Vendelboturner6286

Based on comprehensive P efficiency measurement, IPM-288, TM 96-25, TM 96-2, M 1477, PUSA 1342 were found to be the best highly efficient genotypes, whereas M 1131, PS-16, Pusa Vishal, M 831, IC 325828 were highly inefficient. Highly efficient genotypes identified would be valuable genetic resources for P efficiency for utilizing in the mungbean breeding programme.Developing new food products is a complex process. Even if a company performs new product development activities successfully, it is still uncertain if consumers will adopt the product. The Bass diffusion model has often been used to study product adoption. However, existing modifications of the Bass diffusion model do not capture the complexity of consumer food choice and they have limitations in situations where there is no sales data. To avoid these challenges, the system dynamics approach can be employed. This paper aimed at extending the existing system dynamics Bass diffusion model to investigate the dynamic adoption process of insect-based food from a consumer research perspective. We performed a structured review of the literature on edible insects to build the model. The model was used to study adoption of the product amongst consumers in the Netherlands. Simulations revealed that diffusion of a radical innovation, such as an insect-based burger, can proceed for many years before there are observable adopters in the total population, under the currently reported practices in the Netherlands. Expanding awareness of this innovation requires many decades, which can be quickened by developing strategies aimed at increasing word-of-mouth. Nevertheless, the low likelihood to adopt such food remains a challenge towards full adoption, even when the sensory quality of products is improved. To fully explore how to improve the diffusion outcome of edible insects, more knowledge on mechanisms related to positive and negative word-of-mouth, and adoption of insect-based burgers by people who initially reject them, is needed. Selleck Ataluren Our study demonstrated that system dynamics models could have potential in designing new food product strategies in companies, as they facilitate decision-making and uncover knowledge gaps.Introduction Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements. Methods We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken. Results Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements. Conclusion The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.HIV invades the brain during acute infection. Yet, it is unknown whether long-lived infected brain cells release productive virus that can egress from the brain to re-seed peripheral organs. This understanding has significant implication for the brain as a reservoir for HIV and most importantly HIV interplay between the brain and peripheral organs. Given the sheer number of astrocytes in the human brain and their controversial role in HIV infection, we evaluated their infection in vivo and whether HIV infected astrocytes can support HIV egress to peripheral organs. We developed two novel models of chimeric human astrocyte/human peripheral blood mononuclear cells NOD/scid-IL-2Rgc null (NSG) mice (huAstro/HuPBMCs) whereby we transplanted HIV (non-pseudotyped or VSVg-pseudotyped) infected or uninfected primary human fetal astrocytes (NHAs) or an astrocytoma cell line (U138MG) into the brain of neonate or adult NSG mice and reconstituted the animals with human peripheral blood mononuclear cells (PBMCs). We also transplanted uninfected astrocytes into the brain of NSG mice and reconstituted with infected PBMCs to mimic a biological infection course. As expected, the xenotransplanted astrocytes did not escape/migrate out of the brain and the blood brain barrier (BBB) was intact in this model. We demonstrate that astrocytes support HIV infection in vivo and egress to peripheral organs, at least in part, through trafficking of infected CD4+ T cells out of the brain. Astrocyte-derived HIV egress persists, albeit at low levels, under combination antiretroviral therapy (cART). Egressed HIV evolved with a pattern and rate typical of acute peripheral infection. Lastly, analysis of human cortical or hippocampal brain regions of donors under cART revealed that astrocytes harbor between 0.4-5.2% integrated HIV gag DNA and 2-7% are HIV gag mRNA positive. These studies establish a paradigm shift in the dynamic interaction between the brain and peripheral organs which can inform eradication of HIV reservoirs.