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Identification of Rana dybowskii Ferritin-Heavy chain gene and analysis of its role during bacterial infection
Ferritin is widely present in organisms, which can maintain iron relatively stable and participate in the immune response. In this study, the full-length coding sequence (CDS) of the Rana dybowskii ( R. dybowskii ) Ferritin-Heavy Chain ( Fer-H ) gene was cloned by the polymerase chain reaction (PCR) method and characterized by bioinformatics analysis. In order to further explore its role, the inflammation model was established by using Aeromonas hydrophila ( Ah ). The activity of antioxidant enzymes in some tissues was detected, and the expression level of the R. dybowskii Fer-H ( RdFer-H ) gene was detected by quantitative real-time PCR and Western blot analysis. Bioinformatics analysis revealed that the Fer-H gene was 534 bp long, encoding 177 amino acids, and there was a Pfam Ferritin domain. When compared to other species with the same nucleotide sequence, Rana temporaria has the highest homology (94%) with the Fer-H gene. The activities of antioxidant enzymes indicated that the activities of SOD and CAT increased significantly, while the activity of GSH-Px decreased distinctly. This meant that the bacterial infection had caused serious oxidative damage to R. dybowskii . The qRT-PCR results confirmed the broad expression of the Fer-H gene in all R. dybowskii tissues. Furthermore, the transcription level was significantly up-regulated after bacterial infection, and the protein accumulations were consistent with the transcript levels in liver and muscle tissue according to Western blot after Ah infection. This study hypothesizes that the Fer-H gene contributes to R. dybowskii ’s immune response during bacterial infection. It also broadens the research idea for exploring the anti-infection immune response mechanism of amphibians.
RAUM-GANs: a multi-layer GAN-enhanced framework for accurate multiple sclerosis lesion segmentation in MRI
The dilemma of sweet temptation: How sugar perception confusion in sweetened beverages shapes consumer avoidance behavior
Despite widespread consumption of sugar-sweetened beverages, consumers face contradictory information from health authorities, marketing, and social media, yet limited research examines how this information conflict affects purchasing decisions. This study investigates how sugar perception confusion influences purchasing avoidance through ambivalent attitudes. Based on cognitive dissonance and information processing theories, we developed a cognitive-affective-behavioral model examining relationships among sugar perception confusion, ambivalent attitudes, and purchasing avoidance behaviors. Using PLS-SEM analysis of 531 Chinese consumers, results show sugar perception confusion significantly affects ambivalent attitudes (β = 0.576, p < 0.001), which strongly predict purchasing avoidance (β = 0.593, p < 0.001). Sugar perception confusion also directly influences purchasing avoidance (β = 0.155, p < 0.001), with ambivalent attitudes serving as a significant mediator (indirect effect β = 0.342, p < 0.001). These findings advance consumer information processing theory and provide evidence-based insights for optimizing information environments to support informed decision-making.
Strengthening mechanisms of indigenous bacteria in granite residual soil improvement via microbial induced calcite precipitation
The role of demographic characteristics in US medical students’ professional well-being and medical school experiences: An intersectional approach
Introduction Previous findings have been mixed about the role of demographic characteristics in medical students’ well-being and school experiences when those characteristics were examined in isolation. The aim of this study was to investigate the roles of gender, race and ethnicity, and sexual orientation in medical students’ professional well-being and medical school experiences using an intersectional approach. Method We analyzed data from the 2019–2022 Association of American Medical Colleges Graduation Questionnaire ( N = 66,795). The independent variable was intersectional groups, composed of 16 intersectional groups that combined various genders, races and ethnicities, and sexual orientations. The outcome variables were professional well-being (i.e., burnout, career regret) and medical school experiences (i.e., general mistreatment, discrimination, emotional climate, faculty-student interaction, faculty professionalism, and satisfaction with medical education). Given the large sample, we focused on effect sizes versus statistical significance. Results The intersectional groups differed from each other on all professional well-being and all medical school experience variables except emotional climate, with at least small effect sizes (ηp 2 ≥ .01). Black female sexual minority students reported the most negative outcomes on all variables. The largest differences were primarily with White male heterosexual (e.g., discrimination: d = 1.68, 95% CI [1.53, 1.84]) and White female heterosexual (e.g., disengagement: d = 0.63, 95% CI [0.48, 0.79]) students. However, being a member of a greater number of marginalized groups was not necessarily associated with more negative outcomes, and patterns of group differences varied across domains of professional well-being and medical school experiences. Discussion Examining the combination of medical students’ gender, race and ethnicity, and sexual orientation yielded larger and more consistent effect sizes than examining each factor individually, suggesting that an intersectional approach can identify the unique challenges confronted by medical students from specific demographic groups.
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.