Research involvement among undergraduate medical students in Bangladesh: a multicenter cross-sectional study.

Background: The involvement of undergraduate medical students in research is pivotal for the advancement of evidence-based clinical practice. This study aimed to assess the extent of research involvement and the factors influencing it among undergraduate medical students in Bangladesh.

Methods: A multi-center cross-sectional study involving 2864 medical students from both public and private medical colleges was conducted between June and December 2023.

Obstetric and pregnancy-related factors associated with caesarean delivery in Bangladesh: a survey in Rajshahi district.

Objectives: Caesarean section (CS) delivery is the most common operative obstetric procedure globally. The increasing trend of CS deliveries poses a significant threat to both child and maternal health. The adverse maternal outcomes associated with caesarean delivery represent a substantial public health concern worldwide.

Threat or prospect? Exploring the impact of digital entrepreneurs' artificial intelligence perception and intention to adopt blockchain technology on the achievement of SDGs.

This paper explores how digital entrepreneurs' intention toward blockchain technology adoption, perception of reduced costs, and knowledge of Artificial Intelligence impact achieving UN's Sustainable Development Goals (SDGs), drawing attention from various sectors. Present study applies explanatory sequential mixed method for data collection. Moreover, to work with the dual face patterned data, PLS-SEM is used to perform quantitative analysis of the data collected from 389 digital entrepreneurs who are chosen through purposive sampling and then content analysis is performed for the qualitative data according to the explanatory sequential mixed method's rule of thumb.

A Comprehensive Bioinformatics Approach to Identify Molecular Signatures and Key Pathways for the Huntington Disease.

Huntington disease (HD) is a degenerative brain disease caused by the expansion of CAG (cytosine-adenine-guanine) repeats, which is inherited as a dominant trait and progressively worsens over time possessing threat. Although HD is monogenetic, the specific pathophysiology and biomarkers are yet unknown specifically, also, complex to diagnose at an early stage, and identification is restricted in accuracy and precision. This study combined bioinformatics analysis and network-based system biology approaches to discover the biomarker, pathways, and drug targets related to molecular mechanism of HD etiology.

Biometrical and histomorphometrical changes of testis in the dynamics of postnatal ontogenesis from birth to puberty of Black Bengal goat.

Objectives: The study aimed to account for baseline biometrical and histomorphometric testicular changes in Black Bengal goats during postnatal development.

Materials And Methods: Black Bengal goats, divided into group I of VII; day 0; 1, 2 weeks; 1, 2, 4, and 6 months of age, respectively, were used in this study.

Results: The biometrical and histomorphometric values of the testis varied significantly ( < 0.

Prevalence and factors associated with chronic school absenteeism among 207,107 in-school adolescents: Findings from cross-sectional studies in 71 low-middle and high-income countries.

Background: Despite the negative impact of chronic school absenteeism on the psychological and physical health of adolescents, data on the burden of adolescent chronic school absenteeism (ACSA) and interventions and programs to address it are lacking. We estimated the global, regional and national level prevalence of ACSA and its correlation with violence and unintentional injury, psychosocial, protective, lifestyle, and food security-related factors among in-school adolescents across low and middle-income, and high-income countries (LMICs-HICs).

Objectives: This study aimed to estimate the prevalence of chronic school absenteeism (CSA) as well as to determine its associated factors among in-school adolescents across 71 low-middle and high-income countries.

Reflective practice and psychotherapy case experience of Specialty Doctors and Associate Specialists (SAS) working in psychiatry: UK-wide survey.

Aims And Method: To survey nationwide opportunities for Balint-type and reflective support group participation and psychotherapy training among doctors classified as Specialty Doctors and Associate Specialists in psychiatry ('SAS psychiatrists') and the professional benefits and barriers to access.

Results: Approximately 9% of SAS psychiatrists responded, from all UK regions. A minority reported participating in a Balint-type group (27.

Effects of imidacloprid-contaminated feed exposure on spermatogenic cells and Leydig cells in testes of adult male rabbits (.

This research was undertaken to assess the results of repeated exposure to the insecticide; imidacloprid (IMI)-contaminated feed on testicular tissue, spermatogenic cell population, Leydig cell number, and sperm morphology in adult male rabbits (n = 24). The treatment groups received IMI (Bildor® 100 mg/L water spray on green grass)-contaminated green grass without wash (n = 8, not-washed-feed rabbit group) and after wash (n = 8, washed-feed rabbit group) once daily for two weeks on an alternate day basis. The rest of the rabbits, as control, received a normal pesticide-free standard feed.

Bioinformatics and System Biology Techniques to Determine Biomolecular Signatures and Pathways of Prion Disorder.

Prion disorder (PD) is caused by misfolding and the formation of clumps of proteins in the brain, notably Prion proteins resulting in a steady decrease in brain function. Early detection of PD is difficult due to its unpredictable nature, and diagnosis is limited regarding specificity and sensitivity. Considering the uncertainties, the current study used network-based integrative system biology approaches to reveal promising molecular biomarkers and therapeutic targets for PD.

In Vitro, In Silico and Network Pharmacology Mechanistic Approach to Investigate the -Glucosidase Inhibitors Identified by Q-ToF-LCMS from Fruit Subcritical CO Extract.

The fruit of have been traditionally used as an antidiabetic remedy in Malaysia and neighbouring countries. Despite its potential for diabetes treatment, no scientific study has ever been conducted to predict the inhibitor interaction of the protein -glucosidase identified in an extract prepared with a non-conventional extraction technique. Hence, the major aim of this research was to evaluate the in vitro antioxidant, the -glucosidase inhibitors, and the molecular dynamic simulations of the -glucosidase inhibitors identified by Quadrupole Time-of-Flight Liquid Chromatography Mass Spectrometry (Q-ToF-LCMS) analysis.

Medical Cannabis in Canadian Schools: A Scoping Review of Existing Policies.

An increasing number of children and youth in Canada are taking medical cannabis for complex medical conditions. While they deserve safe and consistent access to pharmacotherapy throughout the day, administrative policies on cannabis use in schools are inconsistent. A scoping review identified policies and publications associated with medical cannabis in Canadian schools.

Early Prediction of Diabetes Using an Ensemble of Machine Learning Models.

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of significant complications, including cardiovascular disease, kidney failure, diabetic retinopathy, and neuropathy, among others, which contribute to an increase in morbidity and mortality rate. If diabetes is diagnosed at an early stage, its severity and underlying risk factors can be significantly reduced. However, there is a shortage of labeled data and the occurrence of outliers or data missingness in clinical datasets that are reliable and effective for diabetes prediction, making it a challenging endeavor.

Structural-Guided Identification of Small Molecule Inhibitor of UHRF1 Methyltransferase Activity.

Ubiquitin-like containing plant homeodomain Ring Finger 1 (UHRF1) protein is recognized as a cell-cycle-regulated multidomain protein. UHRF1 importantly manifests the maintenance of DNA methylation mediated by the interaction between its SRA (SET and RING associated) domain and DNA methyltransferase-1 (DNMT1)-like epigenetic modulators. However, overexpression of UHRF1 epigenetically responds to the aberrant global methylation and promotes tumorigenesis.

Development of a Smartphone-Based Expert System for COVID-19 Risk Prediction at Early Stage.

COVID-19 has imposed many challenges and barriers on traditional healthcare systems due to the high risk of being infected by the coronavirus. Modern electronic devices like smartphones with information technology can play an essential role in handling the current pandemic by contributing to different telemedical services. This study has focused on determining the presence of this virus by employing smartphone technology, as it is available to a large number of people.

Warranty Seal Deformation Identification for Product Warranty Violation.

Product warranty seals or stickers are criteria for after-sale warranty services. The unauthorized removal or modification of a seal will void the warranty. So far, there is no detection method to confirm the warranty, other than the visual inspection of the deformation of the seal.

HGSORF: Henry Gas Solubility Optimization-based Random Forest for C-Section prediction and XAI-based cause analysis.

A stable predictive model is essential for forecasting the chances of cesarean or C-section (CS) delivery, as unnecessary CS delivery can adversely affect neonatal, maternal, and pediatric morbidity and mortality, and can incur significant financial burdens. Limited state-of-the-art machine learning models have been applied in this area in recent years, and the current models are insufficient to correctly predict the probability of CS delivery. To alleviate this drawback, we have proposed a Henry gas solubility optimization (HGSO)-based random forest (RF), with an improved objective function, called HGSORF, for the classification of CS and non-CS classes.

An Improved Machine-Learning Approach for COVID-19 Prediction Using Harris Hawks Optimization and Feature Analysis Using SHAP.

A healthcare monitoring system needs the support of recent technologies such as artificial intelligence (AI), machine learning (ML), and big data, especially during the COVID-19 pandemic. This global pandemic has already taken millions of lives. Both infected and uninfected people have generated big data where AI and ML can use to combat and detect COVID-19 at an early stage.

Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries.

Background: Hypertension is the most common modifiable risk factor for cardiovascular diseases in South Asia. Machine learning (ML) models have been shown to outperform clinical risk predictions compared to statistical methods, but studies using ML to predict hypertension at the population level are lacking. This study used ML approaches in a dataset of three South Asian countries to predict hypertension and its associated factors and compared the model's performances.

Computational Identification of Druggable Bioactive Compounds from and against Colorectal Cancer by Targeting Thymidylate Synthase.

Colorectal cancer (CRC) is the second most common cause of death worldwide, affecting approximately 1.9 million individuals in 2020. Therapeutics of the disease are not yet available and discovering a novel anticancer drug candidate against the disease is an urgent need.

Machine learning models for classification and identification of significant attributes to detect type 2 diabetes.

Unlabelled: Type 2 Diabetes (T2D) is a chronic disease characterized by abnormally high blood glucose levels due to insulin resistance and reduced pancreatic insulin production. The challenge of this work is to identify T2D-associated features that can distinguish T2D sub-types for prognosis and treatment purposes. We thus employed machine learning (ML) techniques to categorize T2D patients using data from the Pima Indian Diabetes Dataset from the Kaggle ML repository.

Balint in the time of COVID-19: Participant and facilitator experience of virtual Balint groups compared with in-person.

Background: Current literature highlights peer and psychological support as important for staff well-being, to cope in pandemic conditions.

Aims: Our organisation increased Balint group provision during unfamiliar challenges of COVID-19. This unique context allowed comparison of multiple new virtual and face-to-face (F2F) Balint experiences.

Spirulina ameliorates arsenic induced reproductive toxicity in male rats.

Spirulina (), has numerous health benefits including antioxidant, immunomodulatory, and anti-inflammatory activities, works against heavy metal toxicity, and is often used as a food supplement in human, animals, birds and fishes. This study aimed to evaluate the protective ability of the dietary spirulina against the toxic effects of inorganic arsenic (iAs) on male reproductive parameters in rats. Seventy-two mature Long-Evans male rats, dividing into six groups (T0, T1, T2, T3, T4 and T5) (12 rats/group) were included in this study.

A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data.

The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people. To get rid of this unexpected situation, quick identification of COVID-19 patients is required.