Correlation between blood pressure and five food groups as a coronary heart disease risk factor in middle aged Indian male population

Background: Social and lifestyle changes are responsible for the increasing prevalence of coronary heart disease risk factors. Objective of the study was to correlate blood pressure and five food group as a coronary heart disease risk factor in Indian population.Methods: 31 male executives over the age of 30 years working in industry were included in the study. Systolic and diastolic blood pressures were measured with the help of a standard mercury sphygmomanometer.Results: Statistical analysis was carried out and Pearson Correlation was applied. The study showed significant correlation between systolic blood pressure and food group I and food group IV consumption.Conclusions: The present study highlights observation that the blood pressure as a risk factor for coronary heart disease is silently affecting the middle aged Indian male population due to unhealthy life style

Deployment of a Robust and Explainable Mortality Prediction Model: The COVID-19 Pandemic and Beyond

This study investigated the performance, explainability, and robustness of deployed artificial intelligence (AI) models in predicting mortality during the COVID-19 pandemic and beyond. The first study of its kind, we found that Bayesian Neural Networks (BNNs) and intelligent training techniques allowed our models to maintain performance amidst significant data shifts. Our results emphasize the importance of developing robust AI models capable of matching or surpassing clinician predictions, even under challenging conditions. Our exploration of model explainability revealed that stochastic models generate more diverse and personalized explanations thereby highlighting the need for AI models that provide detailed and individualized insights in real-world clinical settings. Furthermore, we underscored the importance of quantifying uncertainty in AI models which enables clinicians to make better-informed decisions based on reliable predictions. Our study advocates for prioritizing implementation science in AI research for healthcare and ensuring that AI solutions are practical, beneficial, and sustainable in real-world clinical environments. By addressing unique challenges and complexities in healthcare settings, researchers can develop AI models that effectively improve clinical practice and patient outcomes

Clinical profile of patients with prosthetic heart valve thrombosis undergoing fibrinolytic therapy and NYHA class as a predictor of outcome

Background: Prosthetic heart valve thrombosis (PHVT) is a potentially fatal complication of heart valve replacement with mechanical prostheses mainly due to thrombosis.Aim: The study aimed to evaluate the clinical profile of the patients presenting with PHVT undergoing fibrinolytic therapy and analyzing patients with respect to New York Heart Association (NYHA) functional class on presentation and its association with outcome of fibrinolytic therapy.Settings & design: This was prospective, observational study conducted from June, 2016 to April, 2017. Total 133 patients with prosthetic heart valve thrombosis were included. Materials and methods: Routine blood investigations included complete hemogram, liver and renal function tests. Prothrombin time with INR was done on admission. The diagnosis of PHVT was assessed by fluoroscopy and/or echocardiography (transthoracic/transesophageal). Follow-up at 6 months was scheduled for all patients.Statistical analysis: Parametric values between two groups were performed using the independent sample t-test or chi-square test, as appropriate. Univariate and multivariate logistic regression was used to find out factors associated with outcome.Results: All patients received fibrinolytic therapy in which 108 (81.2%) were treated with streptokinase and 25 (18.8%) were treated with urokinase. On presentation, 48.9% patients were in NYHA class III, 41.4% in NYHA class IV and 9.77% in NYHA class II. Fibrinolytic therapy was successful in 105 patients (78.9%) and it failed in 28 patients (21.1%). Mortality in NYHA class II was 0%, NYHA class III was 4.6% and in NYHA class IV was 23.6%. During 6 months follow up prosthetic heart valve thrombosis recurred in 12 (11.43%) patients.Conclusion: From our single centre experience, fibrinolytic therapy is fairly effective first line therapy for prosthetic heart valve thrombosis and NYHA functional class on presentation can predict the outcome of fibrinolytic therapy

Formulation and Evaluation of Cefotaxime Sodium Loaded Emulgel for Topical Bacterial Infections

The bacterial infections are very common and become a serious issue like in case of infections of one and more reproductive organ, inflammation on protective membrane of brain and spinal cord, inflammation of lungs air sacs, body drainage system infections, problem in body’s extreme response and infection caused by sexually transmitted bacteria in male and female. Generally, these bacterial infections are treated by using antibiotics like cefotaxime that is a semisynthetic, β-lactamase resistant, third-generation broad-spectrum cephalosporin. The common side effects of cefotaxime are uneasiness of stomach before vomiting, sneezing, itching. The topical antibacterial dosage forms like creams, gel, and ointment have some demerits and low duration of drug release. The emulgel is an alternative for topical drug delivery with several merits like enhanced skin penetration and improved bioavailability, reduced dosing, improved patient acceptability with targeted drug delivery, freedom of termination of the therapy at any time, drug delivery in controlled fashion for prolong duration. The aim of study was to develop a biphasic promising drug delivery system emulgel of cefotaxime. The 23 experimental design was used to prepare various emulgel batches to determinant the effect of liquid paraffin, span 20 and tween 20 on the performance of emulgel. The Batch F1 showed the maximum drug release while batch F8 up to 240 minutes. The drug release kinetics study of Batch F8 showed the Higuchi-Matrix as a best fit model and the Fickian Diffusion as a mechanism of drug release with R2 value 0.9158 and K value 8.4741

Mapping interindividual dynamics of innate immune response at single-cell resolution

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells. This approach identified 1,275 expression quantitative trait loci (local false discovery rate 10%) that manifested during the responses, many of which were colocalized with susceptibility loci identified by genome-wide association studies of infectious and autoimmune diseases, including the OAS1 splicing quantitative trait locus in a COVID-19 susceptibility locus. In summary, our analytical approach provides a unique framework for delineation of the genetic variants that shape a wide spectrum of transcriptional responses at single-cell resolution

Common genetic variation drives molecular heterogeneity in human iPSCs.

Technology utilizing human induced pluripotent stem cells (iPS cells) has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterization of many existing iPS cell lines limits their potential use for research and therapy. Here we describe the systematic generation, genotyping and phenotyping of 711 iPS cell lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative. Our study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPS cell phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of genomic copy-number alterations that are repeatedly observed in iPS cells. In addition, we present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells