Meldonium: drug which brought disrepute to sport

World of sports have been rocked by doping scandals every now and then and World Anti-Doping Agency(WADA) has banned several offending drugs at different times to counter this menace. Meldonium is the recent addition to the long list of drugs banned by WADA to prevent its misuse among the athletes. Meldonium is a carnitine synthesis inhibitor and has been approved by some European countries for the management of cardiac diseases like angina pectoris and congestive cardiac failure. Apart from these, it has numerous other indications like bronchial asthma, bronchitis and retinopathies. It had also been used by athletes across the world because of its presumptive role in increasing the performance

Diagnosis of tubercular brain abscess through ocular manifestation

Central nervous system tuberculosis is a severe form of extra‑pulmonary tuberculosis. It mainly presents as meningitis or tuberculoma. Tubercular brain abscess (TBA) is a rare manifestation of tuberculosis in an immunocompetent patient. We report a case of TBA who presented to us due to the defective vision and headache.Keywords: Brain abscess, papilledema, tuberculosi

Effect of resveratrol on diabetic neuropathy in wistar albino rats

Background: Type 2 diabetes mellitus (DM) is a common chronic disease with increasing prevalence worldwide. Prolonged uncontrolled hyperglycemia, dyslipidemia are major risk factor for its complication like neuropathy. Since there is no definite treatment for diabetic neuropathy, this study aims to evaluate the effect of resveratrol on diabetic neuropathy in high fat diet with low dose streptozotocin induced type-2 DM model in wistar albino rats.Methods: First type 2 diabetic rat model was established. Wistar albino rats, fed with high-fat diet (HFD) rendered diabetic with streptozotocin, were divided into 6 groups, disease control (DC) treated with vehicle, standard control (SC) which received metformin, test groups treated with 5, 10, and 20 mg/kg b.w. of resveratrol and combination of half dose of metformin and resveratrol (10 mg/kg) (TC). A group of six normal animals served as normal control (NC), another six as HFD control. Fasting plasma glucose, lipid profile were measured one week after induction of diabetes. The animals were then treated orally for 2 weeks after which the same parameters were repeated. Behavioral biomarkers for neuropathy are measured in 4 weeks and 6 weeks of treatment. The in-vivo results were analyzed by one way ANOVA followed by Tukey’s multiple comparison test for biochemical parameters and Kruskal Wallis test followed by Dun’s multiple comparison test for behavioral biomarkers.Results: Increase in fasting plasma glucose (FPG), deranged lipid profile, increased neuropathy in DC compared to NC, HFD control while a significant decrease in FBG, improved pain behavior with SC, test groups (p<0.05) as compared to the DC group.Conclusions: Resveratrol prevents diabetic neuropathy

Effects of resveratrol on oxidative stress in high fat diet /streptozocin induced diabetic wistar albino rats

Background: Diabetes mellitus is a common chronic disease. One of the pathophysiology is found to be oxidative stress. This study aims to evaluate the effect of resveratrol on oxidative stress in high fat diet (HFD)/streptozotocin induced diabetic rats.Methods: Wistar albino rats, fed with HFD rendered diabetic with streptozotocin, were divided into 6 groups, namely the diabetic control treated with vehicle (DC), standard control which received metformin (SC), test groups treated with 5,10, and 20 mg/kg b.w. of resveratrol and combination of half dose of metformin and resveratrol (10 mg/kg)(TC). A group of six normal animals served as normal control (NC), another six as HFD control. Fasting blood glucose, lipid profile and serum MDA and SOD were measured one week after induction of diabetes. The animals were then treated orally for 2 weeks after which the same parameters were repeated. The in-vivo results were analysed by one way ANOVA followed by Tukey’s multiple comparison test.Results: The DC group demonstrated a increase in the fasting blood glucose compared to NC, HFD control while a significant decrease in the fasting blood glucose was observed with SC, Test groups (p<0.05) as compared to the DC group. TC showed a significant improvement in dyslipidemia compared to their baseline values (p<0.05). There was significant change in the serum MDA level and SOD activity.Conclusions: Resveratrol improves oxidative stress in diabetic rats

Machine learning for the classification of breast cancer tumor: a comparative analysis

The detection and diagnosis of Breast cancer at an early stage is a challenging task. With the increase in emerging technologies such as data mining tools, along with machine learning algorithms, new prospects in the medical field for automatic diagnosis have been developed, with which the prediction of a disease at an early stage is possible. Early detection of the disease may increase the survival rate of patients. The main purpose of the study was to predict breast cancer disease as benign or malignant by using supervised machine learning algorithms such as the K-nearest neighbor (K-NN), multilayer perceptron (MLP), and random forest (RF) and to compare their performance in terms of the accuracy, precision, F1 score, support, and AUC. The experimental results demonstrated that the MLP achieved a high prediction accuracy of 99.4%, followed by random forest (96.4%) and K-NN (76.3%). The diagnosis rates of the MLP, random forest and K-NN were 99.9%, 99.6%, and 73%, respectively. The study provides a clear idea of the accomplishments of classification algorithms in terms of their prediction ability, which can aid healthcare professionals in diagnosing chronic breast cancer efficiently

Energy Management Analysis of Residential Building Using ANN Techniques

  The process of limiting the amount of energy that is utilized is known as energy conservation. This can be accomplished by making more effective use of the energy that is available. As a result, there is a requirement for more effective management of the consumption of energy in buildings. It is essential to have an accurate load calculation for a residential building because the loads for heating and cooling add up a significant portion of the total building loads. In this study, the load analysis of the HVAC (Heating, Ventilation, and Air Conditioning) system in a residential building was carried out by taking into consideration three different neural networks. These networks are known as the feed forward network, the cascaded forward back propagation network, and the Elman back propagation network. During the process of conducting a load study of the heating and cooling loads on an HVAC system, performance measurements like MAE (mean absolute error), MSE (mean square error), MRE (mean relative error), and MAPE (mean absolute percentage error) are taken into consideration. It has been discovered that the cascaded forward back propagation method is the most effective method, with MAE, MSE, MRE, and MAPE values of 0.08, 0.0336, 0.0051, and 0.51% respectively for heating load and MAE, MSE, MRE, and MAPE values of 0.0975, 0.0406, 0.0053, and 0.53% respectively for cooling load

Diabetes Prediction: A Study of Various Classification based Data Mining Techniques

Data Mining is an integral part of KDD (Knowledge Discovery in Databases) process. It deals with discovering unknown patterns and knowledge hidden in data. Classification is a pivotal data mining technique with a very wide range of applications. Now a day’s diabetic has become a major disease which has almost crippled people across the globe. It is a medical condition that causes the metabolism to become dysfunctional and increases the blood sugar level in the body and it becomes a major concern for medical practitioner and people at large. An early diagnosis is the starting point for living well with diabetes. Classification Analysis on diabetic dataset is a part of this diagnosis process which can help to detect a diabetic patient from non-diabetic. In this paper classification algorithms are applied on the Pima Indian Diabetic Database which is collected from UCI Machine Learning Laboratory. Various classification algorithms which are Naïve Bayes Classifier, Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Support Vector Classifier and XGBoost Classifier are analyzed and compared based on the accuracy delivered by the models

ESMP: A high-throughput computational pipeline for mining SSR markers from ESTs

With the advent of high-throughput sequencing technology, sequences from many genomes are being deposited to public databases at a brisk rate. Open access to large amount of expressed sequence tag (EST) data in the public databases has provided a powerful platform for simple sequence repeat (SSR) development in species where sequence information is not available. SSRs are markers of choice for their high reproducibility, abundant polymorphism and high inter-specific transferability. The mining of SSRs from ESTs requires different high-throughput computational tools that need to be executed individually which are computationally intensive and time consuming. To reduce the time lag and to streamline the cumbersome process of SSR mining from ESTs, we have developed a user-friendly, web-based EST-SSR pipeline “EST-SSR-MARKER PIPELINE (ESMP)”. This pipeline integrates EST pre-processing, clustering, assembly and subsequently mining of SSRs from assembled EST sequences. The mining of SSRs from ESTs provides valuable information on the abundance of SSRs in ESTs and will facilitate the development of markers for genetic analysis and related applications such as marker-assisted breeding

Mining for SSRs and FDMs from expressed sequence tags of Camellia sinensis

Simple Sequence Repeats (SSRs) developed from Expressed Sequence Tags (ESTs), known as EST-SSRs are most widely used and potentially valuable source of gene based markers for their high levels of crosstaxon portability, rapid and less expensive development. The EST sequence information in the publicly available databases is increasing in a faster rate. The emerging computational approach provides a better alternative process of development of SSR markers from the ESTs than the conventional methods. In the present study, 12,851 EST sequences of Camellia sinensis, downloaded from National Center for Biotechnology Information (NCBI) were mined for the development of Microsatellites. 6148 (4779 singletons and 1369 contigs) non redundant EST sequences were found after preprocessing and assembly of these sequences using various computational tools. Out of total 3822.68 kb sequence examined, 1636 (26.61%) EST sequences containing 2371 SSRs were detected with a density of 1 SSR/1.61 kb leading to development of 245 primer pairs. These mined EST-SSR markers will help further in the study of variability, mapping, evolutionary relationship in Camellia sinensis. In addition, these developed SSRs can also be applied for various studies across species

TGF-β1 enhances cardiomyogenic differentiation of skeletal muscle-derived adult primitive cells

The optimal medium for cardiac differentiation of adult primitive cells remains to be established. We quantitatively compared the efficacy of IGF-1, dynorphin B, insulin, oxytocin, bFGF, and TGF-beta1 in inducing cardiomyogenic differentiation. Adult mouse skeletal muscle-derived Sca1+/CD45-/c-kit-/Thy-1+ (SM+) and Sca1-/CD45-/c-kit-/Thy-1+ (SM-) cells were cultured in basic medium (BM; DMEM, FBS, IGF-1, dynorphin B) alone and BM supplemented with insulin, oxytocin, bFGF, or TGF-beta1. Cardiac differentiation was evaluated by the expression of cardiac-specific markers at the mRNA (qRT-PCR) and protein (immunocytochemistry) levels. BM+TGF-beta1 upregulated mRNA expression of Nkx2.5 and GATA-4 after 4 days and Myl2 after 9 days. After 30 days, BM+TGF-beta1 induced the greatest extent of cardiac differentiation (by morphology and expression of cardiac markers) in SM- cells. We conclude that TGF-beta1 enhances cardiomyogenic differentiation in skeletal muscle-derived adult primitive cells. This strategy may be utilized to induce cardiac differentiation as well as to examine the cardiomyogenic potential of adult tissue-derived stem/progenitor cells