An Evaluation of Extension Activities in the Development of Aquaculture in Kerala

Aquaculture is one of the prime catalysts for the socio-economic development of Indian economy contributing to the nations food and nutritional security, export earnings, income and employment generation. In this study an evaluation of extension activities in the development of aquaculture in Kerala. This study was conducted with a view to examine how the Kerala fisheries department offered extension services to the aquaculture farmers in the freshwater and brackish water sectors of the state through various agencies like Fish Farmers Development Agency(FFDA), Brackish water Fish Farmers Development Agency (BFFDA). In this study there are 3 category of respondent’s fresh water beneficiary farmers, brackish water beneficiary farmers and fisheries extension officers. The main motive of the thesis is to make an attempt to explore the responses of local producers to the extension programs of the state with special reference to the aquaculture sector of Kerala, India. The most important technical constraint faced by the fresh water farmers was lack of knowledge followed by non-availability of quality seeds. In the case of brackish water farming, it was infection of disease followed by lack of knowledge. The overall activities of the department of fisheries were ‘fairly good’. It indicate the need for improvements in the delivery of extension services to various target groups. The state fisheries department has already moving towards evolving these modes of extension activities by community participation.

Molecular Characterization and Gene Expression Profiling of Antimicrobial Peptides in Penaeid Shrimps

The constitutive production of AMPs in shrimps ensures that animals are able to protect themselves from low-level assaults by pathogens present in the environment. As these molecules play important roles in the shrimp immune defense system, the expression level of these AMPs are possible indicators of the immune state of shrimps. The present study also indicates the antiviral property of AMPs, especially ALF, stressing the importance of their up-regulation through the application of immunostimulants/probiotics as a prophylactic strategy in aquaculture. The present study shows that shrimp defense system is equipped enough to evade WSSV infection to a certain extent, when the animals were maintained on marine yeast and probiotic diet, whereas the control diet fed group succumbed to WSSV infection. This study reveals that marine yeast and probiotic supplemented diet can delay the process of WSSV infection and confer greater protection to the animals. Particularly, the protection conferred by marine yeast, C. haemulonii S27 and Bacillus MCCB101 were highly promising imparting greater hope to the aquaculture community to overcome the prevailing disease problems in aquaculture. It may be inferred from the present study that up-regulation of AMP genes could be effected by the application of immunostimulants and probiotics. Also, AMP expression profile could be used as an effective tool for screening immunostimulants and probiotics for application in shrimp culture. Ultimately, it is likely that no single compound or strategy will provide a solution to the problem of disease within aquaculture and that, in reality, a suite of techniques will be required including the manipulation of the rearing environment, addition of probionts as a matter of routine during culture, and the use of immunostimulants and other supplements during vulnerable growth phases. Finally, the development of good management practices, the control of environmental variables, genetic improvement in the penaeid species, understanding of host-virus interaction, modulation of the shrimp immune system, supported by functional genomics and proteomics of this crustacean, as a whole suggests that the control of WSSV is not far.

Haematology of Fenneropenaeus indicus in response to environmental alterations and microbial infections

Aquaculture has developed to become one of the fastest growing food producing sectors in the world.Today India is one among the major shrimp producing countries in the world.There are extensive and intensive shrimp culture practices. In extensive shrimp culture, shrimps are stocked at low densities (< 25 PLs m'2)in large ponds or tidal enclosures in which little or no management is exercised or possible. Farmers depend almost entirely on natural conditions in extensive cultures. Intensive shrimp culture is carried out in high densities (>200 PLs m'2). Much of the world shrimp production still comes from extensive culture.There is a growing demand for fish and marine products for human and animal consumption. This demand has led to rapid growth of aquaculture, which some times has been accompanied by ecological impacts and economic loss due to diseases. The expansion of shrimp culture always accompanies local environmental degradation and occurrence of diseases.Disease out breaks is recognised as a significant constraint to aquaculture production. Environmental factors, water quality, pollution due to effluent discharge and pathogenic invasion due to vertical and horizontal transmission are the main causes of shrimp disease out breaks. Nutritional imbalance, toxicant and other pollutants also account for the onset of diseases. pathogens include viruses, bacteria, fungi and parasites.Viruses are the most economically significant pathogens of the cultured shrimps world wide. Disease control in shrimp aquaculture should focus first on preventive measures for eliminating disease promoting factors.ln order to design prophylactic and proactive measures against shrimp diseases, it is mandatory to understand the immune make up of the cultivable species, its optimum culture conditions and the physico chemical parameters of the rearing environment. It has been proven beyond doubt that disease is an end result of complex interaction of environment, pathogen and the host animal. The aquatic environment is abounded with infectious microbes.The transmission of disease in this environment is extremely easy, especially under dense, culture conditions. Therefore, a better understanding of the immune responses of the cultured animal in relation to its environmental alterations and microbial invasions is essential indevising strategic measures against aquaculture loss due to diseases. This study accentuate the importance of proper and regular health monitoring in shrimps employing the most appropriate haematological biomarkers for application of suitable prophylactic measures in order to avoid serious health hazards in shrimp culture systems.

An evaluation of Primary health care system in Kerala

The thesis entitled An Evaluation of Primary Health Care System in Kerala. The present study is intended to examine the working of primary health care system and its impact on the health status of people. The hypothesis tested in the thesis includes, a. The changes in the health profile require reallocation of resources of primary health care system, b. Rate of utilization depends on the quality of services provided by primary health centers, and c. There is a significant decline in the operational efficiency of the primary health care system. The major elements of primary health care stated in the report of AlmaAta International Conference on Primary Health Care (WHO, 1994)” is studied on the basis of the classification of the elements in to three: Preventive, Promotive, and Curative measures. Preventive measures include Maternal and Child Health Care including family Planning. Provision of water and sanitation is reviewed under promotive measures. Curative measures are studied using the disease profile of the study area. Collection of primary data was done through a sample survey, using pre-tested interview schedule of households of the study area. Multi stage random sampling design was used for selecting the sample. The design of the present study is both descriptive and analytical in nature. As far as the analytical tools are concerned, growth index, percentages, ratios, rates, time series analysis, analysis of variance, chi square test, Z test were used for analyzing the data. Present study revealed that no one in these areas was covered under any type of health insurance. Conclusion states that considering the present changes in the health profile, traditional pattern of resource allocation should be altered to meet the urgent health care needs of the people. Preventive and promotive measures like health education for giving awareness among people to change health habits, diet pattern, life style etc. are to be developed. Proper diagnosis and treatment of the disease at the beginning of the stage itself may help to cure majority of disease. For that, Public health policy must ensure the primary health care as enunciated at Alma- Ata international Conference. At the same time Public health is not to be treated as the sole responsibility of the government. Active community participation is an essential means to attain the goals.

Studies on the microbial diseases of dendrobium hybrid (orchids)

There is no baseline data available at present on the nature of various diseases that occur in a orchid population, under cultivation, in any commercial orchid farm maintained by small scale entrepreneurs who invest considerable amount of money, effort and time. The available data on type of disease symptoms, causative agent, , nature of pathogens, as to bacteria or ftmgi or any other biological agents, and their source, appropriate and effective control measures could not be devised, for large scale implementation and effective management, although arbitrary methods are being practiced by very few farms. Further influence of seasonal variations and environmental factors on disease outbreak is also not scientifically documented and statistically verified as to their authenticity. In this context, the primary objective of the present study was to create a data bank on the following aspects 1. Occurrence of different disease symptoms in Dendrobium hybrid over a period of one year covering all seasons 2. Variations in the environmental parameters at the orchid farms 3. Variations in the characteristics of water used for irrigation in the selected orchid farm 4. Microbial population associated with the various disease symptoms 5. Isolation and identification of bacteria isolated from diseased plants 6. Statistical treatment of the quantitative data and evolving statistical model

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

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.

Characterization and virulence potential of phenotypically diverse Aeromonas veronii isolates recovered from moribund freshwater ornamental fishes of Kerala, India

In the present study, we investigated the involvement of Aeromonas spp. in eliciting disease outbreaks in freshwater ornamental fishes across the state of Kerala, India. We investigated three incidences of disease, in which the moribund fishes exhibited clinical signs such as haemorrhagic septicemia (in gouramy, Trichogaster sp.), dropsy (in Oscar, Astronotus ocellatus) and tail rot/fin rot (in gold fish, Carassius carassius). Pure cultures (n = 20 from each fish; 60 in total) of Aeromonas spp. were recovered from the abdominal fluid as well as from internal organs of affected fishes, although they could not be identified to species level because of the variations in their phenotypic characters. The molecular fingerprinting of the isolates using Enterobacterial Repetitive Intergenic Consensus PCR proved the genetic diversity of the isolates from the three sites. The phylogenetic trees constructed using concatenated sequences (using 16S rRNA, gyrA, gyrB and rpoD genes) indicated that they were related to Aeromonas veronii. They exhibited marked cytotoxic and haemolytic activity, which were responsible for the pathogenic potential of the isolates. The isolates possessed multiple virulence genes such as enterotoxins (act and alt), haemolytic toxins (aerA and hlyA), genes involved in type III secretion system (ascV, aexT and ascF–ascG), glycerophospholipid-cholesterol acyltransferase (gcat) and a type IV pilus (tapA) gene, as determined by PCR. Virulence of representative isolates to goldfish was also tested, and we found LD50 values of 104.07–105.35 cfu/fish. Furthermore, the organisms could be recovered as pure cultures from the lesions as well as from the internal organs.

Soft Computing Approach for Optimization of siRNA Efficiency Prediction for Post-transcriptional Gene Silencing

Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics.