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Sanjay Ghosh

Bio: Sanjay Ghosh is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Bilateral filter & Normalized Difference Vegetation Index. The author has an hindex of 30, co-authored 196 publications receiving 3079 citations. Previous affiliations of Sanjay Ghosh include Indian Institutes of Technology & University of Cambridge.


Papers
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Journal ArticleDOI
TL;DR: It is proposed that cav-1 binding to eNOS reductase compromises its ability to bind CaM and to donate electrons to the eN OS heme, thereby inhibiting NO synthesis.

152 citations

Journal ArticleDOI
TL;DR: The present work reports for the first time, the alkali stable cellulase from alkali tolerant fungus Penicillium citrinum, which may have potential effectiveness as additives to laundry detergents.
Abstract: The enzymatic hydrolysis of cellulose has potential economical and environment-friendly applications. Therefore, discovery of new extremophilic cellulases is essential to meet the requirements of industry. Penicillium citrinum (MTCC 6489) that was previously isolated from soil in our laboratory, produced alkali tolerant and thermostable cellulases. Endoglucanase and filter paper activity hydrolase (FPAse) production of P. citrinum were studied using wheat bran substrate in solid state and submerged culture. Zymogram analysis of endoglucanase revealed the presence of two isoforms differing in molecular weight. One of them was 90 kDa and other one was 38 kDa. Partially purified endoglucanase showed two different peaks at pH 5.5 and 8.0, respectively, in its pH optima curve. But FPase showed only one peak (at pH 6.5) in its pH optima curve. Cellulase of P. citrinum is thermostable in nature. The present work reports for the first time, the alkali stable cellulase from alkali tolerant fungus Penicillium citrinum. Thermostable endoglucanase from P. citrinum may have potential effectiveness as additives to laundry detergents.

147 citations

Journal ArticleDOI
TL;DR: Results indicate that SOD is a major determinant of intracellular survival of Leishmania, and cloned a SOD gene from L. tropica and generated SOD-deficient parasites by expressing the corresponding antisense RNA from an episomal vector.
Abstract: Intracellular parasitic protozoans of the genus Leishmania depend for their survival on the elaboration of enzymic and other mechanisms for evading toxic free-radical damage inflicted by their phagocytic macrophage host. One such mechanism may involve superoxide dismutase (SOD), which detoxifies reactive superoxide radicals produced by activated macrophages, but the role of this enzyme in parasite survival has not yet been demonstrated. We have cloned a SOD gene from L. tropica and generated SOD-deficient parasites by expressing the corresponding antisense RNA from an episomal vector. Such parasites have enhanced sensitivity to menadione and hydrogen peroxide in axenic culture, and a markedly reduced survival in mouse macrophages. These results indicate that SOD is a major determinant of intracellular survival of Leishmania.

128 citations

Journal ArticleDOI
TL;DR: The results indicate that the three NOS isozymes, despite their general structural similarity, differ markedly in their strengths, interfaces, and in how l-Arg and H4B influence their formation and stability.

127 citations

Journal ArticleDOI
TL;DR: Structures of the murine inducible NOS oxygenase domain (iNOS(ox) complexed with NHA indicate that NHA and L-Arg both bind with the same conformation adjacent to the heme iron and neither interacts directly with it nor with H(4)B, and identical binding modes for active and inactive quinonoid-dihydrobiopterin indicate that conformational differences cannot explain pterin inactivity.
Abstract: Nitric oxide synthases (NOSs) catalyze two mechanistically distinct, tetrahydrobiopterin (H4B)-dependent, heme-based oxidations that first convert l-arginine (l-Arg) to N^ω-hydroxy-l-arginine (NHA) and then NHA to l-citrulline and nitric oxide. Structures of the murine inducible NOS oxygenase domain (iNOS_(ox)) complexed with NHA indicate that NHA and l-Arg both bind with the same conformation adjacent to the heme iron and neither interacts directly with it nor with H_4B. Steric restriction of dioxygen binding to the heme in the NHA complex suggests either small conformational adjustments in the ternary complex or a concerted reaction of dioxygen with NHA and the heme iron. Interactions of the NHA hydroxyl with active center β-structure and the heme ring polarize and distort the hydroxyguanidinium to increase substrate reactivity. Steric constraints in the active center rule against superoxo-iron accepting a hydrogen atom from the NHA hydroxyl in their initial reaction, but support an Fe(III)-peroxo-NHA radical conjugate as an intermediate. However, our structures do not exclude an oxo-iron intermediate participating in either l-Arg or NHA oxidation. Identical binding modes for active H_4B, the inactive quinonoid-dihydrobiopterin (q-H_2B), and inactive 4-amino-H_4B indicate that conformational differences cannot explain pterin inactivity. Different redox and/or protonation states of q-H_2B and 4-amino-H_4B relative to H_4B likely affect their ability to electronically influence the heme and/or undergo redox reactions during NOS catalysis. On the basis of these structures, we propose a testable mechanism where neutral H_4B transfers both an electron and a 3,4-amide proton to the heme during the first step of NO synthesis.

117 citations


Cited by
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Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal Article
TL;DR: In this article, the authors present a document, redatto, voted and pubblicato by the Ipcc -Comitato intergovernativo sui cambiamenti climatici - illustra la sintesi delle ricerche svolte su questo tema rilevante.
Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

4,187 citations

Journal ArticleDOI
TL;DR: This review concentrates on advances in nitric oxide synthase (NOS) structure, function and inhibition made in the last seven years, during which time substantial advances have been made in the authors' understanding of this enzyme family.
Abstract: This review concentrates on advances in nitric oxide synthase (NOS) structure, function and inhibition made in the last seven years, during which time substantial advances have been made in our understanding of this enzyme family. There is now information on the enzyme structure at all levels from primary (amino acid sequence) to quaternary (dimerization, association with other proteins) structure. The crystal structures of the oxygenase domains of inducible NOS (iNOS) and vascular endothelial NOS (eNOS) allow us to interpret other information in the context of this important part of the enzyme, with its binding sites for iron protoporphyrin IX (haem), biopterin, L-arginine, and the many inhibitors which interact with them. The exact nature of the NOS reaction, its mechanism and its products continue to be sources of controversy. The role of the biopterin cofactor is now becoming clearer, with emerging data implicating one-electron redox cycling as well as the multiple allosteric effects on enzyme activity. Regulation of the NOSs has been described at all levels from gene transcription to covalent modification and allosteric regulation of the enzyme itself. A wide range of NOS inhibitors have been discussed, interacting with the enzyme in diverse ways in terms of site and mechanism of inhibition, time-dependence and selectivity for individual isoforms, although there are many pitfalls and misunderstandings of these aspects. Highly selective inhibitors of iNOS versus eNOS and neuronal NOS have been identified and some of these have potential in the treatment of a range of inflammatory and other conditions in which iNOS has been implicated.

3,418 citations

Journal Article
TL;DR: This volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of the instrument and its ancillary tools are simply and well presented.
Abstract: I read this book the same weekend that the Packers took on the Rams, and the experience of the latter event, obviously, colored my judgment. Although I abhor anything that smacks of being a handbook (like, \"How to Earn a Merit Badge in Neurosurgery\") because too many volumes in biomedical science already evince a boyscout-like approach, I must confess that parts of this volume are fast, scholarly, and significant, with certain reservations. I like parts of this well-illustrated book because Dr. Sj6strand, without so stating, develops certain subjects on technique in relation to the acquisition of judgment and sophistication. And this is important! So, given that the author (like all of us) is somewhat deficient in some areas, and biased in others, the book is still valuable if the uninitiated reader swallows it in a general fashion, realizing full well that what will be required from the reader is a modulation to fit his vision, propreception, adaptation and response, and the kind of problem he is undertaking. A major deficiency of this book is revealed by comparison of its use of physics and of chemistry to provide understanding and background for the application of high resolution electron microscopy to problems in biology. Since the volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of The instrument and its ancillary tools are simply and well presented. The potential use of chemical or cytochemical information as it relates to biological fine structure , however, is quite deficient. I wonder when even sophisticated morphol-ogists will consider fixation a reaction and not a technique; only then will the fundamentals become self-evident and predictable and this sine qua flon will become less mystical. Staining reactions (the most inadequate chapter) ought to be something more than a technique to selectively enhance contrast of morphological elements; it ought to give the structural addresses of some of the chemical residents of cell components. Is it pertinent that auto-radiography gets singled out for more complete coverage than other significant aspects of cytochemistry by a high resolution microscopist, when it has a built-in minimal error of 1,000 A in standard practice? I don't mean to blind-side (in strict football terminology) Dr. Sj6strand's efforts for what is \"routinely used in our laboratory\"; what is done is usually well done. It's just that …

3,197 citations

Journal ArticleDOI
TL;DR: It is suggested that designing a suitable image‐processing procedure is a prerequisite for a successful classification of remotely sensed data into a thematic map and the selection of a suitable classification method is especially significant for improving classification accuracy.
Abstract: Image classification is a complex process that may be affected by many factors. This paper examines current practices, problems, and prospects of image classification. The emphasis is placed on the summarization of major advanced classification approaches and the techniques used for improving classification accuracy. In addition, some important issues affecting classification performance are discussed. This literature review suggests that designing a suitable image-processing procedure is a prerequisite for a successful classification of remotely sensed data into a thematic map. Effective use of multiple features of remotely sensed data and the selection of a suitable classification method are especially significant for improving classification accuracy. Non-parametric classifiers such as neural network, decision tree classifier, and knowledge-based classification have increasingly become important approaches for multisource data classification. Integration of remote sensing, geographical information systems (GIS), and expert system emerges as a new research frontier. More research, however, is needed to identify and reduce uncertainties in the image-processing chain to improve classification accuracy.

2,741 citations