Search Results (1,228)

Background/Objectives: Intraoperative neurophysiological monitoring (IONM) is used to detect and prevent neurological injury during extramedullary spinal cord tumor (EMSCT) resection, but its diagnostic accuracy lacks systematic validation with recent evidence. This meta-analysis evaluates the performance of somatosensory evoked potentials (SSEPs), transcranial motor evoked potentials (TcMEPs), and multimodal (SSEP + TcMEP) IONM in predicting deficits during EMSCT resections. Methods: Following PRISMA-DTA guidelines, we searched MEDLINE, PubMed, and Ovid (inception to April 2025) for studies on IONM in EMSCT surgeries (PROSPERO: CRD420251047345). Pooled sensitivity, specificity, and reversibility metrics were calculated using bivariate models, with quality assessed via QUADAS-2. Z-test and Bayesian meta-analysis were used for comparisons. Results: Across 20 studies (2672 patients), multimodal IONM showed a log DOR of 4.310 (95% CI: 3.581–5.039) and an AUC of 94.2%, TcMEP monitoring showed a log DOR of 4.367 (95% CI: 3.765–5.127) and an AUC of 92%, while SSEP monitoring showed a log DOR of 3.463 (95% CI: 2.702–4.224) and an AUC of 82%. All modalities demonstrated high specificity (>95%), indicating low false-positive rates. Bayesian analysis revealed >90% probability that TcMEP-based approaches were superior to SSEPs. Reversible TcMEP changes were associated with an 11% (95% CI: 4–24%) postoperative deficit rate, compared to 35% (95% CI: 12–67%) for SSEPs. Conclusions: These findings caution against relying solely on SSEPs and support the use of multimodal IONM strategies, which enhance early detection of impending neurological injury, enable timely surgical interventions, and help prevent permanent neurological damage in EMSCT resections. Although TcMEP and multimodal monitoring showed similar diagnostic accuracy, we continue to recommend multimodal approaches as the current standard of care, pending prospective studies to determine if TcMEP alone can reliably replace multimodal monitoring. Full article

Amid rapid urbanization, Chinese cities face mounting ecological pressure, making it critical to balance environmental protection with public well-being. As visual perception accounts for over 80% of environmental information acquisition, it plays a key role in shaping experiences and evaluations of ecological space. However, current ecological planning often overlooks public perception, leading to increasing mismatches between ecological conditions and spatial experiences. While previous studies have attempted to introduce public perspectives, a systematic framework for analyzing the spatial relationship between ecological and visual sensitivity remains lacking. This study takes 56,210 street-level points in Tianjin’s central urban area to construct a coordinated analysis framework of ecological and perceptual sensitivity. Visual sensitivity is derived from social media sentiment analysis (via GPT-4o) and street-view image semantic features extracted using the ADE20K semantic segmentation model, and subsequently processed through a Multilayer Perceptron (MLP) model. Ecological sensitivity is calculated using the Analytic Hierarchy Process (AHP)—based model integrating elevation, slope, normalized difference vegetation index (NDVI), land use, and nighttime light data. A coupling coordination model and bivariate Moran’s I are employed to examine spatial synergy and mismatches between the two dimensions. Results indicate that while 72.82% of points show good coupling, spatial mismatches are widespread. The dominant types include “HL” (high visual–low ecological) areas (e.g., Wudadao) with high visual attention but low ecological resilience, and “LH” (low visual–high ecological) areas (e.g., Huaiyuanli) with strong ecological value but low public perception. This study provides a systematic path for analyzing the spatial divergence between ecological and perceptual sensitivity, offering insights into ecological landscape optimization and perception-driven street design. Full article

Background/Objectives: The Human Papillomavirus (HPV) is one of the most common causes of STIs, posing a significant public health problem. Today, the transmission of HPV can be very effectively prevented, making it important to vaccinate the target population at a young age. The aim of this study was to examine the attitudes and beliefs of parents regarding the HPV vaccine and the HPV vaccination of their child. Methods: This cross-sectional study was conducted in Osijek, Croatia, from June 2021 to September 2022 via a self-administered questionnaire and included 215 respondents. Results: The results showed that respondents who would vaccinate their child were significantly more likely to be those who work in the healthcare field, who had heard of the term HPV, who had sought information about the HPV vaccine on their own, and who had received information about vaccination from school doctors. The attitude towards vaccination was more negative among respondents who did not intend to vaccinate their child. In predicting the decision not to vaccinate one’s child against HPV, bivariate logistic regression revealed that the probability of non-vaccination increases with working outside the field of healthcare (OR = 4.61) and a negative attitude towards vaccination (OR = 1.46), while the probability of non-vaccination decreases if information was received from a school doctor (OR = 0.46). Furthermore, multivariate logistic regression showed that there is a significant model in predicting non-vaccination against HPV, consisting of two predictors: working outside the healthcare field (OR = 8.15) and a negative attitude towards vaccination (OR = 1.49). Conclusions: Given that parents are responsible for making the decision about HPV vaccination, it is necessary to invest additional efforts in educating them about the importance of preventing HPV infections and the benefits of HPV vaccination itself. Full article

Intensive human interference has severely disrupted the natural and ecological environments of coastal areas, threatening ecosystem services (ESs). Meanwhile, the relationships between ESs exhibit certain variations across different spatial scales. Therefore, identifying the scale effects of interrelationships among ESs and their underlying driving mechanisms will better support scientific decision-making for the hierarchical and sustainable management of coastal ecosystems. Therefore, employing the Integrated Valuation of ESs and Tradeoffs (InVEST) model combined with GIS spatial visualization techniques, this investigation systematically examined the spatiotemporal distribution of four ESs across three scales (grid, county, and city) during 2000–2020. Complementary statistical approaches (Spearman’s correlation analysis and bivariate Moran’s I) were integrated to systematically quantify evolving ES trade-off/synergy patterns and reveal their spatial self-correlation characteristics. The geographical detector model (GeoDetector) was used to identify the main driving factors affecting ESs at different scales, and combined with bivariate Moran’s I to further visualize the spatial differentiation patterns of these key drivers. The results indicated that: (1) ESs (except for Water yield) generally increased from coastal regions to inland areas, and their spatial distribution tended to become more clustered as the scale increased. (2) Relationships between ESs became stronger at larger scales across all three study levels. These ESs connections showed stronger links at the middle scale (county). (3) Natural factors had the greatest impact on ESs than anthropogenic factors, with both demonstrating increased explanatory power as the scale enlarges. The interactions between factors of the same type generally yield stronger explanatory power than any single factor alone. (4) The spatial aggregation patterns of ESs with different driving factors varied significantly, while the spatial aggregation patterns of ESs with the same driving factor were highly similar across different spatial scales. These findings confirm that natural and social factors exhibit scale dependency and spatial heterogeneity, emphasizing the need for policies to be tailored to specific scales and adapted to local conditions. It provides a basis for future research on multi-scale and region-specific precision regulation of ecosystems. Full article

Background: Chorioamnionitis is the inflammation of the placenta, amniotic fluid, and fetal membranes and its histological confirmation, histologic chorioamnionitis (HCA) is defined as the diffuse infiltration of neutrophils into the chorioamniotic membranes. Several biomarkers have been evaluated for its early prediction, including interleukin-6 (IL-6), which can be measured in plasma, amniotic fluid, and cervicovaginal fluid (CVF). Aims and Scope: We aimed to systematically review and meta-analyze the role of IL-6 in the prediction of HCA, in several body fluids and among distinct subgroups. Methods: A literature search was conducted in PubMed, Embase, Cochrane Library, and CT.gov between March 2024 and July 2024. Studies that measured IL-6 in AF, CVF, or plasma and conducted a placental examination were included. The Quality Assessment of Diagnostic Accuracy Studies—2 (QUADAS-2) tool was used to assess methodological quality. Bivariate analysis combined with a linear mixed model was used for quantitative synthesis, and summary estimates were calculated. Summary Receiver Operating Characteristic (SROC) curves were constructed to evaluate diagnostic accuracy. The z-test was used for subgroup comparisons. Results: In total, 43 studies were included in this meta-analysis, 23 for amniotic fluid (AF), 9 for plasma, and 11 for CVF. AF IL-6 in the overall population had a very good diagnostic performance with an AUC = 0.82 (95% CI: 0.78–0.85) for HCA prediction, with a sensitivity of 65% (95% CI: 0.55–0.74) and a specificity of 84% (95% CI: 0.76–0.89), performing superiorly for the preterm labor (PTL) group (Area Under Curve (AUC) = 0.88, 95% confidence interval (CI): 0.85–0.91) compared with the Preterm premature rupture of membranes (PPROM) subgroup (AUC = 0.76, 95% CI: 0.72–0.80). Plasma IL-6 in the overall population had a good diagnostic performance with an AUC = 0.79 (95% CI: 0.76–0.83), similar to that for the PTL and PPROM subgroups, with a sensitivity of 72% (95% CI: 0.58–0.83) and a specificity of 79% (95% CI: 0.72–0.84). CVF IL-6 in the PPROM group had an excellent diagnostic accuracy, the highest observed in our research (AUC = 0.91, 95% CI: 0.88–0.93), higher than CVF in the overall population, where diagnostic accuracy remained very good. The QUADAS-2 tool revealed a high risk of bias overall. Conclusions: CVF IL-6 could serve as a valid, non-invasive screening test for pregnant women to stratify risk for HCA, while a combination of AF, CVF, and plasma IL-6 could be a tractable diagnostic tool for clinicians, but large-scale Randomized Control Trials are needed to validate this hypothesis. Full article

Flood frequency analysis is essential for designing resilient hydraulic infrastructure, but traditional stationary models fail to capture the influence of climate variability and land-use change. This study applies a bivariate logistic model with non-stationary marginals to eight gauging stations in Sinaloa, Mexico, each with over 30 years of maximum discharge records. We compared stationary and non-stationary Gumbel and Generalized Extreme Value (GEV) distributions, along with their bivariate combinations. Results show that the non-stationary bivariate GEV–Gumbel distribution provided the best overall performance according to AIC. Importantly, GEV and Gumbel marginals captured site-specific differences: GEV was most suitable for sites with highly variable extremes, while Gumbel offered a robust fit for more regular records. At station 10086, where a significant increasing trend was detected by the Mann–Kendall and Spearman tests, the stationary GEV estimated a 50-year return flow of 772.66 m³/s, while the non-stationary model projected 861.00 m³/s for 2075. Under stationary assumptions, this discharge would be underestimated, occurring every ~30 years by 2075. These findings demonstrate that ignoring non-stationarity leads to systematic underestimation of design floods, while non-stationary bivariate models provide more reliable, policy-relevant estimates for climate adaptation and infrastructure safety. Full article

This study focuses on quantifying wind–temperature load combination coefficients for long-span hybrid cable-stayed suspension bridges (HCSSBs) to overcome limitations of traditional methods in ignoring load correlation and geometry nonlinearity. A probabilistic framework is proposed to use site-specific load data to determine load combination coefficients, focusing on load correlation and geometric nonlinearity while assuming that stress reflects load effects and that 100-year samples are statistically representative. Long-sequence meteorological data, including wind and temperature measurements, were used to construct marginal and bivariate joint distributions, which characterize the randomness and correlation of wind and temperature loads. Load samples covering the design reference period were generated and validated via convergence tests. Four load scenarios (individual temperature, individual wind, linear superposition, and nonlinear coupling) were designed, and key control points are screened using indicators reflecting the comprehensive load effect $\stackrel{-}{\mathit{EII}}$, combined load proportion $\zeta$, and nonlinear influence $\eta$. Based on stress responses of key control points, load combination coefficients were derived with probability modeling. A case study for a bridge with span length of 2300 m shows that the load combination coefficients for the main girder are 0.60 (east wind) and 0.59 (west wind), while they are 0.51 (east wind) and 0.58 (west wind) for the main tower. These results demonstrate that the proposed method enables the provision of rational load combination coefficients. Full article

Background/Objectives: Orthorexia nervosa and appearance-related pressures are increasingly discussed in youth sport, where performance demands may amplify perfectionistic tendencies and the internalization of cultural body ideals. This study examined how sociocultural attitudes toward appearance and perfectionism relate to orthorexic tendencies among adolescent football athletes. Methods: The study included players from a soccer school, with a final sample of 83 participants. All were Polish citizens aged 16–19. A cross-sectional design was used with standardized instruments: the Polish adaptation of the Düsseldorf Orthorexia Scale (DOS) to index symptoms of ON risk, the Sport Perfectionism Questionnaire (positive/negative perfectionism), and the SATAQ-3 subscales to assess sociocultural internalization/pressures and information exposure. Results: Across the entire sample (n = 73), most athletes were classified as having no risk of ON—60 people (82.2%), a smaller proportion showed an increased risk—10 people (13.7%), and symptoms of ON were found in 3 people (4.1%). In bivariate analyses, orthorexic tendencies co-occurred with perfectionism. In multivariate models, the addition of the perfectionism block provided a significant increase in explained variance over age, BMI, and sociocultural attitudes, while the SATAQ-3 block contributed only a small amount of additional variance in the presence of other predictors. Conclusions: Orthorexic risk is present but not widespread in adolescent football athletes. Perfectionistic tendencies emerge as salient psychosocial correlates of orthorexic symptoms, while sociocultural pressures appear relevant but partly overlapping and not uniquely predictive when modeled together. Full article

Objective: The objective of this study was to assess clinical-functional vulnerability (CFV) and associated factors in community-dwelling older adults treated in primary care. Methods: A cross-sectional study was conducted with non-institutionalized elderly individuals ≥60 years randomly selected from five Health Units in Jundiaí/SP, Brazil, in 2023. Sociodemographic data, health behaviors, and data on oral health (number of teeth; chewing: good/fair/poor), cognitive function (10-CS), nutritional status (MNA), health literacy (HLS-14), sarcopenia (SARC-F+CC) and frailty (IVCF-20) were collected. Descriptive and bivariate analyses between the outcome (CFV) and the independent variables were performed using the chi-squared test and binary logistic regression models (p < 0.05). Results: A total of 211 older adults participated in this study; 72% were female and the mean age was 70.41 years (±7.45). Regarding CFV, a high risk was identified in 9.5% of the participants (n = 19), a moderate risk in 34.6% (n = 73), and a low risk in 55.9% (n = 118). After adjusting the regression model, the following variables were associated with CFV: lower income (OR = 1.90; 95%CI: 1.02–3.55), poor (OR = 5.18; 95%CI: 2.13–12.63) and fair (OR = 2.36; 95%CI: 1.10–5.05) chewing, risk of malnutrition or malnourished (OR = 2.36; 95%CI: 1.23–5.52), and low literacy (OR = 1.86; 95%CI: 1.09–3.45). Conclusion: Socioeconomic factors, nutritional status (underweight or malnourished), poor or fair chewing, and low health literacy were associated with CFV among older people. Strengthening primary health care through targeted interventions may help prevent frailty or delay its progression. Understanding the predictors of frailty can guide health professionals, managers, and researchers in designing preventive and health promotion strategies, as well as public policies within Primary Health Care. Full article

Background and Objectives: Postpartum lumbopelvic pain (PLPP) is a common condition that negatively affects many women’s quality of life. We aimed to analyze the influence of emotional well-being, kinesiophobia, and sleep quality as predictors of PLPP during the first year postpartum. Materials and Methods: A cross-sectional study was conducted with 192 women in their first year postpartum. Validated questionnaires were administered to evaluate pain (Oswestry Disability Index, ODI), postpartum depression (PPD) (Edinburgh Postnatal Depression Scale, EPDS), sleep quality (Pittsburgh Sleep Quality Index, PSQI), and kinesiophobia (Tampa Scale of Kinesiophobia, TSK-11). Bivariate correlations and binary logistic regression were performed to identify predictors of PLPP. Results: Overall, 42.2% of participants reported lumbopelvic pain. The prevalence of postpartum depressive symptoms was 59.9%, and kinesiophobia was present in 30.7% of women with pain. Both PPD and kinesiophobia were significantly associated with the presence of PLPP (p < 0.001). In the multivariate model, depression was the main predictor (OR = 8.1), followed by kinesiophobia (OR = 3.6). Sleep quality was not an independent predictor but may be related to PLPP through indirect mechanisms. No significant associations were found with sociodemographic, obstetric, or lifestyle variables. Conclusions: PPD and kinesiophobia are key factors in the occurrence of PLPP, while sleep quality may act as a mediating variable. These findings highlight the need for postnatal interventions addressing emotional health and fear of movement to improve the prevention and management of lumbopelvic pain in this population. Full article

In semi-arid regions, flood events are often characterized by rapid runoff and high hydrological variability, posing significant challenges for infrastructure safety and flood risk assessment. Traditional flood frequency analysis methods, typically based on univariate models using annual flood peak, may fail to capture the full complexity of such events. This study investigates the limitations of the univariate approach through the analysis of the 2004 flood event in the Jaguaribe River basin (Brazil), which caused the Castanhão Reservoir to receive a discharge of more than 5 hm³ and fill from 4.5% to over 70% of its capacity in just 55 days. Although the peak discharge in 2004 was not an exceptional record, the combination of high flood volume and short duration revealed a much rarer event than suggested by peak flow alone. To improve compound flood risk assessment, a bivariate frequency analysis based on copula functions was applied to jointly model flood peak and average flood intensity. The latter is a variable newly proposed in this study to better capture the short-duration but high-volume flood until peak that can strongly influence dam safety. Specifically, for the 2004 event, the univariate return period of flood peak was only 35 years, whereas the joint return period incorporating both peak flow and average flood intensity reached 995 years—underscoring a potential underestimation of flood hazard when relying solely on peak flow metrics. Our bivariate return periods and the average flood intensity metric provide actionable information for climate adaptation, supporting adaptive rule curves and risk screening during initial impoundment and high-inflow events in semi-arid reservoirs. Collectively, the proposed methodology offers a more robust framework for assessing extreme floods in intermittent river systems and offers practical insights for dam safety planning in climatically variable regions such as the Brazilian Semi-Arid. Full article

Background and Objectives: Urban–rural health disparities reflect differences in health outcomes, healthcare access, and socio-economic conditions between populations. In Serbia, limited research has quantified how socio-demographic and socio-economic characteristics influence settlement type and healthcare utilization. The aim of this study was to examine the relationship between settlement type and socio-demographic/socio-economic factors, and to assess whether these differences are reflected in patterns of healthcare utilization. Materials and Methods: Data were drawn from the 2019 Serbian National Health Survey, a nationally representative, stratified, two-stage random sample including 12,439 adults aged ≥20 years. Settlement type (urban vs. rural) was the primary dependent variable. Descriptive statistics, Chi-square and t-tests, and bivariate and multivariate logistic regression models were used to assess associations. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with significance set at p < 0.05. Results: Urban residence was more likely among unmarried individuals, those living in Šumadija/Central Serbia, and those with higher education. Primary or lower education reduced the odds of urban residence, and middle-income groups were less likely to live in urban areas compared to the richest. Settlement type was not significantly associated with hospital or day hospital use. However, rural residents had lower use of prescribed medicines, higher use of non-prescribed medicines, and more frequent physiotherapy visits. Private practice use was over twice as likely in urban settlements. Conclusions: To address urban–rural healthcare disparities in Serbia, targeted strategies could include enhancing health literacy in rural areas, incentivizing physicians to work in underserved regions, expanding telemedicine and mobile health services, improving access to prescribed medications, and strengthening public–private healthcare integration to ensure equitable access across all settlement types. Full article

Reservoir landslides undergo saturated–unsaturated transitions under hydrological variations. Matric suction significantly influences slip-zone soil strength. Existing studies lack analysis of suction–rate–strength coupling, while Amontons’ model fails for cohesive soils. This study investigated Huangtupo landslide slip-zone soil in the upper reaches of the Yangtze River using pressure plate and saturated salt solution methods to determine the soil–water characteristic curve. Suction-controlled ring shear tests were conducted under three matric suction levels ($\Psi$ = 0, 200, and 700 kPa) across net normal stresses (${\sigma }_{net}$ = 100–800 kPa) and shear rates ($\dot{\gamma }$ = 0.05–200 mm/min). Key findings revealed the following: (1) significant suction–rate coupling effects were shown, with 700 kPa suction yielding 30% higher residual strength than saturated conditions, validating matric suction’s role in enhancing effective stress and particle contact strength; (2) residual cohesion showed strong logarithmic correlation with shear rate, with the fastest growth below 10 mm/min, while the residual friction angle varied minimally (0.68°), contributing little to overall strength; (3) a bivariate model relating residual cohesion to $\dot{\gamma }$ and $\Psi$ was established, overcoming traditional single-factor limitations. The study demonstrates that dual-parameter Coulomb modeling effectively captures multi-field coupling mechanisms in unsaturated slip-zone soils, providing theoretical foundations for landslide deformation prediction and engineering design under dynamic hydrological conditions. Full article

Background: Aviation is one of the most demanding professions, exposing pilots to persistent stressors such as fatigue, irregular schedules, and high safety responsibility. These conditions heighten vulnerability to depression, anxiety, and stress (DAS), yet the protective mechanisms mitigating such effects remain less well understood. Objective: This study examined the roles of resilience, coping strategies, and fatigue in predicting DAS among commercial airline pilots. Method: A sample of 200 pilots completed validated self-report measures: the Connor–Davidson Resilience Scale (CD-RISC), the Coping Inventory for Stressful Situations (CISS), the Fatigue Severity Scale (FSS), and the Depression Anxiety Stress Scale (DASS-21). Data were analyzed using bivariate correlations, hierarchical multiple regression, and mediation/moderation analyses via the PROCESS macro. Results: Resilience was negatively correlated with total DAS scores (r = −0.46, p < 0.001), while fatigue (r = 0.42, p < 0.001) and avoidance coping (r = 0.38, p < 0.001) were positively correlated. The regression model accounted for 46% of the variance in DAS (R² = 0.46). Task-focused coping predicted lower stress levels, whereas avoidance coping predicted higher anxiety and depression. Resilience moderated the relationship between stress and depression, buffering the impact of stress on mood outcomes. Mediation analyses indicated that coping styles partially explained the protective effect of resilience. ANOVA results confirmed that pilots with high resilience reported significantly lower depression scores than those with medium or low resilience, F(2, 197) = 6.72, p < 0.01. Conclusions: Resilience emerged as both a direct and indirect buffer against psychological strain in aviation. These findings underscore the importance of promoting adaptive coping and resilience training, alongside effective fatigue management, to enhance pilot well-being and maintain safety in aviation systems. Full article

Background/Objectives: Glidants and lubricants are commonly used pharmaceutical excipients that enhance powder flowability and reduce inter-particle friction, respectively, but they also negatively impact critical quality attributes such as tablet tensile strength and drug release rate. Quantifying these effects is essential as the pharmaceutical industry transitions from batch to continuous manufacturing. Methods: This study develops a rational-function-based modeling approach to capture the effects of lubricants and glidants on tableting. The framework automatically identifies upstream critical material attributes and process parameters, such as excipient concentration and mixing time, and describes their coupling to first and second orders. Reduced-order models were constructed to evaluate the influence of these variables on the four stages of powder compaction—die filling, compaction, unloading, and ejection—using formulations composed of 10% acetaminophen, microcrystalline cellulose, and varying small concentrations of magnesium stearate or colloidal silica. Tablets were fabricated across a wide range of relative densities by varying dosing position and turret speed. Results: The modeling approach successfully quantified the effects of lubricant and glidant mixing conditions on each compaction stage, providing mechanistic insight into how upstream conditions propagate through the tableting process and influence critical quality attributes. Conclusions: Overall, the rational-function-based framework offers a systematic approach to quantify and predict the impact of lubricants and glidants on tablet performance, thereby enhancing product and process understanding in continuous manufacturing. Full article