THE CONCEPT OF SEX IN HINDI SHORT STORIES OF THE POST—PREMCHAND PERIOD 1935-60

HINDI

Neurotransmitters Functional Balance in Neurodegenerative Disease Management:recent Advances

The recent developments in neurobiology have rendered new prominence and potential to study about the structure and function of brain and related disorders. Human behaviour is the net result of neural control of the communication between brain cells. Neurotransmitters are chemicals that are used to relay, amplify and modulate electrical signals between neurons and/or another cell. It mediates rapid intercellular communication through the nervous system by interacting with cell surface receptors. These receptors often trigger second messenger signaling pathways that regulate the activity of ion channels. The functional balance of different neurotransmitters such as Acetylcholine (Ach), Dopamine (DA), Serotonin (5-HT), Norepinephrine (NE), Epinephrine (EPI), Glutamate and Gamma amino butyric acid (GABA) regulates the growth, division and other vital functions of a normal cell / organism (Sudha, 1998). Any change in neurotransmitters' functional balance will result in the failure of cell function and may lead to the occurrence of diseases. Abnormalities in the production or functioning of neurotransmitters have been implicated in a number of neurological disorders like Schizophrenia, Alzheimer's, Epilepsy, Depression and Parkinson's disease. Changes in central and peripheral neuronal signaling system is also noted in diabetes, cancer, cell proliferation, alcoholism and aging. Elucidation of neurotransmitters receptor interaction pathways and gene expression regulation by second messengers and transcriptional factors in health and disease conditions can lead to new small molecules for development of therapeutic agents to improve neurological disease conditions. Increased awareness of the global effects of neurological disorders should help health care planners and the neurological community set appropriate priorities in research, prevention, and management of these diseases.

Influence of compounding and process variables on quality of condams made from natural rubber latex

Condoms are widely accepted as a contraceptive for family planning and population control. It is also accepted as the most effective barrier against sexually transmitted diseases, especially AIDS, the incurable disease. But presence of pinholes and low film strength of condoms make it unsuitable for the purpose. Quality improvement of condoms by reducing the pinhole formation and increasing the film strength is thus an essential requirement for population control as well as for preventing the spread of sexually transmitted diseases. Strict implementation of WHO specification of condoms further increases the rejection percentage. This causes higher rejection loss to condom manufacturers because the defects could be identified only at the final stage of processing. If the influence of various factors which cause these defects is known, manufacturers can take remedial measures to reduce the defectives so that rejection loss can be decreased and quality of condoms increased. In the present study, it was proposed to conduct experiments to improve the quality of condoms by reducing the pinhole rejection percentage and increasing the tensile properties, burst volume, and burst pressure. Ageing property improvement also was an important target among other parameters. Until a cure for AIDS is found, a high quality latex condom is the only effective device in the prevention of the spread of HIV, AIDS and STD's. Hence it is all the more necessary to have high quality condoms.

Marine Bacteria As Source Of Pigment For Application As Dye In Textile Industry

The textile industry is one amongst the rapidly growing industries world wide, which utilizes enormous amounts of synthetic dyes. Consequently, the effluent from these textile industries poses serious threat to the environment which is often very difficult to treat and dispose. This has become a very grave problem in environment conservation and hence natural pigments have drawn the attention of industry as safe alternative. In this context, in the present study an attempt was made to bioprospect marine bacteria towards isolation of a suitable and ideal pigment that could be used as a natural dye. A marine Serratia sp. BTWJ8 was recognized to synthesize enormous amounts of a prodigiosin-like pigment. The pigment was isolated and characterized for various properties. The pigment was evaluated for application as a dye in the textile industry. Results of the studies indicated that this pigment could be used as a natural dye for imparting red-yellow colour to various grades of textile materials. The colour was observed to be stable after wash performance studies

Spectroscopic Investigation of Tooth Caries and Demineralization

Dental caries persists to be the most predominant oral disease in spite of remarkable progress made during the past half- century to reduce its prevalence. Early diagnosis of carious lesions is an important factor in the prevention and management of dental caries. Conventional procedures for caries detection involve visual-tactile and radiographic examination, which is considered as “gold standard”. These techniques are subjective and are unable to detect the lesions until they are well advanced and involve about one-third of the thickness of enamel. Therefore, all these factors necessitate the need for the development of new techniques for early diagnosis of carious lesions. Researchers have been trying to develop various instruments based on optical spectroscopic techniques for detection of dental caries during the last two decades. These optical spectroscopic techniques facilitate noninvasive and real-time tissue characterization with reduced radiation exposure to patient, thereby improving the management of dental caries. Nonetheless, a costeffective optical system with adequate sensitivity and specificity for clinical use is still not realized and development of such a system is a challenging task.Two key techniques based on the optical properties of dental hard tissues are discussed in this current thesis, namely laser-induced fluorescence (LIF) and diffuse reflectance (DR) spectroscopy for detection of tooth caries and demineralization. The work described in this thesis is mainly of applied nature, focusing on the analysis of data from in vitro tooth samples and extending these results to diagnose dental caries in a clinical environment. The work mainly aims to improve and contribute to the contemporary research on fluorescence and diffuse reflectance for discriminating different stages of carious lesions. Towards this, a portable and compact laser-induced fluorescence and reflectance spectroscopic system (LIFRS) was developed for point monitoring of fluorescence and diffuse reflectance spectra from tooth samples. The LIFRS system uses either a 337 nm nitrogen laser or a 404 nm diode laser for the excitation of tooth autofluorescence and a white light source (tungsten halogen lamp) for measuring diffuse reflectance.Extensive in vitro studies were carried out on extracted tooth samples to test the applicability of LIFRS system for detecting dental caries, before being tested in a clinical environment. Both LIF and DR studies were performed for diagnosis of dental caries, but special emphasis was given for early detection and also to discriminate between different stages of carious lesions. Further the potential of LIFRS system in detecting demineralization and remineralization were also assessed.In the clinical trial on 105 patients, fluorescence reference standard (FRS) criteria was developed based on LIF spectral ratios (F500/F635 and F500/F680) to discriminate different stages of caries and for early detection of dental caries. The FRS ratio scatter plots developed showed better sensitivity and specificity as compared to clinical and radiographic examination, and the results were validated with the blindtests. Moreover, the LIF spectra were analyzed by curve-fitting using Gaussian spectral functions and the derived curve-fitted parameters such as peak position, Gaussian curve area, amplitude and width were found to be useful for distinguishing different stages of caries. In DR studies, a novel method was established based on DR ratios (R500/R700, R600/R700 and R650/R700) to detect dental caries with improved accuracy. Further the diagnostic accuracy of LIFRS system was evaluated in terms of sensitivity, specificity and area under the ROC curve. On the basis of these results, the LIFRS system was found useful as a valuable adjunct to the clinicians for detecting carious lesions.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.