Feasibility Study on Vanillin Production from Jatropha curcas Stem Using Steam Explosion as a Pretreatment

Jatropha curcas stem was analyzed for chemical compositions: 19.11% pentosan, 42.99% alphacellulose and 24.11% lignin based on dry weight of 100-g raw material. The condition to fractionate cellulose, hemicellulose and lignin in J. curcas stem using steam explosion was optimized. The procedure started from cutting J. curcas stem into small pieces and soaked in water for overnight. After that, they were steam exploded at 214 °C and 21 kg/cm2 for 5 min. The obtained hydrolysate contained 1.55 g/L ferulic acid which after that was used as substrate for vanillin production by Aspergillus niger and Pycnoporus cinnabarinus in one-step process. The maximum 0.65 g/L of vanillin were obtained with the conversion rate of 45.2% based on the initial ferulic acid.

Analysis of Physicochemical Properties on Prediction of R5, X4 and R5X4 HIV-1 Coreceptor Usage

Bioinformatics methods for predicting the T cell coreceptor usage from the array of membrane protein of HIV-1 are investigated. In this study, we aim to propose an effective prediction method for dealing with the three-class classification problem of CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made efforts in investigating the coreceptor prediction problem as follows: 1) proposing a feature set of informative physicochemical properties which is cooperated with SVM to achieve high prediction test accuracy of 81.48%, compared with the existing method with accuracy of 70.00%; 2) establishing a large up-to-date data set by increasing the size from 159 to 1225 sequences to verify the proposed prediction method where the mean test accuracy is 88.59%, and 3) analyzing the set of 14 informative physicochemical properties to further understand the characteristics of HIV-1coreceptors.

Glucose-dependent Functional Heterogeneity In β-TC-6 Murine Insulinoma

To determine if the murine insulinoma, β-TC-6, is a suitable substitute for primary pancreatic β-cells in the study of β- cell functional heterogeneity, we used three distinct functional assays to ascertain the cell line-s response to glucose or a glucose analog. These assays include: (i) a 2-NBDG uptake assay; (ii) a calcium influx assay, and; (iii) a quinacrine secretion assay. We show that a population of β-TC-6 cells endocytoses the glucose analog, 2- NBDG, at different rates, has non-uniform intracellular calcium ion concentrations and releases quinacrine at different rates when challenged with glucose. We also measured the Km for β-TC-6 glucose uptake to be 46.9 mM and the Vm to be 8.36 x 10-5 mmole/million cells/min. These data suggest that β-TC-6 might be used as an alternative to primary pancreatic β-cells for the study of glucose-dependent β-cell functional heterogeneity.

Tolerance of Heavy Metals by Gram Positive Soil Bacteria

With the intention of screening for heavy metal tolerance, a number of bacteria were isolated and characterized from a pristine soil. Two Gram positive isolates were identified as Paenibacillus sp. and Bacillus thuringeinsis. Tolerance of Cd2+, Cu2+ and Zn2+ by these bacteria was studied and found that both bacteria were highly sensitive to Cu2+ compared to other two metals. Both bacteria showed the same pattern of metal tolerance in the order Zn+ > Cd2+ > Cu2+. When the metal tolerance in both bacteria was compared, Paenibacillus sp. showed the highest sensitivity to Cu2+ where as B. thuringiensis showed highest sensitivity to Cd2+ and Zn2+ .These findings revealed the potential of Paenibacillus sp. in developing a biosensor to detect Cu2+ in environmental samples.

Optimization of Protein Hydrolysate Production Process from Jatropha curcas Cake

This was the first document revealing the investigation of protein hydrolysate production optimization from J. curcas cake. Proximate analysis of raw material showed 18.98% protein, 5.31% ash, 8.52% moisture and 12.18% lipid. The appropriate protein hydrolysate production process began with grinding the J. curcas cake into small pieces. Then it was suspended in 2.5% sodium hydroxide solution with ratio between solution/ J. curcas cake at 80:1 (v/w). The hydrolysis reaction was controlled at temperature 50 °C in water bath for 45 minutes. After that, the supernatant (protein hydrolysate) was separated using centrifuge at 8000g for 30 minutes. The maximum yield of resulting protein hydrolysate was 73.27 % with 7.34% moisture, 71.69% total protein, 7.12% lipid, 2.49% ash. The product was also capable of well dissolving in water.

Virulent-GO: Prediction of Virulent Proteins in Bacterial Pathogens Utilizing Gene Ontology Terms

Prediction of bacterial virulent protein sequences can give assistance to identification and characterization of novel virulence-associated factors and discover drug/vaccine targets against proteins indispensable to pathogenicity. Gene Ontology (GO) annotation which describes functions of genes and gene products as a controlled vocabulary of terms has been shown effectively for a variety of tasks such as gene expression study, GO annotation prediction, protein subcellular localization, etc. In this study, we propose a sequence-based method Virulent-GO by mining informative GO terms as features for predicting bacterial virulent proteins. Each protein in the datasets used by the existing method VirulentPred is annotated by using BLAST to obtain its homologies with known accession numbers for retrieving GO terms. After investigating various popular classifiers using the same five-fold cross-validation scheme, Virulent-GO using the single kind of GO term features with an accuracy of 82.5% is slightly better than VirulentPred with 81.8% using five kinds of sequence-based features. For the evaluation of independent test, Virulent-GO also yields better results (82.0%) than VirulentPred (80.7%). When evaluating single kind of feature with SVM, the GO term feature performs much well, compared with each of the five kinds of features.