RT-Bst: an integrated approach for reverse transcription and enrichment of cDNA from viral RNA

The synthesis of cDNA from RNA is challenging due to the inefficiency of reverse transcription (RT). In order to address this, a method was developed known as RT-Bst for sequential RT of RNA and Bst DNA polymerase amplification for enrichment of cDNA in a single tube reaction. Using genomic RNA from bacteriophage MS2, the yield of cDNA produced by RT alone and RT-Bst were compared by analysis of PCR-amplified products. Using random primers a superior performance was observed when amplifying MS2 RNA following RT-Bst compared to RT alone, indicating that greater quantities of cDNA were present after RT-Bst. RT-Bst was also compared with RT alone for their relative ability to produce sufficient cDNA to amplify 8 target regions spanning the respiratory syncytial virus (RSV) genome. Six out of 8 targets were amplified consistently by PCR subsequent to RT-Bst amplification whereas only 3 out of 8 targets could be amplified after RT alone. RSV sequences were selectively amplified using RSV specific primers from a mixed template containing an excess of MS2 RNA in a RT-Bst reaction without amplifying MS2 sequences. This suggests that RT-Bst can be used to amplify RNA sequences non-specifically using random primers and specifically using sequence specific primers and enhances the yield of cDNA when compared to RT alone.

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimization approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment, and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimization technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.