Targeted Public Distribution System in Food Grains:Extent of Utlization by the Tribal Population in Kerala

In India, Food Security meant supply of food grains and the medium was Public Distribution System. Public Distribution System (PDS) is a rationing mechanism that entitles households to specified quantities of selected commodities at subsidized prices. The Objectives of PDS are maintaining Price Stability, rationing during times of scarcity, welfare of the poor, and keeping a check on private trade. Kerala has registered remarkable improvement in poverty reduction in general over the years among all social sections, including scheduled caste and scheduled tribe population. As part of the structural adjustment intended to reduce public expenditure, PDS has been modified as Revamped PDS (RPDS) during 1992 and later on as Targeted PDS (TPDS) in 1997, intended to target households on the basis of income criterion, classifying people as Below Poverty Line (BPL) and Above Poverty Line (APL). TPDS provides 25Kg. of food gra.ins through the Fair Price Shops per month @ Rs.3/- per Kg. of rice/ wheat to the BPL category and @Rs.8.90 and Rs.6.7O for rice and wheat respectively to the APL category of people. Since TPDS is intended to target the poor people, the subsidy spent by the government for the scheme should be beneficial to the poor people and naturally they should utilize the benefits by purchasing the food grains allotted under the scheme. Several studies have shown that there is underutilization of the allotments under TPDS. Therefore, the extent of utilization of TPDS in food grains, how and why remains as a major hurdle, in improving the structure and system of PDS. Livelihood of the tribal population being under threat due to increasing degradation of the resources, the targeting system ought to be effective among the tribal population. Therefore, performance of the TPDS in food grains, in terms of the utilization by the tribal population in Kerala, impact thereof and the factors, if any, affecting proper utilization were considered as the research problem in this study. The study concentrated on the pattern of consumption of food grains by the tribal people, whether their hunger needs are met by distribution of food grains through the TPDS, extent to which TPDS in food grains reduce their share of expenditure on food in the total household expenditure, and the factors affecting the utilization of the TPDS in food grains by the tribal population. Going through the literature, it has been noted that only few studies concentrated on the utilization of TPDS in food grains among the tribal population in Kerala.The Research Design used in this study is descriptive in nature, but exploratory in some aspects. Idukki, Palakkad and Wayanad have more than 60% of the population of the tribals in the state. Within the three districts mentioned above, 14 villages with scheduled tribe concentration were selected for the study. 95 tribal colonies were selected from among the various tribal settlements. Collection of primary data was made from 1231 households with in the above tribal colonies. Analysis of data on the socio-economic factors of the tribal people, pattern of food consumption, extent of reduction in the share of expenditure on food among the household expenditure of the tribal people and the impact of TPDS on the tribal families etc. and testing of hypotheses to find out the relation/association of each of the six variables, using the data on BPL and APL categories of households separately have resulted in findings such as six percent of the tribal families do not have Ration Cards, average per capita consumption of food grains by the tribal people utilizing TPDS meets 62% of their minimum requirement, whereas the per capita consumption of food grains by the tribal people is higher than the national average per capita consumption, 63% deficiency in food grains may be felt by tribal people in general, if TPDS is withdrawn, and the deficit for BPL tribal people may be 82%, TPDS facilitates a reduction of 9.71% in the food expenditure among the total household expenditure of the tribal people in general, share of food to non-food among BPL category of tribals is 55:45 and 40:60 among the APL, Variables, viz. household income, number of members in the family and distance of FPS from tribal settlements etc. have influence on the quantity of rice being purchased by the tribal people from the Fair Price Shops, and there is influence of household income and distance of FPS from tribal settlements on the quantity of rice being purchased by the tribal people from the open market. Rationing with differential pricing on phased allotments, rectification of errors in targeting, anomalies in norms and procedures for classifying tribal people as BPL/APL, exclusive Income Generation for tribal population, paddy cultivation in the landholdings possessed by the tribal people, special drive for allotment of Ration Cards to the tribal people, especially those belonging to the BPL category, Mobile Fair Price Shops in tribal settlements, ensure quality of the food grains distributed through the TPDS, distribution of wheat flour in packed condition instead of wheat through the Fair Price Shops are recommended to address the shortcomings and weaknesses of the TPDS vis-avis the tribal population in Kerala.

Enhanced /3-adrenergic receptors in the brain and pancreas during pancreatic regeneration in weanling rats

Adrenergic stimulation has an inyortant role in the pancreatic It-cell proliferation and insulin secretion. In the present study. we have investigaled how sympathetic system mgulales the panrrealic n I rnerui nr ht an:ilyiing I'pinephi inn 1111 ), Norepinephrinc (NE) and /1-adrenergic receptor changes in the brain as (%eli is in the I swirls. Fill and NII showed a significant decrease in the brain regions, pancreas and plasma :rt 72Ius iller partial prurcrealectonty. We observed an increase in the circulating insulin levels at 72 hrs. Scatchard analysis using I CHI propranolol showed a significant increase in the number of loth the low affinity and high affinity t-adrenergic receplors in cerebral cortex and hypothalamus of partially pancreatectornised rats during peak DNA synthesis. The affinity of the receptors decrea,ed significantly in the low and high affinity receptors of cerebral cortex and the high affinity hypothalamic receptors. In file brain stein, low affinity receptors were increased significantly during regeneration whereas there was no change in the high affinity receptors. The pancreatic ff-adrenergic receptors were also up regulated at 72 firs after partial panerealectony. In vitro studies showed that /i-adrenergic receptors are positive regulators of islet cell proliferation and insulin secretion. Thus our results suggest that the t-adrenergic receptors are functionally enhanced during pancreatic regeneration, which in turn increases pancreatic ft-cell proliferation an(hilisulin secretion in wean hug rats.

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.

Decreased GyBAA Receptor Function in the Brain Stem during Pancreatic Regeneration in Rats

Gamma amino outyric acid is a major inhibitory neurotrarsr titter in the central nervous system. In the preset study sv, Have investigate(' the alteration of GABA receptor, In t he hrain stem of rats during pancreatic regeneration. Three groups of rats were used for the study: sham operated, 72 It and 7 days partially pancreatectonnsea. GABA was (juan- (ified by [H]GABA receptor iispiacement method. GABA receptor kin: 10, pat at i et•ers were studied by using the binding of F'.](iAhA as ligand to the Triton X-100 treated me,i1,;-:mes a1,J displacement with unlabelled GABA. GhRA,v receptor activity was studied by using the [` -1 h3cuculline and displacement with unlabellecV euculline. ;.\13A content significantly decreased (1' < (1.(101 ) it, 0-e brain stern during the regeneration of pancreas. 'I hl, high affinity (IAI3A receptor binding sho?:ed it sigii'f cant decrease in 131„.,\ (P < 11.01) and K,I 1).05) n 72 h and 7 days after partial pancreatee 'timv. ";:flhicuculline hin(Iing showed it signih eat, 'le ( r(, :,e in /Jn1,s and K,I (P < 0.001) in 72 h pa^.rcreaw,, mised rats when compared with sham wt--tt' as P,n and K,I reversed to near sham after 7 da,s of pancreatectomv. The results sugge,) that GAB A throur,r; ('GABA receptors in brain Atcem has a regulatory uie during active regeneration of pancreas which will have inunense clinical significance in the treatment of cliahetcs.

Signatures of Higher Functions of Brain Dynamics in Electroencephalogram: A Nonlinear Analysis

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.

Bone marrow cells differentiation to neurons in the rat brain using Serotonin and GABA:Their role on glutamate receptors, IP3, cAMP and cGMP functional regulation in unilateral Parkinsonism induced by 6-hydroxydopamine

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.

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

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.

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.

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.