37 resultados para avian brain


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5-Hydroxytryptamine2A (5-HT2A) receptor kinetics was studied in cerebral cortex and brain stem of streptozotocin (STZ) induced diabetic rats. Scatchard analysis with [3H] (±) 2,3dimethoxyphenyl-l-[2-(4-piperidine)-methanol] ([3H]MDL100907) in cerebral cortex showed no significant change in maximal binding (Bmax) in diabetic rats compared to controls. Dissociation constant (K) of diabetic rats showed a significant decrease (p < 0.05) in cerebral cortex, which was reversed to normal by insulin treatment. Competition studies of [3H]MDL100907 binding in cerebral cortex with ketanserin showed the appearance of an additional low affinity site for 5-HT2A receptors in diabetic state, which was reversed to control pattern by insulin treatment. In brain stem, scatchard analysis showed a significant increase (p < 0.05) in Bmax accompanied by a significant increase (p < 0.05) in Kd. Competition analysis in brain stem also showed a shift in affinity towards a low affinity State for 5-HT2A receptors. All these parameters were reversed to control level by insulin treatment. These results show that in cerebral cortex there is an increase in affinity of 5-HT2A receptors without any change in its number and in the case of brain stem there is an increase in number of 5HT2A receptors accompanied by a decrease in its affinity during diabetes. Thus, from the results we suggest that the increase in affinity of 5-HT2A receptors in cerebral cortex and upregulation of 5-HT2A receptors in brain stem may lead to altered neuronal function in diabetes.

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The binding of (-)[ 3H ]dihydroalprenolol , an antagonist of norepinephrine , to $-adrenergic receptors in different regions of the brain of male and female rats of various ages was measured . The binding to the synaptosomal fraction of corpus striatum , hypothalamus, cerebral cortex, cerebellum and the brainstems shows a significant decrease in the binding in old rats of both sexes . Only in the female corpus striatal region, the binding in the adult and the old is the same . In the case of females, the highest binding is seen in the young. In the male, an increase in binding occurs up to adulthood , after which it declines, suggesting a definite sex-related difference in the Q-adrenergic receptor.

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Department of Biotechnology, Cochin University of Science and Technology

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The present study was designed to investigate the protective effect of glucose, oxygen and epinephrine resuscitation on impairment in the functional role of GABAergic, serotonergic, muscarinic receptors, PLC, BAX, SOD, CAT and GPx expression in the brain regions of hypoxia induced neonatal rats. Also, the role of hormones - Triiodothyronine (T3) and insulin, second messengers – cAMP, cGMP and IP3 and transcription factors – HIF and CREB in the regulation of neonatal hypoxia and its resuscitation methods were studied. Behavioural studies were conducted to evaluate the motor function and cognitive deficit in one month old control and experimental rats. The efficient and timely supplementation of glucose plays a crucial role in correcting the molecular changes due to hypoxia, oxygen and epinephrine. The sequence of glucose, epinephrine and oxygen administration at the molecular level is an important aspect of the study. The additive neuronal damage effect due to oxygen and epinephrine treatment is another important observation. The corrective measures by initial supply of glucose to hypoxic neonatal rats showed from the molecular study when brought to practice will lead to healthy intellectual capacity during the later developmental stages, which has immense clinical significance in neonatal care.

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The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored.

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Department of Biotechnology, Cochin University of Science and Technology

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In the present study, a detailed investigation on the alterations of muscarinic M1, M3, α7 nicotinic acetylcholine receptor (α7 nAchR), GABA receptors and its subtypes; GABAAα1 and GABAB in the brain regions of streptozotocin induced diabetic and insulin induced hypoglycemic rats were carried out. Gene expression of acetylcholine esterase (AChE), choline acetyltransferase (ChAT), GAD, GLUT3, Insulin receptor, superoxide dismutase (SOD), Bax protein, Phospholipase C and CREB in hypoglycemic and hyperglycemic rat brain were studied. Muscarinic M1, M3 receptors, AChE, ChAT, GABAAα1, GABAB, GAD, Insulin receptor, SOD, Bax protein and Phospholipase C expression in pancreas was also carried out. The molecular studies on the CNS and PNS damage will elucidate the therapeutic role in the corrective measures of the damage to the brain during hypoglycemia and hyperglycemia.

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Parkinson's disease is a chronic progressive neurodegenerative movement disorder characterized by a profound and selective loss of nigrostriatal dopaminergic neurons. Our findings demonstrated that glutamatergic system is impaired during PD. The evaluations of these damages have important implications in understanding the molecular mechanism underlying motor, cognitive and memory deficits in PD. Our results showed a significant increase of glutamate content in the brain regions of 6- OHDA infused rat compared to control. This increased glutamate content caused an increase in glutamatergic and NMDA receptors function. Glutamate receptor subtypes- NMDAR1, NMDA2B and mGluR5 have differential regulatory role in different brain regions during PD. The second messenger studies confirmed that the changes in the receptor levels alter the IP3, cAMP and cGMP content. The alteration in the second messengers level increased the expression of pro-apoptotic factors - Bax and TNF-α, intercellular protein - α-synuclein and reduced the expression of transcription factor - CREB. These neurofunctional variations are the key contributors to motor and cognitive abnormalities associated with PD. Nestin and GFAP expression study confirmed that 5-HT and GABA induced the differentiation and proliferation of the BMC to neurons and glial cells in the SNpc of rats. We also observed that activated astrocytes are playing a crucial role in the proliferation of transplanted BMC which makes them significant for stem cell-based therapy. Our molecular and behavioural results showed that 5-HT and GABA along with BMC potentiates a restorative effect by reversing the alterations in glutamate receptor binding, gene expression and behaviour abnormality that occur during PD. The therapeutic significance in Parkinson’s disease is of prominence.

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In the present study a detailed investigation on the alterations of dopamine and its receptors in the brain regions of streptozotocin induced diabetic and insulin induced hypoglycaemic rats were carried out. Glutamate receptor, NMDARI gene expression in the hypoglycaemic and hyperglycaemic brain was also studied. EEG recording in hypoglycaemic and hyperglycaemic will be carried out to measure brain activity. in vitro studies on glucose uptake and insulin secretion, with and without specific antagonists were carried out to confirm the specific receptor subtypes - DA D1, DA D2 and NMDA involved in the functional regulation during hyperglycaemic and hypoglycaemic brain damage. The molecular studies on the brain damage through dopaminergic and glutamergic receptors will elucidate the therapeutic role in the corrective measures of the damage to the brain during hypoglycaemia and hyperglycaemia. This has importance in the management of diabetes and antidiabetic treatment for better intellectual functioning of the individual.

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Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

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I) To study the changes in the content of brain rrrorroamirres in streptozotocirr-irrduced tliabetes as a lirnction of age and to lirrd the role oliadrenal lrornroncs in diabetic state. 2) To assess the adrenergic receptor function in the brain stem ofstreptozotocin-induced diabetic rats ofdillerent ages. 3) To study the changes in the basal levels of second messenger cAMP in the brain stenr ofstreptozotocin-induced diabetic rats as a function of age. 4) To study the changes occurring in the content ofmorroamines and their metabolites in whole pancreas and isolated pancreatic islets of streptozotocin-diabetic rats as a function ofage and the effect of adrenal hormones. 5) To study the adrenergic receptors and basal levels of cAMP in isolated pancreatic islets in young and old streptozotoein-diabetic rats. 6) The in virro study of CAMP content in pancreatic islets of young and old rats and its ellect on glucose induced insulin secretion. 7) 'lhe in vitro study on the involvement of dopamine and corticosteroids in glucose induced insulin secretion in pancreatic islets as a function of age.

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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.

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Axial brain slices containing similar anatomical structures are retrieved using features derived from the histogram of Local binary pattern (LBP). A rotation invariant description of texture in terms of texture patterns and their strength is obtained with the incorporation of local variance to the LBP, called Modified LBP (MOD-LBP). In this paper, we compare Histogram based Features of LBP (HF/LBP), against Histogram based Features of MOD-LBP (HF/MOD-LBP) in retrieving similar axial brain images. We show that replacing local histogram with a local distance transform based similarity metric further improves the performance of MOD-LBP based image retrieval

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Retrieval of similar anatomical structures of brain MR images across patients would help the expert in diagnosis of diseases. In this paper, modified local binary pattern with ternary encoding called modified local ternary pattern (MOD-LTP) is introduced, which is more discriminant and less sensitive to noise in near-uniform regions, to locate slices belonging to the same level from the brain MR image database. The ternary encoding depends on a threshold, which is a user-specified one or calculated locally, based on the variance of the pixel intensities in each window. The variancebased local threshold makes the MOD-LTP more robust to noise and global illumination changes. The retrieval performance is shown to improve by taking region-based moment features of MODLTP and iteratively reweighting the moment features of MOD-LTP based on the user’s feedback. The average rank obtained using iterated and weighted moment features of MOD-LTP with a local variance-based threshold, is one to two times better than rotational invariant LBP (Unay, D., Ekin, A. and Jasinschi, R.S. (2010) Local structure-based region-of-interest retrieval in brain MR images. IEEE Trans. Inf. Technol. Biomed., 14, 897–903.) in retrieving the first 10 relevant images