Decreased [ 3 H] YM-09151-2 binding to dopamine D2 receptors in the hypothalamus, brainstem and pancreatic islets of streptozotocin -induced diabetic rats

In the present study dopamine was measured in the hypothalamus, brainstem, pancreatic islets and plasma, using HPLC. Dopamine D2 receptor changes in the hypothalamus, brainstem and pancreatic islets were studied using [3H] YM-09151-2 in streptozotocin-induced diabetic and insulintreated diabetic rats. There was a significant decrease in dopatnine content in the hypothalamus (P<0.001), brainstem (P<0.001), pancreatic islets (P<0.001) and plasma (P<0.00I) in diabetic rats when compared to control. Scatchard analysis of [3H] YM-09151-2 in the hypothalamus of diabetic rats showed a significant decrease in Bax (P<0.001) and Kd, showing an increased affinity of D2 receptors when compared to control. Insulin treatment did not completely reverse the changes that occurred during diabetes. There was a significant decrease in B,nax (P<0.01) with decreased affinity in the brainstem of diabetic rats. The islet membrane preparation of diabetic rats showed a significant decrease (P<0.001) in the binding of [3H] YM-09 151-2 with decreased Kd (P<0.001) compared to control. The increase in affinity of D2 receptors in hypothalamus and pancreatic islets and the decreased affinity in brainstem were confirmed by competition analysis. Thus our results suggest that the decreased dopamine D, receptor function in the hypothalamus, brainstem and pancreas affects insulin secretion in diabetic rats, which has immense clinical relevance to the management of diabetes.

Quadratic Predictor based Differential Encoding and Decoding of Speech Signals

Modeling nonlinear systems using Volterra series is a century old method but practical realizations were hampered by inadequate hardware to handle the increased computational complexity stemming from its use. But interest is renewed recently, in designing and implementing filters which can model much of the polynomial nonlinearities inherent in practical systems. The key advantage in resorting to Volterra power series for this purpose is that nonlinear filters so designed can be made to work in parallel with the existing LTI systems, yielding improved performance. This paper describes the inclusion of a quadratic predictor (with nonlinearity order 2) with a linear predictor in an analog source coding system. Analog coding schemes generally ignore the source generation mechanisms but focuses on high fidelity reconstruction at the receiver. The widely used method of differential pnlse code modulation (DPCM) for speech transmission uses a linear predictor to estimate the next possible value of the input speech signal. But this linear system do not account for the inherent nonlinearities in speech signals arising out of multiple reflections in the vocal tract. So a quadratic predictor is designed and implemented in parallel with the linear predictor to yield improved mean square error performance. The augmented speech coder is tested on speech signals transmitted over an additive white gaussian noise (AWGN) channel.