ANTIHYPERGLYCEMIC AND ANTIDYSLIPIDEMIC POTENTIAL OF IPOMOEA BATATAS LEAVES IN VALIDATED DIABETIC ANIMAL MODELS

Objective: The present study was undertaken to investigate the antidiabetic potential of the leaves of Ipomoea batatas.Methods: The crude powder, 95% ethanolic, 50% ethanolic and aqueous extracts of Ipomoea batatas leaves were administered to normoglycemic and streptozotocin (STZ)-induced diabetic rats in a single dose study. The chloroform, butanol and aqueous fractions of aqueous extract were investigated for their antihyperglycemic on STZ-induced diabetic rats. Multiple dose study of an aqueous fraction was also done in STZ and neonatal STZ-induced diabetic rats. Further, the aqueous fraction was measured against the alpha glucosidase and aldose reductase enzymes, and glucose uptake in L6 myotubes.Results: The aqueous extract showed significant lowering of postprandial hyperglycemia of post sucrose loaded normal rats and significantly declined the blood glucose level of STZ-induced diabetic rats. The aqueous fraction at a single dose of 100 mg/kg b. w in comparison with chloroform and butanol fractions significantly lowered the blood glucose level of STZ-induced diabetic rats. The aqueous fraction in a multiple dose study were found to significantly improved the percent glycated hemoglobin (%HbA1c), fasting blood glucose, oral glucose tolerance (OGTT), serum insulin, lipid profile, liver and kidney parameters in STZ-induced diabetic rats. Marked improvement in OGTT and serum insulin levels was also found in neonatal STZ-induced diabetic rats. In vitro study, the aqueous fraction of I. batatas increased glucose uptake in L6 myotubes and inhibits the α-glucosidase and aldose reductase enzymes.Conclusion: The present study demonstrated the significant antidiabetic activity of the I. batatas leaves by promoting insulin secretion, alpha glucosidase and aldose reductase enzyme inhibition.Â

miR-135a targets IRS2 and regulates insulin signaling and glucose uptake in the diabetic gastrocnemius skeletal muscle

AbstractAlthough aberrant miRNA signatures are associated with diabetes, yet, the status and role of altered miRNAs in the diabetic skeletal muscle is currently poorly understood. Here, we report that 41 miRNAs are altered in the diabetic gastrocnemius skeletal muscle and of these, miR-135a that is identified as a critical regulator of myogenesis, is significantly up-regulated. IRS2 is predicted as its potential putative target and its levels are down-regulated in the diabetic gastrocnemius skeletal muscle. In C2C12 cells, while miR-135a levels decreased during differentiation, IRS2 levels were up-regulated. miR-135a significantly reduced IRS2 protein levels and its 3′UTR luciferase reporter activity and these were blunted by the miR-135a inhibitor and mutation in the miR-135a binding site. Knock-down of endogenous miR-135a levels increased IRS2 at the mRNA and protein levels. miR-135a also attenuated insulin stimulated phosphorylation and activation of PI3Kp85α and Akt and glucose uptake. miR-135a levels were also found to be elevated in the human diabetic skeletal muscle. In-vivo silencing of miR-135a alleviated hyperglycemia, improved glucose tolerance and significantly restored the levels of IRS2 and p-Akt in the gastrocnemius skeletal muscle of db/db mice without any effect on their hepatic levels. These suggest that miR-135a targets IRS2 levels by binding to its 3′UTR and this interaction regulates skeletal muscle insulin signaling

Factors Affecting the Productivity of Coffee in Gulmi and Arghakhanchi Districts of Nepal

Coffee is one of the major potential cash crops with lucrative export value grown in mid-hills of Nepal. Nepalese coffee production has suffered long by low productivity. Research was conducted from February to May, 2019 to analyze the factors affecting the productivity of coffee in Arghakhanchi and Gulmi districts of Nepal. These two districts were, purposively selected for this study taking account of comparative advantage and past studies recommendations for coffee sector. Altogether, 100 coffee growing households 50 from each, Arghakhanchi and Gulmi, were sampled by using multistage sampling technique. A pre-tested semi-structured interview schedule was used to collect the primary information while secondary information was collected reviewing the relevant publications. Ordinary Least Square (OLS) regression model was used to determine the factors affecting the productivity of coffee. The study revealed that the number of active family members involved in coffee production (0.000), adoption of income diversification through intercropping (0.005), training (0.072) and technical assistance (0.021) had positive and significant effect on coffee productivity. Encouraging the household to have coffee production as their primary occupation, providing technical assistance on rational land utilization and intercropping and strengthening the skill and knowledge of farmers through trainings could significantly support in increasing the productivity of coffee

The DNA-binding domain of Drosophila melanogaster c-Myb undergoes a multistate denaturation

The DNA-binding domain of Drosophila c-Myb protein has been studied using different spectroscopic probes, namely CD, fluorescence, acrylamide quenching and NMR, to determione the structure of some of its sub-domains and their relative stabilities in aqueous solutions. While CD and fluorescence spectroscopy showed that the protein had completely lost its tertiary and secondary structures in approximately 3 M urea, solvent accessibility of the tryptophan residues was still partial, as determined by acrylamide quenching. This suggested the presence of significant amounts of residual structure which persisted until the urea concentration was raised to approximately 6.0 M. Thermal-denaturation experiments also indicated the presence of an intermediate in the unfolding pathway. The experimental data could be fitted assuming a minimum of three states in both modes of denaturation. The thermodynamic parameters for the apparent three-state transition have been determined. From the protein stability curve, we have determined that Drosophila melanogaster Myb R123 has maximal stability at 16°C and pH 7.0

Synthesis and biological evaluation of thiazolidinedione derivatives of chalcones and flavones as antihyperglycemic and antidyslipidemic agents

A series of chalcone and flavone derivatives (6a-d, 9a-f) based on 2,4-thiazolidinedione have been synthesized and evaluated for in vivo antihyperglycemic activity in sucrose loaded (SLM) and streptozotocin (STZ) induced diabetic animal models and also for antidyslipidemic activity in the triton model. Compounds 9d, 9e, and 9f exhibited potent blood glucose-lowering activity in both SLM and STZ models. Compounds 6c, 6d, and 9c, 9e, and 9f showed moderate lipid-lowering activity. The selected most potent compounds 6d and 9e were also studied in db/db mice for both antihyperglycemic and antidyslipidemic activity

Synthesis and biological evaluation of thiazolidinedione derivatives of chalcones and flavones as antihyperglycemic and antidyslipidemic agents

579-588A series of chalcone and flavone derivatives (6a-d, 9a-f) based on 2,4-thiazolidinedione have been synthesized and evaluated for in vivo antihyperglycemic activity in sucrose loaded (SLM) and streptozotocin (STZ) induced diabetic animal models and also for antidyslipidemic activity in the triton model. Compounds 9d, 9e, and 9f exhibited potent blood glucose-lowering activity in both SLM and STZ models. Compounds 6c, 6d, and 9c, 9e, and 9f showed moderate lipid-lowering activity. The selected most potent compounds 6d and 9e were also studied in db/db mice for both antihyperglycemic and antidyslipidemic activity

Biotransformation of artemisinin mediated through fungal strains for obtaining derivatives with novel activities

Artemisinin, a sesquiterpene lactone, is the active antimalarial constituent of Artemisia annua. Several fungal strains Saccharomyces cerevisiae, Aspergillus flavus, Aspergillus niger and Picchia pastoris were used to biotransform artemisinin. Among these strains, A. flavus was the only microorganism capable of transforming artemisinin to deoxyartemisinin in higher yields than the previous reports. The structure of deoxyartemisinin was elucidated by spectroscopy. Deoxyartemisinin showed antibacterial activity against Staphylococcus aureus, S. epidermidis and S. mutans at a minimum inhibitory concentration (MIC) of 1 mg/mL compared to artemisinin whose MIC was >2 mg/mL

Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approach involves selecting a smaller set of relevant sensor signals using feature selection and using them to train a machine learning algorithm. However, this fails to address two prominent problems: (1) sensors are susceptible to failure when exposed to extreme conditions over a long periods of time; (2) sensors are electrical devices that can be affected by noise or electrical interference. Using the failed and noisy sensor signals as inputs largely reduce the prediction accuracy. To tackle this problem, it is advantageous to use the information from all sensor signals, so that the failure of one sensor can be compensated by another. In this work, we propose an Artificial Neural Network (ANN) based framework to exploit the information from a large number of signals. Secondly, our framework introduces a data augmentation approach to perform accurate predictions in spite of noisy signals. The plausibility of our framework is validated on real life industrial application from Robert Bosch GmbH.Comment: 16 pages, 7 figures. Currently under review. This research has obtained funding from the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-