Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractQuantitative structure-activity relationship models for prediction of sensory irritants (logRD50) of volatile organic chemicals    Next Abstract[Regulations and policies for control of volatile organic compounds and the emission standards in Taiwan] »

Ecotoxicol Environ Saf


Title:QSPR analysis of air-to-blood distribution of volatile organic compounds
Author(s):Luan F; Liu HT; Ma WP; Fan BT;
Address:"Department of Applied Chemistry, Yantai University, Yantai 264005, PR China. fluan@sina.com"
Journal Title:Ecotoxicol Environ Saf
Year:2008
Volume:20071211
Issue:3
Page Number:731 - 739
DOI: 10.1016/j.ecoenv.2007.10.024
ISSN/ISBN:1090-2414 (Electronic) 0147-6513 (Linking)
Abstract:"Quantitative structure property relationship (QSPR) models for the prediction of human blood:air partition coefficient (log K(blood)) of volatile organic compounds (VOCs) has been developed based on the linear heuristic method (HM) and non-linear radial basis function neural networks (RBFNNs). Molecular descriptors that are calculated from the structures alone were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. RBFNN was performed to obtain more accurate models. Both the linear and the non-linear models can give very satisfactory prediction results: the correlation coefficient R was 0.964 and 0.979, and the root-mean-square (RMS) error was 0.3303 and 0.2542 for the whole data set, respectively. The prediction result of the non-linear model is better than that obtained by the linear model. In addition, this paper provides an effective method for predicting log K(blood) from its structures and gives some insight into the structural features related to the solubility of VOCs in human blood"
Keywords:"Air Air Pollutants/blood/*metabolism Humans Linear Models Models, Biological Models, Chemical Neural Networks, Computer Nonlinear Dynamics Quantitative Structure-Activity Relationship Solubility Volatile Organic Compounds/blood/*metabolism;"
Notes:"MedlineLuan, F Liu, H T Ma, W P Fan, B T eng Netherlands 2007/12/11 Ecotoxicol Environ Saf. 2008 Nov; 71(3):731-9. doi: 10.1016/j.ecoenv.2007.10.024. Epub 2007 Dec 11"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 26-12-2024