Search Results (17,842)

Background: Canada’s cervical cancer elimination plan is challenged by suboptimal screening participation and rising incidence of cervical cancer over the past decade. Cytology, the primary cervical screening method in Canada, is being replaced with HPV testing, which offers superior sensitivity for detecting pre-cancerous lesions and supports initiating screening at age 25 or older and extending screening intervals to five years. Research has shown that women’s insufficient knowledge and negative attitudes toward HPV screening represent a significant barrier to screening uptake. Methods: We conducted a web-based national survey using Best–Worst Scaling (trade off utilities) to quantify women’s preferences for screening test modality, age of initiation, and screening intervals. We also assessed preferences for information sources, provider type, and communication methods. Underscreened individuals were oversampled. Results: Among adequately screened (N = 1778) and underscreened (N = 1570) individuals, preferences favoured co-testing (cytology plus HPV testing), initiating screening at age 21, and three-year screening intervals. Underscreened participants showed relatively higher preference for HPV self-sampling, and as opposed to adequately screened participants, preferred screening by a gynecologist rather than a family physician. Across groups, participants preferred receiving screening-related information and communication by email over postal mail. Conclusions: The misalignment between women’s preferences and current HPV test-based screening implementation plans requires immediate education interventions and modernized, user-preferred communication channels for cervical screening-eligible individuals in Canada. Full article

Introduction: Sleep is an essential dimension of good physical and mental health. Lesbian, gay, and bisexual (LGB) women experience inequities in sleep duration and disturbance compared to heterosexual women. Psychosocial and behavioral characteristics are important to sleep in the general population; they may advance our understanding about sleep inequities among LGB women and provide key information for developing promising interventions. Methods: Data for this project were provided by the Women’s Health Initiative (WHI). The sample size for this project was 1436: 884 LG women and 552 bisexual women. Outcome variables were sleep duration and disturbance. The authors sought to clarify the associations, including the strength, between psychosocial factors and sleep outcomes among LGB women. Associations between psychosocial characteristics, health behaviors, and sleep outcomes were tested using multivariable, hierarchical, nested, linear regression models, stratified by sexual orientation. Results: Social strain, social function, optimism, and negative emotional expressiveness were significantly associated with sleep outcomes for LGB women. Health behaviors were not consistently or strongly associated with sleep outcomes for LGB women. Conclusions: The findings point to the importance of social strain, social function, negative emotional expressiveness, and optimism in LGB women’s sleep. It is possible that LGB women’s sleep could be improved with evidence-based interventions that use our findings. Full article

Tick-borne pathogens (TBPs) are increasingly recorded in urban areas, where synanthropic wildlife may sustain pathogen transmission cycles. The European hedgehog (Erinaceus europaeus), frequently infested with ectoparasites, may serve as an urban reservoir of zoonotic TBPs. We investigated TBPs in host tissues and associated ectoparasites (Ixodes spp. and Archaeopsylla erinacei) from 129 hedgehogs in northwestern Italy. Anaplasma phagocytophilum, Borrelia burgdorferi sensu lato and Rickettsia spp. were detected in skin, spleen and ectoparasites (Ixodes spp. and Archaeopsylla erinacei). One spleen sample was positive for B. miyamotoi. Molecular identification revealed A. phagocytophilum ecotype 1, B. afzelii and B. bavariensis. A flea-borne Rickettsia closely related to the zoonotic Rickettsia asembonensis was identified for the first time in European hedgehogs. All pathogens were more prevalent in skin than in spleen. In skin, A. phagocytophilum and B. burgdorferi s.l. showed a positive interaction, whereas both were negatively associated with Rickettsia spp. These findings highlight hedgehogs as potential urban reservoirs of zoonotic TBPs, posing a potential risk for humans and domestic animals. The marked skin tropism of these pathogens supports the use of skin for TBP surveillance and underlines its role as a key interface for vector-borne transmission. Full article

This work reports the reuse of waste glass as a sustainable silica source for the synthesis of mesoporous silica, as an alternative to conventional silica precursors. Silica gel was produced through alkaline dissolution of glass powder using sodium hydroxide and subsequently employed as a precursor for the synthesis of porous silica. The waste-derived glass powder and the synthesized silica-based materials were characterized to assess their structural, morphological, surface, and textural properties. XRD analysis confirmed the amorphous nature of all samples, while FTIR spectra indicated successful silica network formation with modifications in bond connectivity. SEM imaging revealed spherical particles with average diameters of approximately 0.19 ± 0.02 µm for silica gel and 0.15 ± 0.03 µm for the mesoporous silica. Zeta potential measurements indicated a negative surface charge and good colloidal stability in aqueous media. Nitrogen sorption analysis revealed that the specific surface area was limited by the low solubility of silica gel in acidic media, which prevents ideal condensation on the surface of surfactant micelles. The results demonstrate that waste glass-derived silica gel is a promising precursor, although the synthesis conditions did not yield a highly ordered mesostructure, highlighting the need for further control of precursor solubility and pH. Full article

Italy is estimated to host thousands of abandoned mines, many of which contain large volumes of mine residues that negatively affect land and aquatic ecosystems, also posing a risk to human health. This study evaluates the effectiveness of spaceborne imaging spectroscopy combined with laboratory spectroscopy for characterizing the mineralogy and geochemistry of residues from the abandoned Montevecchio sulfide mine in southwestern Sardinia, a site recognized as a significant source of environmental pollution. Mine tailings and their downstream dispersion along the Rio Irvi River were systematically studied and sampled in the field. Collected samples were analyzed in the lab using an Analytical Spectral Device (ASD) spectroradiometer, complemented by powder X-ray Diffraction (XRD) for mineralogical characterization. Affected zones were subsequently mapped using the Environmental Mapping and Analysis Program (EnMAP) hyperspectral satellite data at a 30 m spatial resolution, by applying a polynomial fitting technique to the image spectra. The results reveal the presence of Fe- and Zn-bearing sulfates and oxy/hydroxides, indicative of acidic-to-circum-neutral drainage conditions in the mine tailings and along affected streams. Specifically, EnMAP was able to detect jarosite and subtle chemical and physical variations in Fe-hydroxides. This integrated approach enabled the delineation of environmental conditions and zones with varying acidity based on the spectral characteristics of secondary minerals. Overall, the study demonstrates the potential of EnMAP data for mapping acid mine drainage and assessing environmental impacts in legacy mining areas. Full article

Background/Objective: Informal caregiving for individuals with severe mental disorders (SMDs) often leads to significant psychological distress. However, the specific coping strategies that determine mental health outcomes among siblings remain poorly understood. This study aimed to analyze the predictive capacity of various coping strategies regarding health, perceived stress, self-esteem, and caregiving experience for siblings. Methods: A cross-sectional study was conducted with a sample of siblings of patients with SMDs (N = 60) from mental health service. Self-report measures were used to assess perceived health, perceived stress, self-esteem, coping strategies, and caregiving experience. Multiple linear regression analyses were performed for each dependent variable, controlling for collinearity. Results: The siblings reported a higher mean use of problem-focused coping strategies compared to emotion-focused coping strategies. Regression models were statistically significant for all analyzed variables, except for somatic symptoms. Emotion-focused maladaptive coping (EFMC) strategies emerged as the most consistent and powerful predictor, showing a significant association with positive caregiving appraisal (β = 0.657), depression (β = 0.500), poor health (β = 0.453), negative stress (β = 0.449), social dysfunction (β = 0.429), self-esteem (β = −0.390), and anxiety (β = 0.368). In contrast, problem-focused strategies were largely non-significant, except for an association with positive and negative aspects of caregiving (β_PFMC = 0.509, β_PFMC = 0.312, respectively), and positive stress (β_PFAC = −0.272). Conclusions: These results suggest that while siblings of people with SMDs report a greater use of problem-focused coping strategies, the adoption of EFMC strategies is the most detrimental factor observed, given their negative influence on mental health, self-esteem, and caregiving experience. Full article

School burnout is an increasing concern in highly competitive educational contexts. As artificial intelligence (AI) becomes embedded in classrooms, it shapes both learning processes and students’ stress experiences. Grounded in Mindset Theory and Conservation of Resources framework, this longitudinal study examined whether AI learning support moderates the link between stress mindset and school burnout. A sample of 850 Chinese middle school students (Mage = 15.09, 41% boys) completed two waves of surveys one year apart. Regression results showed that viewing stress as enhancing predicted lower subsequent burnout after controlling for baseline burnout and demographics. Although AI learning support did not directly predict burnout, its interaction with stress mindset was significant: the negative association between a positive stress mindset and burnout was observed when AI learning support was high. These findings suggest that AI can function as an external resource that amplifies adaptive beliefs, offering new pathways for fostering resilience in digital learning environments. Full article

Duckweed/algal bloom-type black–odorous waters (DAWs) exhibit composite optical properties of vegetation and pollution, posing intractable remote sensing identification challenges in complex environments. Current methods suffer from three critical limitations: a misclassification rate exceeding 25% due to spectral confusion with artificial green covers, an 18.7% false-negative rate for small patches (stemming from the imbalance between CNNs and Transformers), and insufficient feature dimensionality to characterize the dual properties of DAWs. To address these gaps, this study proposes a novel method that integrates the ASGICTVS feature set with a customized SwinTf-Unet model. The ASGICTVS feature set combines vegetation-sensitive metrics, optical water quality indicators, and visual features. The SwinTf-Unet model utilizes an optimized 4 × 4 window, an embedded feature fusion module, and an adaptive shifted window stride to balance global context capture and local detail reconstruction. Experiments on 21,104 GF-2 satellite samples demonstrate that the method achieves 87.50% precision, 88.41% recall, an 85.32% F1-score, and an 83.46% Intersection over Union (IoU), outperforming DeepLabV3+ by 14.56 percentage points in the IoU. With an inference time of 0.87 s per 512 × 512-pixel image and a stable performance across cross-regional datasets (IoU: 82.1–85.3%), it exhibits strong efficiency and generalization. This study resolves DAW spectral confusion, enables high-precision segmentation, and establishes a standardized feature threshold system, providing reliable technical support for large-scale automated DAW monitoring and regional water environment management. Full article

This study develops a mathematical optimization framework to determine optimal inspection policies for imperfect production systems subject to stochastic deterioration. System degradation is modeled using a Weibull power law process, which captures the increasing likelihood of transitions from in-control to out-of-control states over time. When deterioration occurs, a reverse-order inspection strategy based on negative binomial sampling is employed, wherein an inspection continues until a predefined number of conforming items is obtained. The proposed model integrates inspection decisions with production learning effects and Bayesian demand updating. Learning-by-doing is incorporated through an experience-dependent production cost function, while demand uncertainty is addressed using Bayesian posterior estimation. A comprehensive expected total cost function is formulated, including production, inspection, inventory holding, warranty, and rework costs. The analytical properties of the model are examined, demonstrating that the expected total cost function is strictly convex with respect to the inspection decision variable. This convexity guarantees the existence and uniqueness of the optimal solution. Numerical experiments and sensitivity analyses illustrate the effects of defect rates, learning parameters, warranty periods, and demand uncertainty on the optimal inspection policy. The results show that jointly optimizing inspection intensity, learning effects, and demand information leads to significant cost reductions and robust decision-making in deteriorating production systems. Full article

This paper aims to investigate the impact of ethnic diversity among employees and managers on firm performance, focusing on return on assets and return on equity. The analysis is conducted on a sample of 391 U.S. companies over a five-year period, 2020–2024. The quantitative framework includes a wide range of indicators related to financial performance, ethnic diversity among employees, ethnic categories of managers, and other control variables. The research methodology employs the ordinary least squares (OLS) method to highlight these effects, using fixed-effects and random-effects regression models, both linear and nonlinear. By estimating the regression models, the empirical results support the hypotheses established in the current state of the literature, indicating that ethnic diversity affects firm performance in a mixed manner, with both positive and negative effects on ROA and ROE. These findings are particularly relevant for practitioners, given the need to integrate minority representation into performance assessment, risk evaluation, and decision-making processes. Furthermore, regarding the female component within firms, this dimension contributes to the promotion of sustainability and a sound ESG-oriented approach. Consequently, social factors such as ethnicity can influence companies’ financial performance and shape how firms are perceived by investors. Full article

This study investigates left-turn safety at urban intersections using surrogate safety measures derived from field video observations. Time-to-Collision (TTC) among motorized traffic and Post-Encroachment Time (PET) among pedestrian and motorized traffic were extracted for left-turn conflicts across five intersection types in Thessaloniki, Greece, and linked to geometric attributes, signal operations, and traffic conditions. Count-based models (Poisson, Negative Binomial) were estimated alongside machine-learning approaches (Random Forest, Gradient Boosting with Poisson loss). For PET events, the Poisson model had the best balance of parsimony and predictive accuracy, whereas the Negative Binomial model provided a superior fit for TTC events. Results indicate that PET-defined conflicts increased with pedestrian volume and the presence of shared and protected left-turn lanes, and decreased with higher opposing flow, greater average acceleration, and wider end-approach lanes. By contrast, TTC events were associated with lower average speeds, the presence of protected signal phasing for left turns, and the number of passenger cars. Machine-learning models underperformed relative to classical count models, reflecting limited sample size and the discrete event structure. The analysis indicates that the determinants of TTC and PET differ, with certain variables such as pedestrian activity and lane configuration having contrasting effects on the two surrogate safety measures. The analysis reveals that pedestrian demand and shared lane configurations significantly increase PET occurrences, whereas TTC events are more strongly associated with vehicle volumes, speeds, and signal phasing. This distinction underscores the importance of tailoring safety assessment and intervention strategies to the type of interaction being evaluated. Full article

Triple-negative breast cancer (TNBC) represents the most aggressive breast cancer subtype, with its highly heterogeneous tumor microenvironment posing substantial challenges for precision diagnosis and therapy. To address this, we aim to construct a novel prognostic framework based on tumor-immune interactions. Through integrative analysis of single-cell RNA sequencing data from 30 TNBC samples (106,132 cells), we identify key tumor expression metaprograms and uncover their interaction with an immunosuppressive dendritic-cell subset, a process associated with the NECTIN1–NECTIN4 axis. Leveraging these interactions, we developed and validated two immunological prognostic models using multi-cohort transcriptomic data, including the stress response tumor cell and pDC_CLEC4C prognostic model (SPSM) and the immune response tumor cell and pDC_CLEC4C prognostic model (IPSM). These models effectively stratified TNBC patients into distinct risk groups, with the low-risk group characterized by an immunologically active microenvironment and elevated expression of immune checkpoint genes, suggesting a potential responsiveness to immunotherapy. Furthermore, we identified several potential therapeutic agents, including imatinib and bortezomib. Collectively, our dual-model framework provides a tool for risk stratification, offers translational insights for precision treatment, and presents new directions for understanding TNBC heterogeneity and therapeutic development. Full article

Background: Transcranial Direct Current Stimulation (tDCS) has shown potential in improving negative symptoms (NS) and Cognitive Impairment Associated with Schizophrenia (CIAS). However, heterogeneity in stimulation protocols and sample characteristics limit definitive conclusions regarding tDCS effectiveness in schizophrenia. Given the detrimental effects of cigarette smoking, particularly on cognition, this study explored the role of cigarette smoking as a modifiable individual factor potentially contributing to methodological heterogeneity by evaluating tDCS effects on NS and CIAS in Smoker (SM) and Non-Smoker (NoSM) patients. Methods: Post hoc analyses of a double-blind RCT were performed on 50 patients, randomized to 2 mA active or sham-tDCS (15 weekday sessions) with bilateral bipolar-nonbalanced prefrontal placement. The sample was divided according to the smoking status, consisting of 28 SM and 22 NoSM. Separate one-way analyses of covariance (ANCOVA) were performed within each subgroup to assess changes over time between treatment conditions. Clinical outcomes included Positive and Negative Symptoms Scale (PANSS), Brief Assessment of Cognition in Schizophrenia (BACS), Clinical Global Impression (CGI) and Calgary Depression Scale for Schizophrenia (CDSS) total scores. Results: SM exhibited baseline lower cognitive scores in verbal memory, motor speed and working memory domains. NS improved in both SM and NoSM with large effect size. Significant improvement in CIAS, specifically in working memory and verbal fluency, were found exclusively in NoSM. Conclusions: Cigarette smoking appeared to limit tDCS effectiveness in improving CIAS but not NS in schizophrenia. We suggested that the neurotoxic milieu linked to chronic exposure to neurotoxins of cigarette smoking could be responsible for these effects, counterbalancing the neuroprotective effects of tDCS. Further studies are warranted to replicate these findings. Full article

Background/Objectives: Traumatic experiences may lead to both negative and positive outcomes. Positive psychological changes following trauma are commonly referred to as posttraumatic growth (PTG). The present study aims to examine factors associated with posttraumatic growth among Syrian refugees who have been living in Turkey for an extended period. Methods: This cross-sectional study included a sample of 240 Syrian refugees. Participants completed the Posttraumatic Stress Disorder Checklist (PCL-5), the Posttraumatic Growth Inventory (PTGI), and the Mindful Attention Awareness Scale (MAAS). Path analysis was conducted to examine the effects of PTSD symptoms and mindfulness levels on posttraumatic growth. In addition, Multivariate Adaptive Regression Spline (MARS) analysis was used to identify threshold values for the contributions of these variables to posttraumatic growth. Results: The mean age of the participants was 36.9 ± 10.4 years, and 47% were female. The direct effect of PTSD symptoms on posttraumatic growth was negative and statistically significant (β = −0.291, p < 0.001). PTSD symptoms also had an indirect effect on posttraumatic growth through mindfulness (β = −0.254), resulting in a total effect of −0.545. According to the MARS model, when MAAS scores exceeded 78, mindfulness demonstrated a positive effect on posttraumatic growth. Conclusions: The findings indicate that PTSD symptoms among refugees are associated with posttraumatic growth through both direct and indirect pathways. Furthermore, mindfulness emerges as a key factor in understanding the development of posttraumatic growth in this population. Full article

Background/Objectives: High-risk, low-frequency incidents such as building collapses and large chemical fires can result in acute, high-dose exposures to toxic agents for first responders and the surrounding community. While these exposures may last for hours to days, their contribution to firefighters’ risks for cancer and other diseases is relatively unknown. In February 2023, a freight train transporting chemicals derailed and caught fire in East Palestine, Ohio, US. More than 350 firefighters, primarily volunteer, responded to the incident. In this cross-sectional study, we evaluated epigenetic markers of toxicity in responding firefighters. We hypothesized that exposures from responding to the train derailment would alter the expression of microRNAs (miRNAs) linked to carcinogenesis. Methods: We enrolled 62 responding firefighters and a comparison group of 26 firefighters from the same region who did not respond to the incident. We measured the relative expression of 800 miRNAs in blood samples using the nCounter Human v3 miRNA expression panel. We compared the expression of miRNA between exposure groups in negative binomial regression models, adjusting for potential confounders. Results: At a false discover rate cut-off of 5% (q-value < 0.05), 16 miRNAs had significantly higher expression and one significantly lower among firefighters that responded to the incident. Top disease-related pathways in which these miRNAs were enriched included those relevant to neurodegenerative diseases, vascular disease, and multiple cancer sites. Conclusions: Overall, results suggest responding to one large incident can have non-transient impacts on miRNA expression. Whether this translates into longer-term health risks or adaptive responses to exposures is unclear. Full article