Tag: pubmed

Biophys J. 2025 Nov 7:S0006-3495(25)00740-4. doi: 10.1016/j.bpj.2025.11.005. Online ahead of print.

ABSTRACT

A high degree of structural complexity arises in dynamic neuronal dendrites due to extensive branching patterns and diverse spine morphologies, which enable the nervous system to adjust function, construct complex input pathways and thereby enhance the computational power of the system. Recognition of pathological changes due to neurodegenerative disorders is of crucial importance due to the determinant role of dendrite morphology in the functionality of the nervous system. Nevertheless, direct noninvasive measurements to collect adequate structural data in a reasonable time are currently not feasible. Here, we present a stochastic coarse-grained framework based on first-passage analysis to infer key dendritic morphological features affected by neurodegenerative diseases-including the density and size of spines, the extent of the tree, and the segmental increase of dendrite shaft diameter towards the soma-from the statistical characteristics of a measurable temporary signal generated by tracers that have diffusively passed through the complex dendritic structure. Thus, our theoretical approach can provide a noninvasive route to link dendritic morphology with possible accessible readouts in neurodegenerative disease monitoring. As a prospective application, we discuss how externally detectable signals could be realized in practice, suggesting potential pathways toward experimental implementation.

PMID:41206512 | DOI:10.1016/j.bpj.2025.11.005

Mil Med. 2025 Nov 6:usaf549. doi: 10.1093/milmed/usaf549. Online ahead of print.

ABSTRACT

BACKGROUND: The U.S. Emergency Medical Service (EMS) system faces persistent workforce shortages. Thousands of military personnel transition out of service each year with EMS-related training, yet little is known about their roles or willingness to pursue civilian EMS careers. Despite low national unemployment rates among veterans, many remain underutilized in healthcare occupations. We aim to describe the current roles of nationally certified military EMS clinicians and assess their interest in transitioning to civilian EMS employment.

MATERIALS AND METHODS: We conducted a cross-sectional survey of National Registry-certified EMS clinicians actively serving in the U.S. military. Respondents recertifying between October 2021 and April 2022 were invited to complete a voluntary, one-time survey. The analytic sample included military-affiliated clinicians aged 18-85 who reported an EMS job role and responded to a question about interest in civilian EMS transition. Descriptive statistics multivariable Poisson regression with robust standard errors were used to characterize EMS roles and identify factors associated with transition interest. Referent groups for categorical variables were selected based on the subgroup with the largest number of respondents.

RESULTS: Among 1,937 included respondents, the median age was 32 years (interquartile range: 27-40), and most were male (66.6%) and White, non-Hispanic (58.3%). Respondents represented all major military branches, with the largest proportion from the Air Force (60.3%). Most held emergency medical technician certification (82.5%). Overall, 60.5% expressed interest in civilian EMS employment after separation. Transition interest was highest among clinicians in the Army (prevalence ratio: 1.23; 95% confidence interval: 1.11-1.36), Navy (1.31; 1.17-1.45), and Coast Guard (1.13; 1.01-1.27) compared to the Air Force. Those in educational or non-traditional roles had higher prevalence of interest than those in hospital-based roles, while older clinicians had significantly lower prevalence of interest.

CONCLUSION: Findings from this convenience sample suggest that a substantial portion of military EMS clinicians, particularly younger personnel and those affiliated with the Army, Navy, and Coast Guard, may be interested in transitioning to civilian EMS roles. While not representative of all military EMS personnel, these patterns highlight the potential utility of structured veteran-to-civilian EMS pathways. Future research using more representative sampling strategies is needed to confirm these trends and inform workforce development efforts.

PMID:41206493 | DOI:10.1093/milmed/usaf549

Int J Soc Psychiatry. 2025 Nov 8:207640251379130. doi: 10.1177/00207640251379130. Online ahead of print.

ABSTRACT

The study investigates how social media affects privacy perceptions among university students, combining a historical perspective on privacy with contemporary data on young adults; interactions with digital platforms. An online survey of 219 students (122 women and 97 men) assessed their awareness of social media’s overt and hidden influences on personal decisions and privacy concerns. Statistical analyses included t-tests, Wilcoxon-Mann-Whitney tests, χ² tests, and correlation measures. Results highlighted significant gender differences. Women were more aware of social media’s influence (54.9% vs. 38.1% of men) and expressed greater privacy concerns (41.8% vs. 36.1%). These findings emphasize the need for gender-sensitive educational initiatives to improve privacy awareness and inform policies to safeguard user rights. Further research is recommended to explore broader demographics for a comprehensive understanding of social media’s impact on privacy.

PMID:41206484 | DOI:10.1177/00207640251379130

Biostatistics. 2024 Dec 31;26(1):kxaf028. doi: 10.1093/biostatistics/kxaf028.

ABSTRACT

Disease mapping analyses the distribution of several disease outcomes within a territory. Primary goals include identifying areas with unexpected changes in mortality rates, studying the relation among multiple diseases, and dividing the analysed territory into clusters based on the observed levels of disease incidence or mortality. In this work, we focus on detecting spatial mortality clusters, that occur when neighbouring areas within a territory exhibit similar mortality levels due to one or more diseases. When multiple causes of death are examined together, it is relevant to identify not only the spatial boundaries of the clusters but also the diseases that lead to their formation. However, existing methods in literature struggle to address this dual problem effectively and simultaneously. To overcome these limitations, we introduce perla, a multivariate Bayesian model that clusters areas in a territory according to the observed mortality rates of multiple causes of death, also exploiting the information of external covariates. Our model incorporates the spatial structure of data directly into the clustering probabilities by leveraging the stick-breaking formulation of the multinomial distribution. Additionally, it exploits suitable global-local shrinkage priors to ensure that the detection of clusters depends on diseases showing concrete increases or decreases in mortality levels, while excluding uninformative diseases. We propose a Markov chain Monte Carlo algorithm for posterior inference that consists of closed-form Gibbs sampling moves for nearly every model parameter, without requiring complex tuning operations. This work is primarily motivated by a case study on the territory of a local unit within the Italian public healthcare system, known as ULSS6 Euganea. To demonstrate the flexibility and effectiveness of our methodology, we also validate perla with a series of simulation experiments and an extensive case study on mortality levels in U.S. counties.

PMID:41206482 | DOI:10.1093/biostatistics/kxaf028

Nucleic Acids Res. 2025 Nov 6:gkaf1146. doi: 10.1093/nar/gkaf1146. Online ahead of print.

ABSTRACT

The ProteomeXchange consortium of proteomics resources (http://www.proteomexchange.org) was established to standardize open data practices in the mass spectrometry (MS)-based proteomics field. Here, we describe the main developments in ProteomeXchange in the last 3 years. The six member databases of ProteomeXchange, spread out in three different continents, are the PRIDE database, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public. We provide updated data submission statistics, showcasing that the number of datasets submitted to ProteomeXchange resources has continued to accelerate every year. Through June 2025, 64 330 datasets had been submitted to ProteomeXchange resources, and from those, 30 097 (47%) just in the last 3 years. We also report on the improvements in the support for the standards developed by the Proteomics Standards Initiative, e.g. for Universal Spectrum Identifiers and for SDRF (Sample and Data Relationship Format)-Proteomics. Additionally, we highlight the increase in data reuse activities of public datasets, including targeted reanalyses of datasets of different proteomics data types, and the development of novel machine learning approaches. Finally, we summarize our plans for the near future, covering the development of resources for controlled-access human proteomics data, and for the support of non-MS proteomics approaches.

PMID:41206473 | DOI:10.1093/nar/gkaf1146

J Infect Dis. 2025 Nov 6:jiaf562. doi: 10.1093/infdis/jiaf562. Online ahead of print.

ABSTRACT

BACKGROUND: A promoter variant commonly found in sub-Saharan Africans and their descendants disrupts Duffy antigen (Fy) expression on erythrocytes, leading to the Fy-negative phenotype, and confers partial resistance to blood-stage Plasmodium vivax infection. In addition, the 125G→A substitution, rare in Africans, defines the Fya/Fyb polymorphism that can modulate vivax malaria risk in Amazonians. The combined effect of these FY polymorphisms on P. vivax infection risk remains little explored at the population level.

METHODS: We studied a household-based random sample of 1,737 Amazonians, with a well-balanced distribution of FY alleles, who were exposed to P. vivax transmission and contributed 7,878.9 person-years of follow-up. We fitted a multivariable zero-inflated negative binomial model to incidence data, assuming that zero counts could arise from individuals at risk who remained uninfected over 5 years of follow-up (“sampling zeroes”) or from not-at-risk individuals (“structural zeroes”).

RESULTS: Plasmodium vivax infections were heterogeneously distributed in the population, with 0 to 11 cases per person (average incidence, 25.8 cases/100 person-years at risk). We show that Fy-negativity remains a major malaria resistance trait in Amazonians and contributes significantly to the “structural zeroes” observed in P. vivax incidence data. Moreover, the differences in P. vivax infection risk associated with the Fya/Fyb polymorphism observed among young participants were attenuated with increasing age, most likely because more susceptible Fy(b+) individuals develop clinical immunity faster than less susceptible Fy(a+) individuals.

CONCLUSIONS: FY polymorphism appears to modulate the rate at which immunity to P. vivax develops in Amazonians, with clear clinical and public health implications.

PMID:41206468 | DOI:10.1093/infdis/jiaf562

Eur J Med Res. 2025 Nov 8;30(1):1091. doi: 10.1186/s40001-025-03200-3.

ABSTRACT

INTRODUCTION: Bone mineral density (BMD) is a key indicator of bone health, particularly in older populations, where lower BMD is linked to increased risk of osteoporosis and fractures. Metabolic factors like serum uric acid (UA) and high-density lipoprotein cholesterol (HDL-C) have emerged as possible determinants of bone health. The uric acid to HDL cholesterol ratio (UHR) may offer a new perspective on these metabolic influences. This study explores the association between UHR and femoral neck BMD, with a focus on non-linear relationships and subgroup variations by body mass index (BMI), age, and sex.

METHODS: The study used data from 2178 participants from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). UHR was calculated as the ratio of serum UA to HDL-C. BMD measurements were obtained using dual-energy X-ray absorptiometry (DXA) at the femoral neck. A two-piecewise linear regression model was applied to examine the non-linear relationship between UHR and BMD. Stratified analyses were conducted by BMI, gender, and age groups.

RESULTS: A significant inflection point was found at UHR 19. Below this threshold, UHR was positively associated with femoral neck BMD (β = 0.0054, p = 0.013), while above the threshold, the association was negative but not statistically significant (β = – 0.0016, p = 0.478). Stratified analysis revealed that the relationship between UHR and BMD remained significant among Mexican Americans even after adjusting for covariates (β = 0.0145, p = 0.012).

CONCLUSION: This study identifies a non-linear association between UHR and femoral neck BMD, with a key inflection point at UHR 19. These findings suggest that UHR could be a useful biomarker for bone health, especially in populations with higher metabolic risks. Further longitudinal studies are necessary to establish causality and explore potential interventions targeting UHR to improve bone health.

PMID:41206450 | DOI:10.1186/s40001-025-03200-3

J Infect Dis. 2025 Nov 5:jiaf563. doi: 10.1093/infdis/jiaf563. Online ahead of print.

ABSTRACT

The life-course impact of childhood tuberculosis (TB)-including its connection to frailty-remains poorly understood. We analyzed 8,459 adults ≥50 years in ELSI-Brazil (2015-2016), including 74 with self-reported TB before age 15. Frailty (phenotype) was assessed and compared using Poisson models before and after propensity-score matching (1:4; 283 controls); mediation tested chronic obstructive pulmonary disease (COPD). Frailty was more frequent with childhood TB (23.0% vs. 8.8%; p=0.001). After matching, childhood TB was associated with higher frailty prevalence (PR 2.52; 95% CI 1.43-4.44); mediation through COPD was small and not statistically significant. Findings support a life-course approach to TB care.

PMID:41206432 | DOI:10.1093/infdis/jiaf563

Eur J Pediatr. 2025 Nov 8;184(12):740. doi: 10.1007/s00431-025-06578-8.

ABSTRACT

This study aimed to systematically identify the key characteristics of retracted articles in pediatric literature and explore the patterns and reasons of pediatric retraction from 1995 to 2024. We searched PubMed and Retraction Watch databases to identify all retracted publications in the field of pediatrics. After the screening process, data were extracted into Excel. Statistical analysis was conducted using Jamovi and Excel. A correlation matrix was used for the important retraction-related factors. After screening, 590 unique retracted pediatric articles were included, with most of them, 572 (96.9%), having retraction notices available; 516 (87.5%) published as open access; 433 (73.4%) from Asia-mostly China; 348 (59%) retracted by the publisher; 301 (51.0%) published by Hindawi; 275 (46.6%) observational studies; and 221 (37.5%) retracted due to misconduct. Articles with four authors showed the highest retraction rate, and the retraction rate generally decreased as the number of authors increased. Most retractions occurred in 2023. The most common pediatric age group included in the retracted papers was children. The median H-index of authors of retracted papers was 8 for first authors and 10 for senior authors. The median time from submission to acceptance of retracted papers was 50 days and that from publication to retraction was 15 months. Additionally, time to retraction was positively correlated with the journal’s impact factor (r = 0.106, p = 0.015) and the citation count (r = 0.213, p < 0.001) but showed no significant correlation with time to acceptance (r = – 0.019, p = 0.675).

CONCLUSION: The increasing number of retracted pediatric papers reflects a growing concern with a complex pattern and various determinants. Researchers and publishers should adopt strong regulations and guidelines to improve the integrity of scientific research, especially pediatric research.

WHAT IS KNOWN: • Retractions in biomedical research have been increasing over the past decades, often due to research misconduct, plagiarism, or data fabrication. • Previous studies have analyzed retraction patterns across several medical specialties, but pediatric research remains underexplored despite its ethical and clinical sensitivity.

WHAT IS NEW: • This is the most comprehensive analysis of retracted publications in pediatric literature, covering 590 articles from 1995 to 2024 and revealing distinct geographic, temporal, and publisher- and author-related patterns. • The study highlights a strong dominance of retractions from Asia-especially China-and shows that research misconduct and peer-review manipulation are the leading causes, underscoring the urgent need for stricter integrity measures in pediatric research.

PMID:41206416 | DOI:10.1007/s00431-025-06578-8

J Neurol. 2025 Nov 8;272(12):754. doi: 10.1007/s00415-025-13439-9.

ABSTRACT

OBJECTIVE: The objective of this study is to present a report from the Big Multiple Sclerosis Data (BMSD) statistics workshop (Bari – Italy, June 2023) which focused on advanced statistical approaches for real-world data (RWD) analyses in multiple sclerosis (MS). The report emphasises the application of these approaches in predicting individual treatment response, assessing comparative effectiveness and safety of therapies and their sequences, and harmonizing data for large-scale federated analyses.

METHODS: The BMSD network, comprising five national registries and the international MSBase database (> 350,000 total patients), convened in June 2023 in Bari (Italy) to review methodological advances in RWD analysis. Experts discussed strengths, limitations, and regulatory implications of frequentist, Bayesian, and machine learning (ML) approaches, with case studies on treatment response modelling, comparative effectiveness, safety surveillance, and Common Data Model (CDM)-based federated learning.

RESULTS: Bayesian and ML techniques, integrated with causal inference frameworks, can improve personalized predictions of treatment benefit and risk by using high-dimensional longitudinal data. Propensity score-based methods and marginal structural models remain essential for minimizing confounding in comparative analyses, but require rigorous diagnostics and sensitivity analyses. Adoption of a CDM facilitates harmonization of heterogeneous datasets, while federated learning enables privacy-preserving, multi-jurisdictional collaboration. Together, these innovations address key challenges in studying treatment sequences, rare adverse events, and underrepresented patient groups.

CONCLUSIONS: This workshop report highlights how advanced statistical and computational methodologies enhance the robustness, interpretability, and regulatory relevance of MS RWD studies. By promoting the integration of complementary statistical and computational approaches within harmonized data infrastructures, the BMSD network is positioned to accelerate the translation of real-world evidence into precision medicine for MS.

PMID:41206399 | DOI:10.1007/s00415-025-13439-9