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Long-term outcomes of venous graft preservation in a rat autologous transplant model
Abstract Venous grafts remain the most used conduits in coronary artery bypass grafting (CABG) but are highly susceptible to early failure due to ischemia–reperfusion injury, intimal hyperplasia, and accelerated atherosclerosis. Specialized preservation solutions such as DuraGraft and TiProtec aim to protect endothelial integrity during intraoperative storage; however, their long-term effects on venous graft adaptation remain unclear. In this study, saline, DuraGraft, and TiProtec were compared in a rat model of arterialized autologous jugular vein interposition grafting. Male Wistar rats were assigned to one of the three storage solutions or a Sham group with immediate implantation. Jugular veins were harvested, preserved for 2 h, and implanted into the infrarenal abdominal aorta using end-to-end microsurgical anastomoses. After 16 weeks, all grafts remained patent and exhibited pronounced arterial remodeling, including dilation, wall thickening, intimal hyperplasia, and loss of endothelium-dependent relaxation, while endothelium-independent relaxation was preserved. Although TiProtec-treated grafts showed slightly enhanced relaxation compared with saline-treated grafts, no preservation solution demonstrated a significant functional or structural advantage at 16 weeks. These findings suggest that long-term arterial loading is the dominant determinant of venous graft remodeling.
Numerical assessment of Lorentz-force-driven nanofluid cooling in trapezoidal ducts for improved solar panel performance
Analytical surface-impedance modeling of disordered dielectric metasurface monolayers
Expression of Concern: A study on the temperature profile of bifurcation tunnel fire under natural ventilation
SRP-Net: sensitive risk propagation network with asymmetric cross-attention for educational data
Abstract In the digital transformation of education, detecting sensitive information in structured educational data faces the challenge of semantic mismatch between titles and content, as well as isolated risk assessment that ignores field relevance. We propose the Sensitive Risk Propagation Network (SRP-Net), which is a sequential two-stage architecture that aligns within the field and then propagates across fields. The first stage adopts asymmetric cross attention, treating field names as queries to align with instance values and statistical fingerprints (key values). In the second stage, these aligned representations are input into a sensitivity aware graph neural network through batch dynamic subgraph extraction to avoid excessive smoothing. We have developed Edu KG BERT for domain adaptation through structured knowledge injection and developed the open-source Edu-Sens, which is the first benchmark dataset for education sensitive data synthesized using privacy preserving protocols. SRP-Net achieved an accuracy of 0.8779 Macro-F1 and 95.58% accuracy on Edu-Sens, which is 3.06% higher than the non graph baseline and significantly better than traditional machine learning and pure semantic baselines. The ablation study confirmed the synergistic necessity of explicit in field alignment and dynamic cross field propagation.
From expert opinion to data driven selection of sports equipment: Boot selection in alpine ski racers
To compete successfully in alpine ski racing, not only physical, mental, and skiing technique preparation are important, but also wisely chosen and properly tuned skiing equipment. While equipment related safety aspects are mostly ensured by official rules (e.g., competition rules provided by the International Skiing Federation), the performance optimization and customization of equipment is mostly reliant on coaches and experts in the skiing industry. Therefore, knowledge often is dependent on individual person’s experience and not publicly available. This aspect can also hinder companies or teams to spread knowledge within their own team. However, there is the necessity to select the optimal equipment for each athlete individually within a range of available equipment variations. To improve the process of ski boot selection for racers within a whole company, the presented research had the goal to provide a decision model by extracting and objectifying knowledge from few experts within the company. Based on a Delphi-type expert elicitation approach, together with the company’s boot experts a data collection sheet was designed, including the relevant parameter to decide which ski boot is appropriate for an individual athlete. Thereafter, data analysis of 198 datasets included classification methods based on random forest models to create boot choice recommendation models. Results revealed well predictable recommendation for boot size (accuracy 77%) and acceptable accuracy (57%) for prediction of boot model. With existing limitations of extracting subjective and individual expertise, this approach helps to objectify personalized expertise and distribute knowledge within relevant interest groups.
Gene-expression patterns can be used to estimate mortality risk and chronological age
Personal mastery and its predictors among pediatric nurses: a cross-sectional study
The role of premorbid cognitive performance in the neuropsychological assessment of people with HIV in South Africa
Background Cognitive assessment in people with HIV may be confounded by psychosocial factors, especially those linked to childhood circumstances, which are rarely measured in studies investigating HIV effects on the brain. These factors may affect premorbid (pre-HIV) cognitive performance. We investigated how psychosocial factors influence premorbid cognitive performance in people with and without HIV. Methods Participants were recruited into the CONNECT Study from a low-income area in Cape Town, South Africa. The Wechsler Adult Intelligence Scale (WAIS)-IV SA Information subtest served as an indicator of premorbid cognitive performance. We also measured global cognitive performance across seven cognitive domains (Global T-score), standard demographic variables (age, sex, education), and 12 psychosocial measures of childhood and adult circumstances, clustered using principal component analysis in prior analyses. Linear regression models examined associations between Global T-score and HIV status, adjusting sequentially for demographics and premorbid performance. Mediation analysis tested whether psychosocial effects on cognitive performance were mediated by premorbid performance. Results 177 people with HIV and 88 without HIV were assessed. People with HIV had lower premorbid cognitive performance than those without HIV (WAIS-IV SA Information: 3.89 vs. 5.24, p < .001). Premorbid performance was associated with 2/3 demographic, 5/7 childhood, and 2/5 adult psychosocial measures, as well as the Childhood Psychosocial Variables principal component (p s ≤ .002). Global T-scores were 3.95 points lower in people with HIV than those without (p < .001). Adjustment for demographics reduced this to 2.92 (p < .001), for premorbid performance to 2.70 (p < .001), and for both to 2.23 (p = .002). Mediation analysis indicated 39% partial mediation. Conclusions In this setting, cognitive differences between people with and without HIV partly reflect premorbid disparities linked to childhood psychosocial circumstances. Analyses that do not account for these risks may misattribute low cognitive performance to HIV-associated brain injury. Both premorbid cognition and psychosocial history should be considered when interpreting adult cognitive assessments.
Colchicine use after acute myocardial infarction is associated with reduced dialysis dependence in advanced chronic kidney disease
Abstract Evidence-based treatments to improve renal outcomes in patients with advanced chronic kidney disease (CKD) after acute myocardial infarction (AMI) are limited. We aimed to evaluate the clinical effects of colchicine therapy after AMI in these patients. This retrospective cohort study used data from the TriNetX US Collaborative Network and included adults with an estimated glomerular filtration rate ≤ 45 mL/min/1.73 m 2 who were newly diagnosed with AMI between January 1, 2012, and December 31, 2022. Patients were grouped by colchicine use within 1 month after AMI and matched 1:1 by propensity score (n = 1,200 per group). Cox proportional-hazards and Kaplan–Meier analyses assessed outcomes. The primary outcome was dialysis dependence; secondary outcomes included major adverse cardiac events (MACE) and mortality. A landmark analysis was conducted for different colchicine initiation times after AMI. Over a maximum follow-up period of 4 years, colchicine use within one month was associated with reduced risks of dialysis dependence (hazard ratio (HR), 0.65; 95% confidence interval (CI) 0.53–0.79) compared to non-use. However, no significant between-group difference was observed in the risk of MACE (HR 1.04; 95% CI 0.94–1.15) and all-cause mortality (HR 1.03; 95% CI 0.87–1.22). These results were consistent in the landmark analysis. Notably, initiation of colchicine within two weeks was associated with a lower risk of all-cause mortality (HR 0.85; 95% CI 0.73–0.99) in landmark analyses. In patients with advanced CKD experiencing AMI, early colchicine therapy may reduce the risks of dialysis dependence. Any potential survival benefit remains uncertain and should be confirmed in prospective studies.
Correction: The increase in varus tilt of the joint line convergence angle under weight-bearing is correlated with medial meniscus extrusion in patients with knee osteoarthrosis
Transfer learning based CEEMDAN-VMD secondary decomposition and multi-scale modeling for short-term electricity market price trend forecasting
Spatiotemporal weather forecasting via multi-scale graph neural networks and latent diffusion models
Accurate weather prediction is crucial in agriculture, disaster prevention, and public safety. Challenge: Traditional numerical models have high computational costs and struggle with atmospheric nonlinearity and chaos, while existing deep learning methods face limitations in handling spatial heterogeneity and non-Euclidean data. Solution: This paper introduces the STGLDWeather method. It combines multi-scale spatiotemporal graph neural networks (MS-ST-GNN) and latent diffusion models (LDM) to capture multi-scale spatiotemporal dependencies in weather data and model the temporal evolution of weather conditions in latent space. Conclusion: Experiments on real weather datasets show that STGLDWeather significantly outperforms existing state-of-the-art baselines in prediction accuracy and computational efficiency, particularly excelling in temperature, geopotential height, and wind speed forecasts.
Association of the HPV vaccination intention‒behavior gap with ehealth literacy and health beliefs among chinese female college students: cross-sectional study
Abstract With the strengthening of public health, Chinese female college students have shown higher levels of HPV vaccination intention, but the actual vaccination rate is very low. This significant intention–behavior gap has become a major challenge for the prevention and control of HPV among colleges and universities. This study aims to explore the intention–behavior gap for HPV vaccine uptake among Chinese female college students on the basis of eHealth literacy (eHL) and the health belief model (HBM). A cross-sectional survey was conducted from June 16 to July 16, 2024, to assess socioeconomic status, eHL and HBM among female college students at Guangdong Medical University. Descriptive statistics were calculated, and binary logistic regression analysis was performed using SPSS 29.0 to identify significant independent associations between female college students’ HPV vaccination intentions and behavior. Among the 2884 valid participants with an intention to receive an HPV vaccination, only 41.3% had converted from intention to uptake (≥ 1 dose).The key influencing factors included being from urban areas (adjusted OR: 1.24; 95% CI 1.04– 1.47; p = 0.018), monthly consumption (adjusted OR: 1.24; 95% CI 1.13–1.37; p < 0.001), household income (adjusted OR: 1.10; 95% CI 1.01 –1.21; p = 0.029), and parental education level (adjusted OR: 1.23; 95% CI 1.13–1.33; p < 0.001). Moreover, the participants’ eHL level positively influenced their HPV vaccination conversion rate (adjusted OR: 1.02; 95% CI 1.00–1.04; p = 0.036). For HBM, trust in formal information had a significant positive influence on HPV vaccination conversion rate (adjusted OR: 1.10; 95% CI 1.04–1.16; p = 0.002), whereas perceived behavioral barriers had a significant negative influence (adjusted OR: 0.72; 95% CI 0.66 – 0.79; p < 0.001). This study confirms a substantial HPV vaccination intention‒behavior gap among Chinese female college students, influenced by socioeconomic factors, eHL, and health beliefs—specifically trust in formal information and perceived barriers. Therefore, we suggest that targeted measures should be undertaken to reduce socioeconomic gaps, improve the eHL of those with pre-existing vaccination intention, enhance institutional trust in formal medical institutions and authoritative information channels, and reduce the psychological and practical obstacles to HPV vaccination to effectively bridge the intention–behavior gap and thereby improve vaccination coverage female college students in China.
Atomistic insight into Al-Mg friction stir welding process via molecular dynamics simulation
Friction stir welding (FSW) has recently intrigued academics’ interest due to advances in high strength, low heat generation, tiny grain size, no melting, and the ability to produce dissimilar welding. It created a weld joint by stirring and applying stress to the interface of two metallic plates with a high-hardness tool. The impact of tool pin geometries during the stirring process and the existence of the friction stir welding tool are typically disregarded, particularly in molecular dynamics (MD) simulations, despite a large number of earlier reports. Therefore, in this report, the dissimilar welding joint of Mg-Al by friction stir welding (FSW) is investigated via MD simulation. The effects of travel speed, rotation speed of the tool, and tool pin geometry on the formation of Mg-Al weld joints are examined. The results indicate that Al atoms mix more effectively in the Mg plate than Mg atoms do in the Al plate. Improving the travel speed from 500 to 2000 m/s leads to a more severe atomic strain distribution, leading to a high-temperature zone up to 1000 K and an amorphous fraction of 18.8%. Moreover, the plastic deformation and high-temperature zone tend to become greater when the rotation speed increases. The mechanical atomic mixing level fluctuates with rotation speed, reaching a maximum value at 12 rad/ps. Rotating at 12 rad/ps also leads to the highest levels of mechanical atomic mixing and amorphous atoms. Considering the tool pin geometry, the rectangular prism and cone geometries gain a higher level of heating. The triangular and tube geometries create a better stirring effect. The results enhance atomic-level understanding of the mechanics of the FSW process. The following studies should evaluate the influence of offset distance and tool angle on the material flow of base metals.
ZMW-RSVP: a time-frequency prior-guided normalization-free RSVP-BCI decoding model
Treatment terminations during radiation therapy: A retrospective descriptive single-center analysis
Background Radiotherapy (RT) is a cornerstone of cancer management, substantially improving local tumor control and overall survival. However, a subset of patients fail to complete the prescribed RT course. Identifying the factors associated with treatment termination is essential to enhancing cancer care delivery and patient outcomes. Methods This retrospective, single-center analysis included 10039 patients who underwent RT between January 2020 and December 2024. Patients who terminated treatment before completion were identified in institutional RT records. Demographic and clinical characteristics, treatment intent, and reasons for termination were primarily evaluated using descriptive statistical analyses, with exploratory comparative analyses performed between curative- and palliative-intent groups. Results Between 01/01/2020 and 12/31/2024, RT was terminated in 297/10039 patients (2.96%). The most leading causes of termination was deterioration in performance status (143 patients, 48.1%). Of these, 170 patients (57.2%) had been treated with palliative intent. Lung cancer (96 patients, 32.3%) was the most frequent primary diagnosis, while the brain (92 patients, 31%) was the most commonly irradiated site. The median number of prescribed fractions was 13 (range: 2–44), and patients completed a median of 51.6% (range: 5–93%) of these fractions before termination. The most common reason was deterioration in performance status (48.1%). Treatment termination rates were significantly higher in palliative cases compared with curative cases (6.13% [170/2,772] vs. 1.75% [127/7,267]; χ² = 134.4; p < 0.001). Relative risk analysis indicated that palliative-intent patients had a 3.50-fold higher risk of treatment termination. Performance deterioration was more frequent in the palliative group (72.4% vs. 27.3%; p < 0.001). Treatment-related toxicity (grade III-IV) occurred predominantly in curative-intent patients (88.9% vs. 11.1%; p < 0.001). Conclusion Most RT terminations occurred among patients with poor performance status and advanced disease. These findings suggest that multidisciplinary supportive care may be relevant and should be evaluated in future prospective studies.
The Internet of Vehicles (IoV) and privacy-preserving systems
Mechanistic origin of high-cycle fatigue enhancement by grain refinement in AZ81 magnesium alloy for sports equipment
Lightweight, high-strength alloys are increasingly demanded in sports equipment. Magnesium (Mg) alloys are attractive due to their low density and high specific strength. This study systematically investigates the grain size–dependent high-cycle fatigue (HCF) behavior of AZ81 Mg alloy with comparable basal textures. The fine-grained (FG, ~ 8 μm) sample exhibits significantly improved mechanical performance compared with the coarse-grained (CG, ~ 62 μm) counterpart. The yield strength increases from 134.2 MPa to 164.5 MPa (~22.6%), and the ultimate tensile strength rises from 231.7 MPa to 283.7 MPa (~22%), while maintaining comparable ductility. More importantly, the fatigue strength at 10⁶ cycles increases from 80 MPa to 110 MPa, representing a 37.5% enhancement. Microstructural analyses reveal that grain refinement suppresses extension twinning and persistent slip band formation, while promoting the activation of <c + a> and non-basal <a> dislocations. The FG microstructure also contains finer and more uniformly distributed Mg 17 Al 12 precipitates, facilitating Orowan strengthening. These combined effects reduce strain localization and delay fatigue crack initiation. The findings clarify the mechanistic origin of grain refinement–induced fatigue enhancement and provide guidance for the design of Mg alloys in weight-critical sports applications.