✍ Scribed by Huabei Zhang
No coin nor oath required. For personal study only.
A nonlinear model equation based on tissue composition (a content of lipids, proteins, and water) for the tissue/blood partition coefficients of compounds was developed. Based on this model, our nonlinear regression analysis for neutral compounds partitioning into the kidney, brain, muscle, lung, liver, heart, and fat resulted in equations with high fitting power (training set: n ¼ 166, r 2 ¼ 0.851, s ¼ 0.260, Q 2 ¼ 0.833) and strong predictive power (test set: n ¼ 49, r 2 ¼ 0.851, s ¼ 0.246, Q 2 ¼ 0.836). This model shows that the tissue/blood partition coefficients of a compound depend strongly on tissue compositions. The magnitudes of partition coefficients of a compound in different tissues are mainly modulated by volume fractions or weight fractions of tissue compositions.
📜 SIMILAR VOLUMES
Partitioning of up to thirty-six nonionizable chemicals between seven tissues (fat, liver, brain, kidney, muscle, lung, heart) and blood in humans was modeled using membrane accumulation, protein binding, and distribution in the aqueous phases as relevant processes. The extent of membrane accumulati
## Abstract **Summary:** A new method for the measurement of monomer partitioning for emulsion polymerisation is presented. The method is based on measuring the partition coefficients for films cast from different latexes. Its validity was demonstrated for methyl methacrylate (MMA) and butyl acryla
## Abstract We show that highly porous silica‐based nanoparticles prepared via micro‐emulsion and sol–gel techniques are stable colloids in aqueous solution. By incorporating a magnetic core into the porous silica nano‐composite, it is found that the material can be rapidly separated (precipitated)