Chemiluminescent multiassay of pesticides with horseradish peroxidase as a label

Competitive chemiluminescent immunoassay based on a combination of five antibodies was used in a combination with neural network to identify and estimate amounts of three cross-reacting s-triazines (atrazine, terbythylazine and ametryn). Antibodies with different cross-reactivity towards s-triazines...

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Bibliographic Details
Published in:Biosensors & bioelectronics 1999-03, Vol.14 (3), p.273-281
Main Authors: Samsonova, Jeanne V, Rubtsova, Maya Yu, Kiseleva, Anna V, Ezhov, Alexander A, Egorov, Alexey M
Format: Article
Language:English
Subjects:
Antibodies
Atrazine - analysis
Cell immobilization
Chemiluminescence
Colorimetry
Cross Reactions
Enhanced chemiluminescence reaction
Enzyme-Linked Immunosorbent Assay
Enzymes
Herbicides - analysis
Horseradish Peroxidase
Immunology
Luminescent Measurements
Luminometer
Multianalyte immunoassay
Neural networks
Pattern recognition
Pesticides
Pesticides - analysis
s-Triazines
Sensitivity and Specificity
Triazines - analysis
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Summary:Competitive chemiluminescent immunoassay based on a combination of five antibodies was used in a combination with neural network to identify and estimate amounts of three cross-reacting s-triazines (atrazine, terbythylazine and ametryn). Antibodies with different cross-reactivity towards s-triazines were immobilized in separate wells an eight-well microtiter strip. Training of neural networks was carried out with four different learning procedures. The best topology for the data measured was a net with two hidden layers with ten neurons in the first and 15 in the second layer trained with the Schmidhuber method. s-Triazine classification of environmental samples containing various analyte mixtures was correct in 70–100% of all cases depending on the type of analyte. The test developed can be proposed as an alternative field test for multianalyte environmental monitoring.
ISSN:0956-5663
1873-4235
DOI:10.1016/S0956-5663(98)00129-8