Primary hemocyte culture of Penaeus monodon as an in vitro model for white spot syndrome virus titration, viral and immune related gene expression and cytotoxicity assays

Immortal cell lines have not yet been reported from Penaeus monodon, which delimits the prospects of investigating the associated viral pathogens especially white spot syndrome virus (WSSV). In this context, a method of developing primary hemocyte culture from this crustacean has been standardized by employing modified double strength Leibovitz-15 (L-15) growth medium supplemented with 2% glucose, MEM vitamins (1 ), tryptose phosphate broth (2.95 g l 1), 20% FBS, N-phenylthiourea (0.2 mM), 0.06 lgml 1 chloramphenicol, 100 lgml 1 streptomycin and 100 IU ml 1 penicillin and hemolymph drawn from shrimp grown under a bio-secured recirculating aquaculture system (RAS). In this medium the hemocytes remained viable up to 8 days. 5-Bromo-20-deoxyuridine (BrdU) labeling assay revealed its incorporation in 22 ± 7% of cells at 24 h. Susceptibility of the cells to WSSV was confirmed by immunofluoresence assay using a monoclonal antibody against 28 kDa envelope protein of WSSV. A convenient method for determining virus titer as MTT50/ml was standardized employing the primary hemocyte culture. Expression of viral genes and cellular immune genes were also investigated. The cell culture could be demonstrated for determining toxicity of a management chemical (benzalkonium chloride) by determining its IC50. The primary hemocyte culture could serve as a model for WSSV titration and viral and cellular immune related gene expression and also for investigations on cytotoxicity of aquaculture drugs and chemicals

Alignment Model and Training Technique in SMT from English to Malayalam

This paper investigates certain methods of training adopted in the Statistical Machine Translator (SMT) from English to Malayalam. In English Malayalam SMT, the word to word translation is determined by training the parallel corpus. Our primary goal is to improve the alignment model by reducing the number of possible alignments of all sentence pairs present in the bilingual corpus. Incorporating morphological information into the parallel corpus with the help of the parts of speech tagger has brought around better training results with improved accuracy