Search Results (2,696)

The political transition in Syria following the fall of the Al-Assad regime in December 2024 has renewed debates about refugee return. This study examines Syrian refugees’ intentions to return from Jordan and the factors shaping these decisions using a mixed-method design. A stratified random sample of 1070 refugees residing in host areas and camps was surveyed through telephone interviews, complemented by four focus group discussions and two key informant interviews with experts. Although 61% of respondents expressed an intention to return, only 20% indicated concrete or immediate plans, suggesting that return remains largely aspirational rather than imminent. Access to housing and property (55%), economic condition (46%), and safety and security (40%) emerged as central determinants, indicating that structural barriers, rather than regime change alone, shape decision-making. Qualitative findings further reveal that emotional attachment to Syria sustains return aspirations, yet financial hardship, debt in Jordan, and housing destruction in Syria constrain refugees’ capabilities to act. These findings underscore that voluntary, safe, and dignified repatriation depends not only on addressing structural barriers in Syria, but also on maintaining essential protection and support for Syrian refugees in Jordan. Full article

Shapley values are the most widely used point-valued solution concept for cooperative games and have recently garnered attention for their applicability in explainable machine learning. Due to the complexity of Shapley value computation, users mostly resort to Monte Carlo approximations for large problems. We take a detailed look at an approximation method grounded in multilinear extensions proposed in 2021 under the name “Owen sampling”. We point out why Owen sampling is biased and propose unbiased alternatives based on combining multilinear extensions with stratified sampling and importance sampling. Finally, we discuss empirical results of the presented algorithms for various cooperative games, including real-world explainability scenarios. Full article

Background: Advanced liver fibrosis (LF) is a major determinant of prognosis across chronic liver diseases. Current biomarkers are often etiology-specific and lack cross-cohort robustness. Shared molecular drivers across etiologies remain incompletely defined, and effective anti-fibrotic therapies are limited. Methods: We developed a multi-algorithm consensus machine-learning framework to derive a robust LF progression signature. In the training non-alcoholic fatty liver disease (NAFLD) cohort GSE213621 (n = 368), samples were formulated as a binary classification task (mild fibrosis, F0–F2; advanced fibrosis, F3–F4). Candidate genes were screened in parallel using Boruta, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme Gradient Boosting (XGBoost). Genes selected by at least two algorithms were defined as a high-consensus pool, and genes consistently selected by all four algorithms were prioritized to construct a core signature. Model performance was evaluated by stratified cross-validation in the training cohort and externally validated in four independent cohorts of different etiologies (GSE49541, GSE84044, GSE130970, and GSE276114). Cellular sources of signature genes were characterized using single-cell RNA sequencing (scRNA-seq) datasets GSE136103 (human) and GSE172492 (mouse). For therapeutic discovery, the high-consensus expression profile was queried against the Connectivity Map (CMap) to prioritize compounds predicted to reverse the fibrotic transcriptional program. Withaferin A (WFA) was selected for experimental validation in a carbon tetrachloride (CCl₄)-induced mouse LF model and in the transforming growth factor-β1 (TGF-β1)-stimulated human hepatic stellate cell line LX-2. Bulk liver RNA-seq profiling was performed to interrogate WFA-associated molecular changes in vivo. Results: We identified a six-gene signature (CLEC4M, COL25A1, ITGBL1, NALCN, PAPPA, and PEG3) that discriminated advanced from mild fibrosis, achieving a mean AUC of 0.890 in internal cross-validation and an average AUC of 0.864 across external validation cohorts. scRNA-seq analysis revealed cell-type-specific expression with prominent enrichment in fibroblast populations. In vivo, WFA markedly attenuated CCl₄-induced fibrosis (p < 0.05) and reversed 1314 fibrosis-associated differentially expressed genes (adjusted p < 0.05), which were enriched in fatty acid metabolism and PPAR signaling, as well as extracellular matrix (ECM)–receptor interaction and focal adhesion (adjusted p < 0.05). In vitro, WFA suppressed TGF-β1-induced LX-2 activation, reducing α-SMA and Fibronectin expression (p < 0.05). Conclusions: We report a six-gene signature that robustly predicts advanced LF across etiologies, define its cellular context using single-cell atlases, and validate the anti-fibrotic activity of WFA in both in vivo and in vitro models. Bulk liver RNA-seq and cellular evidence further suggest that WFA-associated effects are linked to lipid metabolic programs, ECM remodeling, and attenuation of hepatic stellate cell activation. Full article

Background/Objectives: The high prevalence of obesity and obesity-associated diseases in the United States and worldwide places a tremendous burden on public health. Although lifestyle interventions, such as calorie-restricted diets and increased exercise, are generically recommended to individuals with overweight and obesity, it is well acknowledged that individual responses to the same lifestyle intervention vary significantly, underscoring the importance of individualized or precision nutrition-based approaches in obesity management. Methods: In a recent randomized, parallel-arm pilot study, manuka honey (21 g) was given daily to overweight and obese participants aged 40–75 years for four weeks. The levels of plasma interleukin (IL)-6 at the baseline and after honey treatment were measured. The 14 female participants were stratified into responder (R) and non-responder (NR) groups, based on their circulating IL-6 level changes. Plasma and fecal samples from the R and NR groups were subjected to untargeted metabolomics analysis and 16S rRNA analysis, respectively. Results: Among the female participants with overweight and obesity, 50% had reduced plasma levels of IL-6 after honey intake, and other 50% showed no such responses. Untargeted metabolomics analysis demonstrated that 22 metabolites markedly increased and eight decreased in the R group, relative to the NR group. A decrease in circulating glutamic acid could potentially predict the responsiveness to honey intake. 16S rRNA analysis showed that 23 and 14 genera were uniquely enriched in the R and NR groups, respectively. Enriched Bacteroides and Akkermansia in the R group are capable of metabolizing glutamic acid and thus may contribute to the decreased level of circulating glutamic acid. Conclusions: In this pilot study, participants with overweight and obesity showed different responses to honey intake. Circulating glutamic acid may have the potential to predict the responsiveness of patients to honey and provide guidance for precision nutrition-based dietary intervention. Full article

Background: Auditory brainstem responses (ABRs) are widely used for objective hearing threshold estimation in both adults and children. Click and CE-Chirp stimuli differ substantially in cochlear activation and neural synchrony, yet their relative performance in patients with ski-sloping hearing loss remains insufficiently characterized, particularly with regard to pediatric diagnostic implications. Methods: This study compared ABRs elicited by click and CE-Chirp stimuli in adults with ski-sloping sensorineural hearing loss. The same comparison was also performed in a pediatric cohort including hearing-impaired and normal-hearing children. Adult subjects were further stratified according to audiometric configuration (DROP 1 kHz vs. DROP 2 kHz). ABR thresholds, wave V latency, amplitude, and detectability were analyzed across stimulus types and intensity levels. Associations between ABR thresholds and behavioral audiometric measures were also examined. Results: In adults with ski-sloping hearing loss, CE-Chirp stimulation yielded significantly lower ABR threshold estimates than click stimulation, particularly in the DROP 2 kHz subgroup, and showed stronger correlations with behavioral pure-tone averages across low-, mid-, and high-frequency ranges. Wave V latencies were consistently shorter with CE-Chirp stimulation, while wave V amplitudes did not differ significantly between stimuli at suprathreshold levels. In children, ABR thresholds obtained with CE-Chirp were generally equal to or lower than those obtained with clicks, although statistical significance was limited by sample size. CE-Chirp stimulation was associated with shorter wave V latencies in both hearing-impaired and normal-hearing children and produced larger wave V amplitudes at selected suprathreshold intensities in hearing-impaired children. Conclusions: Click and CE-Chirp stimuli provide complementary information in ABR assessment. While click stimulation remains essential for robust waveform identification, CE-Chirp stimulation appears to offer advantages in threshold estimation and neural synchrony, particularly in ski-sloping hearing loss and pediatric evaluations. Discrepancies between click- and CE-Chirp-derived ABR thresholds should not be attributed solely to maturational or synchrony-related factors but may warrant further frequency-specific audiological assessment to optimize diagnosis and rehabilitation strategies. Full article

Background: The effectiveness of prostate-specific antigen (PSA)-based early detection of prostate cancer remains controversial and implementation-dependent. Screening policy changes have substantially altered PSA testing behavior in the United States, yet longitudinal evidence from non-organized European settings is limited. We assessed 12-year changes in awareness and utilization of PSA-based early detection and identified subgroups requiring targeted counseling. Methods: Two cross-sectional survey waves were conducted in 2009 (Study Phase 1) and 2021 (Study Phase 2) among men recruited via general practitioner practices in urban and rural regions of Germany. The survey was developed and reported according to the Consensus-Based Checklist for Reporting of Survey Studies (CROSS). Identical questionnaires were used across phases. Endpoints were awareness of PSA-based early detection and prior PSA testing. Univariable and multivariable logistic regression evaluated independent associations with sociodemographic and behavioral factors. To assess sensitivity to compositional differences between survey waves, post-stratified weighted analyses re-aligning Study Phase 2 to the Study Phase 1 distribution of age category, educational attainment, and smoking status were conducted. Results: The analytic cohort comprised 890 men (Study Phase 1, n = 755; Study Phase 2, n = 135). Compared with Study Phase 1, Study Phase 2 participants more frequently were non-smokers (63.0% vs. 48.5%, p < 0.001) and had a university degree (38.5% vs. 30.5%, p = 0.002). In primary multivariable analyses, higher educational attainment (OR 1.71, 95% CI 1.24–2.36) and paternity (OR 1.94, 95% CI 1.25–3.01) were independently associated with greater awareness, whereas increasing age (OR 1.39, 95% CI 1.29–1.50) and higher educational attainment (OR 1.63, 95% CI 1.19–2.24) were independently associated with utilization. Study phase was not independently associated with either endpoint in primary models. In post-stratified sensitivity analyses, study phase was positively associated with utilization, indicating sensitivity of temporal contrasts to population composition. Conclusions: In primary multivariable analyses, we did not detect statistically significant temporal differences in awareness or utilization of PSA-based early detection within this German non-organized setting. The emergence of a study phase effect in weighted sensitivity analyses suggests that apparent time trends may be influenced by compositional differences between survey waves. Persistent social gradients, particularly related to educational attainment, underscore the importance of targeted, evidence-based counseling in opportunistic early detection systems. Larger, prospectively designed studies are needed to distinguish true temporal change from sampling-related effects. Full article

Background: Insulin resistance is defined as reduced tissue responsiveness to insulin-mediated glucose actions. Gold standard methods like hyperinsulinemic-euglycemic clamp and hyperglycemic clamps are costly and rarely used in large epidemiological studies. The aim was to evaluate the best performing machine learning algorithm for insulin resistance predictions in Brazilian adolescents. Methods: We used data from 37,454 Brazilian adolescents from 12 to 17 years, sampled from the Study of Cardiovascular Risk Factors in Adolescents (2013–2014). Covariates included other cardiovascular risk factors. We evaluate seven machine learning models stratifying the subset by sex. The performance of the models was assessed by area under the curve (AUC), calibration curves and decision curve analysis (DCA). Finally, we adopted the SHAP approach to assess the importance of each variable to the best performing ML model. Results: The Logistic Regression model presented the best AUC value (AUC = 0.8 for boys and girls). The best performing ML models had higher calibration in girls than in boys. The DCA curves showed prevalence of almost equal values for girls and for boys. The most important clinical predictors for both sexes were waist circumference, triglycerides and age. Conclusions: Logistic Regression proved to be the best clinical prediction model comparable to complex models. Further studies are needed in more diverse populations. Full article

Background: Periprostatic adipose tissue (PPAT) fibrosis is a histological feature potentially linked to prostate cancer (PCa) aggressiveness, though its role is not fully understood. This study investigates the correlation between PPAT fibrosis and PCa aggressiveness and develops a radiomics model based on PPAT MRI features for non-invasive prediction. Methods: This retrospective study included 51 patients who underwent radical prostatectomy. PPAT samples were collected, stained with Sirius Red and quantitatively evaluated for fibrosis using 12 indices via 3D reconstruction with Imaris software. Patients were stratified by cancer aggressiveness based on Grade Groups. Radiomic features were extracted from T1-weighted MRIs of the PPAT. An XGBoost model was developed to predict aggressiveness using these features. Results: Significant correlations were found between multiple PPAT fibrosis indices and PCa aggressiveness (p < 0.05), with more aggressive tumors showing increased fiber complexity. PPAT fibrosis was also significantly associated with primary tumor location in the peripheral zone (p < 0.05). Conversely, PPAT volume showed no significant correlation with aggressiveness (p = 0.616). The radiomics model based on PPAT features achieved an AUC of 0.86 in predicting cancer aggressiveness. Conclusions: PPAT fibrosis is a promising marker of PCa aggressiveness, superior to PPAT volume. The significant link with tumor location provides new insights into the tumor microenvironment (TME). MRI-based radiomics of PPAT offers a potential non-invasive method for assessing fibrosis and aggressiveness, aiding in early diagnosis and personalized treatment. Full article

Background: Reducing dietary salt intake is a global public health priority. However, empirical evidence is needed to clarify whether higher levels of health literacy (HL) and eHealth literacy (eHL), together with the use of diversified information dissemination channels, are positively associated with better salt-related knowledge, attitudes, and practices (KAP). This study examined the indirect associations via eHL and the number of sources of salt-reduction information (NSSI) in the relationship between HL and salt-related KAP. Methods: A cross-sectional survey was conducted from 2022 to 2023 using multistage stratified random sampling among residents aged 15–69 in 22 counties/districts of Jiangxi Province, China. Data on sociodemographic characteristics, HL, eHL, NSSI, and salt-related KAP were collected through face-to-face household interviews using a standardized electronic questionnaire system. Spearman correlation analysis and multiple linear regression were applied to assess associations among HL, eHL, NSSI, and salt-related KAP. Path analysis was employed to evaluate the indirect associations between HL and salt-related KAP via eHL and NSSI. Results: A total of 5396 residents participated, of whom 51.50% were male. Participants aged 15–34, 35–54, and 55–69 years accounted for 13.10%, 42.96%, and 43.94% of the sample, respectively. After adjustment for covariates, individuals with adequate HL, adequate eHL, and a greater NSSI had significantly higher total salt-related KAP scores (p < 0.001). In the path analysis, the standardized direct association of HL with the total salt-related KAP was 0.229 (p < 0.001). The standardized indirect associations via NSSI and eHL were 0.089 (95% CI: 0.069 to 0.111, p < 0.001) and 0.057 (95% CI: 0.033 to 0.089, p < 0.001), respectively, accounting for 23.73% and 15.20% of the total association. Conclusions: High levels of HL and eHL, together with increased exposure to multiple salt-reduction information sources, are associated with improved salt-related KAP. Both eHL and NSSI partially explain the association between HL and salt-related KAP. Future salt-reduction interventions should integrate conventional health education with mobile health technologies to expand information dissemination channels and support sustained salt-reduction behaviors. Full article

Background/Objectives: Attention-deficit/hyperactivity disorder (ADHD) frequently persists into adulthood and is characterized by heterogeneous clinical presentations influenced by gender, demographic and psychosocial factors. Although gender-related differences in adult ADHD have been reported, individuals residing in rural settings remain underrepresented in empirical research. Guided by Gender-Based Analysis Plus (GBA+) framework, this study examined gender differences and psychosocial correlates of ADHD subtypes among adults in a rural Canadian population. Methods: A cross-sectional study was conducted using de-identified medical record data collected between February 2021 and January 2024 from a rural outpatient clinic in Northern British Columbia, Canada. The sample comprised 660 adults aged 19 years and older with a documented ADHD diagnosis. The combined presentation was the most common (67.0%), followed by the inattentive presentation (30.3%), while the hyperactive/impulsive presentation was rare (2.7%). In bivariate analyses, ADHD presentation was not significantly associated with gender, age group, employment status, or marital status. Prescribed ADHD medication differed across presentations (χ² (1) = 12.36, p < 0.001), with a higher proportion of individuals with the inattentive presentation reporting pharmacological treatment. In the pooled logistic regression model, prescribed ADHD medication was the only variable independently associated with presentation (OR = 0.54, 95% CI 0.38–0.77, p = 0.001). In gender-stratified models, this association remained evident among women, whereas no stable inferential conclusions could be drawn for men or gender-diverse participants. Conclusions: Within a GBA+ perspective, the findings suggest that gender may shape recognition and entry into care, rather than the clinical subtype identified at assessment, underscoring the need for a comprehensive assessment in rural clinical practice. Full article

Background: Epicardial adipose tissue (EAT) is an imaging-derived biomarker increasingly associated with cardiovascular inflammation and metabolic risk. Computed tomography (CT) allows for accurate volumetric quantification of EAT, but the clinical interpretation of longitudinal changes remains challenging. Artificial Intelligence (AI) may provide additional value by identifying patterns and predictors of EAT variation. Purpose: To evaluate longitudinal changes in CT-derived EAT volume and to assess the feasibility and performance of AI-based models in discriminating patients with EAT increase after immunotherapy. Methods: In this retrospective single-center study, EAT was volumetrically segmented on baseline and follow-up CT scans. EAT change (ΔEAT) was calculated, and patients were dichotomized according to EAT increase (ΔEAT > 0). Three supervised AI models—Support Vector Machine (SVM), Artificial Neural Network (ANN), and Extreme Gradient Boosting (XGBoost)—were trained using imaging-derived and clinical variables. Given the limited sample size and class imbalance, stratified two-fold cross-validation was adopted. Model performance was assessed using AUC, accuracy, and F1-score, and model interpretability was explored using permutation importance. Results: EAT volume showed a statistically significant increase at follow-up. In the AI analysis, SVM and ANN demonstrated good discriminative performance, with ANN achieving the highest AUC (~0.90). XGBoost failed to show meaningful predictive capability. Baseline EAT volume and follow-up duration emerged as the most relevant features. Conclusions: AI-based models, particularly SVM and ANN, are feasible tools for the analysis of CT-derived EAT changes, even in small cohorts. These results support the integration of AI-assisted EAT assessment into imaging-based cardio-oncology research. Full article

Introduction: Stereotactic radiotherapy (SRT) is increasingly used in oligometastatic non-small-cell lung cancer (NSCLC) and is known to elicit systemic immune effects, although the underlying mechanisms remain not fully understood. Methods: In this prospective pilot study, we evaluated plasma cytokine variations in 19 patients with oligometastatic or oligoprogressive NSCLC undergoing SRT. Peripheral blood samples were collected before treatment (T0) and one month after SRT (T1) and the concentrations of nine cytokines (IFN-γ, IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12p70, IL-17A and TNF-α) were quantified using a multiplex Luminex assay. Non-parametric tests and Cox regression models were used to investigate associations between cytokine levels, clinical variables, systemic treatments, and survival outcomes. SRT induced significant post-treatment increases in IFN-γ, IL-2, and IL-6, consistent with systemic pro-inflammatory activation and T-cell stimulation. Cytokine dynamics were influenced by patient- and tumor-related factors: female sex was associated with higher IL-2 and TNF-α levels; oncogene-addicted tumors showed lower IL-6 levels; and oligoprogressive disease exhibited attenuated cytokine variations compared with metachronous oligometastatic disease. Tyrosine kinase inhibitors were associated with globally reduced cytokine levels and blunted IL-1/IL-2 changes, whereas patients receiving immune checkpoint inhibitors displayed higher IL-2 and IL-6 concentrations and greater post-SRT increases in IFN-γ. Oncogene-addicted status and IL-12 variation emerged as independent predictors of overall survival and a composite model integrating these variables significantly stratified prognosis. Conclusions: These findings suggest that SRT triggers measurable systemic immune activation in oligometastatic NSCLC, which is further shaped by tumor biology, disease burden, and concomitant systemic therapies. Although limited by the small sample size, this study supports the feasibility and potential utility of cytokine profiling to refine patient selection and guide biomarker-driven combinations of SRT with targeted and immune-based treatments, warranting validation in larger prospective cohorts. Full article

Background and Objectives: Sexual dysfunction (SD) is common in multiple sclerosis (MS) but remains under-recognized in routine care. This study aimed to quantify the burden of SD in men and women with relapsing–remitting MS (RRMS), describe sex-stratified patterns across primary/secondary/tertiary domains, and examine associations with fatigue and MS-related health-related quality of life (HRQoL). Materials and Methods: In this cross-sectional observational study, RRMS participants were voluntarily recruited online via a QR code linking to a Google Forms survey. Men completed the International Index of Erectile Function-5 (IIEF-5), and women the Female Sexual Function Index (FSFI). MS-specific SD domains were assessed using the Multiple Sclerosis Intimacy and Sexuality Questionnaire (MSISQ), alongside the Fatigue Severity Scale (FSS) and the Multiple Sclerosis Quality of Life questionnaire (MSQOL-54). Sex differences were tested using parametric/non-parametric methods as appropriate, with false discovery rate (FDR) and Bonferroni adjustments for multiple comparisons. Results: Thirty-seven participants were included (16 men; 21 women). Mean age did not differ by sex (35.9 ± 4.0 vs. 38.9 ± 10.4 years; p = 0.23). All participants reported at least some degree of difficulty across MSISQ domains. Among men, 87.5% screened positive for erectile dysfunction within this sample (mild 37.5%, mild-to-moderate 12.5%, moderate 12.5%, severe 25.0%). When dysfunction type was defined as the highest MSISQ domain score, secondary SD was most frequent in both sexes (75.0% men; 76.2% women; p = 0.49). Women showed higher secondary domain scores at the uncorrected level (p = 0.04), but this did not survive FDR correction. In HRQoL and symptom measures, women reported markedly higher fatigue (FSS 46.1 ± 12.4 vs. 25.5 ± 12.7; p_FDR < 0.001) and poorer physical health indices, including pain-related outcomes. Conclusions: SD has represented a substantial burden within this RRMS sample, with secondary domain predominance in both sexes, highlighting the clinical relevance of symptom-related and functional interference. These findings support the value of multidimensional sexual health assessment in clinical research settings and may be relevant for clinical assessment and future research in MS. Full article

Validated instruments assessing gender stereotype endorsement among adolescents are scarce and often overlook contemporary domains like digital privacy. To address this gap, this study developed and validated the Gender Stereotypes and Roles Adherence Battery for Adolescents (GAB-A) in a sample of 2955 Italian adolescents attending public secondary schools in Rome (56.4% male; mean age 14.3 years). The battery comprises three modules: the Gender Stereotyped Attitude Scale (GSAS), Gender Role Activities Scale (GRAS), and Gendered Traits Inventory (GTI). Psychometric analysis confirmed robust factor structures, notably identifying a distinct “Relational Control” factor within the GSAS that assesses beliefs normalizing partner surveillance. The results revealed a stark pattern of gender differentiation: males endorsed prescriptive attitudes (GSAS, d = 1.07) and roles (GRAS, d = 0.88) substantially more than females, particularly regarding violence myths. Conversely, essentialist trait beliefs (GTI) showed negligible gender differences (d = 0.11). Associations between stereotypes and psychological health were gender-moderated; within-group analyses indicated that endorsement predicted higher distress, hostility, and alexithymia in males, while being unrelated to well-being in females. Finally, gender-stratified normative data and operational cut-offs were established. The GAB-A provides a psychometrically sound tool for identifying elevated endorsement profiles and evaluating violence prevention interventions. Full article

Contaminated environmental surfaces (fomites) act as pathogen reservoirs, yet surveillance data in arid megacities like Riyadh, Saudi Arabia—characterized by extreme heat and indoor climate control—remain limited. This study established a city-wide molecular baseline for surface contamination and evaluated meteorological influences. We conducted a stratified, longitudinal study (February 2023–May 2024), collecting 270 swabs from seven zones, including hospitals, airports, ATMs, and community hubs. Samples were pooled (N = 55) and screened using QIAstat-Dx multiplex PCR panels. Nineteen pools (34.5%) tested positive. Viral pathogens (SARS-CoV-2, Adenovirus, Rhinovirus) were detected in 10 pools (18.2%) and non-viral pathogens (bacteria/parasites) in 13 pools (23.6%), with 7.3% co-detections. Hospitals and airports emerged as primary hubs for respiratory viruses, while Cryptosporidium was the most frequent non-viral pathogen (n = 6), predominating on ATM interfaces. Binary logistic regression indicated that higher ambient temperature was significantly associated with detecting viral rather than non-viral pathogens among positive samples (OR = 1.728, p = 0.032). Despite outdoor aridity, public surfaces in Riyadh harbored diverse pathogens. The link between heat and viral detection suggests indoor microclimates drive persistence during hot seasons, necessitating targeted hygiene measures in high-risk nodes. Full article