Novel insights into the kinetics and mechanism of arsenopyrite bio-dissolution enhanced by pyrite.

Arsenopyrite and pyrite often coexist in metal deposits and tailings, thus simultaneous bioleaching of both sulfides has economic (as well as environmental) significance. Important targets in bio-oxidation operations are high solubilization rates and minimized accumulation of Fe(III)/As-bearing secondary products. This study investigated the role of pyrite bioleaching in the enhancement of arsenopyrite dissolution.

Identification and profiling of the community structure and potential function of bacteria from the fruiting bodies of Sanghuangporus vaninii.

Sanghuangporus sp., a medicinal and edible homologous macrofungus known as 'forest gold', which has good effects on antitumor, hypolipidemia and the treatment of gynecological diseases. However, the natural resources of fruiting body are on the verge of depletion due to its long growth cycle and over exploitation.

In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology.

Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of Mycobacterium tuberculosis (Mtb). Bacillus Calmette-Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine.

Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method.

Mitochondrial dysfunction has been considered as an important contributing factor in the etiology of drug-induced organ toxicity, and even plays an important role in the pathogenesis of some diseases. The objective of this investigation was to develop a novel prediction model of drug-induced mitochondrial toxicity by using a naïve Bayes classifier. For comparison, the recursive partitioning classifier prediction model was also constructed.

Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method.

Toxicological testing associated with developmental toxicity endpoints are very expensive, time consuming and labor intensive. Thus, developing alternative approaches for developmental toxicity testing is an important and urgent task in the drug development filed. In this investigation, the naïve Bayes classifier was applied to develop a novel prediction model for developmental toxicity.

Predicting drug-induced liver injury in human with Naïve Bayes classifier approach.

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task.

[Diversity of uncultured actinomycetes in saline-alkali soil from Jiuquan area of Hexi Corridor].

In order to more accurately understand community structure and diversity of actinomycetes in saline-alkali soil from Jiuquan area of Hexi Corridor, the community structure and diversity from three kinds of soil samples (primary, secondary saline alkali soil and farmland soil) were analyzed using uncultured methods. The results showed that the 16S rDNA clone library of actinomycetales from the primary saline-alkali soil belonged to 19 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; the 16S r DNA clone library of actinomycetales from the secondary saline-alkali soil belonged to 14 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; the 16S rDNA clone library of farmland soil belonged to 7 OTUs, Micrococcineae, Propionibacterineae, Corynebacterineae, Frankineae, Pseudonocardineae and unknown groups of Actinomycetales; Micrococcineae was the common population in the three soils, and also was the dominant population in primary saline alkali soil and farmland soil. The diversity index and rarefaction curves analysis showed that actinomycetes species richness was in order of primary saline-alkali soil > secondary saline-alkali soil > farmland soil.

Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.

Drug-induced eosinophilia is a potentially life-threatening adverse effect; clinical manifestations, eosinophilia-myalgia syndrome, mainly include severe skin eruption, fever, hematologic abnormalities, and organ system dysfunction. Using experimental methods to evaluate drug-induced eosinophilia is very complicated, time-consuming, and costly in the early stage of drug development. Thus, in this investigation, we established computational prediction models of drug-induced eosinophilia using SVM and naïve Bayesian approaches.