A Study of Prevalence of Metabolic Syndrome in Young Patients with Acute Myocardial Infarction

BACKGROUND AND OBJECTIVES: The metabolic syndrome also called as syndrome X is a collection of metabolic abnormalities that confer a person with it to high danger of cardiovascular disease and diabetes. Aim of this study is to find the prevalence of metabolic syndrome in young patients with acute myocardial infarction and to find the prevalence of individual components of metabolic syndrome in the study population. MATERIALS AND METHODS: The present study is conducted on patients admitted with a diagnosis of AMI to the Coronary Care Unit (CCU) of Government Rajaji Hospital, Madurai during the period of February 2016 to July 2016. All patients admitted with a diagnosis of AMI to the Coronary Care Unit (CCU) of Government Rajaji Hospital with Age < 45 years are included in the study. Acute myocardial infarction is defined as at least two of the following: prolonged chest discomfort, typical electrocardiographic changes, or elevated cardiac troponin levels, as outlined by the Joint European Society of Cardiology/American College of Cardiology Committee. Patients with rheumatic heart disease, congenital heart disease, severe anemia/ chronic kidney and liver disease, cocaine abuse, lack of definitive mi criteria and age > 45 years are excluded from the study. Detailed demographic data and clinical examination is done. Blood pressure, fasting blood sugar and fasting lipid profile is done in all patients. Patients were classified as having metabolic syndrome according to the international diabetes federation (IDF) criteria. RESULTS AND INTERPRETATION: A total of about sixty two patients were studied, of which 35 (56%) of the patients fulfilled the criteria for metabolic syndrome. Remaining patients with age 80 for female and > 90 for males is the mandatory criteria to diagnose metabolic syndrome according to IDF criteria. In our study 42 patients had increased waist circumference of which 35 patients satisfied the remaining criteria for metabolic syndrome. Of the 27 patients without MS, 7 patients (26%) had increased waist circumference. Elevated blood pressure is present in about 71% (n=25) of the patients with metabolic syndrome and 40% (n=11) of patients without metabolic syndrome. Elevated fasting blood sugar >100mg/dl is present in about 88% of patients with metabolic syndrome and 28% of patients without metabolic syndrome. Increased levels of fasting triglyceride is seen in about 77 % (n=27) of patients with metabolic syndrome and 70% (n=19) of the patients without metabolic syndrome. Decreased HDL in seen in about 66% (n=23) of patients with metabolic syndrome and 55% (n=15) of the patients without metabolic syndrome. CONCLUSION: Metabolic syndrome is highly prevalent in young patients with acute myocardial infarction. Each component of metabolic syndrome is an independent risk factor for cardiovascular and cerebrovascular disease. Increasing prevalence of myocardial infarction in young individuals is mainly due to increased in prevalence of metabolic syndrome

Text-Independent Automatic Dialect Recognition of Marathi Language using Spectro-Temporal Characteristics of Voice

Text-independent dialect recognition system is proposed in this paper for Marathi language. India is rich in language varieties. Each language in turn has its unique dialect variations. Maharashtra has Marathi as official language and for Goa it is a co-official language . In literature there are very few studies&nbsp; available for Indian language recognition and then their respective dialect recognition. So research work available&nbsp; for regional languages such as Marathi is extremely limited. As a part of research work, an attempt is made to generate a case study of a low resourced Marathi language dialect recognition system. The study was carried out using Marathi speech data corpus provided by Linguistic Data Consortium for Indian Language (LDC- IL). This corpus&nbsp; includes four major dialects of Marathi speakers. The efficiency and performance evaluation of the explored spectral (rhythmic) and temporal features are carried out to perform classification tasks. We investigated the performance of six different classifiers; K-nearest neighbor (KNN), Naïve Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT) classifier , Stochastic Gradient Descent (SGD) classifier and Ridge Classifier (RC). Experimental results have demonstrated that the RC classifier worked well with 84.24% of accuracy for fifteen spectral and temporal features. With twelve MFCCs it has been observed that SGD&nbsp; has outperformed among all classifiers with accuracy of 80.63%. For further study, a prominent feature subset as a part of dimensionality reduction&nbsp; has been identified using chi square, mutual information and ANOVA-f test. In this chi-square based feature extraction method has proven to be the best over over mutual information and ANOVA f-test

Computational binding mechanism of Mycobacterium tuberculosis UDP-NAG enolpyruvyl transferase (MurA) with inhibitors fosfomycin, cyclic disulfide analog RWJ-3981, pyrazolopyrimidine analog RWJ-110192, purine analog RWJ-140998, 5-sulfonoxy-anthranilic aci

Worldwide, tuberculosis (TB) remains the most frequent and important infectious disease causing morbidity and death. One-third of the world&#x27;s population is infected with Mycobacterium tuberculosis (Mtb), the etiologic agent of TB. In this context, TB is in the top three, with malaria and HIV being the leading causes of death from a single infectious agent, and about two million deaths are attributable to TB annually. The bacterial enzyme MurA catalyzes the transfer of enolpyruvate from phosphoenolpyruvate (PEP) to uridine diphospho-N-acetylglucosamine (UNAG), which is the first committed step of bacterial cell wall biosynthesis. In this work, 3D structural model of Mtb-MurA enzyme has been developed, for the first time, by homology modeling and molecular dynamics simulation techniques. The model provided clear insight in its structure features, i.e. substrate binding pocket, and common docking site. Multiple sequence alignment and 3D structure model provided the putative substrate binding pocket of Mtb-MurA with respect to E.coli MurA. This analysis was helpful in identifying the binding sites and molecular function of the MurA homologue. Molecular docking study was performed on this 3D structural model, using different classes of inhibitors like fosfomycin, cyclic disulfide analog RWJ-3981, pyrazolopyrimidine analog RWJ-110192, purine analog RWJ-140998, 5-sulfonoxy-anthranilic acid derivatives T6361, T6362 and the results showed that the 5-sulfonoxyanthranilic acid derivatives is showed best interaction compared with other inhibitor, taking in to this we also design a new efficient analogs of T6361 and T6362 which are showed even better interaction with Mtb-MurA than the parental5-sulfonoxy-anthranilic acid derivatives. Further the comparative molecular electrostatic potential and cavity depth analysis of Mtb-MurA suggested several important differences in its substrate and inhibitor binding pocket. Such differences could be exploited in the future for designing of a more specific inhibitor for Mtb-MurA enzym

Study of thyroid function in patients admitted in intensive care unit

Background: The thyroid gland produces two related hormones, tetraiodothyronine (T4) and triiodothyronine (T3) play a critical role in cell differentiation during development and maintain thermogenic and metabolic homeostasis in the adult. Critically ill patients have been defined as those that by dysfunction or failure of one or more organ system depend on survival from advanced instruments monitoring and therapy. The objective was to study the thyroid dysfunction in critically ill patients admitted in intensive care units and its relation to the mortality and severity of disease.Methods: This is a cross sectional study carried out in Dr. Pinnamaneni Siddhartha institute of medical sciences and research foundation, Chinoutpalli, Andhra Pradesh from 1st January 2022 to 30th September 2022 involving 100 patients. Patients of age above 18 years, both sexes, admitted to intensive care units with critical illness were analyzed and approved by institutional ethics committee of Dr. PSIMS and RF data were entered in MS-excel and analyzed in SPSS V22 software. Descriptive statistics, Mann-Whitney U test, logistic regression, ROC curves were applied. P values were reported for all statistical tests and a value of&lt;0.05 was considered to be significant.Results: Out of 100 critically ill patients out of which 17 patients had sepsis, 18 had acute renal failure, 19 patients had acute respiratory failure, 19 patients had diabetic ketoacidosis, 16 patients had congestive cardiac failure, and 11 patients had stroke and their correlation with t3 hormone decrement showed positive correlation.Conclusions: Thyroid profile can be used in predicting the mortality in ICU patients

Application of Soft Computing for the Prediction of Warpage of Plastic Injection

This paper deals with the development of accurate warpage prediction model for plastic injection molded parts using softcomputing tools namely, artificial neural networks and support vector machines. For training, validating and testing of thewarpage model, a number of MoldFlow (FE) analyses have been carried out using Taguchi’s orthogonal array in the designof experimental technique by considering the process parameters such as mold temperature, melt temperature, packing pressure,packing time and cooling time. The warpage values were found by analyses which were done by MoldFlow PlasticInsight (MPI) 5.0 software. The artificial neural network model and support vector machine regression model have beendeveloped using conjugate gradient learning algorithm and ANOVA kernel function respectively. The adequacy of the developedmodels is verified by using coefficient of determination. To judge the ability and efficiency of the models to predictthe warpage values absolute relative error has been used. The finite element results show, artificial neural network modelpredicts with high accuracy compared with support vector machine model

Optimizing the Temperature of Hot outlet Air of Vortex Tube using Taguchi Method.

AbstractVortex tube produces hot and cold streams from inlet pressurized gas. Though mainly used for spot cooling purposes, it may also be used for heating/pre-heating applications. In this work, the effect of - inlet air pressure, hot tube length, hot tube internal diameter, orifice diameter, and nozzle diameter, on hot-outlet air temperature is analyzed. Taguchi's parameter design approach is used to optimize the response. Above parameters are considered at three levels each. L-27 Orthogonal Array is used for experimentation with two replicates. From the ANOVA table, all the parameters considered are found to be statistically significant. Relevant graphs are drawn; optimum response value at optimal factor levels is predicted. Through confirmatory test, experimental results are validated