Identificando as frutas para o desenvolvimento de smoothie para público infanto-juvenil.

Estimular maior consumo de frutas do público infanto-juvenil exige tanto pesquisas que indiquem os motivos que determinam as escolhas e preferências alimentares, quanto o desenvolvimento de produtos à base de frutas baseado na preferência do referido público. O smoothie, uma bebida elaborada exclusivamente de frutas, pode ampliar a oferta de produtos saudáveis. Para identificar as frutas que melhor combinam com essa bebida e obter as impressões sobre o consumo de frutas foram realizados quatro grupos focais com 30 crianças e adolescentes de 10 a 13 anos, em bairros da cidade do Rio de Janeiro com Índice de Desenvolvimento Humano - IDH médio e elevado. Dos resultados dos grupos focais foram obtidas as palavras utilizadas por eles para se referir à bebida e definir a combinação das frutas banana, manga e laranja como a mais adequadas. A doçura, a praticidade e o sabor sobressaíram como motivos para as escolhas.Food: the tree that sustains life. 477

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches

Stitching together Multiple Data Dimensions Reveals Interacting Metabolomic and Transcriptomic Networks That Modulate Cell Regulation

DNA variation can be used as a systematic source of perturbation in segregating populations as a way to infer regulatory networks via the integration of large-scale, high-dimensional molecular profiling data