Verification of FANTASTIC integrated code

FANTASTIC is an acronym for Failure Analysis Nonlinear Thermal and Structural Integrated Code. This program was developed by Failure Analysis Associates, Palo Alto, Calif., for MSFC to improve the accuracy of solid rocket motor nozzle analysis. FANTASTIC has three modules: FACT - thermochemical analysis; FAHT - heat transfer analysis; and FAST - structural analysis. All modules have keywords for data input. Work is in progress for the verification of the FAHT module, which is done by using data for various problems with known solutions as inputs to the FAHT module. The information obtained is used to identify problem areas of the code and passed on to the developer for debugging purposes. Failure Analysis Associates have revised the first version of the FANTASTIC code and a new improved version has been released to the Thermal Systems Branch

Computer codes for thermal analysis of a solid rocket motor nozzle

A number of computer codes are available for performing thermal analysis of solid rocket motor nozzles. Aerotherm Chemical Equilibrium (ACE) computer program can be used to perform one-dimensional gas expansion to determine the state of the gas at each location of a nozzle. The ACE outputs can be used as input to a computer program called Momentum/Energy Integral Technique (MEIT) for predicting boundary layer development development, shear, and heating on the surface of the nozzle. The output from MEIT can be used as input to another computer program called Aerotherm Charring Material Thermal Response and Ablation Program (CMA). This program is used to calculate oblation or decomposition response of the nozzle material. A code called Failure Analysis Nonlinear Thermal and Structural Integrated Code (FANTASTIC) is also likely to be used for performing thermal analysis of solid rocket motor nozzles after the program is duly verified. A part of the verification work on FANTASTIC was done by using one and two dimension heat transfer examples with known answers. An attempt was made to prepare input for performing thermal analysis of the CCT nozzle using the FANTASTIC computer code. The CCT nozzle problem will first be solved by using ACE, MEIT, and CMA. The same problem will then be solved using FANTASTIC. These results will then be compared for verification of FANTASTIC

Repertoire of SSRs in the Castor Bean Genome and Their Utilization in Genetic Diversity Analysis in Jatropha curcas

Castor bean and Jatropha contain seed oil of industrial importance, share taxonomical and biochemical similarities, which can be explored for identifying SSRs in the whole genome sequence of castor bean and utilized in Jatropha curcas. Whole genome analysis of castor bean identified 5,80,986 SSRs with a frequency of 1 per 680 bp. Genomic distribution of SSRs revealed that 27% were present in the non-genic region whereas 73% were also present in the putative genic regions with 26% in 5′UTRs, 25% in introns, 16% in 3′UTRs and 6% in the exons. Dinucleotide repeats were more frequent in introns, 5′UTRs and 3′UTRs whereas trinucleotide repeats were predominant in the exons. The transferability of randomly selected 302 SSRs, from castor bean to 49 J. curcas genotypes and 8 Jatropha species other than J. curcas, showed that 211 (∼70%) amplified on Jatropha out of which 7.58% showed polymorphisms in J. curcas genotypes and 12.32% in Jatropha species. The higher rate of transferability of SSR markers from castor bean to Jatropha coupled with a good level of PIC (polymorphic information content) value (0.2 in J. curcas genotypes and 0.6 in Jatropha species) suggested that SSRs would be useful in germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships, and so forth, in J. curcas as well as other Jatropha species

In Silico Identification and Comparative Genomics of Candidate Genes Involved in Biosynthesis and Accumulation of Seed Oil in Plants

Genes involved in fatty acids biosynthesis, modification and oil body formation are expected to be conserved in structure and function in different plant species. However, significant differences in the composition of fatty acids and total oil contents in seeds have been observed in different plant species. Comparative genomics was performed on 261 genes involved in fatty acids biosynthesis, TAG synthesis, and oil bodies formation in Arabidopsis, Brassica rapa, castor bean and soybean. In silico expression analysis revealed that stearoyl desaturase, FatB, FAD2, oleosin and DGAT are highly abundant in seeds, thereby considered as ideal candidates for mining of favorable alleles in natural population. Gene structure analysis for major genes, ACCase, FatA, FatB, FAD2, FAD3 and DGAT, which are known to play crucial role in oil synthesis revealed that there are uncommon variations (SNPs and INDELs) which lead to varying content and composition of fatty acids in seed oil. The predicted variations can provide good targets for seed oil QTL identification, understanding the molecular mechanism of seed oil accumulation, and genetic modification to enhance seed oil yield in plants

Repertoire of SSRs in the castor bean genome and their utilization in genetic diversity analysis

Castor bean and Jatropha contain seed oil of industrial importance, share taxonomical and biochemical similarities, which can be explored for identifying SSRs in the whole genome sequence of castor bean and utilized in Jatropha curcas. Whole genome analysis of castor bean identified 5,80,986 SSRs with a frequency of 1 per 680 bp. Genomic distribution of SSRs revealed that 27% were present in the non-genic region whereas 73% were also present in the putative genic regions with 26% in 5 UTRs, 25% in introns, 16% in 3 UTRs and 6% in the exons. Dinucleotide repeats were more frequent in introns, 5 UTRs and 3 UTRs whereas trinucleotide repeats were predominant in the exons. The transferability of randomly selected 302 SSRs, from castor bean to 49 J. curcas genotypes and 8 Jatropha species other than J. curcas, showed that 211 (∼70%) amplified on Jatropha out of which 7.58% showed polymorphisms in J. curcas genotypes and 12.32% in Jatropha species. The higher rate of transferability of SSR markers from castor bean to Jatropha coupled with a good level of PIC (polymorphic information content) value (0.2 in J. curcas genotypes and 0.6 in Jatropha species) suggested that SSRs would be useful in germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships, and so forth, in J. curcas as well as other Jatropha species

SMDB: Soybean Marker DataBase

Soybean Marker Database (SMDB) is a repository of important genomic information for soybean. At present several genomic databases are available for plants. Some of the important oilseeds plant databases are ATPID database, Castor Bean Genome Database, CGPDB, SoyBase, Legume Information System (LIS), Brassica database, Sinbase, etc. To gain comprehensive information from varied amount of resources, we developed  this database which provides general as well as specific information at universal level. Along with this it also furnishes gene level information for various functional categories such as transcription factor, disease resistant varieties, heat shock protein, genetically modified strain of soybean. The bunch of information available to researchers today increases in tremendous manner. Hence understanding the plant genome specific databases for acquiring specific information is the demand of time for crop improvement and  research programmes. SMDB is designed for the purpose of exploring potential gene differences in different plant genotypes, including genetically modified and disease resistant crops beneficial to the farmer who cultivate this crop. SMDB is publicly accessible for academic and research purpose at: http://www.bioinfoindia.org/smdb/

EFFICIENT HYDROALCOHOLIC EXTRACTION FOR HIGHEST DIOSGENIN CONTENT FROM TRILLIUM GOVANIANUM (NAG CHHATRI) AND IT'S IN VITRO ANTICANCEROUS ACTIVITY

ABSTRACTObjective: The present study involves hydroalcoholic extraction of Trillium govanianum (Hindi name: Nag chhatri), which is a high-value medicinalplant found at the altitude of 2500-4000 m. Aiming in this direction, we performed hydrolysis of extract using response surface methodology (RSM)for optimizing diosgenin content. The extracts were evaluated for cytotoxicity.Methods: In RSM, the cumulative effect of independent variables including time (minutes), temperature (°C), and solid-liquid ratio (g/ml)were investigated through central composite design. Cytotoxicity studies of crude rhizome and hydroalcoholic extract were carried out by3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay on three cell lines, viz., MDCK, MCF-7, and MDA-MB-23.Results: The diosgenin content obtained was 5.9%, which is reported for the first time in T. govanianum. Hydrolyzed extract showed less toxicity inMDCK (normal cell line) cells but significantly reduced the proliferation of MCF-7 and MDA-MB-231 cancer cells.Conclusion: Hydrolysis method was optimized by RSM, which proved to be an efficient method for extraction of diosgenin from T. govanianum.Hydrolyzed extract showed antiproliferative activity on cancer cell lines with minimal effect on normal cells.Keywords: Trillium govanianum, Diosgenin, Nag chhatri, Hydrolysis, MDCK, MCF-7, MDA-MB-231

Antibiotic susceptibility profile and detection of plasmid-mediated quinolone resistant genes among extended spectrum b-lactamases (ESBL) producing uropathogens in women

Background/Aim: The most common bacterial diseases in women around the world are urinary tract infections. Aim of this study, was to evaluate the prevalence and current antibiotic resistance rate of uropathogens isolated from the female patients of a tertiary care hospital in Amritsar, Punjab, India. Methods: Samples were collected from patients showing urinary tract infection (UTI) symptoms and analysed using microscopy, dipstick test and urine culturing followed by identification and characterisation of to identify the uropathogens. Antibiotic susceptibility test and MIC were performed. Results: The results revealed that E coli (35.5 %) was the most prominent uropathogen followed by Klebsiella spp (21 %), Enterobacter spp (17 %), Acinetobacter (11 %), Enterococcus spp (6 %), Pseudomonas spp (4.5 %), coagulase negative Staphylococci (4 %), coagulase-positive Staphylococci (0.5 %) and Corynebacterium aurimucosum (0.5 %). The antibiotic susceptibility profile study reported eight isolates with multi-drug resistance properties. However, gentamicin, imipenem and meropenem were found to be the most effective antibiotics against the isolated uropathogens. All the extended spectrum β-lactamase (ESBL)-positive isolates possess the quinolone-resistant gene qnrB, while qnrA was absent. Conclusion: The current study revealed that for appropriate treatment, it is crucial to be aware of the epidemiological data regarding the disease and to begin any empirical antibiotic treatment

Chauhan RS: In silico identification and comparative genomics of candidate genes involved in biosynthesis and accumulation of seed oil in plants. Comp Funct Genomics

Genes involved in fatty acids biosynthesis, modification and oil body formation are expected to be conserved in structure and function in different plant species. However, significant differences in the composition of fatty acids and total oil contents in seeds have been observed in different plant species. Comparative genomics was performed on 261 genes involved in fatty acids biosynthesis, TAG synthesis, and oil bodies formation in Arabidopsis, Brassica rapa, castor bean and soybean. In silico expression analysis revealed that stearoyl desaturase, FatB, FAD2, oleosin and DGAT are highly abundant in seeds, thereby considered as ideal candidates for mining of favorable alleles in natural population. Gene structure analysis for major genes, ACCase, FatA, FatB, FAD2, FAD3 and DGAT, which are known to play crucial role in oil synthesis revealed that there are uncommon variations (SNPs and INDELs) which lead to varying content and composition of fatty acids in seed oil. The predicted variations can provide good targets for seed oil QTL identification, understanding the molecular mechanism of seed oil accumulation, and genetic modification to enhance seed oil yield in plants