Ramchander Merugu

Influence of different cultural conditions on photoproduction of hydrogen by Rhodopseudomonas palustris KU003.

Photoproduction of hydrogen by Rhodopseudomonas palustris KU003 under different cultural conditions with various carbon and nitrogen sources was investigated. Hydrogen production was measured using a Gas chromatograph. Malate promoted more amounts of hydrogen production under anaerobic light conditions than anaerobic dark conditions. Cumulative hydrogen production by the organism was recorded at various time intervals. Incubation period of 120 hrs was optimum for production of hydrogen. pH 7.0±0.4 was optimum for production of hydrogen. L-glutamic acid was a good nitrogen source for production of hydrogen. Growing cells produced more amount of hydrogen than resting cells. Significance of the above results in presence of existing literature is discussed.

New icetexane diterpenes with intestinal α-glucosidase inhibitory and free-radical scavenging activity isolated from Premna tomentosa roots

New icetexane diterpenes (1-2); 8, 11, 13-icetexatriene-10-hydroxy, 11, 12, 16-tri acetoxyl (1) and 8, 11, 13-icetexatriene-7, 10, 11-dihydroxy-12, 13-dihydrofuran (2) along with six known compounds namely acetoxy syranzaldehyde (3), syranzaldehyde (4), coniferaldehyde (5), lupeol (6), betulin (7), and 4-(4-methoxy phenyl)-2-butanone (8) were isolated from the roots of Premna tomentosa. The structures of compounds 1 and 2 were established by detailed spectral analysis using UV, IR, (1)H NMR, (13)C NMR, 1D, 2D and Mass. The newly isolated compounds were screened for rat intestinal α-glucosidase inhibitory and free radical (DPPH) scavenging potentiality. The new icetexane diterpenes (1, 2) and compound 3 were found to have significant α-glucosidase inhibitory and also free radical scavenging (DPPH) activities.

MICRO WAVE ASSISTED GREEN SYNTHESIS OF SILVER NANOPARTICLES USING BOSWELL IA SERRATA FLOWER EXTRACT AND EVALUATION OF THEIR ANTIMICROBIAL ACTIVITY

In the present investigation , we describe a cost effective green synthesis of silver nanoparticles from the extract of Boswellia serrata flow er as reducing agent. The formed s ilver nanoparticles were characterized using UV – Vis absorption spectroscopy, Fourier Transfer Infra Red and Scanning Electron Microscope (SEM). The functional group responsible for Ag 0 reduction was found to be alkanoid compounds from FTIR. The SEM analysi s showed the size of nanoparticles to be between 60 - 84 nm. Antimicrobial activity of the formed nanoparticles exhibited maximum activity against gram negative bacteria than gram positive bacte ria. This is for the first report on the use of Boswellia s errat a flower for the synthesis of silver nanoparticles .

Photoproduction of Hydrogen under Different Cultural Conditions by Alginate Immobilized Rhodopsedomonas palustris KU003

Rhodopsedomonas palustris KU003 was immobilized in alginate and its hydrogen producing abilities were assessed. Maximum hydrogen production took place between 120 and 144 hrs in most carbon sources. Alginate immobilization induced higher amount of hydrogen in malate-, lactate-, and succinate-containing medium in Rps. palustris. Incubation period of 120 hrs was optimum for production of hydrogen. pH 7.0±0.4 was optimum for production of hydrogen. L-glutamic acid was a good nitrogen source for production of hydrogen. Glucose and sorbitol were poorer substrates as they induced only limited amount of hydrogen. Anaerobic light induced comparatively more amount of hydrogen in the bacteria under investigation than in anaerobic dark. Thiourea was a poor nitrogen source for the production of hydrogen by Rps. palustris. Results of the above are discussed in the light of existing literature in this communication.

Protein Sequence Structure Prediction Using Artificial Intelligent Techniques

Predicting structure of the protein is one of the most significant application of modern computational biology. Researchers are working on this field for so many years and have been tried various approaches for getting a good accuracy for the prediction task. With advent of artificial intelligence techniques researchers have started to focus on using machine learning algorithms for the task of protein structure prediction. Also AI techniques provides much better accuracy as compare to traditional methods used previously for protein structure prediction. Here we have been surveyed research work done by the researchers for predicting protein structure using AI techniques. We have been studied top most highly cited articles published in this field and derived a complete summery report regarding the application of AI techniques in protein structure prediction.

Forecasting Stock Market Movements Using Various Kernel Functions in Support Vector Machine

In stock market forecasting achieving good prediction accuracy is always been a highly challenging task for researchers and financial analyst. Forecasting stock market needs to deal with the most volatile, non-parametric and nonlinear data sets. Also there are various factors that may affect the growth of stock market. So in order to make a good stock market forecasting system we need to use all the parameters that may affect the market volatility. Support Vectors Machine (SVM) have been found to be one of most efficient machine learning algorithm in modeling stock market prices and movements. Researchers are using these classification algorithms for so many years and have got a good predictive accuracy. Here in our research we have used SVM algorithm to making prediction for CNX NIFTY index value. In our experiment we have compared prediction accuracy for various Kernel Types of SVM.

Effect of levamisole on alkaline phosphatase activity and immunoglobulin secretion of lipopolysaccharide-stimulated murine splenic lymphocytes

Background: Alkaline phosphatases (APase) are a group of enzymes whose activity increases above normal levels in conditions of diseases such as cancer. In the present study, the role of APase using mitogen-stimulated murine lymphocytes was investigated. Methods: U266B1 cells and RPMI 8226 cultures were kept at 37°C in a humidified incubator with 5% CO2. The cultures were pulsed with 0.5 μCi of 3H-thymidine and were harvested onto glass fiber filter using Skatron automatic cell harvester. The dried filters were transferred into toluene-based scintillation cocktail, and the radioactivity was measured using Beckman scintillation counter. APase activity was determined by p-nitrophenol phosphate hydrolysis. The intracellular immunoglobulin E (IgE) content was quantified by western blot assay. U266 B1 and RPMI 8226 were cultured at 0.25 × 106/ml with and without 1 mM levamisole for 48 h, and 15 ml of the culture supernatant was collected and lyophilized. Electrophoresis was carried out on 30 μl of the dialyzed samples. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was performed and the gels were silver stained. Results: APase may be involved in the constitutive proliferation as well as in Ig secretion of myeloma cells. It was observed that murine splenic lymphocytes showed an increase in proliferative response concomitant with an increase in the APase activity and Ig secretion upon mitogenic stimulation (0.5–2.5 mM, P > 0.05). Conclusion: Levamisole significantly inhibited the APase activity when added to the lipopolysaccharide-stimulated cells at the initiation of the culture. Significance of the present study is discussed in the light of existing literature.

Bioinformatics analysis and modelling of mycotoxin patulin induced proteins

A comparative in silico characterization of the patulin induced proteins has been carried out to analyze their physico-chemical, secondary structural and functional properties. The amino acid composition of patulin induced proteins obtained from biological databases. The composition of leucine, alanine, glycine and proline was high while low concentrations of glutamic acid and histidine residues were seen when compared to other aminoacids. The number of negative and positively charges are comparatively similar. pI value of Hyp was the highest when compared to the other two patulin induced proteins. The instability index of all the proteins was more than 40 showing that all of them are unstable. Aliphatic index shows the “relative volume of protein occupied by aliphatic side chains” which was found to be within a range of 65 to 100. Flr1P is transmembrane in nature while the other two are soluble proteins.