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10.1371/journal.pone.0130494 http://scihub22266oqcxt.onion/10.1371/journal.pone.0130494 C4497723!4497723!26158701     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2015 ; 10 (7): ä Nephropedia Template TP {{tp|p=26158701|t=2015. Data-Driven Method to Estimate Nonlinear Chemical Equivalence |pdf=|usr=}}{{26158701}} gab.com Text Data-Driven Method to Estimate Nonlinear Chemical Equivalence JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=26158701 #FOAvip There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of ?equivalency factors,? which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or ?biphasic,? responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are ?parallel,? which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach. Twit Text FOAVip Data-Driven Method to Estimate Nonlinear Chemical Equivalence ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=26158701 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26158701 #FOAvip English Wikipedia <ref>{{Cite pmid|26158701}}</ref> Data-Driven Method to Estimate Nonlinear Chemical Equivalence #MMPMID26158701 Mayo M; Collier ZA; Winton C; Chappell MA PLoS One 2015[]; 10 (7): ä PMID26158701show ga There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of ?equivalency factors,? which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or ?biphasic,? responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are ?parallel,? which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach. äData-Driven Method to Estimate Nonlinear Chemical Equivalence (epmc).pdf DeepDyve Pubget Overpricing