Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network.

Visual and efficient immunosensor technique for advancing biomedical applications of quantum dots on Salmonella detection and isolation.

It is a great challenge in nanotechnology for fluorescent nanobioprobes to be applied to visually detect and directly isolate pathogens in situ. A novel and visual immunosensor technique for efficient detection and isolation of Salmonella was established here by applying fluorescent nanobioprobes on a specially-designed cellulose-based swab (a solid-phase enrichment system). The selective and chromogenic medium used on this swab can achieve the ultrasensitive amplification of target bacteria and form chromogenic colonies in situ based on a simple biochemical reaction.

Rapid Assessment of Adverse Drug Reactions by Statistical Solution of Gene Association Network.

Adverse drug reaction (ADR) is a common clinical problem, sometimes accompanying with high risk of mortality and morbidity. It is also one of the major factors that lead to failure in new drug development. Unfortunately, most of current experimental and computational methods are unable to evaluate clinical safety of drug candidates in early drug discovery stage due to the very limited knowledge of molecular mechanisms underlying ADRs.

[Application of niche theory in evaluation of main tourism scenic areas in Zhangjiajie City].

Five tourism scenic areas in Zhangjiajie City were selected as research objects, and fifty kinds of resource conditions affecting the development of tourism scenic area were taken as evaluation indices. Through disposing and consolidating the indices level by level, an analysis was made on the niche breadth and niche overlap of the five tourism scenic areas at three levels (I, II, and III). In the five scenic areas, index level had significant effects on the niche breadth (F = 10.