Browse Articles

Rural wealth is associated with the consumption of nutritious and healthy foods in Zambia

From training to practice: A multi-group analysis of factors influencing K-12 teachers’integration of Digital Educational Resources (DERs)

Ensuring teachers effectively integrate digital technologies is crucial for modernizing education, yet the success of large-scale training initiatives often varies. This study investigates the factors shaping technology adoption among 2,821 K–12 teachers following a national digital literacy program. Using a Structural Equation Model (SEM) based on the UTAUT framework, this research employs a multi-group analysis to examine how adoption drivers differ across key demographic segments. Results show that social influence and performance expectancy are the primary drivers of teachers’ intention to use digital resources, which in turn strongly predicts actual use. Notably, the influence of these factors varies significantly depending on teachers’ regional context, educational stage, and prior digital experience, highlighting the limitations of a uniform approach to professional development. The findings provide a nuanced evidence base for designing more targeted and effective teacher support strategies.

Arrhythmic risk in mitral valve prolapse with mitral annular disjunction: meta-analysis of longitudinal studies

Association between the LDL/HDL ratio and sarcopenia in Chinese community-dwelling older adults

Objectives The link between lipid disorders and diverse diseases is amply documented. Yet, research probing how serum lipid levels tie in with sarcopenia remains scarce. This study delves into the connection between the LDL/HDL ratio and sarcopenia among elderly Chinese people. Methods A total of 3,968 senior participants from Chinese communities were included in this cross-sectional study. To explore the relationship between the LDL/HDL ratio and sarcopenia, both a multivariate logistic regression model and a restricted cubic spline model were used. ROC curve analysis was employed to gauge how well the LDL/HDL ratio can detect sarcopenia. Results Among the participants, 780 were diagnosed with sarcopenia. Multivariable logistic regression unveiled a significant positive correlation between the LDL/HDL ratio and sarcopenia. After adjusting for potential confounders, each unit increase in the LDL/HDL ratio corresponded to an approximately 3-fold higher odds of sarcopenia (OR = 3.01, 95% CI: 2.66–3.41, P  < 0.001). A non – linear relationship between the LDL/HDL ratio and sarcopenia was confirmed by RSC analysis ( P  < 0.001). ROC curve analysis showed that the LDL/HDL ratio outperformed its individual components in predictive ability for sarcopenia. Conclusions This study indicates that the LDL/HDL ratio may serve as an independent risk factor for sarcopenia.

Deep learning based real-time prediction of depth of penetration during activated tungsten inert gas welding of 10 mm thick 316LN stainless steel

Genetic etiology and pregnancy outcomes of abnormal fluid accumulation in fetus: A retrospective cohort study

Background This study investigated the genetic etiology of abnormal fetal fluid accumulation, aiming to quantify pathogenic variants and correlate them with clinical outcomes to improve genetic counseling. Methods A cohort of 305 fetuses underwent single-nucleotide polymorphism array (SNP-array) and whole-exome sequencing (WES) of amniotic fluid or cord blood. Results Pathogenic copy number variations (CNVs) were detected in 49 cases, including aneuploidies (e.g., trisomy 21, Turner syndrome) and microdeletions/duplications. Two single-gene mutations (SNAP25, PLD1) were identified in CNV-negative cases. Non-immune hydrops (NIHF) exhibited the highest pathogenic rate (42.7%, 32/75), with non-isolated NIHF (50.0%) showing significantly higher detection than isolated NIHF (17.6%). NIHF also had the highest termination rate and postnatal abnormality rate (11%). Pleural and pericardial effusions followed in severity. Interpretation The findings demonstrate that SNP-array and WES effectively diagnose genetic causes of fluid accumulation. While some NIHF cases may have favorable outcomes, the high termination and abnormality rates underscore its generally poor prognosis. These results emphasize the importance of comprehensive prenatal genetic testing and individualized counseling for families facing such diagnoses.

Correction: Continuous glucose monitoring reveals periodontitis-induced glucose variability, insulin resistance, and gut microbiota dysbiosis in mice

The impact of agricultural support and protection subsidy policy on grain production efficiency: A case study of China

Based on panel data from 31 Chinese provinces from 2012 to 2022, this study employs a difference-in-difference method to assess the impact of the agricultural support and protection subsidy (ASPS) policy on grain production efficiency. The results indicate that the ASPS policy has a significant positive impact on grain production efficiency, and the results remain robust through multiple robustness tests. Furthermore, heterogeneity analysis reveals that the policy’s impact varies substantially across different regions and types of grain crops. Mechanism analysis further demonstrates that the ASPS policy enhance grain production efficiency by improving the grain cultivation areas and productive inputs. Consequently, we propose targeted policy recommendations, including enhancing the intensity and precision of subsidies, implementing differentiated subsidy approaches, and utilizing subsidies to stimulate dual efficiencies in both scale and investment.

Blockchain-based secure MEC model for VANETs using hybrid networks

Abstract Vehicular Ad-hoc Networks (VANETs) are a type of mobile ad-hoc network that enables vehicles to interact with one another and roadside infrastructure. Multi-Access Edge Computing (MEC) provides a promising solution by positioning storage and computation resources closer to the network edge. This helps to reduce the latency and improve performance. The combination of MEC and blockchain enhances data processing and security. This integration improves privacy safeguards, prevents fraud, and supports trusted communication within VANETs. Consequently, this proposed model aims to develop an innovative approach that leverages these technologies. The main objective of the implemented technique is to create a blockchain architecture powered by deep learning, which ensures the safety of VANETs. The network architecture consists of three layers: perception, edge computing, and services. The main goal of the initial layer is to protect the privacy of VANET data through blockchain activities. The perception layer processes data using edge computing and cloud services. The service layer ensures data protection by through the blockchain technology and storing information in a public cloud. The last layer focuses on addressing user demands for throughput and Quality of Service (QoS). The proposed framework is good for assessing the dependability of vehicle nodes stored on the blockchain. To accomplish node authentication, an Adaptive and Dilated Hybrid Network (ADHyNet) is used. In this approach, the Residual Long Short-Term Memory (Res-LSTM) with Gated Recurrent Unit (GRU) forms the ADHyNet, where the Random Number Updated Skill Optimization Algorithm (RNU-SOA) is used to optimize the hyperparameters. Finally, the encryption process is carried out using Homomorphic Encryption combined with Elliptic Curve Cryptography (HECC) to secure data. This process ensures that confidential user information is protected against unauthorized access. The functionality of the system is thoroughly assessed and simulated. The suggested technique outperforms well than other approaches in terms of data security in VANET.

Correction: Experiences, views and perceptions of recovery following musculoskeletal trauma of patients and physiotherapists: A qualitative study

Ketamine and metabolites in snake venom: effects of venom extraction and potential impact on animal models

Abstract In zootoxinology, drugs such as anesthetics and secretion enhancers are used to increase venom yields, but it is unclear whether this affects the venom composition. After injection of ketamine and pilocarpine into two non-front-fanged snakes, mass spectrometry confirmed the presence of both drugs and their metabolites in the venoms. The quantified high concentrations raise concerns about potential interference in bioassays and pharmacological studies, highlighting the need to consider extraction additives in venom research to ensure unbiased results.

Correction: Bone mineral density among children living with HIV failing first-line anti-retroviral therapy in Uganda: A sub-study of the CHAPAS-4 trial

Multi-objective optimization of covering parameters for cotton/spandex core-spun yarn using grey relational analysis in conjunction with the Taguchi technique

Abstract The growing need for high-performance stretchable fabrics led scientists to innovate a new spinning technique, especially for manufacturing cotton/spandex core-spun yarns. This type of yarn is spun by using spandex monofilament or multifilament as a core, which is surrounded by a sheath of staple cotton fibers. The key covering process parameters include spindle speed, delivery roller speed, spandex drafting ratio, spandex linear density, and tension level, which simultaneously influence the core-spun yarn characteristics such as tensile properties, hairiness index, imperfection index, and fabric aesthetic and performance properties. Fine-tuning these multiple covering parameters achieves optimal performance of these types of yarns. This paper aimed at employing multi-objective optimization for the covering parameters of cotton/spandex composite yarn to maximize the yarn tensile properties and minimize both hairiness and imperfection indices using the robust Taguchi technique in conjunction with the grey relational analysis. A full factorial design composed of three factors, namely spandex monofilament drafting ratio, linear density, and core-spun yarn twist multiplier, with five, four, and two levels, was conducted. Average values of the grey relational grades of all combinations were estimated, and its highest value refers to the optimal combinations of the controllable factors, which yield the best performance of cotton/spandex core-spun yarn. This study revealed that core-spun yarn with a 4.2 twist multiplier, a 44 dtex linear density of spandex monofilament, and a 4.4 drafting ratio of spandex yielded the optimal yarn performance characteristics. This study provides a methodological breakthrough with beneficial ramifications for the textile industry seeking a multi-objective optimization of core-spun yarn manufacturing parameters.

OphthoEvidence report: Baseline structural optical coherence tomography biomarkers predictive of visual acuity following epiretinal membrane surgery–A systematic review and meta-analysis protocol

Background Epiretinal membrane is a common retinal condition, particularly in the elderly, than can lead to reduced visual acuity and visual distortion. Structural optical coherence tomography biomarkers have shown potential for predicting visual outcomes following surgery. Objective To evaluate the prognostic value of baseline structural optical coherence tomography biomarkers for visual outcomes following epiretinal membrane surgery. We will assess associations between individual biomarkers and postoperative visual acuity or changes in visual acuity at 6, 12, and 24 months after surgery. Methods We will systematically search MEDLINE, EMBASE, CENTRAL and Web of Science from inception. Eligible studies will include randomized trials and observational studies reporting the association between any baseline optical coherence tomography biomarkers and postoperative visual acuity in patients undergoing epiretinal membrane surgery. Two reviewers will independently and in duplicate perform screening, data extraction, and risk of bias assessment. Meta-analyses using the restricted maximum likelihood random-effects model will be conducted whenever possible. The certainty of evidence for each estimate will be assessed using the GRADE approach. Expected outcomes This review will analyze time-specific association between baseline structural optical coherence tomography biomarkers and postoperative visual acuity and change in visual acuity from baseline at 6, 12, and 24 months after surgery, quality of life measured using any validated scale, and adverse events.

Investigation of licorice extract as a green additive on microstructure, hardness, and wear behavior of electrodeposited nickel coatings

Classification of current density vector map using transformer hybrid residual network

The classification of the current density vector map (CDVM) reconstructed from magnetocardiogram (MCG) is an important indicator for assessing cardiac function and state in clinical diagnosis. Given the limited widespread application of MCG, research on CDVM often encounters challenges such as scarcity of data and difficulties in judgment. There is growing interest in computer-aided methods to assist physicians in analyzing cardiac cases using CDVM. This paper proposes a deep learning-based approachto classify the CDVM. To address the issue of insufficient processed MCG data, data augmentation is carried out by adding noise, making predictions based on auto regressive integrated moving average (ARIMA) model, and utilizing interpolation methods. A transformer hybrid residual network is then employed to classify the CDVM across categories 0 to 4, with transfer learning incorporated into the network structure to initialize model parameters, and the self-attention mechanism of the Transformer enhancing the feature extraction capability. This method achieved a classification accuracy of 97.52%, outperforming previous deep learning approaches, exhibiting both high precision and efficiency. Furthermore, its high scalability ensures that it will continue to meet the evolving needs of physicians as CDVM datasets undergo continuous expansion.

Enhanced YOLOv8 for accurate and efficient floating object detection on water surfaces

Comprehensive analysis of genes associated with necroptosis and pyroptosis in intestinal ischemia-reperfusion injury

Background Intestinal ischemia–reperfusion (II/R) injury is a severe clinical condition in which regulated cell death programs—including pyroptosis and necroptosis—have emerged as key drivers of tissue damage and inflammation. We sought to delineate cell-death–related molecular signatures and candidate therapeutic targets in II/R injury. Methods We obtained transcriptome datasets from Gene Expression Omnibus (GEO) databases for mice (GSE96733, GSE232246) and humans (GSE37013). We cross-referenced genes associated with necroptosis and pyroptosis with differentially expressed genes to identify death-related features. Hub genes were identified through the topological structure of protein interaction networks and validated using an internal validation set, an independent validation set, WGCNA, and qRT-PCR. These genes were also associated with immune cell infiltration. Drug–gene interactions were predicted using DGIdb and verified through molecular docking. Results We identified 1,027 differentially expressed genes (DEGs) in the training set and derived 7 cell death-related differentially expressed genes (DCDEGs) by intersecting gene sets associated with necroptosis and pyroptosis. PPI-based prioritization identified four hub genes— Il1 β, Ripk3, Sting1 (Tmem173), and Tnfaip3 —suggesting cross-regulatory interactions between inflammation and cell death in ischemia-reperfusion pathology. These hub genes were validated using WGCNA analysis and an internal validation set. Immune infiltration analysis indicated significant correlations between hub genes and multiple immune compartments. A predictive model showed good discrimination in the discovery data, and 54 candidate drugs targeting the hub genes were retrieved. qRT-PCR confirmed dysregulation of three hub genes. Conclusion Il1 β, Ripk3, Sting1 , and Tnaip3 were identified as hub genes associated with necroptosis and pyroptosis in intestinal ischemia-reperfusion (II/R) injury. This study provides a reproducible framework and identifies testable targets for translational exploration.

A hybrid machine vision and handcrafted features fusion based approach for fine-grained millet classification

Patient safety risk associated with synchronous telehealth: A scoping review

Objective We aimed to analyze the risks associated with patient safety in synchronous telehealth. Methods Scoping review with search in 3 databases, Medical Literature Analysis and Retrieval System Online (Medline), via PubMed®, Embase® via Elsevier®, and the Cochrane Database of Systematic Reviews, recovering evidence from inception until September 4 th , 2024. Eligible reviews investigated patient safety concerns arising from real-time interactions between healthcare professionals and patients through information and communication technologies (ICT), including telephones and videoconferencing tools. We included systematic reviews examining real-time telehealth interactions between healthcare professionals and patients, addressing safety concerns. We followed standard Joanna Briggs Institute methods for conducting the scoping review. Results A total of 3,641 titles and abstracts were retrieved, and after screening, 15 systematic reviews were included, encompassing 315 studies. These reviews addressed various patient populations, healthcare settings, and telehealth interventions, including virtual consultations, telepharmacy, and telerehabilitation. All 15 reviews reported patient safety risks associated with telehealth, the most frequently reported concern was the patient’s experience, highlighted in 53.3% (n = 8) of the included studies. Additional concerns involved user knowledge gaps and the lack of safety criteria in evaluation protocols. These risks were categorized into five domains: patient experience, safety in prescribing medication, effective communication, training and education, and patient identification. Conclusion This scoping review provides evidence that, although telehealth offers valuable alternatives for healthcare delivery, all evidence highlights specific patient safety risks that require attention. Further research is essential to better understand and mitigate these risks. Strategic investments in education, training, and structured implementation are critical to minimizing adverse events and enhancing patient safety in synchronous telehealth.