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464 papers

The Long-Term Impact of Adolescent Community Weapon-Related Violence Exposure on Depression: Insomnia as a Mediating Pathway.

Lee E et al. · Jul 1, 2026

Adolescents exposed to community weapon-related violence face increased mental health risks, including depression, with insomnia linked to negative mental health outcomes. Given the high rates of insomnia in this population, this study explores insomnia as a mediator between community weapon-related violence and adult depression. Using data from the National Longitudinal Study of Adolescent to Adult Health, we analyzed the association between adolescent weapon-related violence (Wave 1) and depression in adulthood (Wave 4), with insomnia (Wave 2) as a mediator (N = 3924). Community weapon-related violence was associated with higher levels of depression in adulthood, 13 years post-exposure, through insomnia (β = 0.01, p = 0.01). Insomnia accounted for 7% of the total effect of weapon-related violence on depressive symptoms, indicating a partial mediation effect. Our findings identify a pathway through which adolescent community weapon-related violence leads to depression in adulthood, underscoring the need for early interventions targeting insomnia to reduce long-term depression risk in this population.

Psychology

A 12-week Exercise Intervention Among Older Adults With Chronic Coronary Syndrome: Changes and Associations of Movement Behaviors and Cardiovascular Risk Factors.

Ullrich A et al. · Jul 1, 2026

Physical activity (PA) is key to improve the prognosis of patients with chronic coronary syndrome (CCS). This study investigated changes in movement behaviors (MB), obesity markers, cardiorespiratory fitness (VO 2peak ), cardiometabolic risk (CMR), and brain-derived neurotrophic factor (BDNF) and whether changes in MB are associated with VO 2peak , CMR, and BDNF from baseline to 9 months after a 12-week exercise intervention. In total, 35 CCS patients (M = 69.5 ± 6.4 years; 82.9% men) underwent a group-based intervention; including two 1-h exercise sessions per week Data was collected on anthropometrics, blood samples, cardiopulmonary exercise testing, and 7-day accelerometry at baseline, 3-month, and 12-month follow-up. Absolute changes were examined using paired t-tests. Mixed-effects linear regression models were applied to investigate associations of MB with VO 2peak , CMR, and BDNF over time. Intra-class correlations were calculated to estimate within-person variability. From baseline to 3-month follow-up, light PA (23.7 min/d ± 10.9) increased and body mass index (-0.3 kg/m 2 ± 1.2), glucose (-0.8 mmol/L ± 0.3), and diastolic blood pressure (-2.7 mmHg ± 1.3) decreased. From baseline to 12-month follow-up, there were no changes in any marker. Regression models revealed no associations between any measure of habitual movement behaviors and VO 2peak , CMR, and BDNF over time. To conclude, short-term but no long-term changes in MB and cardiovascular health markers were observed among CCS patients after a 12-week exercise intervention. Modeling the associations between MB and VO 2peak , CMR, and BDNF over time revealed considerable within-person variability in the data, which should be considered in future research. TRIAL REGISTRATION: NCT06178263, Retrospectively registered (20/12/2023).

Medicine

Sustained Hypoxia-Inducible Factor 1-Alpha Accumulation Disrupts the Articular Niche to Promote Osteoarthritis Pathogenesis.

Gong W et al. · Jul 1, 2026

The precise role of hypoxia-inducible factor-1α (HIF-1α) in osteoarthritis (OA) pathogenesis remains controversial, often debated between a protective compensatory factor and a disease mediator. Here, we demonstrate that sustained, uncoupled HIF-1α accumulation functions as a potent, compartment-specific pathogenic driver of joint destruction. Using genetically engineered mouse models, we reveal that chondrocyte-specific HIF-1α overexpression (Acan CreERT2 ; Hif1αdPA fl/fl ) triggers spontaneous OA and exacerbates destabilization of the medial meniscus (DMM)-induced post-traumatic joint degeneration. Mechanistically, continuous HIF-1α activation drives pathological angiogenesis that physically dismantles the avascular, hypoxic cartilage niche, forcing a profound metabolic dysregulation that culminates in catastrophic matrix degradation. Conversely, sustained HIF-1α activation within the synovial and superficial cartilage compartments (Prg4- GFPCreERT2; Hif1αdPA fl/fl ) drives a slowly progressive, late-onset spontaneous OA through chronic inflammatory accumulation that actively suppresses Col2a1 expression. Furthermore, this robust inflammatory priming establishes a highly vulnerable microenvironment, whereby DMM surgery significantly accelerates the progression of trauma-induced joint collapse. Finally, transient whole-joint HIF-1α induction via an intra-articular injection of lipid nanoparticles (LNP-mRNA) closely recapitulates these detrimental effects. Collectively, our study reconciles existing controversies by establishing sustained HIF-1α accumulation as a spatiotemporally dynamic, broad disease amplifier across the articular ecosystem, highlighting its targeted inhibition as a promising therapeutic strategy for OA.

Medicine

Explainable machine learning for patient-specific quality assurance in intensity-modulated radiotherapy based on anatomical structures.

Zhang X et al. · Jul 1, 2026

Background Patient-specific quality assurance (PSQA) plays a pivotal role in intensity-modulated radiotherapy (IMRT) to ensure accurate dose delivery. However, conventional measurement-based PSQA approaches are labor-intensive and provide limited insight into the underlying factors contributing to variations in gamma passing rates (GPRs). Anatomical characteristics of the planning target volume (PTV) and organs at risk (OARs) may contain predictive information relevant to GPR performance, yet their potential has not been fully explored within interpretable machine learning frameworks. Purpose This study aimed to develop an interpretable machine learning (ML) framework for predicting GPRs in IMRT based on anatomical features extracted from the PTV and OARs. Methods A retrospective cohort of 243 clinical chest IMRT plans was analyzed. Radiomic and dosimetric features were extracted for each anatomical structure. Two ML regression models-Random Forest (RF) and eXtreme Gradient Boosting (XGBoost)-were developed to predict GPRs for the PTV and OARs under four gamma criteria (3%/3 mm, 3%/2 mm, 2%/3 mm, and 2%/2 mm). The GPR obtained by comparing the dose distribution reconstructed using the independent Monte Carlo (MC) dose calculation software ArcherQA (Wisdom Technology Company Limited, Hefei, China)-based on linear accelerator delivery log files-with the original planned dose distribution was used as the reference standard, and calculated using global gamma analysis with a 10% dose threshold. Model performance was evaluated using the mean absolute error (MAE), root mean square error (RMSE), and Spearman's rank correlation coefficient. Shapley Additive Explanations (SHAP) were applied to interpret feature contributions in the best-performing model. Results Both models demonstrated robust predictive performance across different anatomical structures and gamma criteria. As the gamma criteria became less stringent, prediction errors decreased accordingly. Prediction accuracy was relatively high for OARs; for example, under the 3%/3 mm criterion, the test-set MAE was 0.06% ± 0.01% for the heart and 0.26% ± 0.04% for the whole lung. In contrast, the prediction error was relatively larger for the PTV, with a test-set MAE of 1.98% ± 0.31% under the same criterion. SHAP analysis revealed that texture-related radiomic features contributed most substantially to model predictions. Moreover, feature importance patterns varied according to organ type and gamma-criterion stringency. Conclusions Multi-omics descriptors derived from anatomical structures can reliably predict GPRs in IMRT. The proposed interpretable ML framework not only achieves accurate prediction but also enhances mechanistic understanding through SHAP-based explanations. These findings provide valuable insights into dose verification variability and offer a practical, transparent tool for IMRT patient-specific quality assurance.

Physics and Astronomy

Knowing How to Ask About Digital Culture in Youth Mental Health Care: A Co-Designed Tool.

Paquin V et al. · Jul 1, 2026

Background With the digital cultures that youth are exposed to and participating in come potential risks and protective factors for their mental health. However, despite clear need there is a lack of guidance to help mental health professionals evaluate the role of social media, artificial intelligence, and other technologies in young people's mental health. Aims To co-design with young people the Digital Culture Interview, an interview tool to support the clinical assessment of digital cultural factors in mental health care. Method We recruited a diverse group of 12 participants aged 16-35 years (mean age 22 years) from outpatient mental health clinics in Montreal, Canada. Using the nominal group technique, they identified topics they found most relevant for exploring in a clinical assessment the experiences and practices involving digital technologies. Based on the topics that received the most votes from participants, we co-developed a list of interview questions and written guidance for their administration. Results Participants identified and ranked 48 themes. Drawing from these, 14 questions were developed for inclusion in the Digital Culture Interview, covering four topics: identity and worldview, negative experiences online, coping, and understanding of mental health. Participants emphasised that exploring digital culture in mental health care requires patients' trust and a baseline of knowledge. If done sensitively, this may enhance the patient-clinician alliance and improve mutual understanding. Conclusions The Digital Culture Interview has the potential to enhance rapport and reveal risk and protective factors that are salient to and actionable in mental health care.

Psychology

Automated Pharmacometric Model Development by Leveraging Low-Dimensional Neural ODEs and LASSO Regression.

Bräm DS et al. · Jul 1, 2026

Current pharmacometrics (PMX) model development is a manual process with iterative model building, fitting, and evaluation, which can be resource-intensive and time-consuming. Existing automated model development approaches utilize algorithms that still rely on iterative processes and perform model selection based on goodness-of-fit criteria. Recent advances in machine learning and artificial intelligence, particularly neural ordinary differential equations (NODEs), have demonstrated strong potential for characterizing complex pharmacokinetic (PK) and pharmacodynamic (PD) dynamics directly from data. However, NODEs are inherently black-box models, which limits their interpretability and their ability to provide mechanistic insights, both of which are essential in PMX. We recently presented a promising concept that proposes interpretable ODE-based structural models from NODEs but relied on manually identifying functional relationships, which can be challenging and prevents full automation. In this work, we present an automated model development approach that combines NODEs with least absolute shrinkage and selection operator (LASSO) regression to automatically propose structural models based on the dynamics learned by NODEs. The approach leverages LASSO's feature selection capability, thereby linking data-driven modeling with interpretable mechanistic structures. We demonstrate the applicability of this automated NODE-LASSO model development approach in three different scenarios: neonatal weight development, bi-exponential PK data, and warfarin PK/PD data. The results indicate that our automated NODE-LASSO model development approach can recover meaningful, mechanism-based structures while reducing the need for extensive iterative and manual model development. This highlights its potential as a resource-efficient and interpretable modeling strategy for PMX and its applications in model-informed drug development and clinical research.

Physics and Astronomy

Clinical Remission of an Unresectable Presumptive Haemangiosarcoma in a Dog Treated With Toceranib, Piroxicam, and Propranolol: A Case Report.

Park WD. · Jul 1, 2026

Haemangiosarcoma (HSA) is a highly aggressive vascular tumour in dogs, characterised by rapid growth, early metastasis, and poor prognosis despite conventional treatment with surgery and doxorubicin-based chemotherapy. A 14-year-old spayed female Maltese (4.14 kg) was presented with progressive abdominal distension and anorexia. Imaging revealed a large retroperitoneal mass, and computed tomography identified a 12.1 × 8.0 × 8.5 cm heterogeneous tumour. Exploratory laparotomy confirmed the lesion was unresectable, and biopsy findings were most consistent with presumptive haemangiosarcoma (HSA) due to the small, cautery-affected specimen. Medical therapy was initiated with toceranib phosphate (10 mg every other day), followed one week later by propranolol (0.3 mg/kg twice daily) and piroxicam (0.3 mg/kg once daily). The patient was monitored every 2-4 weeks with physical examination and serial haematology and serum biochemistry. Two months after initiating therapy, the abdominal ultrasonography demonstrated tumour reduction to 4.9 × 2.7 cm, and after 7 months the mass was no longer detectable on radiographic follow-up imaging (radiography and ultrasonography). Throughout treatment, haematologic and biochemical values remained within reference intervals, no clinically significant adverse effects were observed, and the owner reported resolution of abdominal distension with improved activity. This case demonstrates that combined therapy with toceranib, propranolol, and piroxicam achieved radiographic and clinically sustained remission of unresectable canine presumptive HSA while preserving quality of life. These findings suggest that multimodal therapy targeting angiogenesis and tumour growth pathways may represent a promising alternative strategy for managing this malignancy and warrant further clinical evaluation.

Medicine

Long-Term Cardiometabolic Outcomes in Children With Metabolically Healthy and Unhealthy Obesity.

Putri RR et al. · Jul 1, 2026

Importance Metabolically healthy obesity (MHO) in children has been considered a low-risk phenotype, potentially not requiring treatment. However, their long-term cardiometabolic outcomes remain unclear. Objective To compare the occurrence of type 2 diabetes, hypertension, dyslipidemia, and mortality up to young adulthood in children with metabolically healthy obesity (MHO), metabolically unhealthy obesity (MUO), and general population peers, and to investigate the association between obesity treatment response and disease risk. Design, setting, and participants This was a prospective cohort study including children undergoing obesity treatment recorded in the Swedish Childhood Obesity Treatment Register (BORIS) between 1997 and 2020 and their general population comparators, linked with national registers. Children in the cohort with obesity were aged 7 to 17 years at obesity treatment initiation and had complete cardiometabolic data. General population comparators were matched (ratio 1:5) based on sex, birth year, and residential area. Study data were analyzed from February to March 2025. Exposures Exposures included metabolically healthy obesity (MHO), defined as the absence of high blood pressure, impaired fasting glycemia, elevated transaminases, elevated triglycerides, and low high-density lipoprotein cholesterol; otherwise, children were categorized as having metabolically unhealthy obesity (MUO). Main outcomes and measures Type 2 diabetes, hypertension, dyslipidemia, and mortality up to age 30 years. Results A total of 7275 children (median [first quartile {Q1}-third quartile {Q3}] age, 11.1 [9.1-13.5] years; 4004 male [55.0%]) were included, along with 35 636 general population comparators (median [Q1-Q3] age, 11.1 [9.1-13.5] years; 19 596 male [55.0%]). MHO at baseline was present in 3626 children (49.8%; median [Q1-Q3] age, 10.6 [8.8-12.8] years; 1981 male [54.6%]), and MUO was present in 3649 children (50.2%; median [Q1-Q3] age, 11.6 [9.4-14.0] years; 2023 male [55.4%]). By age 30 years, cumulative incidences were as follows: type 2 diabetes (MHO, 9.1%; MUO, 16.8%; general population, 0.5%), hypertension (MHO, 10.8%; MUO, 18.3%; general population, 3.7%), and dyslipidemia (MHO, 5.3%; MUO, 12.7%; general population, 0.9%). A reduction of at least 0.25 body mass index (BMI) z score was associated with reduced incidence rate ratio (IRR) of type 2 diabetes (IRR, 0.22; 95% CI, 0.14-0.35), hypertension (IRR, 0.56; 95% CI, 0.34-0.93), and dyslipidemia (IRR, 0.28; 95% CI, 0.14-0.57), with similar risk reduction for MHO and MUO. Conclusions and relevance Results of this cohort study reveal that a reduction in BMI z score of at least 0.25 was associated with similar risk reductions for both MHO and MUO. Children with MHO face a substantially increased cardiometabolic disease risk already as young adults compared with the general population. Hence, obesity treatment should be recommended for all children with obesity, regardless of initial metabolic status.

Medicine

Malignant Hyperthermia in Sweden: Clinical Presentations and Genetic Findings.

Hellblom A et al. · Jul 1, 2026

Introduction Malignant hyperthermia (MH) is a pharmacogenetic, hypermetabolic and potentially lethal reaction to potent volatile anaesthetics and the muscle relaxant succinylcholine. To improve the understanding of MH, the aim of this retrospective study was to describe the Swedish cohort with respect to clinical manifestations, demographics and genetic findings. Method The Swedish MH Registry covers a total of 2852 individuals belonging to 544 different families investigated for MH since 1980. For this study, the index case in each family was included for further description. Results In total, MH was confirmed in 1555 individuals. Among the 288 index cases with a history of an MH reaction and confirmed MH, 58% were male and 57% were Conclusions We found that MH reactions predominantly occur in young individuals and that case fatality has declined over recent decades, with no deaths reported in the past 20 years. Less than 40% of the genetically investigated MH families, corresponding to around 20% of all Swedish MH families, currently have an identified genetic diagnostic variant. Editorial comment This analysis of the national Swedish Malignant Hyperthermia patient registry presents case factors and outcomes from cases among recognised families from the last 45 years. Presenting symptoms and then case confirmation details are presented, along with results from cases and families where genetic variants has been assessed.

Biochemistry, Genetics and Molecular Biology

Childhood Material Hardship Linked to Adolescent Neurocognition: A Computational Modeling Approach.

Zhang YL et al. · Jul 1, 2026

Childhood material hardship, including insecurity in housing, utilities, food, and medical care, is a critical factor influencing cognitive functioning and mental health outcomes. However, past research on material hardship is limited by cross-sectional data and reliance on conventional behavioral measures of cognitive functioning that suffer from poor reliability and lack of specificity. To address these gaps, this study used a well-validated computational model of cognition to examine individuals' drift rate, which is hypothesized to be driven by the efficiency of evidence accumulation (EEA) for decision-relevant information, a key process that supports higher-order cognitive functioning. Here, we examined how material hardship during childhood was associated with adolescent drift rate, and whether drift rate was linked with attention difficulties. 187 adolescents recruited from the Future of Families and Child Wellbeing Study were included in the analyses. Adolescents exposed to greater material hardship showed lower drift rate, suggesting less effective processing. Growth curve modeling revealed that initial exposure to material hardship, but not changes across childhood, was associated with drift rate in adolescence. Lower drift rate was also associated with concurrent attentional problems and served as a significant indirect pathway linking material hardship to adolescent attention. This is the first longitudinal study that examined the associations among childhood material hardship exposure, adolescent drift rate, and attentional difficulties. Our results suggest that challenges to essential living conditions in childhood may impact cognitive processes underlying goal-directed behavior in adolescents. These findings highlight the application of computational models to reveal specific cognitive processes impacted by adversity. SUMMARY: Existing research on material hardship and cognitive functioning is limited by reliance on cross-sectional task-based performance, resulting in inconsistent findings. We applied the diffusion-decision model to decompose trial-wise performance into underlying cognitive processes, including drift rate, a key evidence accumulation process underlying goal-directed behavior. Greater cumulative childhood material hardship, beyond exposure to other adversity, is associated with lower drift rate, which is linked with greater attentional problems in adolescents. Findings were specific to drift rate, not average response time or accuracy, emphasizing the value of computational methods in capturing cognitive changes associated with material hardship.

Health Professions