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School engagement and student burnout among medical and health science students in Saudi Arabia-cross-sectional study
Abstract School engagement and burnout are contributing factors influencing academic student performance. Student burnout is a serious concern in higher education, where it can result in poor mental and physical health and school dropout. Although recent studies indicate the significance of the relationship between academic engagement and achievement, little is known about how academic engagement and burnout affect medical sciences students in the Madinah region of Saudi Arabia. We aimed to assess the level of school engagement and student burnout among medical and health science students in Madinah, Saudi Arabia. Factors associated with school engagement and student burnout were also explored. A cross-sectional data of 297 students last year medical and health science undergraduate students who were recruited from Taibah University, Madinah. The online survey was shared with students to collect data on sample characteristics, school engagement (using the modified version of the University Student Engagement Inventory), and student burnout (using the modified version of the Maslach Burnout Inventory Student Survey). The data showed that 57.5% of medical science students in the sample were academically engaged, and 55.9% experienced burnout, indicating a moderate to high level of student engagement and burnout. However, there was no correlation between school engagement and student burnout (r = 0.27) among the sample in this study. Nevertheless, school engagement was affected by factors such as student living status (p = 0.036), dropout thoughts (p = 0.008), and cumulative GPA (p = 0.001). In addition to dropout thoughts and GPA, the student burnout level was also predicted by the college (p = 0.012), program duration (p < 0.001), sex (p = 0.016), and average sleeping hours per day (p = 0.019). These results imply that school engagement and burnout may not be directly related or opposites and can interact in a variety of ways depending on factors including student personality and lifestyle, as well as academic and institutional influences. Many factors were linked to school engagement and student burnout. Interventions that aim to reduce student burnout should be tailored based on many factors including program duration and sex of students.
The central lymph node dissection using carbon nanoparticle in transoral vestibular approach endoscopic thyroid surgery
HCF-1 as a key modulator of OGT function and O-GlcNAcylation in the liver
A multinational cross-sectional study on the prevalence and predictors of long COVID across 33 countries
Abstract The symptoms of long COVID (LC) can be debilitating and may be associated with anxiety, social stigma, and quality of life deterioration. Identifying patients at risk of LC is important to offer follow-up care and plan population-level public health measures. The current multinational study aimed to assess the prevalence and predictors of LC in the general population. We conducted an online, multinational, cross-sectional survey between April 2022 and January 2023, targeting participants 18 years and older with a previously confirmed COVID-19 infection. We used convenience sampling to recruit participants through an online Google form. We collected demographic data, past medical history, infection details, post-COVID-19 symptoms, and quality of life. Responses were then translated into English. LC was defined as per the World Health Organization. A single-variable analysis was conducted to identify factors significantly associated with LC development. Following the removal of multicollinear variables, a generalized linear model was established to estimate the contribution of different predictors to LC occurrence. A total of 11,801 respondents from 33 countries were included in the analysis. The mean age for participants was 32.7 ± 12.8 years, with 61% being females. BMI averaged 25.2 ± 4.8 across participants, and 14.8% of them were smokers. Seventy-eight percent of participants reported receiving the COVID-19 vaccine. Respondents with PCR-confirmed COVID-19 were then categorized into those with LC (N = 2335, 19.8%) and without LC (N = 9466 individuals, 80.2%). Our model identified 25 significant predictors. The predictors of higher LC risk included ICU admission (OR 2.08; 95% CI 1.36, 3.18; P = 0.001), female sex (OR 1.8; 95% CI 1.61, 2.02; P < 0.001), fatigue during the infection (OR 1.6; 95% CI 1.43, 1.78; P < 0.001), identifying as Hispanic (OR 1.53; 95% CI 1.26, 1.85; P < 0.001), and pre-existing gastrointestinal disease (OR 1.48; 95% CI 1.22, 1.8; P < 0.001). In conclusion, we identified key LC predictors, including ICU admission, female sex, and acute fatigue as primary risk factors, while African American and Asian ethnicities and receiving even one dose of vaccination demonstrated protective effects.
Rhizosphere effects on cadmium fractionation in contaminated soils: a comparative study of ultisols and alfisols
Highly robust anisotropic zero refraction effects in semi-Dirac photonic crystals
Immune characteristics and SALL1 methylation as prognostic biomarkers in primary and metastasis colorectal cancer
Deep reinforcement learning-based mechanism to improve the throughput of EH-WSNs
An experimental study on the detection mechanism of 2-CEES using SAW sensors under various temperature conditions
Antibiotic carry over is a confounding factor for cell-based antimicrobial research applications
Abstract Chronic wounds often host pathogens like Staphylococcus aureus, prompting interest in developing new antimicrobial and wound healing strategies, including the utilisation of extracellular vesicles (EVs). Whilst there has been a recent emphasis within the EV community to ensure standardization of characterization and isolation techniques, there has been less focus placed on the upstream tissue culture methodologies used for collection of vesicle-containing conditioned medium (CM). Hence, this study investigated the antimicrobial properties of the CM used for EV enrichment. CM exhibited bacteriostatic effects against penicillin-sensitive S. aureus NCTC 6571, but not penicillin-resistant S. aureus 1061 A. Further analysis revealed that the antimicrobial activity was due to residual antibiotics rather than cell-secreted factors, specifically the retention and release of penicillin to tissue culture plastic surfaces. Pre-washing cells and minimizing antibiotic concentrations in basal medium reduced this carry-over effect. These findings emphasize the importance of controlling antibiotic use in tissue culture to avoid misleading conclusions about the antimicrobial potential of CM or EVs. Researchers should carefully consider medium selection and supplementation during method development as accurately determining the antimicrobial mechanisms of any CM is essential for validating future cell-based therapeutic applications.
The association between glycemic indicators and bone mineral density and osteoporosis: a cross-sectional study
Impact of anthropogenic disturbance and climate on bamboo distribution in shifting cultivation landscapes of Northeast India
The transcriptome of the olm provides insights into its evolution and gene expression
Abstract The olm (Proteus anguinus), with a predicted maximum lifespan of more than 100 years, is the longest-lived amphibian, which in addition possesses a range of unique adaptations to its dark, subterranean cave habitat. To assess the underlying molecular signatures, we present the first comprehensive transcriptome of the olm. Our study provides gene expression data across six organs and comparative genomics analyses, accessible via an interactive web server: http://comp-pheno.de/olm. The data uncover significant organ-specific gene expression, with the brain showing the highest number of organ-specific expressed genes. Our findings reveal significantly more genes under strong negative selection than positive selection, particularly in brain-specific expressed genes. Processes under positive selection in the olm resemble those in other long-lived species.
Baseline isotopic variability in plants and animals and implications for the reconstruction of human diet in 1 st century AD Pompeii
Abstract While Pompeii has long captured the imagination with its history and tragic end, recent efforts have shifted towards unveiling everyday lifeways. Our study seeks to explore agricultural and husbandry practices in Pompeii, aiming to explore isotopic variability of different food categories available to the Romans within this unique “snapshot” scenario. To do so, we deploy stable carbon and nitrogen isotope analysis of plants and animals. Our findings suggest a diversity of practices, with isotopic variation in C3 cereals and legumes pointing to the use of a greater variety of cultivation techniques compared to arboreal crops. We highlight distinct management regimes utilised for different animal species and we uncover a spectrum of aquatic environments, indicative of diversity of fishing practices. These findings provide direct support of archaeological evidence and textual interpretations of Roman food systems in Pompeii. However, our dataset also reveals the limitations of bulk isotope approaches in detecting this dietary diversity when we use it to interpret the local human diet through mixing models. Together, our results show that a broad and well-contextualised isotopic baseline can help us understanding ancient food systems, while also revealing the challenges of disentangling dietary complexity using bulk stable isotope data alone.
Coxiella burnetii and HIV infection in people experiencing homelessness
Abstract This study has investigated Coxiella burnetii and HIV infection among the persons experiencing homelessness of São Paulo city, Brazil, and assessed correspondent associated risk factors. A cross-sectional study was carried out with 203 individuals performing serological tests for anti-C. burnetii and anti-HIV antibodies. A prevalence of 14.8% (30/203) was found for anti-C. burnetii IgG antibodies, with titers ranging from 64 to 1024, while anti-HIV seroprevalence was 6.4% (13/203). No statistical association was found between C. burnetii and HIV seropositivity, or between seropositivity and assessed clinical and epidemiological variables. The findings herein highlight the high homelessness exposure to Q fever, possibly influenced by environmental factors such as dust aerosols, stray animal interactions and unsanitary living conditions. To the authors knowledge, this is the first serosurvey of C. burnetii in persons experiencing homelessness to date. The study herein has emphasized the importance of public health strategies targeting vulnerable populations, particularly in Brazilian major cities. Further C. burnetii surveys should be conducted to establish whether transmission may occur in other persons experiencing homelessness worldwide.
In vitro biological activities of silver nanoparticles using methanolic leaf extract of Plumeria rubra
Evaluation of university student education management effect based on data augmentation and transfer learning for remote sensing applications
Abstract Evaluating the effectiveness of education management requires the integration of multi-source data and information. Based on data modeling technology, combined with data enhancement and transfer learning methods, this paper analyzes the differences in the allocation of education management resources in six universities in different semesters, and systematically explores the actual effectiveness of university education management. By combining data enhancement technology, we expanded the training data, simulated various real-life scenarios, and ensured that the model is more robust to various data changes. This study mainly used two models: simulation-verification model and BP (back propagation) neural network model, and analyzed their management efficiency, prediction accuracy, stability and time cycle. This study proposed two models: simulation-verification model (evaluating the effect by simulating the consistency of management conditions and verification results) and BP neural network model (prediction model based on data enhancement and transfer learning). Experiments show that the BP neural network model is superior to the simulation model in management efficiency (ratio of resource input to actual effect) and stability (volatility of model prediction results), with an average management efficiency of 85.9%, prediction accuracy of 93.1%, and stability of 72.3%. The BP neural network model is superior to the simulation verification model in terms of management efficiency, prediction accuracy, and stability, demonstrating the potential of integrating advanced data processing technologies such as data enhancement and transfer learning into the education management system.