40 resultados para lab

em Indian Institute of Science - Bangalore - Índia


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The field bean (Dolichos lab lab ; Tamil name, Mochai ; Kanarese, Avarai) is a legume which is widely cultivated in South India often as a mixed crop with cereals. The kernel of the seed enters into the diet of may South Indian households, and in the Mysore State the seed are used as a delicacy when they are green for over four months in the year. The haulm, husk and pods are commonly used a fodder. As the kernel which is widely used as an article of food and considered to be very nutritious, contains about 24% of protein hitherto uninvestigated and as the quality of protein plays an important role in nutrition, the present work was undertaken.

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Chemically modified microporous materials can be prepared as robust catalysts suitable for application in vapor phase processes such as Friedel-Crafts alkylation. In the present paper we have investigated the use of rare earth metal (Ce3+, La3+, RE3+, and Sm3+) exchanged Na-Y zeolites as catalysts for the alkylation of benzene with long chain linear 1-olefin; 1-dodecene. Thermodesorption studies of 2,6-dimethylpyridine adsorbed catalysts (in the temperature range 573 to 873 K) show that the rare earth zeolites are highly Bronsted acidic in nature. A perfect correlation between catalyst selectivity towards the desired product (2-phenyldodecane) and Bronsted acid sites amount has been observed. (c) 2006 Springer Science + Business Media, Inc.

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The complete amino acid sequence of two non identical subunits of the glucose/mannose-specific lectin from Dolichos lab lab (field bean) has been determined by sequential Edman analyses of the intact subunits and peptides derived by enzymatic and chemical cleavage. Peptides were purified by reverse phase high performance liquid chromatography and ion pair chromatography. The D. lab lab lectin is a glycoprotein having two polypeptide chains of 132 and 105 amino acid residues. The amino acid sequence of the D. Lab lab lectin is compared with the various lectins of the family Leguminosae. The D. lab lab lectin is the only species of the tribe Phaseoleae that contains two nonidentical subunits of almost equal size and that shows a specificity to glucose/ mannose. The lectin shows a greater homology to the glucose/mannose specific lectins, especially concanavalin A. The unique subunit architecture of the D. lab lab lectin indicates the presence of new post translational cleavage sites.

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Sensitivity analysis is an important aspect to be looked into while designing lab-on-a-chip systems. In this paper we will be showing with appropriate design that the best sensitivity of the fluorescence biosensor is achieved for an optimal width of fluidic gap, corresponding to a particular mode spot size. We will be also showing that the sensitivity of the biosensor is affected by efficiency of light coupling, which is influenced by changes in the width of fluidic gap, refractive index of the fluid and higher order modes.

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In this paper we will be presenting the effect of fluidic gap, the effect of change of refractive index of the fluid contained in the gap, and the effect of higher order modes on the efficiency of light coupling and thus on the on the sensitivity of the sensor.

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In this paper we will be presenting the effect of fluidic gap, the effect of change of refractive index of the fluid contained in the gap, and the effect of higher order modes on the efficiency of light coupling and thus on the on the sensitivity of the sensor.

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The analysis of a fully integrated optofluidic lab-on-a-chip sensor is presented in this paper. This device is comprised of collinear input and output waveguides that are separated by a microfluidic channel. When light is passed through the analyte contained in the fluidic gap, optical power loss occurs owing to absorption of light. Apart from absorption, a mode-mismatch between the input and output waveguides occurs when the light propagates through the fluidic gap. The degree of mode-mismatch and quantum of optical power loss due to absorption of light by the fluid form the basis of our analysis. This sensor can detect changes in refractive index and changes in concentration of species contained in the analyte. The sensitivity to detect minute changes depends on many parameters. The parameters that influence the sensitivity of the sensor are mode spot size, refractive index of the fluid, molar concentration of the species contained in the analyte, width of the fluidic gap, and waveguide geometry. By correlating various parameters, an optimal fluidic gap distance corresponding to a particular mode spot size that achieves the best sensitivity is determined both for refractive index and absorbance-based sensing.

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Single pulse shock tube facility has been developed in the High Temperature Chemical Kinetics Lab, Aerospace Engineering Department, to carry out ignition delay studies and spectroscopic investigations of hydrocarbon fuels. Our main emphasis is on measuring ignition delay through pressure rise and by monitoring CH emission for various jet fuels and finding suitable additives for reducing the delay. Initially the shock tube was tested and calibrated by measuring the ignition delay of C2H6-O2 mixture. The results are in good agreement with earlier published works. Ignition times of exo-tetrahdyrodicyclopentadiene (C10H16), which is a leading candidate fuel for scramjet propulsion has been studied in the reflected shock region in the temperature range 1250 - 1750 K with and without adding Triethylamine (TEA). Addition of TEA results in substantial reduction of ignition delay of C10H16.

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The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

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The problem of automatic melody line identification in a MIDI file plays an important role towards taking QBH systems to the next level. We present here, a novel algorithm to identify the melody line in a polyphonic MIDI file. A note pruning and track/channel ranking method is used to identify the melody line. We use results from musicology to derive certain simple heuristics for the note pruning stage. This helps in the robustness of the algorithm, by way of discarding "spurious" notes. A ranking based on the melodic information in each track/channel enables us to choose the melody line accurately. Our algorithm makes no assumption about MIDI performer specific parameters, is simple and achieves an accuracy of 97% in identifying the melody line correctly. This algorithm is currently being used by us in a QBH system built in our lab.

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DNA amplification using Polymerase Chain Reaction (PCR) in a small volume is used in Lab-on-a-chip systems involving DNA manipulation. For few microliters of volume of liquid, it becomes difficult to measure and monitor the thermal profile accurately and reproducibly, which is an essential requirement for successful amplification. Conventional temperature sensors are either not biocompatible or too large and hence positioned away from the liquid leading to calibration errors. In this work we present a fluorescence based detection technique that is completely biocompatible and measures directly the liquid temperature. PCR is demonstrated in a 3 ILL silicon-glass microfabricated device using non-contact induction heating whose temperature is controlled using fluorescence feedback from SYBR green I dye molecules intercalated within sensor DNA. The performance is compared with temperature feedback using a thermocouple sensor. Melting curve followed by gel electrophoresis is used to confirm product specificity after the PCR cycles. (c) 2007 Elsevier B.V. All rights reserved.

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Background: Trypanosoma evansi infections, commonly called 'surra', cause significant economic losses to livestock industry. While this infection is mainly restricted to large animals such as camels, donkeys and equines, recent reports indicate their ability to infect humans. There are no World Animal Health Organization (WAHO) prescribed diagnostic tests or vaccines available against this disease and the available drugs show significant toxicity. There is an urgent need to develop improved methods of diagnosis and control measures for this disease. Unlike its related human parasites T. brucei and T. cruzi whose genomes have been fully sequenced T. evansi genome sequence remains unavailable and very little efforts are being made to develop improved methods of prevention, diagnosis and treatment. With a view to identify potential diagnostic markers and drug targets we have studied the clinical proteome of T. evansi infection using mass spectrometry (MS).Methodology/Principal Findings: Using shot-gun proteomic approach involving nano-lc Quadrupole Time Of Flight (QTOF) mass spectrometry we have identified over 160 proteins expressed by T. evansi in mice infected with camel isolate. Homology driven searches for protein identification from MS/MS data led to most of the matches arising from related Trypanosoma species. Proteins identified belonged to various functional categories including metabolic enzymes; DNA metabolism; transcription; translation as well as cell-cell communication and signal transduction. TCA cycle enzymes were strikingly missing, possibly suggesting their low abundances. The clinical proteome revealed the presence of known and potential drug targets such as oligopeptidases, kinases, cysteine proteases and more.Conclusions/Significance: Previous proteomic studies on Trypanosomal infections, including human parasites T. brucei and T. cruzi, have been carried out from lab grown cultures. For T. evansi infection this is indeed the first ever proteomic study reported thus far. In addition to providing a glimpse into the biology of this neglected disease, our study is the first step towards identification of diagnostic biomarkers, novel drug targets as well as potential vaccine candidates to fight against T. evansi infections.

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We propose a simple speech music discriminator that uses features based on HILN(Harmonics, Individual Lines and Noise) model. We have been able to test the strength of the feature set on a standard database of 66 files and get an accuracy of around 97%. We also have tested on sung queries and polyphonic music and have got very good results. The current algorithm is being used to discriminate between sung queries and played (using an instrument like flute) queries for a Query by Humming(QBH) system currently under development in the lab.

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We report novel results obtained for the Hubbard and t-J models by various mean-field approximations.

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In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.