Perceptual Chasm Between Industry and Academic Leaders on the Quality of Higher Education

In the context of the Information Technology Revolution, Communication Explosion, the Knowledge Economy and Globalization, India’s production of Professionals is phenomenal. With over 300 Universities and 15,600 Colleges spewing out 2.5 million graduates each year, in terms of the volume of production India trails behind only the US and recently China. Each year India produces 350,000 Engineers, twice the number produced by the US. A recent evaluation of Universities and Research Institutes all over the world, conducted by a Shanghai university, has not a single Indian University in the world’s top 300 – China has six

RNA binding proteins in cancer chemotherapeutic drug resistance

Drug resistance has been a major obstacle in the quest for a cancer cure. Many chemotherapeutic treatments fail to overcome chemoresistance, resulting in tumor remission. The exact process that leads to drug resistance in many cancers has not been fully explored or understood. However, the discovery of RNA binding proteins (RBPs) has provided insight into various pathways and post-transcriptional gene modifications involved in drug tolerance. RBPs are evolutionarily conserved proteins, and their abnormal gene expression has been associated with cancer progression. Additionally, RBPs are aberrantly expressed in numerous neoplasms. RBPs have also been implicated in maintaining cancer stemness, epithelial-to-mesenchymal transition, and other processes. In this review, we aim to provide an overview of RBP-mediated mechanisms of drug resistance and their implications in cancer malignancy. We discuss in detail the role of major RBPs and their correlation with noncoding RNAs (ncRNAs) that are associated with the inhibition of chemosensitivity. Understanding and exploring the pathways of RBP-mediated chemoresistance will contribute to the development of improved cancer diagnosis and treatment strategies

Effectiveness of selected Nursing Intervention in improving functional status among Elderly with impaired Mobility

This study intended to be an experimental study to evaluate the effectiveness of selected nursing intervention in improving functional status among elderly with impaired mobility residing in selected old age homes in Madurai. An experimental approach was used for this study. The design adopted for the study was Quasi Experimental pre test post test control group design. Purposive sampling technique was adopted for this study .The sample consisted of 60 patients, in that 30 were in Experimental group and 30 were in Control group. The experimental group was instructed to do the selected therapeutic exercise for 20 days and the control group was treated with routine care. The tool used for data collection procedure was Functional activity index scale. Both descriptive and inferential statistics were used for the analysis of data. The major findings were, before administration of therapeutic exercises in experimental group 30 sample (100%) were partially dependent. But after administration of therapeutic exercises 23 samples (76.66%) were become independent and 7 (23.33%) sample belong to partially dependent group where as in control group in pre and post test 30 (100%) samples were in partially dependent (100%) category. The mean functional activity score of experimental group 46.30 after administration of therapeutic exercise on day 20 is higher than mean functional activity score 33.56 before administration of therapeutic exercises. The obtained‘t’ value is 10.19 which was significant at 0.05 level df (58). There was no association between the functional activity score of the subjects with selected demographic variables like age, sex, education status, co-morbid diseases, body mass index and previous history of fall and fracture. The study concludes that the selected therapeutic exercise found to be effective in improving functional status among elderly with impaired mobility residing in selected old age home in Madurai

d-Lucky Labeling of Graphs

AbstractLet l: V (G) →N be a labeling of the vertices of a graph G by positive integers. Define , where d(u) denotes the degree of u and N(u) denotes the open neighborhood of u. In this paper we introduce a new labeling called d-lucky labeling and study the same as a vertex coloring problem. We define a labeling l as d-lucky if c(u) ≠ c(v) , for every pair of adjacent vertices u and v in G. The d-lucky number of a graph G, denoted by ηdl(G), is the least positive k such that G has a d-lucky labeling with {1,2, ..., k} as the set of labels. We obtain ηdl(G) = 2 for hypercube network, butterfly network, benes network, mesh network, hypertree and X-tree

Carotenoid dynamics in Atlantic salmon

BACKGROUND: Carotenoids are pigment molecules produced mainly in plants and heavily exploited by a wide range of organisms higher up in the food-chain. The fundamental processes regulating how carotenoids are absorbed and metabolized in vertebrates are still not fully understood. We try to further this understanding here by presenting a dynamic ODE (ordinary differential equation) model to describe and analyse the uptake, deposition, and utilization of a carotenoid at the whole-organism level. The model focuses on the pigment astaxanthin in Atlantic salmon because of the commercial importance of understanding carotenoid dynamics in this species, and because deposition of carotenoids in the flesh is likely to play an important life history role in anadromous salmonids. RESULTS: The model is capable of mimicking feed experiments analyzing astaxanthin uptake and retention over short and long time periods (hours, days and years) under various conditions. A sensitivity analysis of the model provides information on where to look for possible genetic determinants underlying the observed phenotypic variation in muscle carotenoid retention. Finally, the model framework is used to predict that a specific regulatory system controlling the release of astaxanthin from the muscle is not likely to exist, and that the release of the pigment into the blood is instead caused by the androgen-initiated autolytic degradation of the muscle in the sexually mature salmon. CONCLUSION: The results show that a dynamic model describing a complex trait can be instrumental in the early stages of a project trying to uncover underlying determinants. The model provides a heuristic basis for an experimental research programme, as well as defining a scaffold for modelling carotenoid dynamics in mammalian systems

HabiSign: a novel approach for comparison of metagenomes and rapid identification of habitat-specific sequences

<p>Abstract</p> <p>Background</p> <p>One of the primary goals of comparative metagenomic projects is to study the differences in the microbial communities residing in diverse environments. Besides providing valuable insights into the inherent structure of the microbial populations, these studies have potential applications in several important areas of medical research like disease diagnostics, detection of pathogenic contamination and identification of hitherto unknown pathogens. Here we present a novel and rapid, alignment-free method called HabiSign, which utilizes patterns of tetra-nucleotide usage in microbial genomes to bring out the differences in the composition of both diverse and related microbial communities.</p> <p>Results</p> <p>Validation results show that the metagenomic signatures obtained using the HabiSign method are able to accurately cluster metagenomes at biome, phenotypic and species levels, as compared to an average tetranucleotide frequency based approach and the recently published dinucleotide relative abundance based approach. More importantly, the method is able to identify subsets of sequences that are specific to a particular habitat. Apart from this, being alignment-free, the method can rapidly compare and group multiple metagenomic data sets in a short span of time.</p> <p>Conclusions</p> <p>The proposed method is expected to have immense applicability in diverse areas of metagenomic research ranging from disease diagnostics and pathogen detection to bio-prospecting. A web-server for the HabiSign algorithm is available at <url>http://metagenomics.atc.tcs.com/HabiSign/</url>.</p