Promising score for teaching and learning environment: an experience of a fledgling medical college in Saudi Arabia

Background: Professional competency of graduates of an institute reflects its teaching and learning environment (TLE). This study aimed to provide a preliminary assessment of the TLE at the College of Medicine at Majmaah University. Methods: A cross-sectional survey was conducted during the 2019-20 academic year among students at the College. A validated scoring tool “the Experience of Teaching and Learning Questionnaire” (available at https://bit.ly/3sVBuEw) was used. The mean score of each section and statement, the difference between the mean scores of different demographic groups, and correlations between sections were analysed. Results: A total of 234 (72.2%) enrolled students participated in this survey, with a male-to-female ratio and a ratio of participants from basic to clinical years being 2:1 and 1:1, respectively. Most participants reported a GPA of above 3/5. The overall mean score was 3.52/5 points. Section one “approaches to learning and studying” has the highest mean score (3.68), and no section scored a mean below three, though section three “demands made by the course” scored a borderline mean of 3.08. Students in clinical years had a significantly higher overall mean score compared to their counterparts (3.66 vs. 3.39, p < 0.001). Conclusions: Students at the College had a positive perception of the TLE, but face challenges in coping with the demands of acquiring knowledge and subject-based skills, and in appreciating the TLE especially during basic science years, highlighting the need for an atmosphere that allows them to meet demands and develop greater appreciation

Development of nonlaboratory-based risk prediction models for cardiovascular diseases using conventional and machine learning approaches

Criticism of the implementation of existing risk prediction models (RPMs) for cardiovascular diseases (CVDs) in new populations motivates researchers to develop regional models. The predominant usage of laboratory features in these RPMs is also causing reproducibility issues in low–middle-income countries (LMICs). Further, conventional logistic regression analysis (LRA) does not consider non-linear associations and interaction terms in developing these RPMs, which might oversimplify the phenomenon. This study aims to develop alternative machine learning (ML)-based RPMs that may perform better at predicting CVD status using nonlaboratory features in comparison to conventional RPMs. The data was based on a case–control study conducted at the Punjab Institute of Cardiology, Pakistan. Data from 460 subjects, aged between 30 and 76 years, with (1:1) gender-based matching, was collected. We tested various ML models to identify the best model/models considering LRA as a baseline RPM. An artificial neural network and a linear support vector machine outperformed the conventional RPM in the majority of performance matrices. The predictive accuracies of the best performed ML-based RPMs were between 80.86 and 81.09% and were found to be higher than 79.56% for the baseline RPM. The discriminating capabilities of the ML-based RPMs were also comparable to baseline RPMs. Further, ML-based RPMs identified substantially different orders of features as compared to baseline RPM. This study concludes that nonlaboratory feature-based RPMs can be a good choice for early risk assessment of CVDs in LMICs. ML-based RPMs can identify better order of features as compared to the conventional approach, which subsequently provided models with improved prognostic capabilities

Clinico-demographic and survival profile of people living with HIV on antiretroviral treatment

ObjectiveTo assess the demographic, clinical, and survival profile of people living with HIV.MethodsA retrospective cohort study was conducted among patients enrolled at a single antiretroviral therapy center in North Karnataka. A total of 11,099 were recruited from April 2007 to January 2020, out of which 3,676 were excluded and the final 7,423 entries were subjected to analysis. The outcome of interest was the time to death in months of people living with HIV on antiretroviral therapy (ART). The clinical and demographic characteristics were examined as potential risk factors for survival analysis. To investigate the factors that influence the mortality of patients using ART, univariate and multivariate Cox regression were performed. Hazard ratio (HR), 95% confidence interval (CI), and p-values were presented to show the significance. The log-rank test was used to determine the significance of the Kaplan–Meier survival curve.ResultsOut of 7,423 HIV-positive people, majority were female (51.4%), heterosexual typology (89.2%), and in the age group 31–45 years (45.5%). The risk of death in male patients was 1.24 times higher (95% CI: 1.14–1.35) than female patients. Patients with age &gt;45 were 1.67 times more likely to die than patients ≤30 (95% CI: 1.50–1.91). In the multivariable analysis, the hazards of mortality increased by 3.11 times (95% CI: 2.09–2.79) in patients with baseline CD4 count ≤50 as compared to those who had baseline CD4 count &gt;200. The risk of death in patients who were diagnosed with TB was 1.30 times more (95% CI: 1.19–1.42) than in those who did not have TB. The survival probabilities at 3 and 90 months were more in female patients (93%, 70%) compared with male patients (89, 54%), respectively.ConclusionThis study proved that age, sex, baseline CD4 count, and tuberculosis (TB) status act as risk factors for mortality among people with HIV. Prevention strategies, control measures, and program planning should be done based on the sociodemographic determinants of mortality

Assessment of Saudi Society’s Knowledge Regarding Hypothyroidism and Its Neuropsychiatric Clinical Manifestations

Background: This study was conducted to assess the level of knowledge and awareness of hypothyroidism and its neuropsychiatric clinical manifestations among the Saudi population. Methods: This was a cross-sectional study employing a convenient sampling technique, conducted between February and May 2022. A questionnaire was distributed online to all participants in all five regions. Results: In this survey, a total of 2016 Saudi citizens participated. When asked about depression, more than half of the participants (59.6%) correctly identified depression as one of the neuropsychiatric clinical symptoms of hypothyroidism. Nearly half of the participants (47.5%) were unaware that anxiety was not a neuropsychiatric manifestation of hypothyroidism. With a percentage of 91.0%, the majority of participants exhibited poor knowledge. The regression analysis showed that males have significantly reduced knowledge about hypothyroidism than females (coefficient −3.686, p-value p-value p-value 0.0001), and healthcare practitioners provides four times more information as compared to family and friends (p-value 0.0001). Conclusion: Due to a lack of knowledge about hypothyroidism and its complications, symptoms, risk factors, and treatment, the most viable solution to these misconceptions would be to implement a variety of educational programs to increase public awareness of this issue

Table2_Isoform switching leads to downregulation of cytokine producing genes in estrogen receptor positive breast cancer.DOCX

Objective: Estrogen receptor breast cancer (BC) is characterized by the expression of estrogen receptors. It is the most common cancer among women, with an incidence rate of 2.26 million cases worldwide. The aim of this study was to identify differentially expressed genes and isoform switching between estrogen receptor positive and triple negative BC samples.Methods: The data were collected from ArrayExpress, followed by preprocessing and subsequent mapping from HISAT2. Read quantification was performed by StringTie, and then R package ballgown was used to perform differential expression analysis. Functional enrichment analysis was conducted using Enrichr, and then immune genes were shortlisted based on the ScType marker database. Isoform switch analysis was also performed using the IsoformSwitchAnalyzeR package.Results: A total of 9,771 differentially expressed genes were identified, of which 86 were upregulated and 117 were downregulated. Six genes were identified as mainly associated with estrogen receptor positive BC, while a novel set of ten genes were found which have not previously been reported in estrogen receptor positive BC. Furthermore, alternative splicing and subsequent isoform usage in the immune system related genes were determined.Conclusion: This study identified the differential usage of isoforms in the immune system related genes in cancer cells that suggest immunosuppression due to the dysregulation of CXCR chemokine receptor binding, iron ion binding, and cytokine activity.</p