Youth (16-24 years) experiencing chronic musculoskeletal pain (CMP) value access to digitally-supportive care. Adopting a three-phase design, we aimed to identify and validate youth's preferences for digital health solutions (DHSs) to support their CMP self-care and measure their preferences for artificial intelligence (AI)-enabled digital coaches and perceived risks of harm. Phase 1 involved focus groups with 20 youth experiencing CMP, applying content analysis to explore the attributes they consider when choosing digitally-supportive care. Phase 2 involved a two-round eDelphi (n=20 youth) to validate attributes identified in Phase 1, rank the importance of digital coach-related attributes, and identify risks of harm with digitally-supportive CMP care. Phase 3 involved two discrete choice experiments (n=41 youth) to measure preferences for digital coach-related attributes and risks of harm. Phase 1 produced 31 discrete attributes of DHSs (11 digital coach-related). Phase 2 validated 31 attributes and identified six risks of harm. Phase 3 identified three most preferred digital coach-related attributes (sample mean[SD] weights representing relative importance): 'Generates a pain self-care plan' (19·6[14·5]%); 'Learns my preferences for my pain self-care' (15·9[12·9]%); and 'Supports my healthcare visits' (11·1[12·4]%). The three most concerning risks of harm were: 'Quality of pain care advice and guidance' (31·8[17·3]%); 'Information being consistent with advice from my healthcare team' (25·8[17·5]%); and 'Data security protections' (14·8[17·6]%). Youth consider a range of attributes and potential harms of DHSs to support their CMP care; a subset appears to be most important. These attributes and risks of harm should be considered in co-design of digitally-supportive CMP care for youth. PERSPECTIVE: The results identify that a subset of digital coach-related attributes and risks of harm dominate youth's preferences for digitally-supportive chronic musculoskeletal pain care. These attributes and risks of harm should be considered in co-design of digital health solutions, and in positioning a solution within a clinical care ecosystem.

Prognostic biomarker panels identified through bulk sequencing approaches have shown utility in localized prostate cancer but are limited by underlying molecular heterogeneity. Spatial transcriptomics offers a complementary approach to investigate spatial gene expression patterns and the tissue- and cell-type-associated localization of their constituent biomarker genes. Using publicly available data, we analyzed biomarker genes from four prognostic panels (Oncotype DX, Prolaris, Decipher, and ProClass-an in-house candidate panel) across 37 tissue sections from two patients with localized high-grade disease. Analyses were performed to quantify biomarker gene abundance across tissue sections using the Visium Spatial Platform, assess spatial variability using global Moran's I, and identify biomarker localization to specific biological niches through spatial co-expression network analysis. Tissue type composition varied markedly between tissue sections. Several genes from Oncotype DX (KLK2, AZGP1, TPM2, GSN, FLNC, COL1A1) and Decipher (ANO7, MYBPC1) were consistently spatially variable across the samples (mean global Moran's I > 0.1). In contrast, cell cycle-associated genes, predominantly in the Prolaris panel, exhibited weak expression limited to a small proportion of sample spots. ProClass genes also showed limited expression, impeding robust spatial analysis. Weighted gene co‑expression network analysis identified spatial modules closely aligned to histopathological annotations, linking most Oncotype DX genes to stromal networks, whereas Decipher genes spanned diverse networks. Spatial transcriptomics revealed significant variability in biomarker gene expression across highly heterogeneous prostate cancer tissue sections from two patients, providing proof-of-concept for its potential use in prognostic biomarker panel research. Several Oncotype DX genes were notably spatially variable, predominantly localizing to stromal regions, whilst the majority of biomarker genes from other panels exhibited non-spatial patterns. Although low-abundance genes may be impacted by current technological limitations, integrating spatial data into biomarker research holds promise for developing "spatially robust" panels to provide reliable prognostic information amidst molecular heterogeneity in prostate cancer.

A new estimator with Monte Carlo simulation and theoretical framework: Its implementations in the sports and radiation sciences

Self-supervised exceptional prototypical network for few-shot grading of gastric intestinal metaplasia.

This study aims to detect potential signals of interstitial lung disease (ILD) associated with antiandrogen agents by employing a multi-algorithm, dual-level (Standardized MedDRA Query [SMQ] and Preferred Term [PT]) framework combined with the updated FDA Adverse Event Reporting System (FAERS) dataset (through 2024). We analyzed data from the fourth quarter of 2003 through the fourth quarter of 2024. Disproportionality analysis employed four complementary methods: reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM). Signals were evaluated at both the SMQ and PT levels. A total of 761 cases of ILD associated with antiandrogen agents were analyzed. We identified seven agents showing positive ILD signals in FAERS. They were apalutamide, bicalutamide, degarelix, darolutamide, flutamide, goserelin, and nilutamide. Among them, darolutamide stood out with a newly identified pharmacovigilance signal, whereas no such signal had been detected in prior FAERS analyses. Bicalutamide exhibited positive signals for both "Interstitial lung disease" and "Pulmonary fibrosis" at the PT level, a pattern not seen with the other drugs. Japan contributed the most reports (61.37%); death and hospitalization were the most common outcomes (54.80%). Female-related ILD reports were mainly observed with goserelin and leuprolide used for breast cancer. This study identified seven antiandrogens with pharmacovigilance signals, among which the signal for darolutamide was detected for the first time. The dual-level analysis generated the hypothesis that bicalutamide-associated ILD may have a greater tendency to evolve into a fibrotic phenotype. The observed Japanese predominance in reporting likely reflects regulatory and reporting-related factors rather than a true biologic excess risk. Female-related ILD reports represent solely a signal-generating observation. These findings are exploratory and require further validation.

The ongoing epidemiological and nutritional transitions impose a significant socioeconomic burden on health systems worldwide. However, evidence integrating population-based biological and lifestyle factors with direct economic valuation in mixed public-private health systems is limited in middle-income countries. Therefore, we analyzed factors associated with outpatient utilization and estimated direct costs (adjusted for International Dollars at Purchasing Power Parity - Int$ PPP) in a representative sample for São Paulo City, Brazil, from 2003 to 2015. Pooled cross-sectional observational study, with quantitative analyses of microdata from the São Paulo Health Survey 2003-2015 (ISA-Capital), combined with administrative data from the Brazilian Unified Health System Department of Informatics (SIA-SUS/DATASUS) and the Brazilian Hierarchical Categorization of Medical Procedures (CBHPM). A two-part regression model (logit and generalized linear model) and average marginal effects (ME) were estimated to identify factors associated with the likelihood of utilization and the direct costs of outpatient services. Utilization and costs were higher in more recent survey years. Socioeconomic factors, notably schooling (ME = 13.28, representing a 43.4% relative increase from the sample mean, p < 0.001), showed a stronger statistical association with direct costs than clinical conditions such as high blood pressure (ME = 10.48, 34.2% relative increase, p < 0.001) and overweight (ME = 5.79, 18.9% relative increase, p < 0.001). Female sex (ME = 3.53, 11.5% relative increase, p = 0.004) and private health insurance ownership (ME = 2.99, 9.8% relative increase, p = 0.021) were also positively associated with the outcomes. Our findings suggest that in the urban context of São Paulo, socioeconomic factors are primarily associated with the outpatient economic burden. Therefore, prioritizing equitable health policies targeting socioeconomically vulnerable groups, aiming to increase outpatient access and utilization, alongside early cardiometabolic risk management, may represent important strategies to strengthen the financial sustainability of Brazil's health system while improving population health.

Chronic Kidney Disease of unknown etiology (CKDu) is a major public health concern in several agricultural regions of Sri Lanka. In areas with a high prevalence of CKDu, elevated concentrations of fluoride and water hardness have been consistently reported in domestic wells, along with emerging evidence of cyanotoxin contamination. This study investigated the potential renal toxicity associated with environmentally relevant concentrations of fluoride, water hardness, and microcystin-LR (MC-LR) using a zebrafish (Danio rerio) model. Twenty groundwater samples were collected from the CKDu-endemic Padaviya region in the North Central Province. Mean fluoride and total hardness concentrations were 1.12 ± 0.64mgL-1 and 424.2 ± 126.1mgL-1, respectively, while MC-LR was detected in 45% of the samples (mean: 0.96µgL-1). Zebrafish embryos (2h post fertilisation) were exposed to the concentrations reflecting maximum and minimum field observation values. Single exposures to fluoride, hardness, and MC-LR resulted in moderate mortality and developmental abnormalities, whereas combined exposure produced significantly higher mortality, 50.0 ± 1.15% (p < 0.05), and increased incidence of oedema, spinal curvature, and growth retardation in larvae. Histopathological examinations of larvae exposed to the combined treatment revealed noticeable pronephric alterations, including tubular vacuolation, cellular swelling, and inflammation indicative of renal damage. Chronic exposure to zebrafish resulted in significant upregulation in Kidney Injury Molecule (KIM-1) gene expression, representing renal tubular injury. These findings suggest that the combined chronic exposure to multiple well water contaminants may induce nephrotoxic effects at concentrations relevant to CKDu-endemic surroundings. Although the results do not establish direct causation, they highlight the importance of considering mixture toxicity in environmental risk assessment and drinking-water management in CKDu-affected regions to address the health issue.

Universal developmental processes offer a window on the role of culture. The present study analyzes differences in the amount and timing of sleep behavior for 419 children from 6 months to 7-8 years of age, as well as aspects of the developmental niches that promote or discourage specific sleep patterns. Samples were recruited in seven different cultural groups of European origin, in Australia, Italy, the Netherlands, Poland, Spain, Sweden, and the United States. Diary data, recorded over seven consecutive days by parents, reveal significant and powerful sample differences in total sleep per 24 hr: For example, sample means at age 6 months ranged from 12.70 hr (Spain) to 15.10 hr (the Netherlands); at 7-8 years they ranged from 10.0 hr (Italy) to 11.12 hr (the Netherlands). Other differences include within-sample variation in total sleep, time of nocturnal sleep onset, the incidence of cosleeping, and marginally, the consolidation of sleep into nighttime hours. Semistructured interviews topically coded to understand parents' culturally shared ideas and practices about the regulation of sleep. Major sample differences were found in four key areas: rest and regularity, bedtime routines, cosleeping, and family adaptation. Cultural variations in these parents' ethnotheories generally correspond to the observed sample difference in children's sleep. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

PTSD symptoms and firearm storage practices among adults in the United States: Examining trauma history subgroups.

This study aims to assess the spectrum of adverse events (AEs) associated with denosumab using in male patients with osteoporosis, leveraging the FDA Adverse Event Reporting System (FAERS) database from the Q3 2010 to Q4 2024. Four disproportionality analysis methods-reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayesian geometric mean (EBGM) were applied to detect denosumab-associated AEs. Clinical priority was assigned to signals by scoring five features using a rating scale. Among 3370 AEs associated with denosumab in male osteoporosis patients, general disorders and administration site conditions, skin and subcutaneous tissue disorders, and metabolism and nutrition disorders showed positive signals at the system organ class (SOCs) level. At the preferred term (PT) level, the most frequently reported AEs included back pain, arthralgia, osteonecrosis of jaw, and hypocalcemia. Notably, a comparative analysis with female patients delineated a distinct male-specific safety profile, characterized by stronger signal intensity for AEs such as hypocalcemia, pain in extremity, pneumonia, increased blood parathyroid hormone, and chronic obstructive pulmonary disease. This study comprehensively characterizes the safety profile of denosumab in male osteoporosis patients revealing distinct gender-specific adverse event patterns, providing a critical reference for optimizing pharmacotherapy and clinical monitoring for male patients with osteoporosis.

Despite widespread clinical use of the long-acting local anesthetic ropivacaine, its population-level safety remains under-explored. This study aimed to analyze and categorize adverse events (AE) associated with ropivacaine reported in the US Food and Drug Administration Adverse Event Reporting System (FAERS). We retrospectively extracted reports on adverse drug events (ADEs) from the FAERS database from the first quarter of 2004 to the fourth quarter of 2024. Using disproportionality analysis, including the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and the empirical Bayesian geometric mean, we assessed whether there was a significant association between ropivacaine and ADEs. The Weibull shape parameter was used to test the time to onset curve. The Kaplan–Meier method was employed to evaluate the cumulative incidence. In the FAERS database, ropivacaine was identified as the primary suspect in 1463 AE reports. The adverse reactions induced by ropivacaine involved 3 system organ categories and 21 high-level group terms. At the preferred term level, 181 positive ADEs were detected. Common ADEs included complications of anesthesia, Horner’s syndrome, delayed awakening after anesthesia, systemic toxicity of local anesthetics, and monoparesis. Gender differences existed in ADEs related to ropivacaine. The median time to onset of ADEs related to ropivacaine was 2 days (range: 1–3 days). Weibull shape parameter testing revealed an early failure pattern for ropivacaine-associated ADEs. This pharmacovigilance study identifies significant safety signals associated with ropivacaine, particularly neurological and cardiac events that predominantly occur within the first 72 hours after administration. The detection of potential gender-specific reporting patterns and specific high-strength signals warrants further clinical investigation. These findings provide valuable hypothesis-generating evidence from real-world data to guide targeted monitoring and inform future research on ropivacaine’s safety profile.

ABSTRACT Objective To determine if physiotherapy outcomes differ in children with concussion treated in-clinic versus virtually. Methods Licensed physiotherapists assessed and treated 23 children with concussion using telehealth delivery during COVID-19. These patients were matched to children assessed and treated in-clinic before (n = 23) and during (n = 23) the COVID-19 pandemic (total sample mean age = 13.5 ± 3.0 years, 65.2% girls). Physiotherapy examination findings, rehabilitation prescription outcomes, and total recovery time were analyzed using Cochran’s Q test, Friedman’s tests, linear mixed-effects models, or frailty models. Results Missed balance (p < 0.001) and vestibular/visual (p = 0.008) assessments were more frequent in the telehealth group, but no differences were observed for completed assessments (p > 0.05). All participants were given low-to-moderate intensity aerobic exercise recommendations, with coordination (n = 42), vestibular/visual (n = 31), and cervical spine (n = 11) therapies also prescribed. For recovery outcomes, neither the in-clinic (COVID, HR: 0.88, 95% CI: 0.41–1.88, p = 0.74) or telehealth (HR: 0.60, 95% CI: 0.27–1.31, p = 0.20) groups differed from the in-clinic (pre) reference group. Conclusion Telehealth delivery produces largely similar outcomes as in-person care, although select assessments cannot be delivered virtually. Telehealth care, particularly hybrid formats, should be further explored for pediatric concussion management.

ABSTRACT Market segmentation may impede carbon reduction, yet evidence on its link to carbon intensity remains inconclusive. Using panel data for 275 prefecture-level cities in China from 2004 to 2019 and a baseline two-way fixed effects model, we examine the relationship between market segmentation and carbon intensity. We find a positive association between market segmentation and regional carbon intensity, with a one-standard-deviation increase in the segmentation index linked to a 1.34% increase relative to the sample mean. Mechanism analysis suggests that this relationship operates through reduced green technological innovation and slower economic scale expansion. Digitalization, measured by a PCA-based composite indicator, mitigates this relationship. Heterogeneity analysis further indicates that the relationship is more pronounced in inland, economically less developed, and small and medium sized cities, as well as in areas with weaker environmental regulation and higher energy intensity. These findings suggest that reducing market segmentation and promoting digitalization may help lower carbon intensity, with implications for market integration policy design.

This work addresses the problem of testing independence in r-tuples of orientations of symmetric objects in three-dimensional space. Such objects naturally occur in crystallography, materials science, and other fields. We propose a novel definition of covariance between two random orientations and utilise it in the construction of multivariate asymptotic tests for pairwise uncorrelatedness based on U-statistics. We evaluate the finite-sample performance of these tests through a simulation study that investigates their power for three models of r-tuples of random orientations and compares them with permutation tests based on sample covariances and total distance multivariance. The application of the proposed tests is demonstrated on a dataset of polycrystalline material with cubic symmetry of the crystal lattice.

PurposeTo evaluate adverse events (AEs) associated with teprotumumab in the reatment of thyroid eye disease (TED).MethodsReports involving teprotumumab were extracted from the U.S.FDA Adverse Event Reporting System (FAERS) from the first quarter of 2020 to the first quarter of 2025. After data standardization, disproportionality analyses were performed using multiple signal detection algorithms, including the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM).ResultsA total of 1,357 reports were identified. Detected signals at the system organ class (SOC) level included ear and labyrinth disorders, eye disorders, social circumstances and reproductive system and breast disorders. A total of 143 Preferred Terms (PTs) met the criteria of four algorithms. Among these, signals within the "Ear and labyrinth disorders" SOC were predominant (n = 598). Tinnitus was the most frequently reported PT (n = 146). The highest disproportionality signals, based on ROR values, were observed for permanent deafness (ROR 10,021.8; 95% CI 5,544.31-18,115.24), autophony (ROR 3,282.12; 95% CI 1,333.19-8,080.12), and patulous eustachian tube (ROR 1,401.68;95% CI 499.54-3,932.99).ConclusionThese findings provide important real-world safety evidence and may support safer clinical use of teprotumumab.

Gestational diabetes mellitus (GDM) is a common pregnancy complication linked to adverse outcomes for both mother and infant. Research on drug-related GDM remains limited. This study aims to explore the risk factors and potential mechanisms of drug-related GDM using the FDA Adverse Event Reporting System (FAERS). We analyzed FAERS data from the past, focusing on drugs potentially associated with GDM. Significant drug signals were identified using statistical reporting odds ratio (ROR), proportional reporting ratio (PRR), empirical Bayesian geometric mean (EBGM), bayesian confidence propagation neural network (BCPNN), and univariate logistic regression analysis. We used multivariate logistic regression to analyze independent risk factors, built a multivariate logistic regression model to predict GDM, and used the generalized variance inflation factor (GVIF) to evaluate the multicollinearity of the predictive factors in the model. Furthermore, we performed gene target prediction, functional enrichment analysis, and protein-protein interaction (PPI) analysis to explore the mechanisms involved, and assessed drug-genes interactions through molecular docking simulations. By analyzing 1137 cases of potentially drug-related GDM, we identified 12 drugs as potential independent risk factors for GDM. We constructed a multivariate logistic regression model incorporating drug and patient characteristics to predict GDM, with an area under the curve (AUC) of 0.847. GVIF analysis confirmed that there was no multicollinearity among the predictors. Potential target genes of antipsychotic drugs are mainly enriched in cellular response to dopamine, phospholipase C-activating G protein-coupled receptor signaling pathway, and blood circulation. After integrating the target gene group and the insulin receptor signaling pathway gene set, the potential target genes have extensive connections with the insulin receptor signaling pathway, with DRD2 and KCNH2 being hub genes in the PPI network. This study identified 12 drugs that may be independent risk factors for GDM, including quetiapine, aripiprazole, olanzapine, prednisolone, venlafaxine, risperidone, escitalopram, clozapine, mirtazapine, ziprasidone, rosuvastatin, and trazodone. The established predictive model has certain clinical value, and the potential mechanisms by which antipsychotic drugs may lead to GDM were further analyzed. These results provide potential clues for the early identification of GDM and early warning of suspected drugs, and offer a reference for further exploration of its pathogenesis.

Advancements in precision medicine, particularly the use of neuroimaging and neurophysiologic techniques, may improve diagnosis, prognosis, and treatment of mental health disorders. Recent efforts to develop large neuroimaging datasets have yielded promising results for identifying mental health biomarkers. This scoping review identifies and characterizes studies of neuroimaging and neurophysiologic techniques used to address a variety of mental health disorders. We searched MEDLINE and Embase (January 2010-September 2023). Eligible studies examined neuroimaging and neurophysiologic techniques (e.g., magnetic resonance imaging [MRI] or electroencephalogram [EEG]) for diagnosis, prognosis, and/or treatment response for eligible mental health disorders. From eligible studies, we abstracted information on populations, clinical settings, imaging techniques, study designs, outcomes, and analytic approaches. From 58,824 unique search results, we identified 441 eligible primary studies and 27 systematic reviews addressing mental health disorders. Most studies focused on depressive disorders (k = 320 primary studies [17 systematic reviews]); fewer examined bipolar disorders (k = 61 [3]), posttraumatic stress disorder (PTSD; k = 39 [2]), obsessive compulsive disorder (OCD; k = 26 [1]), anxiety disorders (k = 22 [3]), or substance use disorders (SUD; k = 25 [0]). Three-quarters of primary studies used MRI-based techniques and 20% employed EEG. Two-thirds of studies focused on diagnosis (nearly all cross-sectional); the remaining studies mostly addressed symptom response to various treatments, including antidepressants and psychotherapy. Most primary studies were small (N < 100; k = 263), and generally included y oung and middle-aged adults; only 5 focused on older adults (sample mean age ≥ 65). Studies were most commonly conducted in China (k = 181), the United States (k = 83), or Canada (k = 22). Although many eligible studies evaluated MRI or EEG for diagnosis and/or treatment response for depressive disorders, most were small and cross-sectional. There was less existing evidence examining other neuroimaging techniques or focusing on other mental health disorders (PTSD, OCD, anxiety disorders, or SUD). Given these evidence gaps, it is likely premature to implement neuroimaging and neurophysiologic tests in clinical settings. To determine clinical utility, future research should use large samples in longitudinal designs and investigate a broader set of disorders. https://doi.org/10.17605/OSF.IO/5PHG2 . not applicable.

Adaptive beamformers such as the minimum-variance distortionless response (MVDR) are highly sensitive to mismatches in both the sample covariance matrix (SCM) and the array steering vector. This paper proposes a closed-loop Neural-MVDR framework for direction-of-arrival estimation that enforces a distortionless constraint consistent with a physically parameterized array model. The method requires no offline supervised pretraining on external labeled datasets. Instead, it performs per-frame, self-supervised adaptation at test time. For each incoming snapshot, it alternates among steering-vector refinement, robust SCM reconstruction parameterized by a lightweight neural module, and analytical MVDR spectral estimation. Experiments on synthetic data and the SWellEx-96 S5 event demonstrate improved robustness compared with the conventional beamformer, conventional MVDR, and representative robust MVDR variants based on eigenspace suppression, covariance matrix tapering, and oracle-approximating shrinkage, respectively.

Spousal bereavement and depression: Testing moderating effects of pre-loss circumstances and social support in India.

Abstract We investigate the overlap matrix between the eigenvectors of a Wigner matrix HN+K of size (N + K) ⇥ (N + K) and those of its principal minor HN of size N ⇥ N , for both the real symmetric ( = 1) and complex Hermitian ( = 2) ensembles, in the regime where N ! 1 while K remains fixed.Our analysis yields two main results. (i) In the bulk of the spectrum, an eigenvector of HN+K associated with an eigenvalue at energy level E projects primarily onto eigenvectors of HN located at the same local spectral level. This phenomenon, which we call local projection, highlights a robust stability of the eigenbasis under matrix growth. (ii) At the spectral edge, the change of basis between the leading eigenspaces of consecutive minors is asymptotically governed by a random antisymmetric perturbation of order N 1/3 . In both cases, we provide the asymptotic law of the overlaps expressed in terms of the Airy and Sine kernels.We further extend our analysis to the case of Wishart matrices, that is, sample covariance matrices of the form W = X &gt; X, where X 2 R T ⇥N is a matrix with i.i.d. random entries. We establish analogous results for the overlaps between eigenvectors of consecutive minors of W , both in the bulk and at the spectral edges (soft and hard). The limiting laws share the same universal structure as in the Wigner case, up to explicit constants depending on the aspect ratio q = N/T . This demonstrates the universality of the eigenvector overlap process across distinct random matrix ensembles.