Tag: pubmed

Comput Biol Med. 2025 Oct 8;198(Pt A):111117. doi: 10.1016/j.compbiomed.2025.111117. Online ahead of print.

ABSTRACT

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disorder, the etiology and pathogenesis of which are currently unclear. Brain imaging genetics, which analyzes genetic factors and neuroimaging phenotypic data in association, is an effective technique for identifying AD-related biomarkers. With the rapid advancement of imaging and genetic sequencing technologies, the association between multimodal imaging data and genetic data has gradually received widespread attention. However, how to make full use of the complementary information between multimodal data is an urgent problem to be solved. Therefore, Multimodal Adaptive Fusion Deep Association Analysis Model (MAFDAA) is proposed to solve the above problems. Firstly, a novel multi-head attention graph convolutional model is proposed to extract and reconstruct complementary information among multimodal data, thus constructing a comprehensive representation of brain information. Secondly, the representation module statistically encodes genetic data to obtain genetic representations, while embedding demographic information as a supplement to the genetic representation. Subsequently, in the association analysis module, nonlinear correlation analysis is conducted between genetic representations and brain reconstruction data, yielding latent association vectors for subsequent research. Finally, the diagnostic module diagnoses the subjects and identifies AD-related biomarkers based on the association analysis results. The experimental results demonstrate that MAFDAA exhibits excellent diagnostic performance. Additionally, the identified biomarkers were analyzed from different perspectives, establishing a new approach for studying the complex genetic mechanisms of neurodegenerative diseases from a micro to macro scale.

PMID:41066822 | DOI:10.1016/j.compbiomed.2025.111117

Appl Radiat Isot. 2025 Oct 6;226:112246. doi: 10.1016/j.apradiso.2025.112246. Online ahead of print.

ABSTRACT

The Korea Institute of Nuclear Safety (KINS) has designated Rice and Napa cabbage, which account for a large proportion of the Korean diet, as staple foods for continuous radioactivity monitoring. Assessing internal exposure from food ingestion is essential for public health and radiation safety. This study evaluated the radioactivity concentrations of these foods and quantified annual effective doses from their ingestion. Samples of Rice and Napa cabbage collected from 15 regions nationwide from 2014 to 2023 by Regional Radioactivity Monitoring Stations (RRMSs) were analyzed for K-40 and Cs-137. Soil types were classified using the United States Department of Agriculture (USDA) soil texture triangle, and regional variations in food radioactivity concentrations were assessed relative to soil texture. Based on these data and intake statistics from the Korea National Health and Nutrition Examination Survey, the annual effective dose from K-40 ingestion was calculated using the International Commission on Radiological Protection (ICRP) dose conversion factor of 0.062 μSv/Bq. K-40 concentrations ranged from 1.65 to 75.6 Bq kg^-1-fresh in Rice and 10.4-122 Bq kg^-1-fresh in Napa cabbage, with cabbage averaging about three times higher. The estimated annual effective doses were 7.53 μSv for Rice and 10.1 μSv for cabbage, corresponding to ∼0.7 % of natural background exposure (2400 μSv y^-1) and ∼5.8 % of the dose from total food ingestion (290 μSv y^-1). These results demonstrate that the radiological impact of staple food consumption in South Korea is negligible and provide a scientific basis for food-based environmental radioactivity monitoring and radiological emergency preparedness.

PMID:41066797 | DOI:10.1016/j.apradiso.2025.112246

Pediatr Neurol. 2025 Sep 15;173:98-106. doi: 10.1016/j.pediatrneurol.2025.09.005. Online ahead of print.

ABSTRACT

BACKGROUND: SLC6A1-Related Neurodevelopmental Disorder (SLC6A1-NDD) is one of the most common monogenic disorders reported in genetic databases. There is no established quality-of-life (QoL) measure that captures the impact of SLC6A1-NDD on patients and caregivers. This study investigates how clinical characteristics of SLC6A1-NDD correlate with QoL scores obtained during our study.

METHODS: We conducted univariable comparisons (n = 52) of the Quality-of-Life Inventory-Disability, Quality-of-Life of Childhood Epilepsy (QOLCE-55, ages 5-18-years), and Pediatric Quality-of-Life Inventory Family Impact Module with 45 clinical characteristics of SLC6A1-NDD. Given the non-normal score distributions of our sample, Spearman’s rank order correlation coefficient and Wilcoxon rank-sum test were utilized.

RESULTS: Lower QOLCE-55 total scores were associated with regression, absence seizures, clinical severity, coordination difficulties, and male gender (P < 0.039). Autism severity was significantly associated with lower total scores on all three QoL measures (P < 0.025; ρ = -0.473 to -0.681). Longitudinal Pediatric Quality-of-Life Inventory Family Impact Module scores suggest family relationships can improve over time.

CONCLUSIONS: Of the three measures utilized, QOLCE-55 had the largest representation of statistically significant clinical features driving subdomain and total scores. Autism severity was a driver of lower QoL in all measures. While this suggests the utility of QOLCE-55 in patients with SLC6A1-NDD, subdomain scores of all three measures captured clinical features that were not represented in total scores. Future studies should utilize these measures in larger cohorts of patients to further explore these findings.

PMID:41066795 | DOI:10.1016/j.pediatrneurol.2025.09.005

N Z Med J. 2025 Oct 10;138(1623):73-81. doi: 10.26635/6965.7067.

ABSTRACT

AIM: In New Zealand, ophthalmologists encounter varying degrees of work stress, job satisfaction and burnout. Significant clinical demands, long work hours and high-pressure responsibilities increase the likelihood of burnout in this specialty. The present study aims to examine differences in ophthalmologists’ work stress, job satisfaction and burnout across public hospital and private practice settings.

METHOD: A cross-sectional quantitative study was conducted using a modified Mini Z 2.0 Burnout Survey to assess workplace satisfaction, stress and burnout among 171 New Zealand ophthalmologists. Demographic and practice-related data were also collected.

RESULTS: Out of 161 delivered surveys, 84 responses were received (52% response rate). Among respondents, 84.5% had public sector roles and 81% worked in the private sector. Twenty-one percent of public sector ophthalmologists reported a joyous workplace (Mini Z score ≥30) compared with 75% in the private sector. Public sector clinicians reported significantly higher burnout symptoms, stress levels and workplace disorder, as well as poorer workload control and misalignment with leadership, compared with their private sector counterparts.

CONCLUSION: The study highlights substantial disparities in job satisfaction and burnout between ophthalmologists working in the public and private sector. Factors such as excessive workload, bureaucratic inefficiencies and limited resource allocation in the public sector contribute to these differences. Adoption of private sector practices, including improved administrative support and autonomy, as well as public-private partnerships, may enhance retention and wellbeing in the public system.

PMID:41066783 | DOI:10.26635/6965.7067

N Z Med J. 2025 Oct 10;138(1623):38-52. doi: 10.26635/6965.7029.

ABSTRACT

AIM: This study aimed to estimate rates and factors associated with eating disorder risk in transgender youth, and to explore the association between this risk and unmet need for gender-affirming hormone therapy (GAHT).

METHODS: In a national cross-sectional survey of participants aged 14-24 years, the five-item Sick, Control, One stone, Fat, Food (SCOFF) instrument was used to assess eating disorder risk. GAHT demand was self-reported. Modified Poisson regressions were employed to assess risk.

RESULTS: Overall, 1,401 participants were eligible, of whom 1,010 (72.1%) had valid SCOFF scores. Of these, 398 (38.4%) participants met the threshold for eating disorder risk. In adjusted analyses, those aged 14-18 years had an increased prevalence ratio (PR) of eating disorder risk compared with their counterparts aged 19-24 years (PR: 1.26; 95% confidence interval: 1.06-1.50). GAHT demand was reported by 645 participants, with 277 (42.9%) having unmet need. No statistical evidence was found relating unmet GAHT need with eating disorder risk (p=0.29).

CONCLUSION: Nearly two in five transgender youth are at eating disorder risk, and unmet GAHT need rates appear higher. While it is recognised that eating disorders are a global health concern, they have not received the priority they deserve. In the calls for urgent action, transgender youth deserve particular attention.

PMID:41066781 | DOI:10.26635/6965.7029

J Craniofac Surg. 2025 Oct 9. doi: 10.1097/SCS.0000000000012044. Online ahead of print.

ABSTRACT

OBJECTIVES: Due to the hard palate’s structure and position, it serves as one of the main structural components in the oral sensorimotor system. This study aimed to examine the hard palate angle, inclination, depth types, and the presence of S-shaped projection in healthy individuals.

METHODS: Cone-beam computed tomography (CBCT) images of 130 healthy individuals, aged between 18 and 58 years, were retrospectively analyzed. Four parameters, such as hard palate angle (HPA), hard palate inclination (HPI), hard palate depth types (HPDT), and hard palate S-shaped projection, were statistically evaluated.

RESULTS: The participants’ mean age was 32.57 ± 12.77 years. The HPA was measured at 139.44 ± 7.65 degrees in healthy subjects (138.03 ± 7.00 degrees in females and 141.16 ± 7.75 degrees in males, P = 0.020). When the findings were analyzed, no significant differences were found between genders in terms of HPDT and HPI classification, or the distribution of HPI types and the presence of an S-shaped projection.

CONCLUSIONS: In this study, the authors evaluated the hard palate angle, inclination, depth types, and the presence of S-shaped projection in healthy individuals. Due to its complex anatomy and central position within the craniofacial region, the hard palate serves as a key landmark, providing important anatomical and clinical insights. The data obtained may assist especially anatomists, dentists, and anesthetists in understanding normal variations and supporting accurate diagnosis and treatment planning.

PMID:41066759 | DOI:10.1097/SCS.0000000000012044

PLoS One. 2025 Oct 9;20(10):e0333379. doi: 10.1371/journal.pone.0333379. eCollection 2025.

ABSTRACT

We propose TIC-FusionNet, a trend-aware multimodal deep learning framework for time series forecasting with integrated visual signal analysis, aimed at addressing the limitations of unimodal and short-range dependency models in noisy financial environments. The architecture combines Exponential Moving Average (EMA) decomposition for denoising and trend extraction, a lightweight Linear Transformer for efficient long-sequence temporal modeling, and a spatial-channel CNN with CBAM attention to capture morphological patterns from candlestick chart images. A gated fusion mechanism adaptively integrates numerical and visual modalities based on context relevance, enabling dynamic feature weighting under varying market conditions. We evaluate TIC-FusionNet on six real-world stock datasets, including four major Chinese and U.S. companies-Amazon, Tesla, Kweichow Moutai, Ping An Insurance, China Vanke-and Apple-covering diverse market sectors and volatility patterns. The model is compared against a broad range of baselines, including statistical models (ARIMA), classical machine learning methods (Random Forest, SVR), recurrent and convolutional neural networks (LSTM, TCN, CNN-only), and recent Transformer-based architectures (Informer, Autoformer, Crossformer, iTransformer). Experimental results demonstrate that TIC-FusionNet achieves consistently superior predictive accuracy and generalization, outperforming state-of-the-art baselines across all datasets. Extensive ablation studies verify the critical role of each architectural component, while attention-based interpretability analysis highlights the dominant technical indicators under different volatility regimes. These findings not only confirm the effectiveness of multimodal integration in capturing complementary temporal-visual cues, but also provide valuable insights into model decision-making. The proposed framework offers a robust, scalable, and interpretable solution for multimodal temporal prediction tasks, with strong potential for deployment in intelligent forecasting, sensor fusion, and risk-aware decision-making systems.

PMID:41066756 | DOI:10.1371/journal.pone.0333379

JMIR Res Protoc. 2025 Oct 9;14:e74295. doi: 10.2196/74295.

ABSTRACT

BACKGROUND: Aggression and violence are prevalent in forensic psychiatric inpatient care. These behaviors significantly impact treatment outcomes, create challenging work environments for staff, and strain relationships between patients and caregivers. Managing such behaviors poses a formidable challenge that necessitates innovative approaches and evidence-based interventions. The Therapeutic Meeting with Aggression (TERMA) model is a staff training program designed to equip staff with strategies to de-escalate patient aggression, thus reducing violence and increasing patients’ and staffs’ perceived safety.

OBJECTIVE: The aim of this project is to evaluate the violence prevention model TERMA regarding perceived safety by patients and staff and adverse events within forensic psychiatric inpatient care. In addition, the project will investigate whether the organizational culture affects the implementation of the TERMA model.

METHODS: The project includes an observational study with a before and after design. Implementation of the TERMA model consists of an 8-seminar staff training program. Data sources include questionnaires, medical records, and registries. Quantitative data will be analyzed using descriptive and comparative statistics. To analyze changes between measurements, dependent sample 2-tailed t tests will be used for normally distributed data, and the Wilcoxon signed-rank test will be applied when normality is not met. The project will also include qualitative interview studies, which are planned to be analyzed using qualitative inductive content analysis.

RESULTS: Participant enrollment began in July 2023 and was concluded by the end of 2024. Data collection and analysis of quantitative data are expected to be completed by early 2026, after which the study findings will be submitted for publication in peer-reviewed scientific journals. Collection of qualitative data is scheduled for the second half of 2025 and 2026.

CONCLUSIONS: This study can add valuable knowledge about the effects of the violence prevention model TERMA.

PMID:41066754 | DOI:10.2196/74295

PLoS Biol. 2025 Oct 9;23(10):e3003431. doi: 10.1371/journal.pbio.3003431. Online ahead of print.

ABSTRACT

Decomposing behavior into elementary components remains a central challenge in computational neuroethology. The current standard in laboratory animals involves multi-view video tracking, which, while providing unparalleled access to full-body kinematics, imposes environmental constraints, is data-intensive, and has limited scalability. We present an alternative approach using inertial sensors, which capture high-resolution, environment-independent, compact 3D kinematic data, and are commonly integrated into rodent neurophysiological devices. Our analysis pipeline leverages unsupervised, computationally efficient change-point detection to break down inertial time series into variable-length, statistically homogeneous segments. These segments are then grouped into candidate behavioral motifs through high-dimensional, model-based probabilistic clustering. We demonstrate that this approach achieves detailed rodent behavioral mapping using head inertial data. Identified motifs, corroborated by video recordings, include orienting movements, grooming components, locomotion, and olfactory exploration. Higher-order behavioral structures can be accessed by applying a categorical hidden Markov model to the motif sequence. Additionally, our pipeline detects both overt and subtle motor changes in a mouse model of Parkinson’s disease and levodopa-induced dyskinesia, highlighting its utility for behavioral phenotyping. This methodology offers the possibility of conducting high-resolution, observer-unbiased behavioral analysis at minimal computational cost from easily scalable and environmentally unconstrained recordings.

PMID:41066739 | DOI:10.1371/journal.pbio.3003431

JCO Precis Oncol. 2025 Oct;9:e2500489. doi: 10.1200/PO-25-00489. Epub 2025 Oct 9.

ABSTRACT

PURPOSE: Lung cancer remains the leading cause of cancer-related mortality worldwide, with a substantial risk of recurrence even in early-stage non-small cell lung cancer (NSCLC) after curative surgery. Circulating tumor DNA (ctDNA)-based detection of minimal residual disease (MRD) has emerged as a promising tool for identifying patients at increased risk of relapse. However, the predictive effectiveness of ctDNA remains uncertain because of variability in study designs, detection strategies, and statistical power.

MATERIALS AND METHODS: We conducted a systematic meta-analysis of 30 studies involving 3,287 patients with postoperative NSCLC to evaluate the diagnostic performance of ctDNA-based MRD testing for recurrence detection and survival prediction. Eligible studies were identified through a comprehensive literature search and quality-assessed using the QUADAS-2 tool. Pooled diagnostic estimates were calculated using bivariate random-effects models. Subgroup analyses compared tumor-informed and tumor-agnostic detection strategies at both landmark and longitudinal postoperative time points.

RESULTS: In landmark analyses, tumor-informed assays demonstrated higher specificity (0.97 v 0.93) and AUC (0.81 v 0.70) than tumor-agnostic approaches, which showed slightly higher sensitivity (0.44 v 0.42). In longitudinal monitoring, the differences narrowed: tumor-informed assays retained higher specificity (0.96 v 0.88), whereas tumor-agnostic methods exhibited modestly higher sensitivity (0.79 v 0.76) and AUC (0.91 v 0.86).

CONCLUSION: Our findings indicate that ctDNA-based MRD testing provides clinically meaningful prognostic information for postoperative recurrence in early-stage NSCLC. Both detection strategies offer complementary strengths, with tumor-informed assays excelling in specificity and tumor-agnostic approaches offering greater sensitivity in some settings. These results highlight the potential of ctDNA MRD testing to enhance postoperative surveillance and guide personalized disease management in early-stage NSCLC.

PMID:41066727 | DOI:10.1200/PO-25-00489