The study aimed to systematically review the evidence on the association between smoking and the risk of diabetic neuropathy, with a particular emphasis on the risk of peripheral neuropathy among individuals with diabetes mellitus.

MEDLINE, EMBASE, SCOPUS, and CENTRAL databases were searched for studies published before August 2024. Cross-sectional, case-control, and cohort studies that assessed the association between smoking and diabetic neuropathy in individuals diagnosed with diabetes mellitus (type 1 or type 2), reported smoking as an exposure, and any type of diabetic neuropathy as an outcome were included in the study. The risk of bias of the included studies was evaluated using the modified risk of bias in non-randomized studies-of exposures (ROBINS-E).

Seventy-five articles, including 228,699 individuals with diabetes met the inclusion criteria. Fifty-four cross-sectional, 8 case-control, and 13 cohort studies provided data for the meta-analyses. Cohort studies demonstrated a significantly increased risk of diabetic peripheral neuropathy (RR 1.28; 95% CI 1.05, 1.51), the most prevalent subtype of diabetic neuropathy. Meta-analyses of cross-sectional and case-control revealed an increased risk of diabetic neuropathy (all types combined) among smokers with diabetes ([OR 1.29; 95% CI 1.17, 1.41], [OR 1.48; 95% CI 1.23, 1.72]). Meta-regression showed no statistically significant impact of total sample size and type of effect estimates on pooled effect estimates for cross-sectional, case-control, and cohort studies.

Smoking is associated with an increased risk of diabetic neuropathy, peripheral neuropathy in particular. Future research should evaluate the precise dynamics of neuropathy pathogenesis among individuals with diabetes to prevent such complications.

PROSPERO CRD42022363380.

Diethyl phthalate (DEP), a widely distributed environmental contaminant, is epidemiologically linked to prostate cancer (PCa). However, its molecular mechanisms beyond endocrine disruption remain poorly defined. We aimed to investigate the core mechanisms potentially underlying DEP-associated prostate carcinogenesis within a genome-exposome interaction framework.

We employed an integrated, multi-level framework combining: (1) Integrated chemical structure-based target prediction; (2) Cross-dataset meta-analysis of PCa transcriptomics (7 GEO datasets) for Differentially Expressed Gene (DEG) identification and Weighted Gene Co-expression Network Analysis (WGCNA); (3) Ensemble machine learning (113 models incorporating RF, XGBoost) for core target screening, augmented by SHAP interpretable to predict potential DEP targets.e AI; and (4) Molecular docking validation (AutoDock Vina, binding free energy assessment).

Integration pinpointed 9 key DEP-PCa targets. Functional enrichment implicated calcium signaling dysregulation, neuroendocrine pathway disruption, and smooth muscle dysfunction as central mechanisms. Machine learning distilled five core regulators: TRPM8, CTSB, CA14, GSTM2, and MYLK. SHAP analysis quantified TRPM8 and CA14 as dominant predictors and revealed critical non-linear interactions: synergistic TRPM8-MYLK co-expression and a CTSB expression threshold effect. Computational validation predicted high-affinity binding of DEP to all five core targets, suggesting potential direct interactions.

Our integrated analysis suggests that DEP may promote prostate carcinogenesis via a multidimensional network centered on calcium signaling perturbation, neuroendocrine dysregulation, and tumor microenvironment acidification, potentially illustrating a genome-exposome interaction mechanism beyond endocrine disruption. We propose that our analytical framework could serve as a reproducible approach for translational exposomics.

Anemia is associated with worse stroke outcomes, but prior studies seldom focus on patients with spontaneous supratentorial intracerebral hemorrhage (ICH) treated in township-level primary hospitals.

We performed a single-center retrospective cohort study of consecutive adults with spontaneous supratentorial ICH and available 90-day outcomes. Anemia was defined by prespecified sex-specific hemoglobin thresholds at admission. The primary outcome was the 90-day modified Rankin Scale (mRS 0-6) analyzed with a partial proportional-odds model. Secondary outcomes were mRS 0-1, 0-2, 0-3, and 90-day all-cause mortality. Prespecified covariates were adjusted in all models. Exploratory mediation analyses assessed whether baseline hematoma volume mediated the association between anemia and 90-day functional outcomes.

Among 158 participants (median age, 66 years; 55 women), 32 had anemia. Anemia was associated with higher odds of greater disability at intermediate-to-high thresholds: mRS ≥ 3 (odds ratio [OR] 3.46; 95% CI 1.33-8.99; P = 0.01) and mRS ≥ 4 (OR 4.64; 95% CI 1.60-13.41; P < 0.01); estimates at other thresholds were directionally similar but not significant. In secondary analyses, anemia was associated with lower odds of achieving mRS 0-2 (OR 0.31; 95% CI 0.11-0.87; P = 0.03) and mRS 0-3 (OR 0.26; 95% CI 0.09-0.71; P = 0.01), with no association for mRS 0-1 (OR 0.59; 95% CI 0.15-2.03; P = 0.41) or 90-day mortality (OR 1.29; 95% CI 0.34-4.76; P = 0.70). Results were stable across sensitivity analyses (excluding the 5 largest and 5 smallest hematoma volumes, including participants lost to follow-up as worst and best cases). Mediation analyses suggested that larger baseline hematoma volume accounted for ~ 18% of the association between anemia and achieving mRS 0-3 (borderline for mRS 0-2).

In a township-level cohort with supratentorial ICH, admission anemia was associated with a shift toward greater 90-day disability. Exploratory mediation findings imply that larger baseline hematoma volume may partly underlie this association and warrant confirmation in prospective multicenter studies. The null results for mRS 0-1 and 90-day mortality should be interpreted cautiously given limited power.

Ischemic stroke (IS) is a cerebrovascular disease resulting from insufficient blood supply to specific areas of the brain, often due to atherosclerosis and thrombosis. While the association between polymorphisms in coagulation-related genes (CRGs) and thrombosis has been suggested, the precise relationship between CRGs and IS remains unclear and requires further exploration.

This study utilized IS-related datasets (GSE16561, GSE9877, GSE58294, GSE224273) and CRGs to identify differentially expressed genes (IS-DEGs) through differential expression analysis. Differentially expressed coagulation-related genes (DE-CRGs) were determined by overlapping CRGs and IS-DEGs. Machine learning models, including random forest, gradient boosting decision trees, and support vector machines, were applied to screen for potential hub genes. These candidate hub genes were then validated using an independent dataset (GSE9877) and confirmed by real-time quantitative PCR (RT-qPCR) in clinical samples from IS patients. Single-cell RNA-seq of GSE224273 was processed via Seurat to map hub-gene expression across endothelial, smooth-muscle, macrophage, monocyte, T, NK, and B-cell clusters.

A total of 18 DE-CRGs were acquired by overlapping 450 IS-DEGs and 203 CRGs. Furthermore, 517 cluster-differentially expressed genes (DEGs) and 1,021 coagulation-score-RGs were obtained based on 18 DE-CRGs. The 29 candidate genes were obtained by overlapping IS-DEGs, cluster-DEGs and coagulation-score-related genes (RGs), five hub genes (REPS2, LIME1, MYH9, C5AR1, ECHDC2) were successfully screened. Subsequently, in GSE9877 dataset, only REPS2, MYH9, C5AR1 had the same expression tendency with that in GSE16561 dataset, while our RT-qPCR results suggested that the expression trend of LIME1, MYH9, C5AR1, ECHDC2 were consistent with that in GSE16561 dataset besides REPS2. Single-cell analysis localized MYH9 predominantly to smooth-muscle and endothelial cells, whereas C5AR1 was enriched in macrophages and monocytes, with both genes significantly upregulated in IS-derived cells. Two hub genes, C5AR1 and MYH9, were eventually selected from this group. Further analyses showed that these genes are significantly enriched in pathways related to complement and coagulation cascades and platelet activation.

The two hub genes, C5AR1 and MYH9, may contribute to the development of IS by promoting thrombosis. These findings offer new insights into the molecular mechanisms of IS and suggest potential biomarkers and therapeutic targets for IS management.

In the context of academically competitive cultures, particularly in China, parental educational anxiety has emerged as a salient psychosocial stressor affecting adolescent mental health. While growing attention has been given to this phenomenon, the psychological pathways through which parental educational anxiety relates to adolescent depression remain insufficiently delineated. This study investigates the mediating roles of moral disengagement and negative coping style, as well as the moderating function of psychological resilience in this relationship.

A total of 1,979 parent-adolescent dyads were recruited from six schools across three provinces in China (Liaoning, Shandong, and Shanghai). Standardized questionnaires were administered separately to both parents and their adolescent children. Structural equation modelling (SEM) was employed using Mplus 8.3 to test the hypothesized chain mediation pathways, while moderation analysis was conducted using SPSS 23.0 to examine whether psychological resilience buffers the direct association between parental educational anxiety and adolescent depression.

Parental educational anxiety was significantly and positively associated with adolescent depression (β = 0.304, t = 14.929, p < 0.001). Moreover, a significant sequential pathway was identified: moral disengagement was positively associated with negative coping style (β = 0.270, t = 13.548, p < 0.001), and both variables jointly mediated the association between parental educational anxiety and adolescent depression. Additionally, psychological resilience moderated this association such that the relationship was attenuated among adolescents with higher resilience (p < 0.001).

These findings highlight a complex chain of cognitive and emotional mechanisms linking parental educational anxiety to adolescent depressive symptoms. Moral disengagement and negative coping style operate as sequential mediators, while psychological resilience serves as a buffering factor. Although causal interpretations are limited by the cross-sectional design, the results underscore the importance of addressing both family-based pressures and adolescents' internal coping resources in interventions aimed at improving youth mental health in high-pressure educational contexts.

Autism Spectrum Disorder (autism) and Attention Deficit/Hyperactivity Disorder (ADHD) often co-occur, although it remains unclear if these conditions share common neurobiological foundations or exhibit distinct alterations in resting-state brain connectivity. We conducted a cross-sectional mega-analytic comparison of functional connectivity patterns linked to autism and ADHD traits in children and adolescents (ages 6-19 years; n=10,168), with follow-up analyses considering autism (n=764 autistic; n=893 neurotypical) and ADHD diagnoses (n=2,026 ADHD; n=2,409 neurotypical). In total, 12,732 unique child and adolescent participants were included: 3,528 in both analyses, 6,640 in the trait analysis only, and 2,564 in the diagnostic analysis only. Autism traits and diagnosis were associated with reduced connectivity between the thalamus, putamen, salience/ventral attention, and frontoparietal networks, while ADHD traits showed the opposite pattern. Hyperconnectivity between the default mode and dorsal attention networks was observed in both autistic and ADHD groups relative to neurotypical individuals and associated with ADHD traits. Despite frequent co-occurrence, autism and ADHD traits exhibit distinct neural signatures, with small effect sizes indicating subtle associations.

The transition to adulthood poses distinct challenges for young adults with autism spectrum disorder (ASD) (ages 18-25), particularly in establishing and achieving long-term goals. This is further complicated for those within the military and veteran communities. This study aimed to evaluate the feasibility, acceptability, and cultural fit of "Launching! to Adulthood," a 12-week telehealth intervention, adapted for military-dependent young adults with ASD and their military/veteran parents.

Building on previous research and incorporating stakeholder feedback, the intervention addressed key transition challenges such as executive functioning, mental health, vocational skills, and social engagement, while also aligning with military cultural values. A total of 20 young adults and 37 parents participated in the program.

Feasibility was demonstrated by high attendance rates, with 93% of young adults and 90% of parents attending all group sessions, and no family dropouts. Both young adults and parents reported high satisfaction with session logistics, though some logistical conflicts and a preference for in-person sessions were noted. Acceptability ratings were strong, with most satisfaction scores exceeding 7 out of 10, and both groups reporting significant gains in confidence and skills related to transitioning to adulthood. Cultural fit was confirmed, with 94% of participants finding the program relevant and aligned with military and family values. Preliminary outcomes indicated improvements in self-confidence, independence, social connections, and family relationships. Participants emphasized the program's effects in addressing the unique needs of the military community.

The findings highlight the importance of culturally tailored interventions in fostering successful transitions for underserved populations, specifically military-dependent young adults with ASD.

Colorectal cancer (CRC) with synchronous peritoneal metastasis (SPM) presents poor prognosis and complex treatment challenges. This study aimed to identify independent prognostic factors and develop nomogram-based prediction models for overall survival (OS) and progression-free survival (PFS) in CRC patients with SPM (CRC-SPM) undergoing cytoreductive surgery (CRS).

We retrospectively analyzed 218 CRC-SPM treated with CRS between October 2010 and April 2022. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for OS and PFS. Nomogram models were constructed based on these factors, and their predictive accuracy was assessed using calibration curves, ROC curves, and Decision Curve Analysis (DCA).

For OS, independent factors included age > 65 years (HR = 2.464, p = 0.005), N2 stage (HR = 2.720, p = 0.005), > 13 lymph nodes resected (HR = 0.496, p = 0.018), and postoperative chemotherapy (HR = 0.300, p = 0.020). For PFS, independent factors were age > 65 years (HR = 1.578, p = 0.040), concurrent liver metastasis (HR = 1.664, p = 0.016), > 14 PCI score (HR = 1.630, p = 0.031), and presence of ascites (HR = 1.706, p = 0.011). Nomogram models for predicting OS and PFS had AUC values of 0.717, 0.759, and 0.773 for OS, and 0.659, 0.689, and 0.790 for PFS at 1, 2, and 3 years, respectively.

This study identified key prognostic factors and developed reliable nomogram models for predicting OS and PFS in CRC-SPM. The findings highlight the importance of postoperative chemotherapy and intraoperative lymph node dissection and suggest focusing on high-risk factors such as age and N2 stage in clinical practice. The nomogram models provide a valuable tool for personalized prognosis assessment and treatment planning.

Parkinson's Disease is a progressively advancing neurological condition. Its severity is evaluated by utilizing the Hoehn and Yahr staging scale. Such assessments may be inconsistent, are more time-consuming, and expensive for patients. To address these shortcomings, this article introduces a machine learning-based gait classification system to assist doctors in identifying the stages of Parkinson's disease. This study utilizes two open-access benchmark datasets from PhysioNet and Figshare to assess ground reaction force collected from patients diagnosed with Parkinson's Disease. This study presents experiments conducted using machine learning algorithms namely Decision Tree, Random Forest, Extreme Gradient Boost, and Light Gradient Boosting Machine classification algorithms to predict severity of Parkinson's Disease. Among all the four algorithms, Light Gradient Boosting Machine classification algorithm have proven its supremacy. It gave an accuracy of 98.25%, Precision of 98.35%, Recall of 98.25%, and F1 Score of 98% for dataset 1. The performance of the algorithm slightly declines on dataset 2. It reports accuracy of 85%, Precision of 95%, Recall of 85% and F1 Score of 89% for dataset 2. Furthermore, this study used Explainable Artificial Intelligence to display the LightGBM classifier's classification pathways for Parkinson's disease severity prediction using Hoehn and Yahr staging on the scale from 0 to 5. This is helps the health experts in decision making. This work provides automated assistance to doctors for the rapid screening of Parkinson's disease patients based on disease severity. This work leaves a scope for integrating wearable sensors and developing real-time monitoring system for screening of Parkinson's Disease patients.

The changing retail food environment contributes to increasing burden of obesity and noncommunicable diseases. The study assessed the density of retail stores along with availability, price, and placement of food options in a low-income urban community of Delhi, India.

An audit of retail stores was conducted using an adapted Nutrition Environment Measure Survey tool covering nine locally relevant food items. For each item, healthier and less healthy options were identified based on global recommendations. Data were collected by personal observation and response of the shopkeeper. The study area was estimated using geospatial methods and population by electoral list. Results are expressed as proportions for availability, price ratio of less healthy to healthier food items, and density of stores per 100,000 population and per sq. km.

Among 70 stores, 88.2%, 7.4%, and 4.4% were small and large corner stores and small convenience stores, respectively. The density of food retail stores was 304 stores per sq. km and 99 stores per 100,000 population. A similar proportion of healthier and less healthy options were available for items like wheat flour, pulses, salt, milk, and bread. The price ratio was <1 for all items except for wheat flour and milk. The mean (95% confidence interval) number of less healthy items displayed at the cash counter, 7.38 (6.48-8.28), was significantly higher (P < 0.001) than that of healthier items, 2.74 (2.28-3.20).

The food environment was characterized by being predominantly small corner stores based on high density, equal availability of less healthy and healthy options, and adverse pricing and placement for healthier options.