Tag: statistics

J Neuroimmunol. 2025 Oct 4;409:578767. doi: 10.1016/j.jneuroim.2025.578767. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the causal relationship between monocyte chemoattractant protein-1 (MCP-1) levels and risk of neuropsychiatric disorders (NPDs), including Alzheimer’s disease (AD), vascular dementia (VD), depression, schizophrenia (SCZ), and anxiety disorders, using two-sample Mendelian randomization (MR).

METHODS: Summary statistics from genome-wide association studies (GWAS) were utilized to examine the relationship between MCP-1 levels and NPDs. MCP-1 summary data were obtained from the IEU OpenGWAS database, while GWAS summary statistics for NPDs were primarily sourced from the FinnGen consortium, with additional replication datasets from the IEU OpenGWAS and UK Biobank. The primary analytical approach was the inverse-variance weighted (IVW) method, complemented by weighted median, MR-Egger regression, and both weighted and simple mode methods in bidirectional MR analyses. Heterogeneity was assessed using Cochran’s Q test, and horizontal pleiotropy was evaluated using MR-Egger regression and the MR-PRESSO test. Results from multiple GWAS sources were synthesized using meta-analysis to provide robust and comprehensive estimates.

RESULTS: In primary MR analysis, IVW results indicated a statistically significant association between elevated MCP-1 levels and increased risk of AD (OR: 1.108; 95 % CI: 1.003-1.224; P_IVW = 0.044) and SCZ (OR: 1.245, 95 % CI: 1.014-1.529, P_IVW = 0.036). No evidence of horizontal pleiotropy was observed (P > 0.05), and leave-one-out sensitivity analysis supported the robustness of these findings. However, no causal associations were identified in replication MR analyses for MCP-1 with any of the NPDs (P_IVW > 0.05). Meta-analysis further confirmed the significant association between MCP-1 levels and AD risk (OR: 1.096, 95 % CI: 1.017-1.182, P = 0.017), while no significant causal relationships were observed for the other NPDs.

CONCLUSION: Elevated MCP-1 levels are causally associated with Alzheimer’s disease risk but not with other NPDs, indicating a disease-specific role and therapeutic potential in AD.

PMID:41066853 | DOI:10.1016/j.jneuroim.2025.578767

Pregnancy Hypertens. 2025 Oct 8;42:101261. doi: 10.1016/j.preghy.2025.101261. Online ahead of print.

ABSTRACT

BACKGROUND: Studies in temperate regions have observed an increased risk of preeclampsia in the winter, while studies conducted in tropical regions have found an increased risk during the rainy season. The effectof season of conception and delivery have been inconsistent and poorly studied in moderate climates such as Los Angeles.

OBJECTIVES: We aimed to study the effects of the season of delivery on the risk of hypertensive disorders of pregnancy.

STUDY DESIGN: We conducted a retrospective cohort study among 24,843 predominantly Hispanic womenwho delivered at a large, urban safety nethospital from1995 and 2008. Logistic regression and multivariable multinomial logistic regression were used to estimateodds ratios and 95% CIs.

RESULTS: Mothers who delivered in the wet season had a significantly increased risk of developing hypertensive disorders of pregnancy compared to those who delivered in the dry season (OR = 1.11, 95 % CI: 1.02, 1.21). When stratifying based on disease severity, only mild preeclampsia indicated an association with season of delivery (OR = 1.12, 95 % CI: 1.01, 1.25). The effect for severe preeclampsia (OR = 1.12, 95 % Cl: 0.96, 1.31) and eclampsia/HELLP syndrome (OR = 0.80, 95 % CI: 0.49, 1.31) did not reach statistical significance, though power was limited in the more severe categories. Results evaluating season of conception as the outcome were similar to those for the season of delivery.

CONCLUSIONS: Among the predominantly Hispanic women who delivered at Los Angeles County + University of Southern California between 1995 and 2008, deliveries in the wet, winter season were associated with an increased risk of hypertensive disorders of pregnancy.

PMID:41066836 | DOI:10.1016/j.preghy.2025.101261

J Mech Behav Biomed Mater. 2025 Oct 6;173:107223. doi: 10.1016/j.jmbbm.2025.107223. Online ahead of print.

ABSTRACT

As the largest organ of the human body, the skin serves as a crucial protective barrier against external damage. While traditional approaches to skin injury treatment increasingly struggle to meet clinical demands, three-dimensional (3D) bioprinting has emerged as an innovative approach for tissue-engineered skin regeneration. Nevertheless, challenges persist regarding the mechanical integrity of bioprinted constructs, particularly post-printing graft shrinkage. This review systematically examines three key strategies for enhancing the mechanical properties of 3D bioprinted skin grafts: (i) Biomaterial innovation through novel material development and composite systems that substantially improve structural stability; (ii) Advanced structural design incorporating bioinspired architectures, topological optimization, and gradient configurations to achieve biomimetic mechanical performance; (iii) Post-fabrication processing techniques involving novel crosslinking methods and parameter modulation to reinforce mechanical strength. By critically analyzing these synergistic enhancement strategies, this work establishes a conceptual framework to guide future research in developing clinically viable 3D bioprinted skin substitutes with optimal biomechanical functionality.

PMID:41066831 | DOI:10.1016/j.jmbbm.2025.107223

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