1,662 research outputs found
Human origin recognition complex is essential for HP1 binding to chromatin and heterochromatin organization
The origin recognition complex (ORC) is a DNA replication initiator protein also known to be involved in diverse cellular functions including gene silencing, sister chromatid cohesion, telomere biology, heterochromatin localization, centromere and centrosome activity, and cytokinesis. We show that, in human cells, multiple ORC subunits associate with hetereochromatin protein 1 (HP1) alpha- and HP1beta-containing heterochromatic foci. Fluorescent bleaching studies indicate that multiple subcomplexes of ORC exist at heterochromatin, with Orc1 stably associating with heterochromatin in G1 phase, whereas other ORC subunits have transient interactions throughout the cell-division cycle. Both Orc1 and Orc3 directly bind to HP1alpha, and two domains of Orc3, a coiled-coil domain and a mod-interacting region domain, can independently bind to HP1alpha; however, both are essential for in vivo localization of Orc3 to heterochromatic foci. Direct binding of both Orc1 and Orc3 to HP1 suggests that, after the degradation of Orc1 at the G1/S boundary, Orc3 facilitates assembly of ORC/HP1 proteins to chromatin. Although depletion of Orc2 and Orc3 subunits by siRNA caused loss of HP1alpha association to heterochromatin, loss of Orc1 and Orc5 caused aberrant HP1alpha distribution only to pericentric heterochromatin-surrounding nucleoli. Depletion of HP1alpha from human cells also shows loss of Orc2 binding to heterochromatin, suggesting that ORC and HP1 proteins are mutually required for each other to bind to heterochromatin. Similar to HP1alpha-depleted cells, Orc2 and Orc3 siRNA-treated cells also show loss of compaction at satellite repeats, suggesting that ORC together with HP1 proteins may be involved in organizing higher-order chromatin structure and centromere function
FACE RECOGNITION IN EIGEN DOMAIN WITH NEURO-FUZZY CLASSIFIER AND EVOLUTIONARY OPTIMIZATION
Face Recognition is a nascent field of research with many challenges. The proposed system focuses on recognizing faces in a faster and more accurate way using eigenface approach and genetic algorithm by considering the entire problem as an optimization problem. It consists of two stages: Eigenface approach is used for feature extraction and genetic algorithm based feed forward Neuro-Fuzzy System is used for face recognition. Classification of face images to a particular class is done using an artificial neural network. The training of neural network is done using genetic algorithm, a machine learning approach which optimizes the weights used in the neural network. This is an efficient optimization technique and an evolutionary classification method. The algorithm has been tested on 200 images (20 classes). A recognition score for test lot is calculated by considering almost all the variants of feature extraction. Test results gave a recognition rate of 97.01%
Virtual Quantification of Protein Stability Using Applied Kinetic and Thermodynamic Parameters
Protein stability, the most important aspect of molecular dynamics and simulations, requires sophisticated instrumentations of molecular biology to analyze its kinetic and thermodynamic background. Sequence- and structure-based programs on protein stability exist which relies only on single point mutations and sequence optimality. The energy distribution conferred by each hydrophobic amino acid in the protein essentially paves way for understanding its stability. To the best of our knowledge, Protein Stability is a first program of its kind, developed to explore the energy requirement of each amino acid in the protein sequence derived from various applied kinetic and thermodynamic quantities. The algorithm is strongly dependent both on kinetic quantities such as atomic solvation energies and solvent accessible surface area and thermodynamic quantities viz. enthalpy, entropy, heat capacity, etc. The hydrophobicity pattern of protein was considered as the important component of protein stabilization
ANALYZING NON-PERFORMING ASSETS IN EDUCATIONAL LOANS: A CASE STUDY OF INDIA
The primary objective of this research study is to investigate non-performing assets in Indian educational loans. Education is a critical foundation of the Indian economy. It represents the primary source of livelihood for the development and the development of an economy. Educational loans are very important in order to achieve technological development and, implicitly, to reduce costs and use sustainable strategies. The data sample was collected from 80 lenders (bank managers) and 80 borrowers of education loans from Pudukkottai district, Tamilnadu state in India. The Multi Stage Disproportionate Sampling method has been applied for the purpose of collecting information from both the borrowers and the lenders. The analysis results refute the hypothesis, as there is no substantial variation in how various types of banks manage non- performing assets in educational credit, since the bulk of NPA instances in educational credit are the consequence of borrowers' intentional default. The majority of defaults were caused by political leaders' announcements of debt forgiveness. The empirical results are relevant and contribute to a better understanding of the impact of non-performing assets in educational loans on sustainable economic growth in India
The Expectation Disconfirmation Theory of Green Banking Practices of State Bank of India with special reference to Kerala - A Structural Equation Modeling Approach
In light of Agenda 2030, sustainability awareness is steadily growing worldwide. All institutions, including banks and financial institutions, are working to reduce their carbon footprints. Several indirect problems have arisen for India as a result of the banking process, such as global warming, climate change, irregular monsoon, air pollution, heavy rain, poor air quality, health problems, ozone depletion, fossil fuel use, recurrent destruction of forests for daily use, improper e-waste disposal. These issues can be overcome with sustainable banking practices (Green banking), which benefit the customer's satisfaction and quality of life. However, sustainability can be achieved only when the customers accept green banking and are satisfied with it. In order to do that, the bank must understand the level of expectations and perception of its customers toward green initiatives and to what extent the initiatives satisfy their day-to-day needs. This paper provides an overview of Expectancy disconfirmation integrations into customer satisfaction of India's largest public sector banks. As part of the present theoretical analysis, we first examine the level of awareness, expectations, and perception differences of customers to determine their satisfaction level. We then provide some evidence from SBI in Kerala regarding dissatisfying factors in green banking practices
Tissue- and development-specific induction and turnover of hsp70 transcripts from loci 87A and 87C after heat shock and during recovery in Drosophila melanogaster
The haploid genome of Drosophila melanogaster normally carries at least five nearly identical copies of heat-shock-inducible hsp70 genes, two copies at the 87A7 and three copies at the 87C1 chromosome sites. We used in situ hybridization of the cDNA, which hybridizes with transcripts of all five hsp70 genes, and of two 3' untranslated region (3'UTR; specific for the 87A7- and 87C1-type hsp70 transcripts) riboprobes to cellular RNA to examine whether all these copies were similarly induced by heat shock in different cell types of D. melanogaster. Our results revealed remarkable differences not only in the heat-shock-inducibility of the hsp70 genes at the 87A7 and 87C1 loci, but also in their post-transcriptional metabolism, such as the stability of the transcripts and of their 3'UTRs in different cell types in developing embryos and in larval and adult tissues. Our results also revealed the constitutive presence of the heat-shock-inducible form of Hsp70 in a subset of late spermatogonial cells from the second-instar larval stage onwards. We suggest that the multiple copies of the stress-inducible hsp70 genes do not exist in the genome of D. melanogaster only to produce large amounts of the Hsp70 rapidly and at short notice, but that they are specifically regulated in a developmental-stage-specific manner. It is likely that the cost/benefit ratio of not producing or of producing a defined amount of Hsp70 under stress conditions varies for different cell types and under different physiological conditions and, accordingly, specific regulatory mechanisms operating at the transcriptional and post-transcriptional levels have evolved
ISOLATION AND IDENTIFICATION OF ENDOPHYTIC FUNGI FROM TERMINALIA CHEBULA OF EASTERN GHATS, TAMILNADU
Objective: Endophytic fungi live inside the higher plants, apparently without causing any harm to the hosts and its produce the secondary metabolites are potential antimicrobial activity. Terminalia chebula has been used in Ayurveda, Unani & Homeopathy medicine. In this study an isolate and identify the endophytic fungi from T. Chebula collected from pachamalai hills of the Eastern Ghats, Tamilnadu.Methods: The plant materials were taken and first rinsed in running tap water to remove the dust and the other debris present in it. Segments of approximately 0.5 cm were cut in sterile lancet blades and surface sterilized by agitating in 70% ethanol (5s), followed by treatment with 4% NaOCl (90s) and then rinsed in sterile distilled water (10s).Thirty six (leaf, stem and fruit samples) segments from T.chebula plant are processed for the isolation of endophytic fungi.Results: About 36 segments (12 segments of each part respectively) of the medicinal plant were screened for the isolation of the endophytic fungi. A total of 27 endophytic fungi was isolated and identified from medicinal plant T.chebula. The leaf segments showed a maximum repository for endophytic fungi than the other segments. Among the 27 endophytic fungi, the predominant endophytic fungi isolated belonged to the genera of Alternaria longipes, Curvularia spp, Mucor, phoma spp, Aspergillus niger, Aspergillus flavus and Penicillium spp. In this study majority of the fungi belonged to hyaline hyphomycetes.Conclusion: In this study conclude that the isolation of endophytic fungi from medicinal plant of terminalia chebula. To isolate the 27 endophytic fungi produce the novel bioactive compound. However Further studies are required to screen these endophytic fungi for production of novel Bioactive compounds.Keywords: Endophytic fungi, Terminalia chebula, bioactive compoundÂ
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