Application of Artificial Intelligence in Medical Education: Current Scenario and Future Perspectives

Introduction: Medical education is a lifetime learning process stretching from undergraduate to postgraduate, specialty training, and beyond. It also applies to various healthcare professionals, including doctors, nurses, and other allied healthcare professionals. Therefore, it is essential to acknowledge the immense role of artificial intelligence in medical education in the current era of rapidly growing technology.Methods: High-quality data that met the study objectives were included. In addition, comprehensive investigations on articles available in reputable databases such as PubMed, Research Gate, PubMed central, Web of Science, and Google Scholar were considered for literature review.Results: Artificial intelligence has fixed various issues in education during the last decade, including language processing,reasoning, planning, and cognitive modelling.Conclusion: It can be used in medical education in the following forms: Virtual Inquiry System, Medical Distance Learning and Management, and Recording teaching videos in medical schools. It can also enhance the value of the non-analytical humanistic aspects of medicine. The goal of this review article was to present the implications of AI in medical education, now and in the coming years

Early results after transatrial repair of RVOT obstruction including teratology of fallot

Background: Right ventricular (RV) dysfunction is a significant cause of morbidity and mortality after surgical correction of RVOT obstruction including tetralogy of Fallot (TOF). Transatrial repair avoids a ventriculotomy (in contrast to the transventricular approach) emphasizing maximal preservation of RV structure and function. We have adopted this technique as less traumatic for the right ventricle. This study evaluates the early surgical results of our approach.Methods: Between January 2005 to January 2014, 77 consecutive patients with RVOT obstruction were referred to our unit for surgical therapy. Of these, 14 were unsuitable for repair and underwent aortopulmonary shunting. In the remaining 63 patients (mean age of 2.67±0.38 years), complete transatrial/transpulmonary repair was performed. Previously placed shunts (four patients) were taken down. In all cases, subpulmonary resection and ventricular septal defect (VSD) closure were accomplished transatrially. In 51 patients, the main pulmonary artery was augmented with an autologous pericardial patch.Results: There were 7 (9%) deaths in this series. No patient required permanent pacemaker. Median ICU and hospital stay were 91 hours and 14 days, respectively. At median follow up of 54 (mean 51±12) months, all patients are asymptomatic, with no significant residual lesion.Conclusions: Transatrial/transpulmonary repair of TOF is associated with remarkably low morbidity and mortality in our early experience

Transcription factor AP-1 in esophageal squamous cell carcinoma: Alterations in activity and expression during Human Papillomavirus infection

<p>Abstract</p> <p>Background</p> <p>Esophageal squamous cell carcinoma (ESCC) is a leading cause of cancer-related deaths in Jammu and Kashmir (J&K) region of India. A substantial proportion of esophageal carcinoma is associated with infection of high-risk HPV type 16 and HPV18, the oncogenic expression of which is controlled by host cell transcription factor Activator Protein-1 (AP-1). We, therefore, have investigated the role of DNA binding and expression pattern of AP-1 in esophageal cancer with or without HPV infection.</p> <p>Methods</p> <p>Seventy five histopathologically-confirmed esophageal cancer and an equal number of corresponding adjacent normal tissue biopsies from Kashmir were analyzed for HPV infection, DNA binding activity and expression of AP-1 family of proteins by PCR, gel shift assay and immunoblotting respectively.</p> <p>Results</p> <p>A high DNA binding activity and elevated expression of AP-1 proteins were observed in esophageal cancer, which differed between HPV positive (19%) and HPV negative (81%) carcinomas. While JunB, c-Fos and Fra-1 were the major contributors to AP-1 binding activity in HPV negative cases, Fra-1 was completely absent in HPV16 positive cancers. Comparison of AP-1 family proteins demonstrated high expression of JunD and c-Fos in HPV positive tumors, but interestingly, Fra-1 expression was extremely low or nil in these tumor tissues.</p> <p>Conclusion</p> <p>Differential AP-1 binding activity and expression of its specific proteins between HPV - positive and HPV - negative cases indicate that AP-1 may play an important role during HPV-induced esophageal carcinogenesis.</p

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere

Potential Impact of MicroRNA Gene Polymorphisms in the Pathogenesis of Diabetes and Atherosclerotic Cardiovascular Disease

MicroRNAs (miRNAs) are endogenous, small (18&ndash;23 nucleotides), non-coding RNA molecules. They regulate the posttranscriptional expression of their target genes. MiRNAs control vital physiological processes such as metabolism, development, differentiation, cell cycle and apoptosis. The control of the gene expression by miRNAs requires efficient binding between the miRNA and their target mRNAs. Genome-wide association studies (GWASs) have suggested the association of single-nucleotide polymorphisms (SNPs) with certain diseases in various populations. Gene polymorphisms of miRNA target sites have been implicated in diseases such as cancers, diabetes, cardiovascular and Parkinson&rsquo;s disease. Likewise, gene polymorphisms of miRNAs have been reported to be associated with diseases. In this review, we discuss the SNPs in miRNA genes that have been associated with diabetes and atherosclerotic cardiovascular disease in different populations. We also discuss briefly the potential underlining mechanisms through which these SNPs increase the risk of developing these diseases

Clinical Implications of Glyoxalase1 Gene Polymorphism and Elevated Levels of the Reactive Metabolite Methylglyoxal in the Susceptibility of Type 2 Diabetes Mellitus in the Patients from Asir and Tabuk Regions of Saudi Arabia

Diabetes mellitus constitutes a big challenge to the global health care system due to its socioeconomic impacts and very serious complications. The incidence and the prevalence rate are increased in the Gulf region including the KSA. Type 2 diabetes mellitus (T2DM) is caused by diverse risk factors including obesity, unhealthy dietary habits, physical inactivity, smoking and genetic factors. The molecular genetic studies have helped in the detection of many single nucleotide polymorphisms (SNP) with different diseases including cancers, cardiovascular diseases and T2DM. The glyoxalase 1 (GLO1) is a detoxifying enzyme and catalyzes the elimination of the cytotoxic product methylglyoxal (MG) by converting it to D-lactate, which is not toxic to tissues. MG accumulation is associated with the pathogenesis of different diseases including T2DM. In this study, we have investigated the association of the glyoxalase 1 SNPs (rs2736654) rs4746 C&gt;A and rs1130534 T&gt;A with T2DM using the amplification refractory mutation system PCR. We also measured the concentration of MG by ELISA in T2DM patients and matched heathy controls. Results show that the CA genotype of the GLO rs4647 A&gt;C was associated with T2DM with OR = 2.57, p-value 0.0008 and the C allele was also associated with increased risk to T2DM with OR = 2.24, p-value = 0.0001. It was also observed that AT genotype of the rs1130534 was associated with decreased susceptibility to T2DM with OR = 0.3, p-value = 0.02. The A allele of rs1130534 was also associated with reduced risk to T2DM with PR = 0.27 = 0.006. In addition, our ELISA results demonstrate significantly increased MG concentrations in serum of the T2DM patients. We conclude that the GLO1 SNP may be associated with decreased enzyme activity and a resultant susceptibility to T2DM. Further well-designed studies in different and large patient populations are recommended to verify these findings

Role of Selected miRNAs as Diagnostic and Prognostic Biomarkers in Cardiovascular Diseases, Including Coronary Artery Disease, Myocardial Infarction and Atherosclerosis

Cardiovascular diseases are the leading cause of death worldwide in different cohorts. It is well known that miRNAs have a crucial role in regulating the development of cardiovascular physiology, thus impacting the pathophysiology of heart diseases. MiRNAs also have been reported to be associated with cardiac reactions, leading to myocardial infarction (MCI) and ultimately heart failure (HF). To prevent these heart diseases, proper and timely diagnosis of cardiac dysfunction is pivotal. Though there are many symptoms associated with an irregular heart condition and though there are some biomarkers available that may indicate heart disease, authentic, specific and sensitive markers are the need of the hour. In recent times, miRNAs have proven to be promising candidates in this regard. They are potent biomarkers as they can be easily detected in body fluids (blood, urine, etc.) due to their remarkable stability and presence in apoptotic bodies and exosomes. Existing studies suggest the role of miRNAs as valuable biomarkers. A single biomarker may be insufficient to diagnose coronary artery disease (CAD) or acute myocardial infarction (AMI); thus, a combination of different miRNAs may prove fruitful. Therefore, this review aims to highlight the role of circulating miRNA as diagnostic and prognostic biomarkers in cardiovascular diseases such as coronary artery disease (CAD), myocardial infarction (MI) and atherosclerosis

Strong Association of Angiotensin Converting Enzyme-2 Gene Insertion/Deletion Polymorphism with Susceptibility to SARS-CoV-2, Hypertension, Coronary Artery Disease and COVID-19 Disease Mortality

Background: The ongoing outbreak of SARS-CoV-2 represents a significant challenge to international health. Several reports have highlighted the importance of ACE2 on the pathogenesis of COVID-19. The spike protein of SARS-CoV-2 efficiently binds to the angiotensin-converting enzyme 2 (ACE2) receptors and facilitates virus entry into the host cell. In the present study, we hypothesize that a functional insertion/deletion polymorphism-rs4646994 I/D and rs4240157 T &gt; C in the ACE gene could be associated with SARS-CoV-2 infection and mortality. Methodology: This study included 117 consecutive COVID-19 patients and 150 age matched healthy controls (ACE2-rs4646994 I/D) and 100 age matched healthy controls with ACE2 rs4240157 T &gt; C. We used Mutation specific PCR (MSP) for ACE2-rs4646994 I/D genotyping and amplification refractory mutation system (ARMS-PCR) for ACE2 rs4240157 T &gt; C genotyping. Results: Results indicated that there were significant differences in the genotype distributions of ACE2-rs4646994 I/D polymorphisms (p &lt; 0.030) and ACE2 rs4240157 T &gt; C between COVID-19 patients and controls (p-values &lt; 0.05). Higher frequency of DD genotype (48.71%) and D allele (0.67) was reported in COVID-19 patients than controls. Our results showed that the ACE2-DD genotype was strongly associated with increased COVID-19 severity (OR 2.37 (95%) CI = (1.19–4.70), RR = 1.39 (1.09–1.77), p &lt; 0.013) and also a strong association was seen with ACE2-ID genotype with COVID-19 severity (OR 2.20 (95%) CI = (1.08–4.46), p &lt; 0.020) in the codominant model. In allelic comparison, the D allele was strongly associated with COVID-19 severity (OR 1.58 (95% CI) (1.11–2.27), RR 1.21 (1.05–1.41) p &lt; 0.010). A significant correlation of ACE2-I/D genotypes was reported with Age (p &lt; 0.035), T2D (p &lt; 0.0013), hypertension (p &lt; 0.0031) and coronary artery disease (p &lt; 0.0001). Our results indicated ACE2-DD genotype was strongly associated with increased COVID-19 mortality (OR 8.25 (95%) CI = (2.40 to 28.34), p &lt; 0.008) and also ACE2-DD + DI genotype was strongly associated with increased COVID-19 mortality with OR 4.74 (95%) CI = (1.5214 to 14.7915), p &lt; 0.007. A significant correlation was reported between COVID-19 patients and age matched controls (p &lt; 0.0007). Higher frequency of heterozygosity TC (40%) followed by ACE2-CC genotype (24.78%) was reported among COVID-19 patients. Using multivariate analysis, ACE2–CT genotype was strong associated with SARS-CoV-2 severity with an OR 2.18 (95% CI) (1.92–3.99), p &lt; 0.010 and also ACE2–CC genotype was linked with COVID-19 severity with an OR 2.66 (95% CI) (1.53–4.62), p &lt; 0.005. A significant correlation of ACE2-T &gt; C genotypes was reported with gender (p &lt; 0.04), T2D (p &lt; 0.035). ACE2-CC genotype was strongly associated with increased COVID-19 mortality OR 3.66 (95%) CI = (1.34 to 9.97), p &lt; 0.011 and also ACE2-C allele was associated with COVID-19 mortality OR 2, 01 (1.1761–3.45), p &lt; 0.010. Conclusions: It is concluded that ACE-DD genotype and D allele was strongly associated with increased COVID-19 patient severity. In addition, ACE I/D polymorphism were strongly associated with advanced age, diabetes and ischemic heart disease in COVID-19 patients whereas ACE-II genotype was a protective factor against the development of severe COVID-19. ACE2-DD genotype was strongly associated with increased COVID-19 mortality. Additionally, ACE2–CC and CT genotypes were strongly associated with COVID-19 severity. Therefore, our study might be useful for identifying the susceptible population groups for targeted interventions and for making relevant public health policy decisions