Decreased a2-adrenergic receptor in the brain stem and pancreatic islets during pancreatic regeneration in weanling rats

Sympathetic stimulation inhibits insulin secretion. a2-Adrenergic receptor is known to have a regulatory role in the sympathetic function. We investigated the changes in the a2-adrenergic receptors in the brain stein and pancreatic islets using [3H]Yohimbine during pancreatic regeneration in weanling rats. Brain stem and pancreatic islets of experimental rats showed a significant decrease (p<0.001) in norepinephrine (NE) content at 72 h after partial pancreatectomy. The epinephrine (EPI) content showed a significant decrease (p<0.001) in pancreatic islets while it was not detected in brain stem at 72 h after partial pancreatectomy. Scatchard analysis of [3H]Yohimbine showed a significant decrease (p<0.05) and Kd at 72 h after partial pancreatectomy in the brain stem. In the pancreatic islets, Scatchard analysis of [3H]Yohimbine showed a signiinfiBca'nnatx decrease (p<0.001) in B,nax and Kd (p<0.05) at 72 h after partial pancreatectomy. The binding parameters reversed to near sham by 7 days after pancreatectomy both in brain stein and pancreatic islets. This shows that pancreatic insulin secretion is influenced by central nervous system inputs from the brain stem. In vitro studies with yohimbine showed that the a2-adrenergic receptors are inhibitory to islet DNA synthesis and insulin secretion. Thus our results suggest that decreased a2-adrenergic receptors during pancreatic regeneration functionally regulate insulin secretion and pancreatic 13-cell proliferation in weanling rats.

Increased 5-HT2C Receptor Binding in the Brain Stem And Cerebral Cortex During Liver Regeneration And Hepatic Neoplasia In Rats

In the present study, serotonin 2C (5-HT2c) receptor binding parameters in the brainstem and cerebral cortex were investigated during liver generation after partial hepatectomy (PH) and N-nitrosodiethylamine (NDEA) induced hepatic neoplasia in male Wistar rats. The serotonin content increased significantly (p<0.01) in the cerebral cortex after PH and in NDEA induced hepatic neoplasia. Brain stem serotonin content increased significantly (p<0.05) after PH and (p<0.001) in NDEA induced hepatic neoplasia. The number and affinity of the 5-HT2c receptors in the crude synaptic membrane preparations of the brain stem showed a significant (p<0.001) increase after PH and in NDEA induced hepatic neoplasia. The number and affinity of 5-HT2c receptors increased significantly (p<0.001) in NDEA induced hepatic neoplasia in the crude synaptic membrane preparations of the cerebral cortex. There was a significant (p<0.01) increase in plasma norepinephrine in PH and (p<0.001) in NDEA induced hepatic neoplasia, indicating sympathetic stimulation. Thus, our results suggest that during active hepatocyte proliferation 5-HT2c receptor in the brain stem and cerebral cortex are up-regulated which in turn induce hepatocyte proliferation mediated through sympathetic stimulation.

Brain Cholinergic and Dopaminergic Functions in Streptozotocin Induced Diabetic Rats: Effects of Curcumin and Vitamin D3 Supplementation

Department of Biotechnology, Cochin University of Science and Technology

Brain Adrenergic and Serotonergic Receptor Function in Streptozotocin-Diabetic Rats

Department of Biotechnology, Cochin University of Science and Technology

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.