Prevalence of depression and anxiety among university students in Jeddah, Saudi Arabia: exploring sociodemographic and associated factors.

Introduction: Previous studies have shown that mental health issues such as depression and anxiety are on the rise globally, particularly among university students. The aim of this study is to assess the prevalence of depressive and anxiety symptoms among university students, and the associated potential risk factors, in Jeddah, Saudi Arabia.

Methods: A cross-sectional questionnaire study was conducted in a sample of 728 students who anonymously completed three sets of questionnaires: a sociodemographic and lifestyle information questionnaire, the Patient Health Questionnaire-9 (PHQ-9) to screen for depressive symptoms and the Generalized Anxiety Disorder-7 (GAD-7) scale to screen for anxiety symptoms.

USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING APPROACHES TO ENHANCE CANCER THERAPY AND DRUG DISCOVERY: A NARRATIVE REVIEW.

Background: This paper looks at how AI and machine learning have been applied over the last ten years to the development of anti-cancer drugs. By speeding up the synthesis of more desirable compounds and the identification of new ones, artificial intelligence (AI) has demonstrated substantial contributions to the research and therapy of anti-cancer therapies.

Methods: This work is a narrative review that examines numerous uses of AI-based techniques in the development of anti-cancer medications.

Impact of thermal treatment on halloysite nanotubes: A combined experimental-computational approach.

Halloysite nanotubes (HNTs) are naturally occurring aluminosilicate minerals, known for their unique tubular structure, which have garnered significant interest for a wide range of applications. This study explores the morphological changes of HNTs when subjected to thermal treatment ranging from 25 °C to 1100 °C using a combination of experimental characterization techniques and molecular dynamics simulations. Techniques such as solid-state NMR (SSNMR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmett-Teller (BET) surface area measurements, and Fourier Transform Infrared Spectroscopy (FT-IR) were employed to analyse the structural evolution.

Do We Need to Hold Aspirin Before Cataract Surgery? A Systematic Review and Meta-Analysis of 65,196 Subjects.

Purpose: Cataract surgery is a common operation, typically carried out on older adults who have many comorbid medical conditions. Many of these patients may be undergoing aspirin therapy for diverse cardiovascular causes. Nevertheless, there is ongoing controversy regarding the administration of aspirin therapy during the perioperative period, as there are concerns regarding the risk of bleeding problems compared to thromboembolic events.

Assessment of Oral Hygiene and Gingivitis in Adolescents With and Without Cystic Fibrosis.

To assess oral hygiene, gingivitis, and the association between them for adolescents with cystic fibrosis (CF) compared to nonCF controls. This was a cross-sectional study of adolescents with CF aged 12 to 17 years (n=27), compared to two non-CF control groups: Medicaid-enrolled adolescents with special health care needs (ASHCN; n=60) and healthy Medicaid-enrolled adolescents (n=185). Dental plaque was a proxy for oral hygiene, and gingival bleeding was a proxy for gingivitis.

Social Media Influencers and Their Impact on Society in Performing Cosmetic Procedures Among Al-Ahsa Community.

Introduction: The popularity of cosmetic surgery has been increasing in recent years, and social media is playing a role in this trend. This study investigated the influence of following social media influencers on the decision to undergo cosmetic procedures in Al Ahsa, Saudi Arabia.

Methodology: A descriptive cross-sectional study was conducted in Al Ahsa, Saudi Arabia.

ArSa-Tweets: A novel Arabic sarcasm detection system based on deep learning model.

Sarcasm in Sentiment Analysis (SA) is important due to the sense of sarcasm in sentences that differs from their literal meaning. Analysis of Arabic sarcasm still has many challenges like implicit indirect idioms to express the opinion, and lack of Arabic sarcasm corpus. In this paper, we proposed a new detecting model for sarcasm in Arabic tweets called the ArSa-Tweet model.

The diagnostic accuracy of the Arabic version of the Pediatric Sleep Questionnaire for screening for pediatric sleep-related breathing disorders in Saudi children.

Background: Pediatric Sleep Questionnaire (PSQ) is a valid, reliable tool for screening for sleep-related breathing disorders (SRBDs) translated into several languages since 2000. The diagnostic accuracy of an Arabic version of the PSQ has never been tested. Our aim was to translate the original version of PSQ into Arabic (Arabic-PSQ), validate it as a reliable screening tool, and compare it to the gold standard diagnostic method for SRBDs.

Coronary risk factor profiles according to different age categories in premature coronary artery disease patients who have undergone percutaneous coronary intervention.

Many studies have investigated the coronary risk factors (CRFs) among premature coronary artery disease (PCAD) patients. However, reports on the proportion and CRFs of PCAD according to different age cut-offs for PCAD is globally under-reported. This study aimed to determine the proportion of PCAD patients and analyse the significant CRFs according to different age cut-offs among percutaneous coronary intervention (PCI)-treated patients.

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery.

Background: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques.

Methods: Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D.

Investigating composition instructors' written feedback practices at KSAU-HS of the academic year 2022-23.

This study explores teachers' written corrective feedback (WCF) strategies and investigates factors determining teachers' WCF practices in English composition classes taught at King Saud bin Abdulaziz University for Health Sciences. Through a thematic analysis of online surveys, instructor written feedback practices on student writing, and semi-structured interviews, the results show that most English composition instructors provided written feedback on all forms of issues and practiced more direct than indirect feedback on correcting those issues. They gave feedback in the margin and end-note feedback on student writing.

Saliva sampling method influences oral microbiome composition and taxa distribution associated with oral diseases.

Saliva is a readily accessible and inexpensive biological specimen that enables investigation of the oral microbiome, which can serve as a biomarker of oral and systemic health. There are two routine approaches to collect saliva, stimulated and unstimulated; however, there is no consensus on how sampling method influences oral microbiome metrics. In this study, we analyzed paired saliva samples (unstimulated and stimulated) from 88 individuals, aged 7-18 years.

Set-based design application on dates harvesting machine.

This paper explores the application of Set-based Design (SBD) in the design of a dates harvesting machine. Dates are a popular fruit with significant economic importance, especially in Saudi Arabia. However, the process of harvesting them is highly labour-intensive, and there is a need for an automated solution to improve efficiency and reduce costs.

Addressing the Effectiveness and Molecular Mechanism of the Catalytic CO Hydration in Aqueous Solutions by Nickel Nanoparticles.

Hydration of carbon dioxide in water solution is the rate limiting step for the CO mineralization process, a process which is at the base of many carbon capture and utilization (CCU) technologies aiming to convert carbon dioxide to added-value products and mitigate climate change. Here, we present a combined experimental and computational study to clarify the effectiveness and molecular mechanism by which nickel nanoparticles, NiNPs, may enhance CO hydration in aqueous solutions. Contrary to previous literature, our kinetic experiments recording changes of pHs, conductivity, and dissolved carbon dioxide in solution reveal a minimal effect of the NiNPs in catalyzing CO hydration.

Examining the Impact of Puberty on Primary Headache Disorders in Female Schoolchildren: A Cross-Sectional Study.

Introduction and aim Headaches are one of the most prevalent childhood disorders. Primary and secondary headaches are the two types of headaches affecting kids and teenagers. The three most typical primary headache forms are tension-type headaches (TTH), migraine, and cluster headaches.

PaCMAP-embedded convolutional neural network for multi-omics data integration.

Aims: The multi-omics data integration has emerged as a prominent avenue within the healthcare industry, presenting substantial potential for enhancing predictive models. The main motivation behind this study stems from the imperative need to advance prognostic methodologies in cancer diagnosis, an area where precision is pivotal for effective clinical decision-making. In this context, the present study introduces an innovative methodology that integrates copy number alteration (CNA), DNA methylation, and gene expression data.

Correlation between Physical Activity and Depression in Community-Dwelling Older Adult Palestinians.

Objective: Investigating the relationship between physical activity (PA) and depressive symptoms is a vital field of research globally. Nonetheless, this association remains unexplored in the context of older Palestinian adults, highlighting the need for additional research on this population. Therefore, this study aimed to examine the association between PA and depressive symptoms among older Palestinian adults.

International pediatric otolaryngology group (IPOG) consensus on approach to aspiration.

Objective: To provide recommendations for a comprehensive management approach for infants and children presenting with symptoms or signs of aspiration.

Methods: Three rounds of surveys were sent to authors from 23 institutions worldwide. The threshold for the critical level of agreement among respondents was set at 80 %.

Explainable Artificial Intelligence Paves the Way in Precision Diagnostics and Biomarker Discovery for the Subclass of Diabetic Retinopathy in Type 2 Diabetics.

Diabetic retinopathy (DR), a common ocular microvascular complication of diabetes, contributes significantly to diabetes-related vision loss. This study addresses the imperative need for early diagnosis of DR and precise treatment strategies based on the explainable artificial intelligence (XAI) framework. The study integrated clinical, biochemical, and metabolomic biomarkers associated with the following classes: non-DR (NDR), non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR) in type 2 diabetes (T2D) patients.

An Explainable Artificial Intelligence Model Proposed for the Prediction of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and the Identification of Distinctive Metabolites.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating illness with a significant global prevalence, affecting over 65 million individuals. It affects various systems, including the immune, neurological, gastrointestinal, and circulatory systems. Studies have shown abnormalities in immune cell types, increased inflammatory cytokines, and brain abnormalities.