A marine actinomycete nocardiopsis mccb 110 as source of novel drugs to manage vibriosis

Aquaculture is a form of agriculture that involves the propagation, cultivation and marketing of aquatic plants and animals in a controlled environment (Swann, 1992). After growing steadily, particularly in the last four decades, aquaculture is for the first time set to contribute half of the fish consumed by the human population worldwide. Given the projected population growth over the next two decades, it is estimated that at least an additional 40 million tonnes of aquatic food will be required by 2030 to maintain the current per capita consumption (FAO, 2006). Capture fisheries and aquaculture supplied the world with about 110 million tonnes of food fish in 2006. Of this total, aquaculture accounted for 47 percent (FAO, 2009). Globally, penaeid shrimp culture ranks sixth in terms of quantity and second in terms of value amongst all taxonomic groups of aquatic animals cultivated (FAO, 2006). In places where warm-water aquaculture was possible black tiger shrimp, Penaeus monodon became the preferred variety of shrimp cultivar owing to its fast growth, seed availability and importantly due to high prices it fetches (Pechmanee, 1997). World shrimp production is dominated by P.monodon, which accounted for more than 50 % of the production in 1999 (FAO, 2000). In the last few years the whiteleg shrimp, Litopenaeus vannamei, has replaced P.monodon in many countries. Indian shrimp culture is dominated by P.monodon with the East Coast accounting for 70% of the production (Hein, 2002). Intensive culture, apart from other problems, results in enhanced susceptibility of the cultured species to diseases (Jory, 1997), which in fact have become the biggest constraint in shrimp aquaculture (FAO, 2003).

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.