Search Results (2,805)

Background/Objectives: Endoscopic retrograde cholangiopancreatography (ERCP) with biliary stent placement is a mainstay of current management for biliary obstruction, with stent occlusion being the most common and severe complication. The mechanism of stent occlusion is well known; however, factors affecting individual stent patency are still controversial. The objective of this study was to determine the duration and factors affecting plastic biliary stent patency. Methods: We conducted a retrospective analysis of the consecutive procedures of endoscopic retrograde cholangiopancreatography (ERCP) and biliary stent placement in a single tertiary center during the period of 2010–2019. The primary outcome of the study was the time of stent patency. Secondary outcomes were the development of cholangitis upon re-stenting and whether subsequent re-stenting was emergent. Re-stenting was considered emergent if it happened before the planned elective re-stenting date, irrespective of indication (development of cholangitis, rising jaundice, suspected dislodgement, etc.). Results: Between 2010 and 2019, a total of 5462 ERCP procedures were performed, with 2659 resulting in plastic biliary stent placement. On average, the plastic biliary stent was patent for 63 (25, 96) days with significant differences between the indications for ERCP groups. The strongest risk factors for the development of cholangitis upon re-stenting was cholangitis during index ERCP (HR = 1.83; 95% CI: 1.48–2.27; p < 0.001), intrabiliary malignancy being the indication for stenting (HR = 1.34; 95% CI: 1.12–1.60; p < 0.001) and increasing number of stents being placed (HR = 1.73; 95% CI: 1.27–2.36; p < 0.001). Conclusions: Patients with an underlying malignancy, history of cholangitis, and multiple biliary stents are at an increased risk for stent occlusion and cholangitis, warranting a tailored stent exchange interval to prevent complications. Full article

Rapid urbanization and widening urban–rural disparities have contributed to decreasing youth engagement with rural development in China. As traditional outreach initiatives struggle to attract young people’s attention, immersive digital technologies have emerged as promising tools for strengthening connections to rural environments. This study explores how immersive virtual reality (VR) experiences shape university students’ behavioral intentions toward rural engagement. Using a cognitive–affective–behavioral (CAB) framework, an immersive VR experiment was conducted with 209 Chinese undergraduates using a panoramic rural video. Partial least squares structural equation modeling (PLS-SEM) validated a serial mediation model linking perceived sensory dimensions, restorative experiences (RE), and place identity (PI) to rural visit intention (RVI) and environmentally responsible behavioral intention (ERBI). The results show that VR significantly enhances RE and PI, with PI serving as the stronger mediator, particularly for students with limited rural exposure. Multigroup analysis further revealed demographic heterogeneity: women demonstrated stronger RE–PI pathways, while urban and short-term rural residents showed greater sensitivity to VR-induced presence. Overall, the findings indicate that immersive VR can reduce urban–rural psychological distance and strengthen youth engagement. The study demonstrates how digital immersive tools may support targeted education and policy interventions aimed at promoting sustainable rural development. Full article

Background: Energy poverty has emerged as a major societal challenge in Europe. Objectives: This study provides evidence on how different dimensions of energy poverty affect specific health outcomes, informing both theoretical understanding and intervention development to address this critical public health issue. Methods: We conducted a cross-sectional analysis using baseline data from the Valencia pilot of the WELLBASED project, examining associations between energy poverty dimensions and health outcomes among 322 vulnerable participants in Valencia, Spain (69.6% women, mean age 48.8 years). Data were collected through validated instruments, including EQ-5D-5L, DASS-21, and SF-12, alongside standardised energy poverty indicators developed by the Energy Poverty Advisory Hub (EPAH). Results: Energy poverty prevalence was notably high, with 69.9% of participants unable to maintain adequate warmth during winter and 72.4% experiencing cooling difficulties during summer. Statistical analyses revealed significant associations between energy poverty indicators and health outcomes. For example, mental health impacts were particularly pronounced, with thermal inadequacy associated with depression, anxiety, and stress (effect sizes eta2 = 0.042–0.126). Physical health showed condition-specific patterns: respiratory conditions linked to heating inadequacy, cardio-vascular conditions to cooling inadequacy, and musculoskeletal conditions to utility bill arrears. Participants with arrears on energy bills reported significantly higher chronic disease burden compared to those without arrears (3.08 vs. 2.40, p = 0.010). Conclusions: These findings suggest that addressing energy poverty is essential for health equity strategies. Urban contexts with Mediterranean climate patterns present unique challenges, re-quiring year-round interventions that address both winter heating and summer cooling, moving beyond the traditional cold-weather focus. Full article

Autophagy is an intracellular process that recycles and degrades cytoplasmic components, including organelles and macromolecules, to provide energy and basic components for cell survival, maintain cellular homeostasis, and avoid self-damage. It is currently not fully known if mouse sperm undergoes the autophagy process, nor is the subcellular distribution, protein levels of autophagy-related proteins, and the biological role of autophagy in epididymal mouse sperm physiology fully understood. We aimed to investigate key autophagy markers, including LC3 (microtubule-associated protein 1A/1B-light chain 3), p62/SQSTM1 (Sequestosome 1), and mTOR (mechanistic Target of Rapamycin), in epididymal mouse sperm under capacitation (Cap) or non-capacitation (NC) conditions. Furthermore, we evaluated the possible role of these autophagy-related proteins on sperm viability, motility, intracellular pH (pHi), intracellular calcium concentrations [Ca²⁺]i, mitochondrial membrane potential, and acrosome reaction (AR) induction in the presence or absence of chloroquine (CQ), K67, and rapamycin. Our results suggest a dynamic re-localization of the autophagy-related proteins LC3, p62/SQSTM1, and mTOR under capacitation conditions. Moreover, treatment with specific autophagy inhibitors, such as CQ and K67, resulted in decreased LC3-II and p62/SQSTM1 protein levels. Additionally, rapamycin did not increase mTOR levels. Interestingly, treatment with these inhibitors also resulted in decreased motility, reduced mitochondrial membrane potential and hindered AR induction without affecting sperm viability. Overall, the presence and dynamic re-localization of LC3, p62/SQSTM1, and mTOR suggest that mouse epididymal sperm could perform initial steps of autophagy under capacitation conditions, and results of the pharmacological treatment could be associated with an important role of these autophagy-related proteins in sperm motility and AR induction. Full article

Durum wheat (Triticum durum) is one of the main raw materials in the food industry, used primarily in the production of pasta. During milling, semolina and flour are obtained with different size distributions, and different compositional and functional characteristics, which influence processes such as gelatinization, retrogradation and the final texture of the products. Understanding these changes is essential for optimizing the technological quality and shelf life of processed foods. The aim was to evaluate how particle size, composition, temperature, and treatment time affect gelatinization, retrogradation, and gel texture. Samples included common wheat flour (control), durum wheat semolina, durum wheat flour, and re-milled semolina (<180 μm). Hydrothermal tests were conducted at 95 °C with varying holding times, and at 140 °C with extended cooling to observe retrogradation. Composition and particle size were found to determine rheological behavior. Semolina showed higher retrogradation and produced firmer gels, while durum wheat flour, with higher protein and ash content, showed atypical profiles and less consistent gels. Increased temperature and time enhanced breakdown and reduced final viscosity, indicating starch thermal degradation. A correlation was observed between final viscosity and gel hardness. This study provides information useful for optimizing the milling, cooking, and development of durum wheat-based products with improved texture and shelf life. Full article

Background: Developmental dysplasia of the hip (DDH) encompasses a spectrum of neonatal hip abnormalities that, if not detected and treated early, may lead to long-term orthopedic sequelae. Universal ultrasound screening using Graf’s method has been proposed to improve early diagnosis, though its implementation remains heterogeneous in Italy. Objectives: This study aimed to describe the outcomes of a universal ultrasound screening program for DDH conducted in a first-level birth center in northern Italy, evaluating DDH incidence, risk factors, management outcomes, and program feasibility. Methods: A prospective observational study was conducted from February 2024 to October 2025 at the Ivrea birth center (Piedmont region, Italy). All consecutive live-born infants (n = 904) underwent hip ultrasound according to Graf’s method, between 0 and 11 weeks of age. Hips were classified as type I (normal), type IIa (physiologically immature), or type IIb–IV (pathological). Infants with type IIa hips were re-evaluated after 2–4 weeks; those with type IIb or worse were referred to pediatric orthopedics. Results: Of 1808 hips examined, 92% were Graf type I and 8% type IIa. After follow-up, 93% of type IIa hips matured spontaneously. Pathological DDH (Graf IIb or worse) was diagnosed in 8 infants (0.88%), of whom 75% were female; 50% had no identifiable risk factors. All affected infants were treated with harness before 12 weeks of age, with complete recovery and no late diagnoses. No infant required surgical treatment. Conclusions: Universal ultrasound screening for DDH was feasible and effective in a first-level birth center, ensuring early diagnosis and absence of late-presenting cases. These findings support universal screening as a safe and equitable approach to reduce DDH-related morbidity and align with national recommendations for standardized early detection programs. Full article

Background and objectives: This study examines how sociodemographic, clinical, and psychological factors within the patient–caregiver dyad affect caregiver burden and health-related quality of life (HRQoL) in cognitive impairment. By comparing baseline data with a 1-year follow-up, the research aims to identify key predictors of caregiver burden and well-being. Methods: A longitudinal observational study was conducted in an Italian rehabilitation hospital, recruiting 132 outpatients and their caregivers at baseline, categorized as (a) Mild Cognitive Impairment (MCI, n = 33); (b) dementia (DEM, n = 58); (c) healthy subjects (No-CI, n = 41). One year after baseline assessment (T0), patients were contacted and invited for an in-person follow-up re-evaluation (T1). Most attrition was related to the COVID-19 pandemic. Statistical analyses included non-parametric tests for group comparisons and stepwise multiple linear regression to identify predictors of burden, adjusting for confounders (e.g., age, gender, education, employment, co-residence). Results: A total of 51 subjects (age: 80.0 ± 6.1) and 34 caregivers (age: 58.8 ± 15.9) were evaluated. Patients were balanced by gender (53% males); most were retired (96%), married (62.7%), and cared for by sons (47%) or wife–husband (47%). Caregivers (females: 85%) were married (68.3%) and active workers (46.4%). Over one year, 17 No-CI subjects developed MCI or DEM; 15 MCI patients progressed to DEM. Caregiver HRQoL negatively correlated with distress and burden in MCI and DEM groups. Patient cognitive status, functional abilities, neuropsychiatric symptoms, and gender predicted caregiver burden, emphasizing the interplay between clinical and demographic factors. Conclusions: It is essential to monitor psychosocial factors in both the patient and the caregiver to develop effective prevention and support strategies. Full article

Bulk nanobubbles (NBs) are remarkably long-lived in liquids, yet the molecular mechanisms underpinning their stability remain unresolved. In this work, 50 ns all-atom molecular dynamics simulations were performed to investigate how gas identity (O₂, N₂, and air with N₂:O₂ = 4:1), initial gas loading, alkalinity (pH 7 and 13), and organic additives (acetic acid/acetate, ethanol/ethoxide, and hexane) influence the stability of 5 nm NBs in water. Stability was evaluated by the percentage of gas atoms retained in the bubble, density profiles, hydrogen-bond statistics, and radial distribution functions. Higher initial gas density markedly enhanced stability, and N₂-NBs consistently outperformed O₂-NBs, consistent with the lower solubility of N₂. Alkaline conditions exerted only a minor stabilizing effect, most pronounced for air-NBs. Organic additives affected stability according to their hydrophobicity: hydrophobic hexane substantially increased gas retention, especially at low gas loading, by promoting gas clustering and re-adsorption at the NB interface, whereas hydrophilic solutes had negligible influence. RDF analyses revealed that this stabilization correlates with weakened gas–water hydrogen bonding and enhanced gas–gas and gas–hexane interactions. These results elucidate the molecular determinants of NB persistence and offer design guidelines for tuning bubble longevity in environmental and industrial systems. Full article

Background/Objectives: Keratoconus (KC) is the most common corneal ectasia. This condition affects quality of vision, especially when it is progressive, and a timely and stage-related treatment is mandatory. Therefore, early diagnosis is crucial to preserve visual acuity. Medical data may be used either in their raw state or in a preprocessed form. Software modifications introduced through updates may potentially affect outcomes. Unlike preprocessed data, raw data preserve their original format across software versions and provide a more consistent basis for clinical analysis. The objective of this study was to distinguish between healthy and KC corneas from raw optical coherence tomography data by using a convolutional neural network. Methods: In total, 2737 eye examinations acquired with the Casia2 anterior-segment optical coherence tomography (Tomey, Nagoya, Japan) were decided by three experienced ophthalmologists to belong to one of three classes: ‘normal’, ‘ectasia’, or ‘other disease’. Each eye examination consisted of sixteen meridional slice images. The dataset included 744 examinations. DenseNet121, EfficientNet-B0, MobileNetV3-Large and ResNet18 were modified for use as convolutional neural networks for prediction. All reported metric values were rounded to four decimal places. Results: The overall accuracy for the modified DenseNet121, modified EfficientNet-B0, modified MobileNetV3-Large and modified ResNet18 is 91.27%, 91.27%, 92.86% and 89.68%, respectively. The macro-averaged sensitivity, macro-averaged specificity, macro-averaged Positive Predictive Value and macro-averaged F1 score for the modified DenseNet121, modified EfficientNet-B0, modified MobileNetV3-Large and modified ResNet18 are reported as 91.27%, 91.27%, 92.86% and 89.68%; 95.63%, 95.63%, 96.43% and 94.84%; 91.58% 91.65%, 92.91% and 90.24%; and 91.35%, 91.29%, 92.85% and 89.81%, respectively. Conclusions: The successful use of a convolutional neural network with raw optical coherence tomography data demonstrates the potential of raw data to be used instead of preprocessed data for diagnosing KC in ophthalmology. Full article

Modern target tracking systems rely on radar as a sensor to detect targets and generate raw track points. These raw track points are affected by the radar’s own noise and the asymmetric non-Gaussian noise resulting from the nonlinear transformation from polar coordinates to Cartesian coordinates. Without effective processing, such data cannot directly support highly reliable situational awareness, early warning decisions, or weapon guidance. Track filtering, as a core component of target tracking, plays an irreplaceable foundational role in achieving real-time, accurate, and stable estimation of moving target states. Traditional deep learning filtering algorithms struggle with capturing long-term dependencies in high-dimensional spaces, often exhibiting high computational complexity, slow response to transient signals, and compromised noise suppression due to their inherent architectural asymmetries. In order to address these issues and balance the model’s high accuracy, strong real-time performance, and robustness, a new trajectory filtering algorithm based on a temporal convolutional network (TCN), Residual Gated Recurrent Unit (ResGRU), and multi-head attention (MHA) is proposed. The TCN-ResGRU-MHA hybrid structure we propose combines the parallel processing advantages and detail-capturing ability of a TCN with the residual learning capability of a ResGRU, and introduces the MHA mechanism to achieve adaptive weighting of high-dimensional features. Using the root mean square error (RMSE) and Euclidean distance to evaluate the model effect, the experimental results show that the RMSE of TCN-ResGRU-MHA is 27.4621 (m) lower than CNN-GRU, which is an improvement of 15.99% in the complex scene of high latitude, and the distance is 37.906 (m) lower than CNN-GRU, which is an improvement of 18.65%. These results demonstrate its effectiveness in filtering and tracking tasks in high-latitude complex scenarios. Full article

As a fundamental and indispensable component of modern electronic devices, the printed circuit board (PCB) has a complex structure and highly integrated functions, with its manufacturing quality directly affecting the stability and reliability of electronic products. However, during large-scale automated PCB production, its surfaces are prone to various defects and imperfections due to uncontrollable factors, such as diverse manufacturing processes, stringent machining precision requirements, and complex production environments, which not only compromise product functionality but also pose potential safety hazards. At present, PCB defect detection in industry still predominantly relies on manual visual inspection, the efficiency and accuracy of which fall short of the automation and intelligence demands in modern electronics manufacturing. To address this issue, in this paper, we have made improvements based on the classical Faster-RCNN object detection framework. Firstly, ResNet-101 is employed to replace the conventional VGG-16 backbone, thereby enhancing the ability to perceive small objects and complex texture features. Then, we extract features from images by using deformable convolution in the backbone network to improve the model’s adaptive modeling capability for deformed objects and irregular defect regions. Finally, the Convolutional Block Attention Module is incorporated into the backbone, leveraging joint spatial and channel attention mechanisms to improve the effectiveness and discriminative power of feature representations. The experimental results demonstrate that the improved model achieves a 4.5% increase in mean average precision compared with the original Faster-RCNN. Moreover, the proposed method exhibits superior detection accuracy, robustness, and adaptability compared with mainstream object detection models, indicating strong potential for engineering applications and industrial deployment. Full article

Violence is a major public health concern, but long-term hospital-based analyses in Latin America remain scarce. This study examined trends, structural breaks, and seasonality of violence-related emergency visits at the José Casimiro Ulloa Emergency Hospital in Lima, Peru, between 2015 and 2024. A retrospective analysis of 14,570 visits was performed, classifying cases according to the World Health Organization typology into self-inflicted, interpersonal community, and interpersonal family violence. Descriptive statistics were stratified by sex, life stage, migratory status, and pandemic period: pre-pandemic (2015–2019), pandemic (2020–2021), and post-pandemic (2022–2024). Time-series analyses included segmented regression and seasonal-trend decomposition. Males (78.3%), youth, and adults were the most affected groups. Interpersonal community violence accounted for 94.2% of cases and closely mirrored the overall series, peaking at 327 visits in July 2019 and falling to 28 in April 2020. Segmented regression showed significant immediate decreases at the onset of the pandemic (−71.6 visits, p < 0.001) and partial rebounds after 2022. Family violence remained consistently low and stable, while self-inflicted violence displayed a pre-pandemic upward trend, a sharp decline in 2020, and higher post-pandemic levels. Seasonality was evident before 2020, disappeared during the pandemic, and re-emerged with reduced amplitude thereafter. The COVID-19 pandemic caused abrupt but heterogeneous disruptions in violence-related emergency visits in Lima. Full article

This study presents an optimized Real-Time Detection Transformer (RT-DETRv2) deep learning model for the automated assessment of Tartary buckwheat germination and evaluates the influence of soaking and ultrasonic pretreatments on the germination ratio. Model optimization revealed that image chip size critically affected performance. The 512 × 512-pixel chip size was optimal, providing sufficient image context for detection and achieving a robust F1-score (0.9754 at 24 h, tested with a ResNet-101 backbone). In contrast, smaller chips (e.g., 128 × 128 pixels) caused severe performance degradation (24 h F1 = 0.3626 and 48 h F1 = 0.1211), which occurred because the 128 × 128 chip was too small to capture the entire object, particularly as the elongated and highly variable 48 h sprouts exceeded the chip dimensions. The optimized model, incorporating a ResNet-34 backbone, achieved a peak F1-score of 0.9958 for 24 h germination detection, demonstrating its robustness. The model was applied to assess germination dynamics, indicating that 24 h of treatment with 0.1% CaCl₂ and ultrasound enhanced total polyphenol accumulation (6.42 mg GAE/g). These results demonstrate that RT-DETRv2 enables accurate and efficient automated germination monitoring, providing a promising AI-assisted tool for seed quality evaluation and the optimization of agricultural pretreatments. Full article

Background: Antimicrobial resistance (AMR) is a global threat that extends beyond clinical settings, impacting animals, food, and the environment. To the best of our knowledge, this review presents the first systematic evaluation of AMR and antimicrobial resistance genes (ARGs) in non-human sources in Qatar, using a One Health framework. Methods: Following PRISMA 2020 guidelines, we searched five major databases: PubMed, Scopus, Web of Science, Embase, Google Scholar (only 3 pages) and QRDI, without date restrictions for studies on AMR and ARGs in animals, food, and environmental sources in Qatar. Only primary studies from Qatar reporting phenotypic or genotypic AMR/ARG data in animals, food, or the environment were included; all human-focused, non-Qatar, or non-primary research were excluded. Eligible studies were screened and analyzed using GraphPad Prism 10.4 and StatsDirect, applying random- or fixed-effects models based on heterogeneity and assessed for quality using the JBI checklist for prevalence. Results: Fifteen eligible studies published up to 2025 were included. Escherichia coli was the most frequently reported organism. High resistance rates were observed in the Access group antibiotics, such as ampicillin (0.50; 95% CI: 0.47–0.53) and tetracycline (0.50; 95% CI: 0.45–0.55), as well as in the Watch group antibiotics, including ciprofloxacin (0.40; 95% CI: 0.36–0.44) and fosfomycin (0.26; 95% CI: 0.20–0.32). Resistance to Reserve group antibiotics was comparatively lower, with pooled estimates of 0.14 (95% CI: 0.08–0.20) for colistin and 0.11 (95% CI: 0.05–0.25) for carbapenems, though lower, remains concerning. The overall pooled estimate for multidrug resistance (MDR) was 0.56 (95% CI: 0.36–0.72), and poultry was identified as the main reservoir, particularly to Critically Important Antimicrobials (CIAs). ARGs, including bla_CTX-M, bla_TEM, mcr-1, and qnr, were detected across all sectors, with wastewater showing a notable ARG burden. Data on other livestock species remain limited. Limitations include a few studies, variable quality, and inconsistent methods affecting comparability and precision. Conclusions: This review highlights significant AMR and ARG prevalence in non-human sources in Qatar and underscores the urgent need for a national One Health surveillance strategy incorporating WHO AWaRe and CIA frameworks to address this escalating public health threat. Full article

This article contends that Sofia Coppola’s Priscilla (2023) uses digital filmmaking to re-animate the commodified image of Priscilla Presley, privileging surface and affect over historical realism. Though Coppola predominantly shoots on film, her decision to film Priscilla digitally—an adaptation of Presley’s memoir—marks a formal shift in her filmography aligned with her ongoing exploration of feminine interiority and aesthetic control. The film traces Priscilla’s life from her first encounter with Elvis Presley to their separation, presenting a visually stylized narrative that immerses viewers in what Walter Benjamin terms a phantasmagoria: a spectacle of commodification divorced from historical consciousness (The Arcades Project). Rather than striving for veracity, Coppola evokes a nostalgic atmosphere that re-members Priscilla through pre-circulated cultural images. This article examines Coppola’s often-criticized “flat” visual style in relation to the Freudian uncanny, i.e., the estrangement of the familiar through temporal and affective distortion. Coppola manipulates digital temporality—looping and flattening time—to produce an oneiric repetition that heightens the artifice of Presley’s image while emotionally distancing viewers. These formal strategies dissipate emotional depth but intensify aesthetic control. Finally, this article considers the political valences of Coppola’s digital aesthetics in a media landscape that both enables visibility and enacts erasure. Full article