Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.

The late adopter scale: A measure of late adopters of technological innovations

Diffusion of Innovation is a topic of interest for researchers and practitioners. Although substantial research is conducted on user categories, researchers often focus on the first half of the curve, ignoring the late adopters. We conduct two studies to measure the attributes of late adopters. In our first study of mobile phone users, we develop the Late-Adopter Scale. We then test it on a sample of laptop users. This scale is multi-dimensional, presents nomological and discriminant validity and has three dimensions: 1) rate of adoption, 2) resistance to innovation, and 3) skepticism. Findings reveal that all three Late Adopter Scale dimensions are significantly associated with low price preference. Moreover, in both samples skepticism is associated with high preference for simple products, lower leading edge status, and lower product involvement. Discussion focuses on implications of this new scale to theory and practice of new product development and diffusion of innovation.