Multi-analyte assay for triazines using cross-reactive antibodies and neural networks
A biosensor system based on total internal reflectance fluorescence (TIRF) was used to discriminate a mixture of the triazines atrazine and simazine. Only cross-reactive antibodies were available for these two analytes. The biosensor is fully automated and can be regenerated allowing several hundred...
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creator | Reder, Sabine Dieterle, Frank Jansen, Hendrikus Alcock, Susan Gauglitz, Günter |
description | A biosensor system based on total internal reflectance fluorescence (TIRF) was used to discriminate a mixture of the triazines atrazine and simazine. Only cross-reactive antibodies were available for these two analytes. The biosensor is fully automated and can be regenerated allowing several hundreds of measurements without any user input. Even a remote control for online monitoring in the field is possible. The multivariate calibration of the sensor signal was performed using artificial neural networks, as the relationship between the sensor signals and the concentration of the analytes is highly non-linear. For the development of a multi-analyte immunoassay consisting of two polyclonal antibodies with cross-reactivity to atrazine and simazine and different derivatives immobilised on the transducer surface, the binding characteristics between these substances like binding capacity and cross-reactivity were characterised. The examination of three different measurement procedures showed that a two-step measurement using only one antibody per step allows a quantification of both analytes in a mixture with limits of detection of 0.2 μg/l for atrazine and 0.3 μg/l for simazine. The biosensor is suitable for online monitoring in the field and remote control is possible. |
doi_str_mv | 10.1016/S0956-5663(03)00202-1 |
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Only cross-reactive antibodies were available for these two analytes. The biosensor is fully automated and can be regenerated allowing several hundreds of measurements without any user input. Even a remote control for online monitoring in the field is possible. The multivariate calibration of the sensor signal was performed using artificial neural networks, as the relationship between the sensor signals and the concentration of the analytes is highly non-linear. For the development of a multi-analyte immunoassay consisting of two polyclonal antibodies with cross-reactivity to atrazine and simazine and different derivatives immobilised on the transducer surface, the binding characteristics between these substances like binding capacity and cross-reactivity were characterised. The examination of three different measurement procedures showed that a two-step measurement using only one antibody per step allows a quantification of both analytes in a mixture with limits of detection of 0.2 μg/l for atrazine and 0.3 μg/l for simazine. The biosensor is suitable for online monitoring in the field and remote control is possible.</description><identifier>ISSN: 0956-5663</identifier><identifier>EISSN: 1873-4235</identifier><identifier>DOI: 10.1016/S0956-5663(03)00202-1</identifier><identifier>PMID: 14623469</identifier><language>eng</language><publisher>Lausanne: Elsevier B.V</publisher><subject>Algorithms ; Antibodies - chemistry ; Antibodies - immunology ; Atrazine - analysis ; Atrazine - chemistry ; Atrazine - immunology ; Biological and medical sciences ; Biosensing Techniques - instrumentation ; Biosensing Techniques - methods ; Biosensors ; Biotechnology ; Calibration ; Complex Mixtures - analysis ; Complex Mixtures - chemistry ; Cross-reactivity ; Equipment Design ; Equipment Failure Analysis - methods ; Feasibility Studies ; Fluoroimmunoassay - instrumentation ; Fluoroimmunoassay - methods ; Fundamental and applied biological sciences. Psychology ; Methods. Procedures. Technologies ; Multi-analyte assay ; Neural networks ; Neural Networks (Computer) ; Reproducibility of Results ; Sensitivity and Specificity ; Simazine - analysis ; Simazine - chemistry ; Simazine - immunology ; TIRF ; Triazines ; Triazines - analysis ; Triazines - chemistry ; Triazines - immunology ; Various methods and equipments</subject><ispartof>Biosensors & bioelectronics, 2003-12, Vol.19 (5), p.447-455</ispartof><rights>2003 Elsevier B.V.</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-b600d8a9f2a80c6d31329ef2a947100a85ebf0b78e984598dc2c92de2f76020a3</citedby><cites>FETCH-LOGICAL-c422t-b600d8a9f2a80c6d31329ef2a947100a85ebf0b78e984598dc2c92de2f76020a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0956566303002021$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15474427$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/14623469$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Reder, Sabine</creatorcontrib><creatorcontrib>Dieterle, Frank</creatorcontrib><creatorcontrib>Jansen, Hendrikus</creatorcontrib><creatorcontrib>Alcock, Susan</creatorcontrib><creatorcontrib>Gauglitz, Günter</creatorcontrib><title>Multi-analyte assay for triazines using cross-reactive antibodies and neural networks</title><title>Biosensors & bioelectronics</title><addtitle>Biosens Bioelectron</addtitle><description>A biosensor system based on total internal reflectance fluorescence (TIRF) was used to discriminate a mixture of the triazines atrazine and simazine. Only cross-reactive antibodies were available for these two analytes. The biosensor is fully automated and can be regenerated allowing several hundreds of measurements without any user input. Even a remote control for online monitoring in the field is possible. The multivariate calibration of the sensor signal was performed using artificial neural networks, as the relationship between the sensor signals and the concentration of the analytes is highly non-linear. For the development of a multi-analyte immunoassay consisting of two polyclonal antibodies with cross-reactivity to atrazine and simazine and different derivatives immobilised on the transducer surface, the binding characteristics between these substances like binding capacity and cross-reactivity were characterised. The examination of three different measurement procedures showed that a two-step measurement using only one antibody per step allows a quantification of both analytes in a mixture with limits of detection of 0.2 μg/l for atrazine and 0.3 μg/l for simazine. The biosensor is suitable for online monitoring in the field and remote control is possible.</description><subject>Algorithms</subject><subject>Antibodies - chemistry</subject><subject>Antibodies - immunology</subject><subject>Atrazine - analysis</subject><subject>Atrazine - chemistry</subject><subject>Atrazine - immunology</subject><subject>Biological and medical sciences</subject><subject>Biosensing Techniques - instrumentation</subject><subject>Biosensing Techniques - methods</subject><subject>Biosensors</subject><subject>Biotechnology</subject><subject>Calibration</subject><subject>Complex Mixtures - analysis</subject><subject>Complex Mixtures - chemistry</subject><subject>Cross-reactivity</subject><subject>Equipment Design</subject><subject>Equipment Failure Analysis - methods</subject><subject>Feasibility Studies</subject><subject>Fluoroimmunoassay - instrumentation</subject><subject>Fluoroimmunoassay - methods</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Methods. Procedures. Technologies</subject><subject>Multi-analyte assay</subject><subject>Neural networks</subject><subject>Neural Networks (Computer)</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Simazine - analysis</subject><subject>Simazine - chemistry</subject><subject>Simazine - immunology</subject><subject>TIRF</subject><subject>Triazines</subject><subject>Triazines - analysis</subject><subject>Triazines - chemistry</subject><subject>Triazines - immunology</subject><subject>Various methods and equipments</subject><issn>0956-5663</issn><issn>1873-4235</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtv1DAQgC0EotvCTwDlAoJDYPxIHJ8QqiggFXGAnq2JPUGGrFNsp2j59Xi7K3qsZGlkzTevj7FnHN5w4P3bb2C6vu36Xr4C-RpAgGj5A7bhg5atErJ7yDb_kRN2mvNPANDcwGN2wlUvpOrNhl19WecSWow47wo1mDPummlJTUkB_4ZIuVlziD8al5ac20ToSripYCxhXHyoeYy-ibQmnGsof5b0Kz9hjyacMz09xjN2dfHh-_mn9vLrx8_n7y9bp4Qo7dgD-AHNJHAA13vJpTBUf0ZpDoBDR-MEox7IDKozg3fCGeFJTLqvB6M8Yy8Pfa_T8nulXOw2ZEfzjJGWNVvNpR5kbXsfyI3gVRRUsDuAt_cmmux1CltMO8vB7sXbW_F2b9VCfXvxdj_g-XHAOm7J31UdTVfgxRHA7HCeEkYX8h3XKa2U0JV7d-CoersJlGx2gaIjHxK5Yv0S7lnlH_LGn9g</recordid><startdate>20031230</startdate><enddate>20031230</enddate><creator>Reder, Sabine</creator><creator>Dieterle, Frank</creator><creator>Jansen, Hendrikus</creator><creator>Alcock, Susan</creator><creator>Gauglitz, Günter</creator><general>Elsevier B.V</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20031230</creationdate><title>Multi-analyte assay for triazines using cross-reactive antibodies and neural networks</title><author>Reder, Sabine ; Dieterle, Frank ; Jansen, Hendrikus ; Alcock, Susan ; Gauglitz, Günter</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-b600d8a9f2a80c6d31329ef2a947100a85ebf0b78e984598dc2c92de2f76020a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Algorithms</topic><topic>Antibodies - chemistry</topic><topic>Antibodies - immunology</topic><topic>Atrazine - analysis</topic><topic>Atrazine - chemistry</topic><topic>Atrazine - immunology</topic><topic>Biological and medical sciences</topic><topic>Biosensing Techniques - instrumentation</topic><topic>Biosensing Techniques - methods</topic><topic>Biosensors</topic><topic>Biotechnology</topic><topic>Calibration</topic><topic>Complex Mixtures - analysis</topic><topic>Complex Mixtures - chemistry</topic><topic>Cross-reactivity</topic><topic>Equipment Design</topic><topic>Equipment Failure Analysis - methods</topic><topic>Feasibility Studies</topic><topic>Fluoroimmunoassay - instrumentation</topic><topic>Fluoroimmunoassay - methods</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Methods. Procedures. Technologies</topic><topic>Multi-analyte assay</topic><topic>Neural networks</topic><topic>Neural Networks (Computer)</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Simazine - analysis</topic><topic>Simazine - chemistry</topic><topic>Simazine - immunology</topic><topic>TIRF</topic><topic>Triazines</topic><topic>Triazines - analysis</topic><topic>Triazines - chemistry</topic><topic>Triazines - immunology</topic><topic>Various methods and equipments</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reder, Sabine</creatorcontrib><creatorcontrib>Dieterle, Frank</creatorcontrib><creatorcontrib>Jansen, Hendrikus</creatorcontrib><creatorcontrib>Alcock, Susan</creatorcontrib><creatorcontrib>Gauglitz, Günter</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Biosensors & bioelectronics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reder, Sabine</au><au>Dieterle, Frank</au><au>Jansen, Hendrikus</au><au>Alcock, Susan</au><au>Gauglitz, Günter</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi-analyte assay for triazines using cross-reactive antibodies and neural networks</atitle><jtitle>Biosensors & bioelectronics</jtitle><addtitle>Biosens Bioelectron</addtitle><date>2003-12-30</date><risdate>2003</risdate><volume>19</volume><issue>5</issue><spage>447</spage><epage>455</epage><pages>447-455</pages><issn>0956-5663</issn><eissn>1873-4235</eissn><abstract>A biosensor system based on total internal reflectance fluorescence (TIRF) was used to discriminate a mixture of the triazines atrazine and simazine. Only cross-reactive antibodies were available for these two analytes. The biosensor is fully automated and can be regenerated allowing several hundreds of measurements without any user input. Even a remote control for online monitoring in the field is possible. The multivariate calibration of the sensor signal was performed using artificial neural networks, as the relationship between the sensor signals and the concentration of the analytes is highly non-linear. For the development of a multi-analyte immunoassay consisting of two polyclonal antibodies with cross-reactivity to atrazine and simazine and different derivatives immobilised on the transducer surface, the binding characteristics between these substances like binding capacity and cross-reactivity were characterised. The examination of three different measurement procedures showed that a two-step measurement using only one antibody per step allows a quantification of both analytes in a mixture with limits of detection of 0.2 μg/l for atrazine and 0.3 μg/l for simazine. The biosensor is suitable for online monitoring in the field and remote control is possible.</abstract><cop>Lausanne</cop><pub>Elsevier B.V</pub><pmid>14623469</pmid><doi>10.1016/S0956-5663(03)00202-1</doi><tpages>9</tpages></addata></record> |
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subjects | Algorithms Antibodies - chemistry Antibodies - immunology Atrazine - analysis Atrazine - chemistry Atrazine - immunology Biological and medical sciences Biosensing Techniques - instrumentation Biosensing Techniques - methods Biosensors Biotechnology Calibration Complex Mixtures - analysis Complex Mixtures - chemistry Cross-reactivity Equipment Design Equipment Failure Analysis - methods Feasibility Studies Fluoroimmunoassay - instrumentation Fluoroimmunoassay - methods Fundamental and applied biological sciences. Psychology Methods. Procedures. Technologies Multi-analyte assay Neural networks Neural Networks (Computer) Reproducibility of Results Sensitivity and Specificity Simazine - analysis Simazine - chemistry Simazine - immunology TIRF Triazines Triazines - analysis Triazines - chemistry Triazines - immunology Various methods and equipments |
title | Multi-analyte assay for triazines using cross-reactive antibodies and neural networks |
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