74% in Asian Indians/Pakistanis, with largest differences for colorectal (43% in Laotians to 72% in Asian Indians/Pakistanis) and prostate (63% in Kampucheans to 97% in Japanese) cancers. CONCLUSIONS: Wide variation in cancer risk within the Asian American and NHPI population highlights the critical need for disaggregated data to effectively target cancer prevention and control interventions.

Adolescent↗
PubMed2026

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals↗
PubMed2026

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans↗
PubMed2026

Plasma proteomic profiling characterizes candidate biomarkers of perimesencephalic non-aneurysmal subarachnoid hemorrhage.

OBJECT: This study aims to explore the plasma proteomic profiles of angiographically confirmed pmSAH and aSAH, and to identify candidate protein biomarkers for discriminating these subtypes on a biological level. METHODS: The differentially abundant proteins of plasma samples from patients with pmSAH (n = 30) and aSAH (n = 30) were analyzed by data-independent acquisition proteomics, and candidate biomarkers were screened. RESULTS: 291 candidate biomarkers were obtained that could be used to distinguish pmSAH patients from aSAH patients, among which 76 were upregulated and 215 were downregulated in pmSAH. Subsequently, the 10 candidate biomarkers were validated by enzyme-linked immunosorbent assay in a validation cohort of 72 subjects. ORM1, ORM2, HP and NMNAT1 were specifically down-regulated in the pmSAH group, while ANP32A was specifically up-regulated in the pmSAH group. FGL2 was specifically up-regulated in the aSAH group. The combined model of ORM2, HP and ANP32A had the best discriminative power (AUC = 0.880). CONCLUSIONS: This study identified ORM2, HP, and ANP32A as candidate biomarkers reflecting biological differences between pmSAH and aSAH. SIGNIFICANCE: Although some proteomic studies have analyzed aneurysmal subarachnoid hemorrhage, to date, there have been no reports on the circulating proteomic analysis of pmSAH. Comparative analysis of the circulating proteomic differences between pmSAH and aSAH may not only help understand the causes of pmSAH, but also contribute to a deeper understanding of mechanisms showing how pmSAH differs from the formation and rupture mechanisms of intracranial aneurysms.

Humans↗
PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗
PubMed2026

Tele-Oncology in the Post-Pandemic Era: Clinical Integration, Access Disparities and Medico-Legal Accountability.

PURPOSE OF THE REVIEW: Tele-health has evolved from a marginal tool confined to rural populations and selected follow-up programs into a structurally integrated component of modern cancer care. Prior to COVID-19, its adoption was constrained by regulatory fragmentation, non-uniform reimbursement, and licensure barriers. This narrative review evaluates the evolutionary integration of tele-health in oncology post-COVID-19, examines digital disparities across patient populations, and addresses the medico-legal implications of this integration, with the objective of providing a comprehensive and clinically actionable framework for the governance of virtual oncology care. RECENT FINDINGS: The pandemic acted as a global catalyst, driving telehealth to over 50% of oncology outpatient encounters in some settings, before stabilising post-pandemic at approximately 10-20% of consultations within hybrid care models. Evidence supports meaningful clinical benefits - improved access to specialist services, reduced travel burden, and sustained continuity of care - with outcomes comparable to in-person care in postoperative follow-up, symptom monitoring, and survivorship. However, persistent disparities in device availability, connectivity, and digital literacy disproportionately affect older, rural, and socioeconomically disadvantaged patients, raising the risk that geographic inequalities are replaced by technological ones. From a medico-legal standpoint, the remote modality does not modify the applicable standard of care, yet restricted physical examination and reliance on patient-reported data introduce risks of diagnostic delay and incomplete clinical assessment, with direct implications for professional liability, data protection under HIPAA and GDPR, cross-border licensure, and multi-party accountability across physicians, institutions, and technology providers. Tele-oncology has become a permanent structural feature of modern cancer care, offering demonstrable benefits in access, continuity, and patient satisfaction. Yet its integration has been uneven, its governance remains fragmented, and its medico-legal landscape is still evolving. Realising the full potential of virtual oncology care - equitably and safely - requires coherent regulatory frameworks, sustained investment in digital infrastructure, and explicit attention to the populations at greatest risk of being left behind.

Humans↗
PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗
PubMed2026

A 20-Y Analysis of Motorcycle Trauma After Helmet Law Repeal.

INTRODUCTION: After Arkansas repealed its universal motorcycle helmet law in 1997, helmet use decreased and motorcycle-related injuries and fatalities increased. Long-term clinical and population-level impacts of this policy change remain incompletely characterized. This study integrates statewide crash and fatality data with trauma center data to evaluate trends in helmet use, injury severity, and mortality at scene and hospitalization. METHODS: We retrospectively reviewed motorcycle-related admissions and emergency department deaths at the state's only adult level I trauma center from 2004 to 2023 across three periods: 2004-2006, 2013-2015, and 2021-2023. Demographics, helmet use, injury severity, and outcomes were assessed. Logistic regression evaluated associations between helmet use, severe head injury (Abbreviated Injury Scale &#x2265;3), and inhospital mortality. Fatality data were obtained from the National Highway Traffic Safety Administration, and crash-level data (2015-2023) were obtained from the State Department of Transportation. RESULTS: Among 1104 trauma admissions, annual admissions nearly tripled over time, with nonhelmeted riders representing 64%-72%. Helmet use was independently associated with lower odds of severe head injury (odds ratio 0.48, P < 0.001). Nonhelmeted riders had higher on-scene fatality risk (relative risk 1.21). Severe head injuries increased and were strong predictors of inhospital mortality. Population-adjusted motorcycle fatality rates rose from 2.34 to 3.18 per 100,000 residents by 2021-2023. CONCLUSIONS: Motorcycle fatalities and severe head injuries increased during the postrepeal period and were associated with helmet nonuse and severe head trauma. Clinical and statewide data show consistent associations among helmet nonuse, severe head injury, and prehospital and in-hospital mortality, highlighting helmet use as a target for injury prevention policy.

Acute brain injury↗
PubMed2026

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to &#x223c;300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq&#x2122; PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans↗
PubMed2026

Infant Dietary Patterns and Early Childhood Weight Outcomes: A Secondary Analysis from the Starting Early Program Trial.

BACKGROUND: The Starting Early Program (StEP) promotes healthy nutrition during early life and leads to healthier child weight, but whether dietary patterns contribute to weight or mediate StEP weight outcomes has not been studied. OBJECTIVES: This secondary analysis identified infant dietary patterns in StEP, determined associations between dietary patterns and child weight outcomes, and examined whether dietary patterns mediated the relationship between StEP and child weight. METHODS: Data were from 377 mother-infant dyads in a randomized trial testing the efficacy of StEP. Dietary patterns at 10 months were identified using latent class analysis. Child weights were abstracted from medical records at 12, 24, and 36 months. Associations between infant dietary patterns and weight-for-age z-score (WFAz) and likelihood of being classified as overweight (WFA &#x2265;85th percentile) were assessed using linear and logistic multivariable regression models. Mediation was used to assess intervention effects on WFAz via impacts on infant dietary patterns. RESULTS: Four classes of infant dietary patterns were identified: Breastfed-High variety, Formula fed-High variety, Formula fed-Low variety, and Mixed fed-Low variety. Compared to the Breastfed-High variety class, infants in the Formula fed-Low variety class had higher WFAz and were more likely to be classified as overweight at 24 and 36 months. Participation in StEP increased membership in Breastfed-High variety, which mediated the association between StEP and lower WFAz at 24 months. CONCLUSIONS: Infant dietary patterns were identified, and some were associated with child overweight. StEP was associated with a dietary pattern most consistent with guidelines, which mediated intervention effects on child weight.

Humans↗
PubMed2026

Global Seroprevalence of Q Fever Antibodies to Coxiella burnetii in Children and Adolescents : A Systematic Review and Meta-analysis.

OBJECTIVE: To comprehensively determine global estimates of Q fever seroprevalence in children and adolescents by conducting a systematic review and meta-analysis. DATA SOURCES: Searches of published articles in MEDLINE, Embase and Scopus databases were conducted from inception until February 2025. STUDY SELECTION: Cross-sectional studies reporting seroprevalence of Q fever/ Coxiella burnetii antibodies, using any established laboratory test, in any population of healthy children and adolescents <20 years old were included. The quality of eligible articles was assessed using a modified Newcastle-Ottawa Scale. DATA EXTRACTION: Data from eligible articles were extracted using a standardized form, which included year of publication, year(s) the study was conducted, numbers of antibody-positive cases/specific population, age, country, geographic region, serology test used and antibody titer cutoff value. DATA SYNTHESIS: DerSimonian and Laird random effects models were used to calculate pooled seroprevalence estimates and 95% confidence intervals in data from 41 eligible articles reporting 42 studies comprising 9841 children and adolescents. Q fever seroprevalence was observed in multiple countries across 7 geographic regions, and varied markedly between countries and regions, with the highest estimate observed by an individual country in Ethiopia (45%) and by region in the Middle East (14%). Seroprevalence estimates were higher in older children and adolescents &#x2265;10 years (15%) compared with younger children <10 years of age (8%). CONCLUSION: Despite varying geographical prevalence, our findings demonstrate that widespread exposure to Q fever antigens occurs across multiple global regions in children and adolescents to potentially serious C. burnetii infection, indicating that diagnostic surveillance and preventive measures should be considered in both endemic and previously unreported areas.

Humans↗