Biochemical Studies on the Protective Effect of Taurine on Experimentally Induced Fulminat Hepatic Failure in Rats

Fulminant hepatic failure (FHF) is a dramatic and challenging syndrome in clinical medicine. Although an uncommon disorder, it is usually fatal and occurs in previously healthy person. While the causes of FHF remain unclear, viral hepatitis and drug-induced liver injury account for the majority of cases. Hepatitis E causes large-scale epidemics of hepatitis in the Indian subcontinent, involving hundreds of thousands of cases with high mortality. FHF is associated with several clinical features like jaundice, shrunken liver, easy bruising, low levels of serum proteins, fatigue, multi-organ failure etc and metabolic derangements like hypoglycemia, hyperlipidemia, hyponatremia, defective protein synthesis, reduced energy production, decreased rate of urea production etc. These disturbances are predominantly attributed to oxidative stress, membrane destabilization and osmolytic imbalances. The options available for these patients are quite minimal with liver transplantation being one of them. But the procedure is ridden with issues causing it to find less favor among the patients and the caregivers. Use of hepatoprotective and cytoprotective drugs, is being considered to be a more acceptable alternative as a strategy to enhance liver regeneration. In this regard use of taurine a naturally occurring amino acid that plays a crucial role in many physiological processes would prove to be effective. In the present study, hepatoprotective effect of taurine on a rat model of induced FHF was studied. Taurine supplementation has effectively counteracted the metabolic and structural aberrations in the liver caused by D-galactosamine intoxication.

Modelling and Analysis of Recurrent Event Data with Multiple Causes

This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival data is a term used for describing data that measures the time to occurrence of an event.In survival studies, the time to occurrence of an event is generally referred to as lifetime.Recurrent event data are commonly encountered in longitudinal studies when individuals are followed to observe the repeated occurrences of certain events. In many practical situations, individuals under study are exposed to the failure due to more than one causes and the eventual failure can be attributed to exactly one of these causes.The proposed model was useful in real life situations to study the effect of covariates on recurrences of certain events due to different causes.In Chapter 3, an additive hazards model for gap time distributions of recurrent event data with multiple causes was introduced. The parameter estimation and asymptotic properties were discussed .In Chapter 4, a shared frailty model for the analysis of bivariate competing risks data was presented and the estimation procedures for shared gamma frailty model, without covariates and with covariates, using EM algorithm were discussed. In Chapter 6, two nonparametric estimators for bivariate survivor function of paired recurrent event data were developed. The asymptotic properties of the estimators were studied. The proposed estimators were applied to a real life data set. Simulation studies were carried out to find the efficiency of the proposed estimators.