Enhanced dopamine D2 receptor function in hypothalamus and corpus striatum: their role in liver, plasma and in vitro hepatocyte ALDH regulation in ethahol treated rats

Dopamine D2 receptors are involved in ethanol self- administration behavior and also suggested to mediate the onset and offset of ethanol drinking. In the present study, we investigated dopamine (DA) content and Dopamine D2 (DA D2) receptors in the hypothalamus and corpus striatum of ethanol treated rats and aldehyde dehydrogenase (ALDH) activity in the liver and plasma of ethanol treated rats and in vitro hepatocyte cultures. Hypothalamic and corpus striatal DA content decreased significantly (P\0.05, P\0.001 respectively) and homovanillic acid/ dopamine (HVA/DA) ratio increased significantly (P\0.001) in ethanol treated rats when compared to control. Scatchard analysis of [3H] YM-09151-2 binding to DA D2 receptors in hypothalamus showed a significant increase (P\0.001) in Bmax without any change in Kd in ethanol treated rats compared to control. The Kd of DA D2 receptors significantly decreased (P\0.05) in the corpus striatum of ethanol treated rats when compared to control. DA D2 receptor affinity in the hypothalamus and corpus striatum of control and ethanol treated rats fitted to a single site model with unity as Hill slope value. The in vitro studies on hepatocyte cultures showed that 10-5 M and 10-7 M DA can reverse the increased ALDH activity in 10% ethanol treated cells to near control level. Sulpiride, an antagonist of DA D2, reversed the effect of dopamine on 10% ethanol induced ALDH activity in hepatocytes. Our results showed a decreased dopamine concentration with enhanced DA D2 receptors in the hypothalamus and corpus striatum of ethanol treated rats. Also, increased ALDH was observed in the plasma and liver of ethanol treated rats and in vitro hepatocyte cultures with 10% ethanol as a compensatory mechanism for increased aldehyde production due to increased dopamine metabolism. A decrease in dopamine concentration in major brain regions is coupled with an increase in ALDH activity in liver and plasma, which contributes to the tendency for alcoholism. Since the administration of 10-5 M and 10-7 M DA can reverse the increased ALDH activity in ethanol treated cells to near control level, this has therapeutic application to correct ethanol addicts from addiction due to allergic reaction observed in aldehyde accumulation.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.

Nonparametric Estimation of Survivor Function in Bivariate Competing Risk Models’

So far, in the bivariate set up, the analysis of lifetime (failure time) data with multiple causes of failure is done by treating each cause of failure separately. with failures from other causes considered as independent censoring. This approach is unrealistic in many situations. For example, in the analysis of mortality data on married couples one would be interested to compare the hazards for the same cause of death as well as to check whether death due to one cause is more important for the partners’ risk of death from other causes. In reliability analysis. one often has systems with more than one component and many systems. subsystems and components have more than one cause of failure. Design of high-reliability systems generally requires that the individual system components have extremely high reliability even after long periods of time. Knowledge of the failure behaviour of a component can lead to savings in its cost of production and maintenance and. in some cases, to the preservation of human life. For the purpose of improving reliability. it is necessary to identify the cause of failure down to the component level. By treating each cause of failure separately with failures from other causes considered as independent censoring, the analysis of lifetime data would be incomplete. Motivated by this. we introduce a new approach for the analysis of bivariate competing risk data using the bivariate vector hazard rate of Johnson and Kotz (1975).