Search Results (29,296)

Background: Migraine is a highly prevalent and disabling neurological disorder among university students that has significant impacts on personal and socioeconomic levels. Despite its impact, migraine remains underdiagnosed and undertreated. Objective: This study aimed to estimate the prevalence of probable migraine among university students in Greece and explore its association with sociodemographic data. Methods: A cross-sectional, questionnaire-based study was conducted between September 2023 and January 2024 among university students in Greece using a convenience sampling method. The Headache Screening Questionnaire—English Version (HSQ-EV) was used to screen for probable migraine, along with additional questions assessing demographic characteristics. Descriptive statistics and bivariate analyses were performed. Results: The prevalence of probable migraine was 20%. Female students were more likely to experience migraine compared to males. Migraine was also statistically significantly associated with marital status and employment status. In a multivariate logistic regression model including sex assigned at birth, age, educational level, marital status, and employment status, older age was independently associated with higher odds of migraine. Conclusions: Migraine is a prevalent health issue among university students in Greece, with clear gender and sociodemographic associations. Future studies with larger, more representative sample sizes and the use of validated diagnostic tools are needed to understand its determinants and inform targeted interventions. Full article

Childhood obesity is a substantial health problem worldwide. The origin of obesity (increased adiposity) can be partly traced back to intrauterine life. However, the determinants of fetal fat deposition remain unclear. This study investigated the association between cord blood adipocytokines related to lipid metabolism (leptin, adiponectin, and insulin-like growth factor-1 [IGF-1]) and fetal adiposity during gestation. A prospective study was conducted in a cohort of 94 singleton pregnancies. Fetal ultrasonography was performed at 24, 30, and 36 weeks of gestation. Estimated fetal adiposity (EFA) was calculated by integrating measurements of cross-sectional arm and thigh fat area percentages and anterior abdominal wall thickness. Plasma cytokine levels and C-peptide immunoreactivity (as a proxy for fetal insulin resistance) were evaluated in cord blood samples obtained at delivery. The associations of cord blood leptin, adiponectin and IGF-1 levels with EFA at 24, 30, and 36 weeks were determined by multiple linear regression, adjusted for potential covariates. The multivariate analyses indicated that leptin was significantly correlated with EFA at 30 and 36 weeks. Leptin was also positively correlated with C-peptide immunoreactivity in the umbilical cord. Cord adiponectin levels were not associated with EFA across gestation. Cord IGF-1 levels were significantly correlated with EFA and estimated fetal body weight (EFW) at 36 weeks. In conclusion, cord leptin was associated with EFA at 30 and 36 weeks, and IGF-1 was associated with EFA at 36 and EFW at 36 weeks. In Conclusion, cord leptin was associated with EFA at 30 and 36 weeks, and IGF-1 was associated with EFA and EFW at 36 weeks. Considering the effects of leptin and IGF-1 on fetal insulin resistance and lipid metabolism, increased levels of leptin and IGF-1 are potential plasma biomarkers of increased fetal adiposity, which may predispose to infant obesity and metabolic dysfunction in later life. Full article

Forest biomass is closely related to carbon sequestration capacity and can reflect the level of forest management. This study utilizes four machine learning algorithms, namely Multivariate Stepwise Regression (MSR), K-Nearest Neighbors (k-NN), Artificial Neural Network (ANN), and Random Forest (RF), to estimate forest aboveground biomass (AGB) in Chenzhou City, Hunan Province, China. In addition, a canopy height model, constructed from a digital surface model (DSM) derived from Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and an ICESat-2-corrected SRTM DEM, is incorporated to quantify its impact on the accuracy of AGB estimation. The results indicate the following: (1) The incorporation of multi-source remote sensing data significantly improves the accuracy of AGB estimation, among which the RF model performs the best (R² = 0.69, RMSE = 24.26 t·ha⁻¹) compared with the single-source model. (2) The canopy height model (CHM) obtained from InSAR-LiDAR effectively alleviates the signal saturation effect of optical and SAR data in high-biomass areas (>200 t·ha⁻¹). When FCH is added to the RF model combined with multi-source remote sensing data, the R² of the AGB estimation model is improved to 0.74. (3) In 2018, AGB in Chenzhou City shows clear spatial heterogeneity, with a mean of 51.87 t·ha⁻¹. Biomass increases from the western hilly part (32.15–68.43 t·ha⁻¹) to the eastern mountainous area (89.72–256.41 t·ha⁻¹), peaking in Dongjiang Lake National Forest Park (256.41 t·ha⁻¹). This study proposes a comprehensive feature integration framework that combines red-edge spectral indices for capturing vegetation physiological status, SAR-derived texture metrics for assessing canopy structural heterogeneity, and canopy height metrics to characterize forest three-dimensional structure. This integrated approach enables the robust and accurate monitoring of carbon storage in subtropical forests. Full article

Hotpot dishes are widely favored by consumers for their flavor profiles developed during the cooking process. This study investigated the quality characteristics and volatile compounds (VOCs) of donkey meat slices across varying boiling durations (0–42 s) using gas chromatography–ion mobility spectrometry (GC-IMS). The results demonstrated that donkey meat boiled for 12–18 s exhibited optimal characteristics in terms of meat retention, color parameters, shear force values, and pH measurements. Forty-eight distinct VOCs were identified in the samples, with aldehydes, alcohols, ketones, acids, furans, and esters representing the predominant categories. Among these compounds, 18 were identified as characteristic aroma compounds, including 3-hexanone, 2, 3-butanedione, and oct-1-en-3-ol. Samples subjected to different boiling durations were successfully differentiated through topographic plots, fingerprint mapping, and multivariate analysis. The abundance and diversity of VOCs reached peak values in samples boiled for 12–18 s. Furthermore, 28 VOCs were identified as potential markers for distinguishing between different boiling durations, including 2-butoxyethanol D, benzaldehyde D, and (E)-2-pentenal D. This study concludes that a boiling duration of 12–18 s for donkey meat during hotpot preparation yields optimal quality characteristics and volatile flavor compound profiles and provides valuable insights for standardizing cooking parameters in hotpot preparations of other meat products. It is necessary to confirm this finding with sensory evaluations in further research. Full article

Background/Objectives: Lymphovascular invasion (LVI) has been consistently linked to poor outcomes in patients with bladder cancer (BC), yet its independent prognostic value, especially after adjusting for established pathological features, remains debated. This study aimed to evaluate the prognostic value of LVI in the context of other pathological features of patients undergoing radical cystectomy. Methods: We conducted a retrospective cohort study including 200 patients treated at the Municipal Clinical Hospital in Cluj-Napoca, Romania. Associations between LVI and overall survival (OS) were assessed using univariable and multivariable Cox proportional hazards models, with Kaplan–Meier curves used for visualizing survival distributions. Results: In univariable analysis, increasing age, presence of LVI, advanced pathological tumor stage (pT ≥ 2), and nodal involvement (pN ≥ 1) were significantly associated with worse OS. LVI was a strong predictor of poor survival (HR 3.13; 95% CI: 2.09; 4.69; p < 0.001). However, in multivariable analysis, only tumor stage (HR 4.85; 95% CI: 2.19; 10.77; p < 0.001) and nodal involvement (HR 1.87; 95% CI: 1.13; 3.09; p = 0.015) remained independently associated with OS. In patients with incomplete nodal staging (Nx), LVI was significantly associated with OS (p = 0.028). Conclusions: Our findings reinforce the prognostic relevance of LVI in bladder cancer and support its role as a marker of aggressive tumor biology, highlighting its value in clinical risk assessment, especially in patients with incomplete nodal staging. Routine reporting of LVI in pathology and consideration in treatment planning are warranted. Full article

Soil quality assessment plays a critical role in promoting sustainable land management, particularly in fragile steppe ecosystems. This study provides a comprehensive geoecological evaluation of heavy metal contamination (Pb, Cd, Zn, Cu, Co, Ni, Fe, and Mn) in soils across five districts of the Akmola region, Kazakhstan. The assessment incorporates multiple integrated pollution indices, including the geochemical pollution index (Igeo), pollution coefficient (CF), ecological risk index (Er), pollution load index (PLI), and integrated pollution index (Zc). Spatial analysis combined with multivariate statistical techniques (PCA and clustering analysis) was used to identify pollutant distribution patterns and differentiate areas by risk levels. The findings reveal generally low to moderate contamination, with cadmium (Cd) posing the highest environmental risk due to its elevated toxic response coefficient, despite its low concentration. The study also explores the connection between current soil conditions and historical land-use changes, particularly those associated with the Virgin Lands Campaign of the mid-20th century. The highest PLI values were recorded in the Yesil and Atbasar districts (7.88 and 7.54, respectively), likely driven by intensive agricultural activity and lithological factors. PCA and cluster analysis revealed distinct spatial groupings, reflecting heterogeneity in both the sources and distribution of soil pollutants. Full article

Body composition is associated with multiple factors. The main objective of this study is to determine the association between diet and sociodemographic factors on the body structure and composition of university students at a public university in Ecuador. This cross-sectional study allowed for the collection of detailed body composition and dietary data from 204 students (41.7% men and 58.3% women, with an average age of 23.3 ± 4.4 years). The study was conducted using validated questionnaires and bioimpedance techniques. Statistical analysis included ANOVA tests, complemented by a PCA-Biplot, to examine the relationships between study variables. Statistical analysis revealed that men’s birthplace had a significant impact on several body measurements, such as hip circumference and weight, but no significant differences were observed in body structure and composition based on nutrient intake. Furthermore, larger upper-arm circumference in women was correlated with higher fat intake. The results of the multivariate analysis indicated a differential influence of dietary components on body composition. The study highlights the need for nutritional intervention strategies and educational programs that consider the diversity of students’ backgrounds to promote healthy habits and mitigate the negative effects of eating habits and irregular physical activity patterns on their health and body composition. Full article

Background: The role of impulse oscillometry (IOS) in evaluating asthma control remains a challenge because the interpretation varies by many factors, including ethnicity. We aimed to assess the diagnostic contribution of spirometry and IOS, established from reference equations, in the detection of uncontrolled asthma. Methods: This retrospective study was conducted in adult asthma subjects with normal spirometry. Uncontrolled asthma was defined as an Asthma Control Test (ACT) score ≤ 19. Receiver operating characteristic (ROC) curves were plotted to compare the diagnostic abilities of the %-predicted of heterogeneity of resistance at 5 Hz and 20 Hz (R5-R20) and the %-predicted of forced expiratory volume in the first second (FEV₁) in detecting uncontrolled asthma. Multivariable risk regressions were performed to identify the %-predicted of R5-R20 as a predictor for uncontrolled asthma. Results: The %-predicted of R5-R20 demonstrated a superior diagnostic ability for detecting uncontrolled asthma compared to the %-predicted FEV₁, with the area under the ROC curves (AuROC) = 0.939 vs. 0.712, respectively, p < 0.001. The %-predicted R5R20 of ≥200 showed the highest AuROC for detecting uncontrolled asthma with an adjusted risk ratio of 10.86 (95%CI; 3.77, 31.29; p < 0.001). Conclusions: IOS demonstrated better diagnostic ability for detecting uncontrolled asthma than spirometry. Full article

Chronic coronary syndrome (CCS) and atrial fibrillation (AF) are prevalent cardiovascular conditions that share numerous risk factors and pathophysiological mechanisms. While clinical scores commonly used in AF—such as CHA₂DS₂VA (which includes congestive heart failure, hypertension, age ≥ 75, diabetes, stroke/TIA, vascular disease, and age 65–74), HAS-BLED (which incorporates hypertension, abnormal renal/liver function, stroke, bleeding history, labile INR, elderly age, and drug/alcohol use), and C₂HEST (incorporating coronary artery disease, COPD, hypertension, elderly age ≥ 75, systolic heart failure, and thyroid disease)—are traditionally applied to rhythm or bleeding risk prediction, their value in estimating the angiographic severity of coronary artery disease (CAD) remains underexplored. We conducted a prospective, single-center study including 131 patients with suspected stable CAD referred for coronary angiography, stratified according to coronary angiographic findings into two groups: significant coronary stenosis (S-CCS) and non-significant coronary stenosis (N-CCS). At admission, AF-related scores (CHA₂DS₂, CHA₂DS₂VA, CHA₂DS₂VA-HSF, CHA₂DS₂VA-RAF, CHA₂DS₂VA-LAF, HAS-BLED, C₂HEST, and HATCH) were calculated. CAD severity was subsequently assessed using the SYNTAX and Gensini scores. Statistical comparisons and Pearson correlation analyses were performed to evaluate the association between clinical risk scores and angiographic findings. Patients in the S-CCS group had significantly higher scores in CHA₂DS₂VA (4.09 ± 1.656 vs. 3.20 ± 1.338, p = 0.002), HAS-BLED (1.98 ± 0.760 vs. 1.36 ± 0.835, p < 0.001), CHA₂DS₂VA-HSF (6.00 ± 1.854 vs. 5.26 ± 1.712, p = 0.021), and C₂HEST (3.49 ± 1.501 vs. 2.55 ± 1.279, p < 0.001). Multivariate logistic regression identified HAS-BLED and C₂HEST as independent predictors of significant coronary lesions. A threshold value of HAS-BLED ≥ 1.5 and C₂HEST ≥ 3.5 demonstrated moderate discriminative ability (AUC = 0.694 and 0.682, respectively), with acceptable sensitivity and specificity. These scores also demonstrated moderate to strong correlations with both Gensini and SYNTAX scores. AF-related clinical scores, especially HAS-BLED and C₂HEST, may serve as practical and accessible tools for early CAD risk stratification in patients with suspected CCS. Their application in clinical practice may serve as supplementary triage tools to help prioritize patients for further diagnostic evaluation, but they are not intended to replace standard imaging or testing. Full article

Aim: The frontal QRS-T (fQRS-T) angle serves as an electrocardiography indicator that visually represents the disparity between the frontal QRS axis and the T axis. The heterogeneity between cardiac depolarization and repolarization rises with an increase in the fQRS-T angle. Prior research has demonstrated a relationship between the fQRS-T angle and the extent of atherosclerosis, along with the risk of cardiovascular mortality. The non-alcoholic fatty liver disease fibrosis score (NFS) is a non-invasive scoring tool used to quantify the degree of liver fibrosis in individuals with non-alcoholic fatty liver disease (NAFLD). Non-alcoholic fatty liver disease increases the risk of atherosclerotic cardiovascular disease, which can be predicted using the NFS. The objective of this study is to examine the potential correlation between the fQRS-T angle and NFS in patients with stable angina pectoris. Materials and Methods: This cross-sectional study included 177 (48 women) non-alcoholic patients who underwent coronary angiography due to stable angina pectoris. Individual NFS values were calculated using clinical and laboratory data. Patients were categorized into two groups based on a NFS threshold value of 0.67. Following a minimum fasting period of 12 h, biochemical laboratory parameters were acquired using a peripheral venous sample, and electrocardiographic data were recorded. Results: The univariate logistic regression analysis revealed significant associations between hypertension (p = 0.018), coronary artery disease (p = 0.014), neutrophil (p = 0.024), hemoglobin (p = 0.038), and low-density lipoprotein (LDL, p = 0.007) with the NFS. The electrocardiographic variables related to the score included the QRS duration (p = 0.015), Pmax (p = 0.026), QTC interval (p = 0.02), and fQRS-T angle (p < 0.001). In the multivariate logistic regression analysis, NFS was independently associated with LDL (OR: 0.984, 95% CI: 0.970–0.998, p = 0.024) and fQRS-T angle (OR: 3.472, 95% CI: 1.886–6.395, p < 0.001). Conclusions: The FQRS-T angle may exhibit a distinct correlation with NAFLD. Extensive investigations should validate this link, since the fibrosis score can serve as an effective tool for monitoring patients prior to the onset of clinical symptoms associated with liver fibrosis. Full article

Background/Objectives: Parenting stress, the emotional strain resulting from the demands of child-rearing, can profoundly affect both parental well-being and children’s emotional and behavioral development. This study examined the impact of maternal parenting stress during early childhood on the longitudinal progression of children’s internalizing, externalizing, and attention deficit hyperactivity disorder (ADHD) symptoms, from early childhood through adolescence. Methods: The study included 406 mother–child pairs from the Rhea mother–child cohort in Crete, Greece. Maternal parenting stress was assessed at age 4 using the Parental Stress Scale (PSS). Children’s symptoms were evaluated at ages 4 (Strengths and Difficulties Questionnaire, ADHD Test), 6, 11, and 15 years (Child Behavior Checklist, Conners’ Parent Rating Scale) through maternal reports. Multivariate mixed regression models, incorporating a random intercept for each child and a random slope for age at follow-up, were used to analyze the trajectories of symptoms from ages 4 to 15. Group-based trajectory modeling was applied to identify trajectory groups from 4 to 15 years, and multinomial logistic regression models were implemented to examine the associations between parental stress and group trajectories. Results: The results revealed that higher parental stress at age 4 was significantly associated with increased internalizing (b = 0.94, 95% CI: 0.68, 1.21), externalizing (b = 1.03, 95% CI: 0.75, 1.30), and ADHD symptoms (b = 0.86, 95% CI: 0.58, 1.14) over the study period. Notably, the impact of parenting stress on behavioral problems decreased with age (interaction with age, p = 0.032). Additionally, higher parenting stress at age 4 was linked to a greater likelihood of belonging to adverse symptom trajectories, including high decreasing, low increasing, and stable high trajectories for both internalizing and externalizing problems. Conclusions: These findings underscore the importance of early maternal parenting stress as a predictor of long-term emotional and behavioral difficulties in children, emphasizing the need for early intervention programs that support maternal mental health and children’s emotional development. Full article

Background: Primary sclerosing cholangitis (PSC) accounts for 10–15% of liver transplants but is the leading cause of retransplant. This study evaluates whether PSC patients have different survival and graft outcomes when receiving grafts from donors after brain death (DBD) versus circulatory (DCD) death. Methods: Using the SRTR database (2004–2024), we compared PSC patients receiving DCD vs. DBD grafts. Demographics and outcomes including graft loss, mortality, and retransplant were analyzed using multivariable logistic and Cox regression, along with propensity-matched analysis. Results: Among 5762 PSC patients, 391 (6.8%) received DCD grafts. Patients receiving DCD grafts were older but had lower MELD scores (19 vs. 22; p < 0.001) and were less often functionally dependent (11.3% vs. 24.4%; p < 0.001). Multivariable Cox regression demonstrated that receipt of a DCD graft was independently associated with time to graft loss (HR 1.59; CI 1.10–2.31; p = 0.013. Similarly, DCD graft receipt significantly increased the likelihood of requiring retransplant (HR 3.25; CI: 1.93–5.46; p < 0.001) but did not increase the likelihood of mortality. Propensity matched analysis further supported these finding with significantly higher graft loss with DCD grafts at one and two years and higher retransplant rates at all time points including 5-years (+7.9%, CI 4.4 to 11.4%; p < 0.001). Conclusions: DCD grafts in PSC patients are linked to worse graft survival and higher retransplant rates. They may be best suited for older, lower-MELD patients, but further studies on perfusion strategies are needed. Full article

The standard treatment for patients with locally advanced non-small cell lung cancer (NSCLC) is concurrent chemoradiation. However, clinical responses are heterogeneous and generally not known until after the completion of therapy. Multiple studies have investigated imaging predictors (radiomics) for different cancer histologies, but little exists for NSCLC. The objective of this study was to develop a multivariate CT-based radiomics model to a priori predict responses to definitive chemoradiation in patients with lung adenocarcinoma. Methods: Patients diagnosed with locally advanced unresectable lung adenocarcinoma who had undergone chemoradiotherapy followed by at least one dose of maintenance durvalumab were included. The PyRadiomics Python library was used to determine statistical, morphological, and textural features from normalized patient pre-treatment CT images and their wavelet-filtered versions. A nested leave-one-out cross-validation was used for model building and evaluation. Results: Fifty-seven patients formed the study cohort. The clinical stage was IIIA-C in 98% of patients. All but one received 6000–6600 cGy of radiation in 30–33 fractions. All received concurrent platinum-based chemotherapy. Based on RECIST 1.1, 20 (35%) patients were classified as responders (R) to chemoradiation and 37 (65%) patients as non-responders (NR). A three-feature model based on a KNN k = 1 machine learning classifier was found to have the best performance, achieving a recall, specificity, accuracy, balanced accuracy, precision, negative predictive value, F1-score, and area under the curve of 84%, 70%, 80%, 77%, 84%, 70%, 84%, and 0.77, respectively. Conclusions: Our results suggest that a CT-based radiomics model may be able to predict chemoradiation response for lung adenocarcinoma patients with estimated accuracies of 77–84%. Full article

This paper reveals a simple methodology to create local-correlation models suitable for the closed-form pricing of two-asset financial derivatives. The multivariate models are built to ensure two conditions. First, marginals follow desirable processes, e.g., we choose the Geometric Brownian Motion (GBM), popular for stock prices. Second, the payoff of the derivative should follow a desired one-dimensional process. These conditions lead to a specific choice of the dependence structure in the form of a local-correlation model. Two popular multi-asset options are entertained: a spread option and a basket option. Full article

This study investigates the impact of data distribution and bootstrap resampling on the anomaly detection performance of the Isolation Forest (iForest) algorithm in statistical process control. Although iForest has received attention for its multivariate and ensemble-based nature, its performance under non-normal data distributions and varying bootstrap settings remains underexplored. To address this gap, a comprehensive simulation was performed across 18 scenarios involving log-normal, gamma, and t-distributions with different mean shift levels and bootstrap configurations. The results show that iForest substantially outperforms the conventional Hotelling’s T² control chart, especially in non-Gaussian settings and under small-to-medium process shifts. Enabling bootstrap resampling led to marginal improvements across classification metrics, including accuracy, precision, recall, F1-score, and average run length (ARL)₁. However, a key limitation of iForest was its reduced sensitivity to subtle process changes, such as a 1σ mean shift, highlighting an area for future enhancement. Full article