GABAA and GABAB Receptor Gene Expression and Functional Regulation During Pancreatic Regeneration and Insulin Secretion in Rats

The present study demonstrate the functional alterations of the GABAA and GABAB receptors and the gene expression during the regeneration of pancreas following partial pancreatectomy. The role of these receptors in insulin secretion and pancreatic DNA synthesis using the specific agonists and antagonists also are studied in vitro. The alterations of GABAA and GABAR receptor function and gene expression in the brain stem, crebellum and hypothalamus play an important role in the sympathetic regulation of insulin secretion during pancreatic regeneration. Previous studies have given much information linking functional interaction between GABA and the peripheral nervous system. The involvement of specific receptor subtypes functional regulation during pancreatic regeneration has not given emphasis and research in this area seems to be scarce. We have observed a decreased GABA content, down regulation of GABAA receptors and an up regulation of GABAB receptors in the cerebral cortex, brain stem and hypothalamus. Real Time-PCR analysis confirmed the receptor data in the brain regions. These alterations in the GABAA and GABAB receptors of the brain are suggested to govern the regenerative response and growth regulation of the pancreas through sympathetic innervation. In addition, receptor binding studies and Real Time-PCR analysis revealed that during pancreatic regeneration GABAA receptors were down regulated and GABAB receptors were up regulated in pancreatic islets. This suggests an inhibitory role for GABAA receptors in islet cell proliferation i.e., the down regulation of this receptor facilitates proliferation. Insulin secretion study during 1 hour showed GABA has inhibited the insulin secretion in a dose dependent manner in normal and hyperglycaemic conditions. Bicuculline did not antagonize this effect. GABAA agonist, muscimol inhibited glucose stimulated insulin secretion from pancreatic islets except in the lowest concentration of 1O-9M in presence of 4mM glucose.Musclmol enhanced insulin secretion at 10-7 and 10-4M muscimol in presence of 20mM glucose- 4mM glucose represents normal and 20mM represent hyperglycaemic conditions. GABAB agonist, baclofen also inhibited glucose induced insulin secretion and enhanced at the concentration of 1O-5M at 4mM glucose and at 10-9M baclofen in presence of 20mM glucose. This shows a differential control of the GABAA and GABAB receptors over insulin release from the pancreatic islets. During 24 hours in vitro insulin secretion study it showed that low concentration of GABA has inhibited glucose stimulated insulin secretion from pancreatic islets. Muscimol, the GABAA agonist, inhibited the insulin secretion but, gave an enhanced secretion of insulin in presence of 4mM glucose at 10-7 , 10-5 and 1O-4M muscimol. But in presence of 20mM glucose muscimol significantly inhibited the insulin secretion. GABAB agonist, baclofen also inhibited glucose induced insulin secretion in presence of both 4mM and 20mM glucose. This shows the inhibitory role of GABA and its specific receptor subtypes over insulin synthesis from pancreatic bete-islets. In vitro DNA synthesis studies showed that activation of GABAA receptor by adding muscimol, a specific agonist, inhibited islet DNA synthesis. Also, the addition of baclofen, a specific agonist of GABAB receptor resulted in the stimulation of DNA synthesis.Thus the brain and pancreatic GABAA and GABAB receptor gene expression differentially regulates pancreatic insulin secretion and islet cell proliferation during pancreatic regeneration. This will have immense clinical significance in therapeutic applications in the management of Diabetes mellitus.

5-HT1A and -HT2c Receptor Gene Expression: Their Functional Role in Pancreatic Regeneration and Insulin Secretion in Rats

Department of Biotechnology, Cochin University of Science and Technology

Consequence modelling,vulnerability assessment and fuzzy fault tree analysis of hazardous storages in an industrial area

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation .

Studies on seed pathology and seedling diseases of some important indigenous tree species of kerala

In forestry, availability of healthy seeds is an important factor in raising planting stock. Initial seed health and storage conditions are the major factors governing the germinability of seeds. Like seeds of agricultural and horticultural crops, forest tree seeds are also liable to be affected by micro-organisms during storage, which affects the germination, and reduces the viability. Further introduction of seed-borne diseases into newly sown crops/areas on account of using unhealthy seeds is also not ruled out. Availability of healthy stock of seedlings is intrinsic for raising plantations and to meet this requirement elimination of nursery diseases by appropriate chemicals is of prime imortance. As exotic tree species may become susceptible to various native pathogens, it is generally considered better to select indigenous tree species for large scale plantations as they are well adapted to local environment. However, before taking up large scale afforestation progranme involving any indigenous tree species, it is essential to have knowledge about seed disorders and seedling diseases and their management. with a View to select appropriate tree species with fewer seed disorders and seedling disease problems for use in further plantation programme, four indigenous tree species such as Albizia odoratissima (L.f) Benth., Lagerstroemia microcazpa Wt., Pterocazpus marsupiwn Roxb. and Xylia xylocarpa (Roxb.) Taub. were evaluated to meet the above parameters

Nature and Ecological significance of Nutrient Regeneration in Different Prawn Culture Fields

The present work "Nature and Ecological Significance of Nutrient Regeneration in different Prawn Culture Fields" was undertaken to understand the seasonal variation of nutrients, nutrient cycling and primary productivity of the prawn culture systems. The main emphasis was to find the qualitative and quantitative estimates of distribution of total phosphorus, inorganic phosphorus, organic phosphorus, total nitrogen and nitrogen fractions in the water. The effect of nutrient cycling on primary productivity and concentration of metals also form one part of the study. The entire thesis comprise of only one major chapter with subchapters such as, Introduction (I), Review of Literature (2), Material and Methods (3), Results (14), Discussion (5), Executive Summary (6) and Biblio~ graphy (7)

Adrenergic and serotonergic function in dna synthesis during rat liver regeneration and in hepatocyte cultures

The adult mammalian liver is predominantly in a quiescent state with respect to cell division. This quiescent state changes dramatically, however, if the liver is injured by toxic, infectious or mechanic agents (Ponder, 1996). Partial hepatectomy (PH) which consists of surgical removal of two-thirds of the liver, has been used to stimulate hepatocyte proliferation (Higgins & Anderson 1931). This experimental model of liver regeneration has been the target of many studies to probe the mechanisms responsible for liver cell growth control (Michalopoulos, 1990; Taub, 1996). After PH most of the remaining cells in the renmant liver respond with co-ordinated waves of DNA synthesis and divide in a process called compensatory hyperplasia. Hence, liver regeneration is a model of relatively synchronous cell cycle progression in vivo. In contrast to hepatomas, cell division is terminated under some intrinsic control when the original cellular mass has been regained. This has made liver regeneration a useful model to dissect the biochemical and molecular mechanisms of cell division regulation. The liver is thus, one of the few adult organs that demonstrates a physiological growth rewonse (Fausto & Mead, 1989; Fausto & Webber, 1994). The regulation of liver cell proliferation involves circulating or intrahepatic factors that are involved in either the priming of hepatocytes to enter the cell cycle (Go to G1) or progression through the cell cycle. In order to understand the basis of liver regeneration it is mandatory to define the mechanisms which (a) trigger division, (b) allow the liver to concurrently grow and maintain dilferentiated fimction and (c) terminate cell proliferation once the liver has reached the appropriate mass. Studies on these aspects of liver regeneration will provide basic insight of cell growth and dilferentiation, liver diseases like viral hepatitis, toxic damage and liver transplant where regeneration of the liver is essential. In the present study, Go/G1/S transition of hepatocytes re-entering the cell cycle after PH was studied with special emphasis on the involvement of neurotransmitters, their receptors and second messenger function in the control of cell division during liver regeneration

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.