BIOCHEMICAL EVALUATION OF ANTIDIABETIC PROPERTIES OF SWERTIAMARIN, A SECOIRIDOID GLYCOSIDE OF ENICOSTEMMA LITTORALE LEAVES, STUDIED IN HIGH-FAT DIET–FED LOW-DOSE STREPTOZOTOCIN-INDUCED TYPE 2 DIABETIC RATS

Objective: Swertiamarin, a secoiridoid glycoside present in the leaves of Enicostemma littorale, is reported to be responsible for its pharmacological and beneficial properties. The present study was aimed to biochemically evaluate the antidiabetic properties of Swertiamarin in high fat diet fed - low dose streptozotocin (STZ)-treated diabetic rats.Methods: High-fat diet-fed low-dose STZ was used to induce experimental type 2 diabetes in rats. Diabetic rats were orally treated with swertiamarin (50 mg/kg b.w./rat/day) for 30 days. The physiological criterions such as food and fluid intake were recorded. Oral glucose tolerance test was performed. The levels of fasting blood glucose, plasma insulin, glycosylated hemoglobin A1c (HbA1c), hemoglobin, and homeostasis model assessment of insulin resistance (HOMA-IR) values were estimated. The activities of key enzymes involved in carbohydrate and glycogen metabolism in the liver and kidney tissues were assayed. The glycogen content in liver tissue was estimated.Result: Oral administration of swertiamarin to diabetic rats established a significant decline in the levels of fasting blood glucose, HbA1c as well as HOMA-IR values and an increase in plasma insulin and hemoglobin levels. The altered activities of key enzymes of carbohydrate and glycogen metabolism in liver and kidney tissues of diabetic rats were restored to near normalcy by swertiamarin treatment.Conclusion: Swertiamarin treatment maintains normoglycemia in diabetic rats by modulating the activities of key carbohydrate and glycogen metabolizing enzymes in the hepatic and renal tissues

Brain Tumor Prediction using Adaptive Connected Component based GLCM and SVM Method

A crucial stage in the diagnosis of brain disorders using magnetic resonance images is feature extraction. The feature extraction procedure is used to reduce the amount of the picture data by removing the necessary information from the segmented image. The segmentation strategy and features that are extracted have an impact on the classification algorithm's dependability. With the aid of a Support Vector Machine, texture features are retrieved in this study using a Grey Level Co-occurrence Matrix, while form features are extracted using connected areas. Images of benign tumours, malignant tumours, and a normal brain all exhibit distinctive features. The classification of MR images can benefit from this change in feature values. A SVM classifier will receive the features that were thusly obtained for training and testing and further able to classify the abnormalities in brain images

Securing Heterogeneous Privacy Protection in Social Network Records based Encryption Scheme

This survey places of interest the major issues concerning privacy and security in online social networks. Firstly, we discuss investigate that aims to protect user data from the an assortment of attack vantage points together with other users, advertisers, third party request developers, and the online social arrangement provider itself. Next we cover social network supposition of user attributes, locate hubs, and link prediction. Because online social networks are so saturated with sensitive information, network inference plays a major privacy role. Social Networking sites go upwards since of all these reasons. In recent years indicates that for many people they are now the mainstream communication knowledge. Social networking sites come under few of the most frequently browsed categories websites in the world. Nevertheless Social Networking sites are also vulnerable to various problems threats and attacks such as revelation of information, identity thefts etc. Privacy practice in social networking sites often appear convoluted as in sequence sharing stands in discord with the need to reduce disclosure-related abuses. Facebook is one such most popular and widely used Social Networking sites which have its own healthy set of Privacy policy

Performance Evaluation Of Thermally Activated Glass Fibre Reinforced Gypsum Building Equipped With Desiccant System

According to International Energy Outlook 2017, the energy consumption of the building sector is expected to increase by 32% from 2015 to 2040. This is due to the accelerating demand for mechanical air conditioning system for maintaining the indoor comfort conditions and high embodied energy of the conventional building materials. Many solutions are proposed globally to address these problems. Thermally Activated Building System (TABS) is one such energy efficient alternative to the conventional mechanical air conditioning system for providing the desirable indoor comfort conditions. In TABS, copper pipes are embedded in its building structures namely ceiling, floor and walls. Chilled water circulated in the copper pipes cools the building structures which in turn cool the indoor environment by radiative and convective heat exchange methods. However, the TABS handles only the sensible load. Therefore, a solid desiccant system is used along with TABS for maintaining the desired indoor humidity. Glass Fibre Reinforced Gypsum (GFRG) is used as a building material which is made up of reinforced glass and gypsum. It is used in the present study due to its low embodied energy. The combination of TABS and GFRG building is named as Thermally Activated Glass Fibre Reinforced Gypsum (TAGFRG) building. Ventilation rate of the proposed TAGFRG is maintained according to the standards prescribed by ASHRAE. To appreciate the energy saving potential and feasibility of TAGFRG building, its thermal performance is compared with that of the conventional concrete building. Both TAGFRG and conventional concrete building are constructed with the same dimensions (1m (L) x 1m (B) x 1m (H)) for such comparison. The present study analyses the influence of various operating parameters on the performance of the proposed TAGFRG. The operating parameters considered are cooling water temperature, cooling surfaces and air velocity. The performance parameters used to evaluate the indoor thermal comfort of the proposed TAGFRG are indoor temperature and humidity, Predicted Percentage Dissatisfied (PPD) and Predicted Mean Vote (PMV). The decrease in supply water temperature and increase in radiant surface area, increase the thermal comfort level of the indoor. The results of the present study will be useful for predicting the optimum design of proposed TAGFRG which has the potential to reduce the energy consumption and carbon emission of the building sector

Medicinal properties of some Dendrobium orchids – A review

 Orchids are known for their aesthetic qualities, and they are often used as decorative items in homes, offices, and public places. While most people admire them for their good looks, others have found practical uses for them. Since a long time ago, people from various parts of the world have used orchids for medicinal purposes. However, the use of orchids in medicine has declined over the years because not enough research has been done to determine their effectiveness and adverse effects

Mono- and bi-cyanoacrylic acid substituted phenothiazine based sensitizers for dye sensitized solar cells

Phenothiazine and cyanoacrylic acid moiety based sensitizers were synthesized for dye sensitized solar cell application. Absorption and electrochemical properties of the sensitizers having mono- and bi-substituted cyanoacrylic acids were studied. The mono-cyanoacrylic acid substituted phenothiazine sensitizer has more light harvesting ability due to its high molar extinction coefficient. The photovoltaic performance of mono-cyanoacrylic acid substituted phenothiazine sensitizer was slightly greater compared to the bi-cyanoacrylic acid substituted phenothiazine sensitizer which was attributed to the effect of anchoring groups in the sensitizer

Application of chemometric analysis to infrared spectroscopy for the identification of wood origin

Chemical characteristics of wood are used in this study for plant taxonomy classification based on the current Angiosperm Phylogeny Group classification (APG III System) for the division, class and subclass of woody plants. Infrared spectra contain information about the molecular structure and intermolecular interactions among the components in wood but the understanding of this information requires multivariate techniques for the analysis of highly dense datasets. This article is written with the purposes of specifying the chemical differences among taxonomic groups, and predicting the taxa of unknown samples with a mathematical model. Principal component analysis, t-test, stepwise discriminant analysis and linear discriminant analysis, were some of the chosen multivariate techniques. A procedure to determine the division, class, subclass and order of unknown samples was built with promising implications for future applications of Fourier Transform Infrared spectroscopy in wood taxonomy classification